Forem: Ezinne Anne😎👩🏿‍💻

7 Automation Tools That Actually Work With Legacy Systems

Ezinne Anne😎👩🏿‍💻 — Mon, 09 Mar 2026 15:34:21 +0000

In the world of modern software engineering, the term "legacy system" often makes people think of dusty old servers and outdated code. However, for most large businesses, these systems are not just old relics—they are the engines that run the company. They hold decades of customer data and handle critical transactions every single day.

Replacing these systems is often too expensive and carries too much risk. Instead of a "rip-and-replace" strategy, modern engineers focus on "integration." This means finding ways to make old infrastructure talk to modern cloud apps, AI agents, and mobile platforms.

The problem is that most companies have a legacy system integration gap. They want to move fast, but their old software doesn't have the "plug-and-play" features of modern apps. This is where automation tools come in. You don't need to rebuild your entire business from scratch; you just need the right "middleware" or "wrapper" to bridge the gap.

This guide explores 7 automation tools that actually work with legacy systems. We will look at how they solve the integration problem using API wrappers, Robotic Process Automation (RPA), and modern middleware.

The Legacy Problem: Why We Can’t Just Delete the Past

Before we look at the tools, we need to understand why legacy systems are still here. According to a report by IBM on Legacy Modernization, many organizations keep these systems because they are incredibly reliable for high-volume tasks. Whether it is a COBOL mainframe in a bank or an AS/400 system in a warehouse, these "green screen" applications are often the core of the business.

The challenge is that these systems usually lack an Application Programming Interface (API). An API is like a digital doorway that allows two programs to talk to each other. Without it, modern tools are locked out. To fix this, we use three main strategies:

Robotic Process Automation (RPA): Software "bots" that click buttons and type data into old screens just like a human would.
API Wrappers: Small pieces of code that surround the old system and give it a modern "RESTful" interface.
Integration Middleware: Powerful platforms that act as a translator between old data formats (like XML) and new formats (like JSON).

Let’s look at the tools that make this happen.

1. UiPath: The Leader in UI-Based Automation

UiPath is the go-to tool when an old system has no API at all. If the only way to get data out of your software is to look at a Windows 95 screen or a terminal window, UiPath is the solution.

How it Works with Legacy Systems

UiPath uses Robotic Process Automation (RPA). It uses "Computer Vision" to "see" the elements on a screen. It can identify text boxes, buttons, and tables even in Citrix environments or remote desktops where traditional code can't reach.

Why it Works for Old Infrastructure

Green Screen Support: It has built-in connectors for mainframes and terminal emulators.
No-Code Design: You can drag and drop actions to create a "bot" that logs in, navigates menus, and extracts data.
AI Integration: It can use AI to read scanned PDFs or handwritten forms and then type that data into your legacy ERP.

Verdict: Use UiPath if you need to automate a system that requires a human to click buttons and navigate menus.

2. n8n: Flexible, Self-Hosted Workflow Logic

n8n is an "iPaaS" (Integration Platform as a Service) that is loved by technical teams. Unlike many cloud-only tools, n8n can be installed on your own servers. This is a game-changer for legacy systems that are hidden behind a corporate firewall for security reasons.

How it Works with Legacy Systems

n8n excels at "orchestration." If you have built a custom API wrapper for your legacy database, n8n can act as the brain that tells that wrapper what to do. It can connect an old SQL database to a modern Slack channel or an AI model.

Why it Works for Old Infrastructure

Custom Code Nodes: You can write JavaScript or Python directly inside n8n to handle weird, old data formats that other tools can't understand.
Self-Hosting: Because you can run it on-premise, it can talk to your old systems without sending sensitive data over the public internet.
Webhooks: It can listen for signals from your old system and trigger modern workflows instantly.

Verdict: Best for technical teams who want full control and the ability to write custom logic for complex legacy data.

3. Zapier: Fast Connections for Modernized Legacy Apps

Zapier is the most famous automation tool for a reason: it is incredibly easy to use. While it is mostly known for connecting modern SaaS apps (like Gmail and Shopify), it is surprisingly effective for legacy systems that have been "slightly" modernized.

How it Works with Legacy Systems

If you have used a tool to create an API for your old system, Zapier can connect it to over 5,000 other apps. It uses "Webhooks" to send and receive data. If your old system can send an email or export a CSV file to a folder, Zapier can grab that information and start a workflow.

Why it Works for Old Infrastructure

User-Friendly: Anyone in the company can set up an automation in minutes.
Filter and Format: It has built-in tools to change the way data looks (e.g., changing a date from "MM/DD/YY" to "YYYY-MM-DD") so it fits into modern apps.
Rapid Prototyping: You can test an automation idea in an afternoon without writing a single line of code.

Verdict: Use Zapier for quick wins where the legacy system can at least send emails or has a basic API.

4. MuleSoft Anypoint Platform: The Enterprise Translator

MuleSoft, owned by Salesforce, is the heavy hitter of legacy integration. It is designed for massive companies that have hundreds of different systems that all need to talk to each other.

How it Works with Legacy Systems

MuleSoft uses a concept called "API-led connectivity." Instead of connecting System A directly to System B, MuleSoft creates a "System API" that sits on top of your legacy mainframe. This "wrapper" makes the mainframe look like a modern web service to the rest of the company.

Why it Works for Old Infrastructure

Mainframe Connectors: It has specialized connectors for IBM i (AS/400), SAP, and Oracle.
DataGraph: It allows you to query data from multiple old systems using a single modern language (GraphQL).
Governance: It provides high-level security and monitoring, which is essential for regulated industries like banking and healthcare.

Verdict: The best choice for large enterprises with a "rip-and-replace" budget but a "keep-and-connect" strategy.

5. Kong Enterprise: The Security Guard for Old APIs

Kong is an API Gateway. While it doesn't "create" the automation, it provides the secure bridge that allows automation to happen. If you are exposing your old infrastructure to the internet so that modern apps can use it, you need Kong.

How it Works with Legacy Systems

When you build an API wrapper around a legacy system, that wrapper is often fragile. Kong sits in front of it. It handles the security (logins), limits how many requests can be sent so the old system doesn't crash (rate limiting), and keeps a log of everything that happens.

Why it Works for Old Infrastructure

Traffic Control: Legacy systems are easily overwhelmed. Kong ensures that modern "fast" apps don't accidentally take down a "slow" old mainframe.
Authentication: It adds modern security (like OAuth2) to old systems that originally had no security at all.
Developer Portal: It makes it easy for your internal developers to find and use the "modernized" versions of your old systems.

Verdict: Essential for companies that want to turn their legacy functionality into a secure, reusable service.

6. Talend: Moving Data from Past to Present

Talend focuses on data integration. Sometimes, you don't need to click buttons on a screen; you just need to move 10 million rows of data from a 1998 database into a modern cloud data warehouse like Snowflake.

How it Works with Legacy Systems

Talend uses "ETL" (Extract, Transform, Load). It goes into the "basement" of your tech stack, pulls out raw data from old databases (like DB2 or Informix), cleans it up, and puts it where modern AI tools can use it.

Why it Works for Old Infrastructure

Data Quality: Legacy data is often "messy." Talend has tools to fix broken addresses, remove duplicates, and standardize names.
Massive Scale: It is built to handle huge amounts of data that would crash simpler tools like Zapier.
Open Source Roots: It offers a free version (Open Studio) for smaller projects, making it accessible for testing.

Verdict: Use Talend when your legacy problem is about moving and cleaning large amounts of data.

7. Microsoft Power Automate: The Desktop Bridge

Microsoft Power Automate is unique because it combines cloud-based automation with "Desktop Flows." Since most legacy systems run on Windows, being a Microsoft product gives it a massive advantage.

How it Works with Legacy Systems

It uses an "On-premises data gateway." This is a small piece of software you install on your local server that creates a secure tunnel to the Microsoft cloud. This allows a cloud-based flow to reach down and grab data from a local Excel file or an old Windows application.

Why it Works for Old Infrastructure

Integrated RPA: It includes "Power Automate Desktop," which can record your actions on a PC and replay them as a bot.
Deep Windows Integration: It works natively with Active Directory and other Windows security tools that legacy systems often rely on.
AI Builder: You can easily add "OCR" (Optical Character Recognition) to your flows to read text from old terminal screens.

Verdict: The perfect choice for companies already using Microsoft 365 and Azure who need to bridge local Windows apps to the cloud.

Comparing the Approaches: Which Tool is Right?

Choosing a tool depends on the "interface" of your legacy system. Use this table to decide:

System Interface	Integration Strategy	Recommended Tool
No API / Green Screen	UI Automation (RPA)	UiPath or Power Automate
Behind a Firewall	On-Premise Orchestration	n8n
Basic API / Webhooks	Quick Cloud Connectors	Zapier
Massive Enterprise Stack	API-Led Middleware	MuleSoft
Fragile API Wrappers	API Gateway Security	Kong Enterprise
Database Only	Data Migration (ETL)	Talend

Conclusion

You do not have to abandon your legacy systems to join the automation revolution. By using tools like UiPath for UI tasks, n8n for flexible logic, or MuleSoft for enterprise-wide connectivity, you can unlock the value hidden in your old infrastructure.

The goal is to stop viewing legacy systems as "technical debt" and start viewing them as "foundational assets." With the right wrapper or middleware, your 20-year-old mainframe can become the heart of your 2026 AI strategy.

What is the oldest system in your tech stack? Start small by automating one simple report or one data entry task.

Best AI Tools for Med Spa & Wellness Clinic Automation

Ezinne Anne😎👩🏿‍💻 — Thu, 26 Feb 2026 18:38:00 +0000

The aesthetics and wellness industry is booming, but managing a med spa often means juggling a mountain of manual tasks. Between booking appointments, sending intake forms, crafting post-treatment care plans, and chasing down reviews, your staff's time is easily consumed by administrative bottlenecks.

By intelligently automating these repetitive tasks, med spas and wellness clinics can unlock unprecedented efficiency, improve client satisfaction, and free up staff to focus on exceptional patient care.

This guide explores the best ways to automate your med spa, focusing on how to connect popular scheduling platforms like Jane App, Acuity Scheduling, and the Zenoti automation features to create smart, AI-driven workflows for appointment reminders, treatment follow-ups, and review requests.

The Automation Engine: How to Connect Your Tools

Before diving into specific workflows, it is vital to understand how these systems talk to each other. Your scheduling software (Jane App, Acuity, or Zenoti) holds the data, but to create truly intelligent automation, you need a "middleman" to process that data and trigger actions.

Instead of writing custom code from scratch, modern clinics use visual workflow automation platforms. These tools connect your clinic software to AI tools (like OpenAI) and communication platforms (like Twilio or Mailchimp).

Top Workflow Automation Platforms for Clinics

Platform	Best For	Technical Skill Required
Zapier	Quick, simple connections between standard apps.	Beginner
Make.com	Complex, multi-step visual workflows with conditional routing.	Intermediate
n8n	Deep customization, open-source options, and advanced API integrations.	Advanced

By using platforms like Make.com or n8n, you can build custom logic that transforms a basic scheduling app into a highly personalized virtual concierge.

1. Smart Appointment Reminders

Appointment management is the backbone of your clinic. While Jane App, Acuity, and Zenoti all have built-in reminder features, they are often generic ("Your appointment is tomorrow at 2 PM").

AI allows you to elevate this communication, reducing no-shows while making clients feel recognized.

The AI-Powered Reminder Workflow

Instead of a static message, you can use automation tools to generate dynamic reminders based on the client's history.

The Trigger: An appointment is booked in Acuity Scheduling for a "HydraFacial."
Data Retrieval: Make.com or n8n checks the client’s profile to see if this is their first visit or a recurring appointment.
AI Generation: The workflow sends a prompt to an AI tool to draft a personalized text message.
The Action: The client receives a customized SMS via Twilio: "Hi Sarah, looking forward to seeing you tomorrow for your second HydraFacial! Remember to avoid retinol tonight so your skin is prepped for the treatment."

This workflow replaces standard notifications with contextual, value-driven communication that drastically reduces cancellation rates.

2. Personalized Treatment Follow-ups & Aftercare

Post-treatment care is crucial for client satisfaction and treatment efficacy. Manual follow-ups are labor-intensive and easy to forget during a busy shift. AI can completely automate your aftercare protocol, ensuring every patient gets exactly what they need.

The Smart Aftercare Workflow

Different treatments require different aftercare. Here is how to automate the distribution of customized instructions immediately after a visit.

The Trigger: A practitioner marks a "Chemical Peel" appointment as Completed in Zenoti.
Data Extraction: n8n extracts the specific type of peel and the client's skin type from their chart.
Content Creation: The AI drafts a friendly, customized aftercare email outlining what to expect over the next 3 days, including specific instructions for their skin type.
Product Upsell: Based on the treatment, the automation appends a link to purchase a specific soothing serum from your online store.
The Action: The email is sent automatically, and a task is created for a staff member to follow up via phone in 72 hours if the client flagged any sensitivities.

This ensures consistent patient care, builds trust, and drives passive retail revenue without adding a single task to your receptionist's plate.

3. Automated Review Requests and Reputation Management

Online reviews are the lifeblood of med spa marketing. Actively soliciting reviews can be tedious, but automating the process ensures a steady stream of fresh, positive feedback on Google and Yelp.

The Conditional Review Workflow

The secret to a great review strategy is timing and routing. You want to push happy clients to public platforms and direct unhappy clients to private, internal channels so you can resolve their issues.

The Trigger: An appointment is completed in Jane App.
The Delay: Make.com holds the workflow for exactly 48 hours to let the treatment results settle.
The Initial Request: An automated SMS goes out asking a simple question: "Hi! How was your experience at [Clinic Name] on a scale of 1 to 5?"
Conditional Routing:
- If they reply 4 or 5: The system automatically texts back a thank-you message with a direct link to your Google My Business page.
- If they reply 1, 2, or 3: The system texts back an apology, asks for private feedback on how to improve, and instantly sends an alert to the clinic manager’s email or Slack channel to handle the situation personally.

This automated "review gating" protects your online reputation while simultaneously boosting your local SEO ranking.

Practical Implementation: Security First

When implementing these AI tools and automation platforms, remember that patient data privacy is non-negotiable.

HIPAA Compliance: Ensure that any platform handling Protected Health Information (PHI) is HIPAA compliant.
Data Minimization: Design your Make.com or n8n workflows to only process the data absolutely necessary for the task. You do not need to send full medical histories to an AI just to generate a review request.
Keep the Human in the Loop: AI is a tool to assist your staff, not replace them. Always ensure high-risk automated messages (like complex medical aftercare) are based on pre-approved templates or reviewed by staff when necessary.

Conclusion

Embracing the best AI tools for your med spa is no longer a luxury; it is a competitive necessity. By leveraging platforms like Make.com, n8n, or Zapier to supercharge the capabilities of Jane App, Acuity Scheduling, or Zenoti, you transform a standard clinic into a modern, efficient powerhouse.

From smart appointment reminders and customized treatment follow-ups to intelligent review requests, these smart workflows will drastically improve your patient experience and protect your bottom line. Stop doing manual data entry, and let automation do the heavy lifting.

The Complete E-commerce Automation Stack: 12 Tools That Talk to Each Other

Ezinne Anne😎👩🏿‍💻 — Sat, 14 Feb 2026 13:58:37 +0000

In today's e-commerce landscape, having great products isn't enough. The difference between a struggling store and a thriving empire lies in operational efficiency. Fragmented systems and manual data entry are silent killers of growth.

Imagine a world where a customer places an order, and your inventory updates, a shipping label generates, and a personalized email fires off, all without a single click. This isn't a pipe dream; it is the power of a fully integrated e-commerce automation stack.

This guide covers the 12 essential tools that connect everything from cart to cash flow. We will look at critical Shopify apps, inventory sync tools, and returns automation solutions that stop working in silos and start working together.

Why Integration is Non-Negotiable

An "automation stack" isn't just a collection of apps; it is a ecosystem where tools share data autonomously. When you wire up your stack correctly, you unlock:

Unrivaled Efficiency: Your team stops doing data entry and starts doing strategy.

Real-Time Accuracy: Inventory levels and shipping statuses are always up to date.

Scalability: You can handle 10 orders or 10,000 orders with the same headcount.

Here are the 12 tools, categorized by function, that build this machine.

Part 1: The Core & Customer Experience

Your foundation must be solid before you can automate it. These tools manage the storefront and the relationship with the buyer.

1. Shopify (The Hub)

Role: The central nervous system. It serves as a storefront, catalog, and checkout.

How It Talks: Shopify creates the "events" (e.g., Order Created, Customer Updated) that trigger every other tool in this list via Webhooks and APIs.

The Automation: When a sale happens here, it signals your fulfillment, marketing, and accounting tools simultaneously.

2. Gorgias (Customer Service)

Role: A helpdesk built specifically for e-commerce that centralizes email, chat, and social comments.

How It Talks: It pulls data from Shopify so agents see order details next to the ticket. It creates tickets based on triggers from other apps.

The Automation: If a customer asks "Where is my order?", Gorgias checks the shipping status and auto-replies with the tracking link, resolving the ticket instantly.

3. Klaviyo (Marketing Automation)

Role: The standard for e-commerce email and SMS marketing.

How It Talks: It syncs deeply with Shopify and your loyalty apps to track exactly what users are browsing and buying.

The Automation: A customer buys a specific item in Shopify; Klaviyo waits 14 days and triggers a "Review Request" or "Cross-sell" email based specifically on that product category.

Part 2: Growth & Retention

Acquiring customers is expensive. These tools automate the process of keeping them and increasing their lifetime value.

4. LoyaltyLion (Loyalty Programs)

Role: Manages points, rewards, and referral tiers.

How It Talks: It pushes point balances to your checkout (Shopify) and your emails (Klaviyo).

The Automation: When a customer enters a VIP tier, LoyaltyLion tags them in Shopify. This tag triggers a special flow in Klaviyo to send them a "Welcome to VIP" exclusive discount code.

5. Octane AI (Conversational Marketing)

Role: AI-powered quizzes and Facebook Messenger automation.

How It Talks: It collects zero-party data (preferences) and pushes it to your marketing platform.

The Automation: A customer completes a product quiz on Octane AI, and their preferences are automatically sent to Klaviyo to segment them for targeted email campaigns.

6. Stamped.io (Social Proof)

Role: Collects product reviews, photos, and NPS scores.

How It Talks: It listens for delivery confirmation to time its requests perfectly.

The Automation: An item is marked "Delivered" in your shipping app. Stamped.io waits 3 days, then sends a review request. If the review is 5 stars, it can auto-post to social media.

Part 3: Operations & Logistics (The Backbone)

This is where automation saves you the most time. These inventory sync tools and fulfillment platforms prevent overselling and shipping errors.

7. Inventory Source (Inventory Sync)

Role: Connects your store to supplier inventory for dropshipping or multi-warehouse management.

How It Talks: It sits between your suppliers and Shopify, constantly checking stock feeds.

The Automation: Your supplier runs out of a SKU. Inventory Source detects this immediately and sets that product to "Out of Stock" on Shopify, preventing backorders before they happen.

8. ShipStation (Fulfillment)

Role: Generates shipping labels and manages carrier rates.

How It Talks: It pulls orders from Shopify and pushes tracking numbers back once the label is printed.

The Automation: You print a label in ShipStation. It automatically marks the Shopify order as "Fulfilled," emails the tracking number to the customer, and closes the open order ticket.

9. Loop Returns (Returns Automation)

Role: A customer-facing portal for self-service returns and exchanges.

How It Talks: It validates the return against the Shopify order history and updates inventory upon receipt.

The Automation: A customer requests a return. Loop auto-approves it based on your rules, issues a return label, and once the carrier scans the package, it can instantly issue a gift card (incentivizing an exchange over a refund).

Part 4: Intelligence & Data

10. Clearco (Capital & Cash Flow)

Role: Provides revenue-based funding for inventory and marketing.

How It Talks: Read-only access to your sales data to determine funding eligibility.

The Automation: Instead of applying for loans manually, the system analyzes your daily sales and automatically offers capital top-ups when you hit growth spikes.

11. Google Analytics 4 (Analytics)

Role: Tracks user behavior and traffic sources.

How It Talks: via native integrations and Google Tag Manager.

The Automation: While primarily for reporting, you can set up "Alerts." If conversion rates drop below 1%, it automates an email to your dev team to check for site errors.

The Glue: Orchestrating the Stack

12. n8n (Workflow Automation)

Sometimes, native integrations aren't enough. You need a custom bridge. n8n is a workflow automation tool (like Zapier, but more powerful and affordable) that connects APIs with infinite flexibility.

Real-World Example: The "High-Value" Watchdog

Let's say you want to treat orders over $500 differently. Most basic apps can't do this logic alone. Here is how n8n automates it:

Trigger: n8n listens for a New Order webhook from Shopify.

Logic Check: It checks: Is the total over $500?

Action A (If Yes): It sends a Slack message to your VIP support team: "High Roller Alert!"

Action B (If Yes): It creates a task in your warehouse software to add a handwritten thank-you note.

Action C (If No): It allows the order to proceed through the standard fulfillment route.

This level of business process automation ensures you aren't just moving data, but applying intelligent logic to it.

Conclusion

Building a tech stack isn't about collecting apps; it's about designing a workflow. By selecting tools that prioritize connectivity, integrating Shopify apps with inventory sync tools and returns automation, you build a business that runs on autopilot.

Start with the foundation (Shopify + Marketing + Fulfillment), and use tools like n8n to fill in the gaps. When your tools talk to each other, you stop working in your business and start working on it.

Top 6 Automation Tools for B2B SaaS Sales Teams (Beyond Salesforce)

Ezinne Anne😎👩🏿‍💻 — Fri, 30 Jan 2026 09:48:00 +0000

B2B SaaS sales is highly competitive, and manual processes slow you down. While Salesforce is powerful, it can feel rigid when you need flexible, multi tool automation. If you rely only on a CRM, you risk missing opportunities to improve prospecting, outreach, and follow ups.

You do not need to replace your CRM. You need to enhance it. The right automation tools help you qualify leads faster, personalize outreach at scale, and make sure no lead is missed. This guide shows you six automation tools that go beyond basic CRM features and help you build smarter sales workflows, including how they can work together using platforms like n8n.

The Changing Landscape of B2B Sales Automation

Today’s B2B buyer journey is complex and spread across many touchpoints. If you rely on one large CRM for everything, you can run into bottlenecks, messy data, and missed deals. Even though Salesforce is powerful, advanced automation often requires heavy customization that takes time and money. That is why many teams now use focused sales tools for specific tasks like engagement, data enrichment, or call insights.

To build an effective sales tech stack, you combine the best tools for each job and connect them using a platform like n8n. This approach helps you automate repetitive work, personalize outreach at every stage, keep your data clean and accurate, and move deals through your pipeline faster.

Top 6 Automation Tools for B2B SaaS Sales Teams (Beyond Salesforce)

Here's a breakdown of the leading automation tools that empower sales teams to achieve unprecedented levels of efficiency and effectiveness.

1. Outreach.io: The Sales Engagement Powerhouse

Outreach.io is a leading sales engagement platform designed to help sales teams create, execute, and analyze personalized communication sequences at scale. It's a comprehensive solution for sales outreach automation, managing emails, calls, and social touches from a single interface.

Core Function: Automates and optimizes multi-channel sales sequences, provides AI-driven insights, and streamlines communication workflows.
Key Features:
- AI-powered email and call coaching
- Sequence automation (emails, calls, tasks)
- CRM synchronization (e.g., Salesforce, HubSpot)
- Advanced analytics and reporting
- Meeting and calendar integration
Why it's a game-changer: Outreach brings intelligence to every touchpoint, ensuring reps send the right message at the right time. Its AI features provide actionable recommendations, transforming sales reps into highly effective communicators.

Automation Use Cases with n8n/API Integration

While Outreach has native CRM integrations, n8n can unlock even more dynamic workflows, especially when integrating with custom systems or niche data sources.

Scenario: Automatically add highly qualified leads from a custom lead-scoring model (e.g., computed in a data warehouse or spreadsheet) into an Outreach sequence.

Workflow Concept:

Trigger: New qualified lead identified in a spreadsheet/database.
Data Transformation: Map lead data to Outreach's required contact fields.
Outreach API Call: Add the prospect to a specific sequence in Outreach.

// Example n8n HTTP Request node for adding a prospect to an Outreach sequence
{
  "requestMethod": "POST",
  "url": "https://api.outreach.io/api/v2/prospects",
  "headers": {
    "Authorization": "Bearer {{ $connections.outreachApi.accessToken }}",
    "Content-Type": "application/json"
  },
  "body": {
    "data": {
      "type": "prospects",
      "attributes": {
        "email": "{{ $json.email }}",
        "first_name": "{{ $json.firstName }}",
        "last_name": "{{ $json.lastName }}",
        "phone_numbers": [
          {
            "number": "{{ $json.phone }}"
          }
        ],
        "title": "{{ $json.title }}",
        "company_name": "{{ $json.company }}"
      },
      "relationships": {
        "sequence": {
          "data": {
            "type": "sequences",
            "id": "{{ $json.outreachSequenceId }}" // ID of the target sequence
          }
        }
      }
    }
  }
}

Performance/Cost Tip: Batch API calls when possible to reduce the number of requests and stay within rate limits. Monitor sequence performance closely; poor personalization can lead to low engagement and higher unsubscribe rates, impacting your Outreach credits.

2. Apollo.io: Your All-in-One Sales Intelligence & Engagement Platform

Apollo.io stands out as a robust sales intelligence platform combined with sales engagement capabilities. It’s a powerful tool for lead generation and automated prospecting, offering a massive B2B database of contacts and companies, alongside an email outreach engine.

Core Function: Provides verified contact data (emails, phone numbers), company insights, and allows for direct multi-channel outreach campaigns.
Key Features:
- Access to a database of millions of contacts
- Advanced search filters (title, industry, company size, tech stack)
- Email and calling sequences
- Email verifier and sender warm-up
- CRM integration
- Intent data
Why it's a game-changer: Apollo empowers sales teams from prospecting to conversion by providing both the leads and the tools to engage them, significantly reducing the time spent on manual research.

Automation Use Cases with n8n/API Integration

Apollo's rich API makes it a prime candidate for API automation for sales, especially for enriching existing lead lists or generating targeted prospect lists based on dynamic criteria.

Scenario: Enrich a list of company names from a CSV with contact information (decision-makers' emails, phone numbers) from Apollo, then push the enriched data to a CRM or Google Sheet.

Workflow Concept:

Trigger: Upload CSV or periodically fetch company names from a database.
Loop through Companies: For each company, search Apollo for relevant contacts.
Apollo API Call (Search Contacts): Use company name and desired job titles to find prospects.
Extract & Transform: Pull out key contact details.
Store/Update: Add enriched data to CRM or a new spreadsheet.

// Example n8n Function node to structure an Apollo API search query
const companyName = $json.companyName; // Assuming companyName comes from previous node
const jobTitles = ["Head of Sales", "VP of Sales", "Sales Director"];
const seniority = ["vp", "director", "c_level"]; // Apollo's seniority codes

return {
  json: {
    "q_organization_domains": [ companyName ], // Or q_organization_names
    "person_titles": jobTitles,
    "person_seniorities": seniority,
    "per_page": 10 // Limit results per company
  }
};

Then, use an HTTP Request node to call https://api.apollo.io/v1/people/search with this JSON body.

Security Tip: Always use API keys securely, preferably through n8n's credential management, and avoid hardcoding them in workflows. Ensure your Apollo searches comply with data privacy regulations like GDPR and CCPA.

3. Clay: The AI-Powered Data Enrichment & Prospecting Engine

Clay is quickly becoming a favorite for advanced sales and marketing teams due to its unparalleled flexibility in data enrichment and lead generation. It's not just a database; it's a platform to build custom, AI-powered data workflows, making it an incredible data enrichment tool and automated prospecting engine.

Core Function: Leverages AI and integrates with hundreds of data sources to find, enrich, and qualify leads based on highly specific criteria. Think of it as a spreadsheet on steroids, connected to the entire internet.
Key Features:
- Build custom AI-powered lead generation workflows
- Integrates with tools like ChatGPT, Google Search, Hunter.io, BuiltWith, LinkedIn Sales Navigator
- Automate web scraping and data extraction
- Combine multiple data points for advanced segmentation
- Real-time data enrichment
Why it's a game-changer: Clay allows sales teams to define exactly who their ideal customer is and then programmatically find and enrich those leads from virtually anywhere, solving the problem of generic, low-quality lead lists.

Automation Use Cases with n8n/API Integration

Clay's real power comes from its ability to be integrated into broader workflows via its API, making it an excellent orchestrator within an AI-powered sales workflow.

Scenario: Identify companies using a specific tech stack (e.g., a competitor's product) and then find relevant contacts within those companies, enriching their data with LinkedIn profiles and verified emails.

Workflow Concept:

Trigger: New target list of companies (e.g., from BuiltWith or Crunchbase).
Clay Worksheet API Call: Push company names into a Clay worksheet for enrichment.
Clay Logic (Internal): Within Clay, configure steps to:
- Find LinkedIn profile URLs for companies.
- Use LinkedIn to find target contacts (e.g., "VP of Marketing").
- Use an email finder integration (e.g., Hunter.io, Dropcontact) within Clay to get verified emails.
- Use AI (e.g., OpenAI integration) to summarize company news or recent funding rounds.
n8n Retrieve Clay Data: Fetch the enriched data from Clay's API once the worksheet processing is complete.
CRM Update/Outreach: Push the highly qualified, enriched leads to Outreach or CRM.

// Example n8n HTTP Request node to trigger a Clay run
{
  "requestMethod": "POST",
  "url": "https://api.clay.com/v1/worksheets/{{ $json.worksheetId }}/run",
  "headers": {
    "Authorization": "Bearer {{ $connections.clayApi.accessToken }}",
    "Content-Type": "application/json"
  },
  "body": {
    "input": [
      {
        "companyName": "Acme Corp",
        "website": "acmecorp.com"
      },
      {
        "companyName": "Globex Inc.",
        "website": "globex.com"
      }
    ]
  }
}

Note: The actual Clay workflow configuration is done within the Clay UI itself, where you define the steps (e.g., "Find emails with Hunter," "Search Google"). n8n then acts as the trigger and retriever.

Cost Consideration: Clay's pricing is usage-based (credits). Optimize your workflows to avoid unnecessary lookups, and leverage caching mechanisms if you're repeatedly enriching the same data points.

4. Clearbit / Lusha: Sales Intelligence and Data Enrichment Platforms

Clearbit and Lusha provide high quality B2B contact and company data for sales and marketing teams. Clearbit is especially strong in company level enrichment and works well with product led and inbound sales motions.

Core function

You get verified company data, contact details, and firmographic insights to identify and qualify the right buyers.

Key features

Large and regularly updated B2B data sets
Company and contact enrichment using domains and emails
Firmographic and technographic data
Advanced filtering and segmentation
Real time enrichment via API

Why it matters

These tools reduce manual research and improve lead quality by enriching records with accurate company and contact data.

Automation with n8n and APIs

When you connect Clearbit or Lusha with n8n, you can automate lead enrichment and scoring for your prospecting workflows.

Example scenario

A new company signs up for a free trial. You use Clearbit or Lusha to find company details and key decision makers, then enrich the lead automatically.

Simple workflow

A new free trial signup occurs
You extract the company domain from the email
You call the Clearbit or Lusha API to fetch company and contact data
You filter contacts by role or seniority
You update your CRM with enriched records

// Example n8n HTTP Request node for Clearbit Company Enrichment API
{
  "requestMethod": "GET",
  "url": "https://company.clearbit.com/v2/companies/find?domain={{ $json.domain }}",
  "headers": {
    "Authorization": "Bearer {{ $connections.clearbitApi.apiKey }}"
  }
}

Further calls would be made to find people based on the company ID or domain.

Data Quality Tip: Always validate enriched data against other sources when accuracy is critical. Add error handling in n8n to manage API limits, missing fields, or failed requests.

5. Chili Piper / Calendly: Meeting Scheduling & Routing Automation

Efficient meeting scheduling is paramount for sales velocity. Chili Piper and Calendly automate this often-tedious process, integrating directly with calendars and CRMs to ensure leads are booked with the right rep instantly.

Core Function: Automate meeting scheduling, intelligent routing of inbound leads, and booking follow-up meetings.
Key Features:
- Instant booking for inbound leads
- Automated round-robin scheduling
- CRM integration (creates events, updates lead status)
- Personalized meeting links
- Meeting reminders and follow-ups
Why it's a game-changer: These tools eliminate the "back-and-forth" of scheduling, improve conversion rates for inbound leads, and ensure equitable lead distribution among reps.

Automation Use Cases with n8n/API Integration

While these tools offer strong native integrations, n8n can orchestrate more complex scenarios, such as dynamic rep assignment or custom post-meeting workflows.

Scenario: A lead fills out a demo request form. Qualify the lead using a custom logic (e.g., firmographics + intent score) and then automatically present a Chili Piper scheduler tailored to a specific sales rep or team.

Workflow Concept:

Trigger: Form submission (e.g., from Webhook, Typeform, HubSpot).
Lead Qualification Node: Apply custom logic to score the lead.
Conditional Logic: If qualified:
- Assign Rep: Use n8n to apply round-robin logic or skill-based assignment to select a sales rep.
- Generate Chili Piper Link: Construct a personalized Chili Piper booking link for the assigned rep.
- Send Email: Send a personalized email to the lead with the booking link.
- CRM Update: Update lead status in CRM.
Else (not qualified): Send to nurture sequence.

// Example n8n Function node to dynamically generate a Chili Piper URL
const repEmail = $json.assignedRepEmail; // From a previous n8n node
const leadEmail = $json.leadEmail;
const leadFirstName = $json.leadFirstName;
const leadLastName = $json.leadLastName;
const template = "your_company_demo_template"; // Pre-configured template in Chili Piper

// Constructing the URL for a specific rep's instant booker
const chiliPiperUrl = `https://meet.chilipiper.com/${repEmail}/` +
                      `?id=${template}` +
                      `&firstName=${encodeURIComponent(leadFirstName)}` +
                      `&lastName=${encodeURIComponent(leadLastName)}` +
                      `&email=${encodeURIComponent(leadEmail)}`;

return { json: { chiliPiperBookingUrl: chiliPiperUrl } };

Scalability Consideration: Ensure your lead assignment logic can scale with team growth. Regularly review your round-robin or skill-based rules to maintain fair distribution.

6. Gong.io / Chorus.ai: Conversation Intelligence & Coaching

Gong.io and Chorus.ai are leaders in conversation intelligence, using AI to analyze sales calls and meetings. They provide unparalleled insights into buyer sentiment, talk tracks, and deal risks, enabling continuous sales coaching and improved performance.

Core Function: Record, transcribe, and analyze sales conversations to extract actionable insights for coaching, deal management, and market intelligence.
Key Features:
- AI-powered transcription and sentiment analysis
- Topic tracking and keyword detection
- Deal risk alerts
- Sales coaching tools and scorecards
- Competitor intelligence
- Integration with video conferencing and CRMs
Why it's a game-changer: These platforms transform raw call data into strategic assets, helping sales leaders identify winning behaviors, improve rep performance, and forecast more accurately.

Automation Use Cases with n8n/API Integration

Integrating conversation intelligence platforms with n8n can automate post-call workflows and synchronize insights with other tools.

Scenario: After a discovery call, automatically extract key topics discussed (e.g., pain points, specific features mentioned) and update the corresponding opportunity in the CRM, or create a follow-up task in a project management tool.

Workflow Concept:

Trigger: Call recording processed by Gong/Chorus API (e.g., webhook for "call completed" event).
Gong/Chorus API Call: Fetch call summary and key insights (e.g., topics, action items).
Process Insights: Use n8n to parse the JSON response and extract relevant data points.
Conditional Logic:
- If "competitor X" was mentioned, create a task for the rep to send a competitive battle card.
- If "pricing" was discussed, update a field in the CRM indicating pricing stage.
CRM/PM Tool Update: Update relevant records in Salesforce/HubSpot or create a task in Asana/Jira.

// Example n8n HTTP Request node to fetch Gong call details
{
  "requestMethod": "GET",
  "url": "https://api.gong.io/v2/calls/{{ $json.callId }}", // Call ID from webhook trigger
  "headers": {
    "Authorization": "Bearer {{ $connections.gongApi.accessToken }}",
    "Content-Type": "application/json"
  }
}

The response would contain a wealth of data about the call, including transcript, topics, and sentiment, which can then be parsed by subsequent n8n nodes.

Performance Tip: Be mindful of the volume of data returned by these APIs. Filter for only the necessary information to reduce processing overhead.

Building a Smart Sales Automation Stack with n8n

Your sales tools work best when they are connected. n8n acts as the central hub that links your entire sales stack and lets your tools work together. Its flexibility and strong API support make it ideal for running complex sales automation workflows without heavy custom development.

Common Ways You Can Use n8n

Unified lead enrichment

You combine tools like Clay, Apollo, and ZoomInfo to enrich leads from multiple sources before sending clean data to your CRM.

Smart outreach triggers

You start Outreach or Apollo sequences based on lead scores, website activity, or intent signals.

Automated follow ups after demos

After a meeting booked with Chili Piper and reviewed in Gong, you automatically update the CRM, create follow up tasks, or send personalized resources.

Data sync and reporting

You keep data consistent across tools and send summaries like daily sales reports to Slack.

With n8n, you scale easily, reduce costs, and stay flexible as your sales strategy changes.

Advanced Strategies to Go Further

If you want more advanced automation, you can connect AI and data quality workflows into your sales stack.

Using AI in sales workflows

You can connect language models to summarize emails, write follow ups, or turn call insights into CRM notes.

Keeping your data clean

You add validation and cleanup workflows so your CRM stays accurate and up to date.

Security and compliance

You protect sensitive data using secure credentials, limited API access, and compliance friendly workflows.

Monitoring and alerts

You track workflow health and get alerts in Slack when something breaks so issues are fixed fast.

Conclusion

Going beyond a single CRM like Salesforce does not mean replacing it. It means strengthening your sales automation with the right set of tools. The tools covered here help you improve outreach, data quality, scheduling, and sales conversations.

When you connect these tools with n8n, you create smart and flexible sales workflows that increase efficiency, boost conversions, and drive revenue. Instead of basic automation, you build systems that adapt to how your sales team actually works.

If you want to improve your sales operations, start testing these tools and use n8n to build automated prospecting and outreach workflows that scale with your team.

7 Best Automation Tools for Recruitment Agencies That Actually Work

Ezinne Anne😎👩🏿‍💻 — Thu, 22 Jan 2026 18:47:28 +0000

In the fiercely competitive world of talent acquisition, recruitment agencies face immense pressure. From identifying passive candidates and crafting compelling outreach to scheduling complex interview rounds and ensuring timely follow-ups, the manual workload can be staggering.
This isn't just about efficiency; it's about staying competitive and delivering top-tier talent faster than your rivals.
The agencies that thrive are the ones embracing technology, strategically deploying automation tools to transform their talent pipelines.

Many tools promise a lot but deliver little in the way of tangible productivity gains. This guide dives deep into the 7 best automation tools for recruitment agencies that actually work, with a special emphasis on how they can be integrated for seamless operations across candidate sourcing, interview scheduling, and automated follow-ups.

We'll dissect the capabilities of leading platforms like BlinqIO, Workable, and Greenhouse, and show you how to leverage their automation features, often by connecting them with robust orchestrators like n8n, to build a truly intelligent recruitment ecosystem.

Why Automation is No Longer Optional for Recruitment Agencies

The "what software do recruiters use" question has evolved. It's no longer just about Applicant Tracking Systems (ATSs); it's about an integrated tech stack that moves candidates through the funnel with minimal manual intervention.
The benefits are clear:
Increased Efficiency: Automate repetitive tasks like data entry, email sequences, and calendar management, freeing up recruiters' time.

Enhanced Candidate Experience: Timely communication, smooth scheduling, and personalized interactions create a positive impression.

Wider Talent Reach: AI sourcing tools can uncover passive candidates across vast data sets that human recruiters might miss.

Improved Data Accuracy & Compliance: Standardized processes reduce errors and ensure adherence to data privacy regulations.

Faster Time-to-Hire: Streamlined workflows mean quicker turnaround times from initial contact to offer acceptance.
The top-ranking content often lists general recruitment tools, but rarely goes into the how of their automation or offers practical integration examples. This guide aims to bridge that gap, providing actionable insights for technical professionals and strategic decision-makers alike.

The 7 Best Automation Tools for Recruitment Agencies That Actually Work

Let's explore the powerful platforms that can redefine your agency's operational efficiency.

1. BlinqIO: The AI-Powered Sourcing & Outreach Agent

What it is:
BlinqIO is an innovative AI agent platform designed to automate the most time-consuming aspects of candidate sourcing and initial outreach. Unlike traditional sourcing tools that merely provide data, BlinqIO acts as an autonomous agent, leveraging AI to identify ideal candidates, craft hyper-personalized messages, and even initiate conversations across various platforms. This is one of the best AI sourcing tools for recruiters who want to scale their outreach.

Key Automation Features:

AI-driven Candidate Identification: Scans vast databases (LinkedIn, GitHub, public profiles) based on your ideal candidate persona and job description.

Automated Personalized Outreach: Generates unique, context-aware emails or messages (e.g., LinkedIn InMails) tailored to each candidate's background and interests.

Conversation Initiation & Qualification: Can engage in initial conversations, answer basic questions, and pre-qualify candidates before handing them off to a human recruiter.

Integration Capabilities: Designed to connect with ATSs, CRMs, and email platforms via webhooks and APIs.
How it Actually Works (Technical Insight):
BlinqIO uses large language models (LLMs) and retrieval-augmented generation (RAG) to understand job requirements and candidate profiles. When you define a target persona (skills, experience, industry), the agent processes this, searches public data, and then, using its generative AI capabilities, creates highly relevant outreach content.

Consider an n8n workflow for BlinqIO:

Trigger: New job opening added to your ATS (e.g., Workable webhook).
BlinqIO Action: Pass job description and ideal candidate profile to BlinqIO's API.

{
 "jobTitle": "Senior AI Engineer",      
 "requirements": ["Python", "Machine Learning", "NLP", "AWS"],        "desiredExperience": "5+ years",      
 "targetPlatforms": ["LinkedIn", "GitHub"] 
}

BlinqIO Output (Webhook): BlinqIO returns a list of identified candidates with their contact info and a draft personalized message.

{
"candidates": [{"name": "Jane Doe",         
"email": "jane.doe@example.com",         
"linkedinProfile": "https://linkedin.com/in/janedoe",
"outreachMessage": "Hi Jane, your work on [specific project] at [previous company] is impressive. We're hiring a Senior AI Engineer..."}]  
}

Action: Push candidate data to your ATS (e.g., Workable API to create a new candidate profile).
Action: Send personalized outreach using an email platform (e.g., Gmail/SendGrid API with BlinqIO's generated message).

Pros: Highly scalable sourcing, superior personalization, reduces manual research and drafting.

Cons: Requires careful prompt engineering for optimal results, ethical considerations for AI-generated outreach.

Ideal Use Case: High-volume roles, niche technical searches, agencies looking to significantly expand their sourcing reach with minimal human effort.

2. Workable: Streamlined ATS with Intelligent Automation

What it is: Workable is a popular Applicant Tracking System (ATS) that excels in offering a user-friendly interface combined with robust automation features to manage the entire recruitment lifecycle. It's often cited as one of the best recruiting platforms for its ease of use and integrated approach.

Key Automation Features:

Automated Candidate Reminders: Sends automated emails to candidates requesting missing information or prompting them for next steps.

Customizable Workflow Automation: Define stages (e.g., Screen, Interview, Offer) and automate actions like sending templated emails, assigning tasks, or updating candidate status based on stage changes.

Automated Interview Scheduling: Integrates with calendars (Google, Outlook) to allow candidates to book slots directly, sending confirmations and reminders.

Email & SMS Templates: Pre-built and customizable templates for various communications, from application acknowledgements to rejection notices, which can be triggered automatically.

Offer Management: Automate offer letter generation and tracking.
How it Actually Works (Practical Implementation):
Workable's strength lies in its intuitive visual workflow builder.
You can set up rules like: "When a candidate is moved to 'Phone Screen' stage, automatically send an email with a Calendly link and assign a task to the hiring manager."

// Example of a Workable automation rule (conceptual)
{
"trigger": {
  "event": "candidate_stage_change",
  "stage": "Phone Screen"  },
"actions": [
 {
  "type": "send_email",
  "template_id": "phone_screen_invite",
  "recipient": "candidate",
  "merge_tags": {"candidate_name": "{{candidate.firstName}}",    "calendly_link": "{{job.calendlyLink}}"}
  },
{
"type": "assign_task",
"task_name": "Review Phone Screen Notes",
"assignee": "hiring_manager",
"due_date": "2_days_after_event"
}]
}

Workable's API also allows for deeper integrations, enabling tools like n8n to push/pull candidate data, manage jobs, and trigger custom actions that Workable's native automations might not cover.

Pros: Excellent user experience, comprehensive features for small to mid-sized agencies, strong interview scheduling automation.

Cons: Advanced customization might require API integration; reporting can be less robust for complex enterprise needs compared to pure CRMs.

Ideal Use Case: Agencies seeking an all-in-one ATS with strong out-of-the-box automation for managing their candidate pipeline efficiently.

3. Greenhouse: Enterprise-Grade Automation for Complex Workflows

What it is: Greenhouse is a leading enterprise-grade ATS renowned for its highly configurable workflows and extensive integration ecosystem. When considering "which ATS is best for recruitment" for larger agencies or those with complex hiring needs, Greenhouse is a top contender, often used by top companies.

Key Automation Features:

Advanced Workflow Customization: Create intricate hiring plans with specific stages, approvals, and automated actions tailored to each role.

Automated Candidate Nurturing: Set up drip campaigns based on candidate status, feedback, or time in stage.

Interview Kit & Scorecard Automation: Automatically generate structured interview kits for interviewers, ensuring consistent feedback and reducing bias. Reminders for feedback can be automated.

Dynamic Rule-Based Actions: Trigger actions like sending rejection emails, moving candidates, or notifying teams based on specific conditions (e.g., score threshold, time in stage).

Extensive API & Webhook Support: Provides powerful tools for connecting Greenhouse with virtually any other system, enabling bespoke automation workflows.

How it Actually Works (Architectural Insights):
Greenhouse's core strength lies in its "Hiring Plan" concept, which is essentially a robust workflow engine. Each stage in a hiring plan can have pre-defined automation rules. For instance, after a candidate completes a "Take-Home Assignment," an automation rule could check if the assignment was submitted. If yes, it moves them to "Review" and notifies the hiring manager. If not, it sends a reminder email after 2 days.

For advanced users, Greenhouse's API is incredibly powerful. You can use n8n to do:

Automated Sourcing & Creation: When BlinqIO identifies a hot lead, automatically create a candidate profile in Greenhouse via API.

Dynamic Candidate Updates: Update candidate statuses or add custom fields based on external events (e.g., an automated assessment tool completes its review).

Custom Reporting & Analytics: Extract detailed data for analysis beyond Greenhouse's native reporting.

// Example: Creating a candidate in Greenhouse via API (conceptual n8n node config)
// This would be part of a larger n8n workflow after candidate identification.
const greenhouseAPIKey = 'YOUR_GREENHOUSE_API_KEY';
const jobBoardAPIKey = 'YOUR_JOB_BOARD_API_KEY'; 
// If creating via job board
const endpoint = 'https://harvest.greenhouse.io/v1/candidates';
const candidateData = {"first_name": "Alice","last_name": "Smith","email_addresses": [{"value": "alice.smith@example.com", "type": "personal" }],
"phone_numbers": [{ "value": "+1234567890", "type": "mobile" }],
"attachments": [{ "filename": "resume_alice.pdf","content_type": "application/pdf", "url": "https://example.com/resume_alice.pdf" }],
"notes": "Sourced by BlinqIO on [Date], matched highly with JobID: 12345.",
"applications": [
{"job_id": 12345, // Target Job ID   
"prospect": false,
"source_id": "YOUR_SOURCING_TOOL_ID" // ID for BlinqIO or similar
}]
};
//Send API request from an n8n HTTP Request node
// Method: POST
// URL: endpoint
// Headers: Authorization: Basic Base64Encode(greenhouseAPIKey + ":")
// Body: JSON.stringify(candidateData)

Pros: Highly customizable, robust for complex organizational structures, strong compliance features, extensive integration marketplace.

Cons: Can have a steeper learning curve, pricing is generally higher, best for larger agencies.

Ideal Use Case: Large recruitment agencies or those with complex, multi-stage hiring processes and significant compliance requirements. It's truly one of the best recruiting platforms for scale.

4. n8n: The Universal Automation Orchestrator

What it is: n8n is a powerful open-source workflow automation platform that allows you to connect any API-enabled application to create custom, intelligent workflows. While not a recruitment-specific tool, n8n is one of the best automation tools for recruitment agencies because it acts as the glue, enabling you to build highly customized integrations and automations between your various recruitment tech stack components.

Key Automation Features:
Visual Workflow Builder: Drag-and-drop interface to create complex automation flows without writing extensive code.

Extensive Integrations: Connects to hundreds of apps and services out-of-the-box, plus custom HTTP requests for any API.

Conditional Logic & Looping: Build sophisticated decision trees and iterative processes within your workflows.

Data Transformation: Manipulate and transform data between different systems to ensure compatibility.

Webhook & API Triggers: Initiate workflows based on events from other platforms (e.g., a new candidate in BlinqIO, a completed interview in Workable).

How it Actually Works (Building an End-to-End Workflow):
This is where you truly enhance e-recruiting productivity.

Imagine a workflow that takes a candidate from AI sourcing to interview scheduling and automated follow-up:

Trigger: BlinqIO Webhook Node: BlinqIO identifies a promising candidate and sends a webhook with candidate details.
Data Processing: JSON Node: Parse the incoming candidate data from BlinqIO.
ATS Check: Workable/Greenhouse API Node (GET): Check if the candidate already exists in your ATS to avoid duplicates. If exists: Update existing record with new details or skip. If new: Proceed to create.
ATS Creation: Workable/Greenhouse API Node (POST): Create a new candidate profile in your ATS using the parsed data.
Personalized Outreach: Gmail/SendGrid Node: Send the personalized outreach message generated by BlinqIO to the candidate.
Response Tracking: Webhook/Email Monitor Node: Monitor for candidate replies. If "Interested" keyword detected, proceed.
Interview Scheduling: Calendly API Node: Generate a unique scheduling link for the candidate based on recruiter availability. Gmail/SendGrid Node: Send this Calendly link to the candidate with an invitation.
ATS Update: Workable/Greenhouse API Node (PATCH): Update the candidate's status in the ATS to "Interview Scheduled" and add interview details.
Automated Reminders: Set Timeout/Cron Node: Schedule a reminder email for the candidate 24 hours before the interview.
Post-Interview Follow-up: Conditional Logic Node: After the interview (triggered by ATS status change or calendar event), wait 24 hours. Gmail/SendGrid Node: Send an automated "Thank You" email to the candidate. Workable/Greenhouse API Node: Update candidate status to "Awaiting Feedback." Slack/Teams Node: Notify the interviewer to submit feedback.

// Simplified n8n workflow structure (visual workflow is more intuitive)
{
"nodes": [  
{"nodeType": "webhook",
"name": "BlinqIO Candidate Webhook",
"type": "n8n-nodes-base.webhook",
"parameters": { ... },
"id": "webhook1"   
},
{
"nodeType": "httpRequest",
"name": "Create Candidate in Workable",
"type": "n8n-nodes-base.httpRequest",
"parameters": {
"url":"https://api.workable.com/v1/jobs/{{$json.jobId}}/candidates",
"method": "POST",
"authentication": "predefined",
"predefinedAuth": "WorkableAPI",
"bodyParameters": [
{
"name": "first_name",
"value": "{{$json.first_name}}" 
},
{
"name": "last_name", 
"value": "{{$json.last_name}}"
},
{ 
"name": "email", 
"value": "{{$json.email}}" 
}         
// ... more candidate fields
]},
"id": "workableCreate",
"connections": {"webhook1": {"outputIndex": 0, "inputIndex": 0 } }},
{"nodeType": "gmail","name": "Send Outreach Email",
 "type": "n8n-nodes-base.gmail","parameters": {       "operation": "send","emailAddress": "{{$json.email}}",      "subject": "Exciting Opportunity at [Company Name]",     
"body": "{{$json.outreachMessage}}"},
"id": "sendEmail","connections": {"workableCreate": { "outputIndex": 0, "inputIndex": 0 } }
}    
// ... many more nodes for scheduling, follow-ups, etc.  ]}

Pros: Unparalleled flexibility, cost-effective (especially the self-hosted version), truly custom automation.

Cons: Requires technical proficiency to set up complex workflows, initial learning curve.

Ideal Use Case: Agencies with a diverse tech stack, unique automation needs, or those wanting to integrate specialized AI tools that don't have native integrations. This is the ultimate tool for recommending technology tools to enhance e-recruiting productivity.

5. Calendly / Chili Piper: Master of Interview Scheduling

What it is: Calendly and Chili Piper are leading interview scheduling automation tools that eliminate the back-and-forth emails typically associated with booking meetings. They are critical components for streamlining the interview process and improving the candidate experience.

Key Automation Features:

Automated Calendar Sync: Connects directly to recruiters' calendars (Google, Outlook, Office 365) to display real-time availability.

Self-Service Booking: Candidates can view available slots and book interviews directly without recruiter intervention.

Automated Confirmations & Reminders: Sends confirmation emails, calendar invitations, and configurable reminders to both candidates and interviewers.

Round-Robin Scheduling: Distributes interviews fairly among a team of recruiters or hiring managers.

Buffer Times: Automatically adds buffer time between meetings to prevent back-to-back scheduling burnout.

Integration with ATS/CRM: Embed scheduling links directly into emails sent from your ATS, or update candidate records post-booking.

How it Actually Works (Integration Example):
These tools integrate seamlessly with your ATS. For example, when a candidate moves to the "Interview" stage in Workable or Greenhouse, an automated email template can be triggered that includes a personalized Calendly link. When the candidate books, Calendly updates the recruiter's calendar, and a webhook can be sent back to n8n or directly to the ATS to update the candidate's status and add the meeting details.

// Example of a Calendly webhook payload (conceptual)
{
"event": "invitee.created",
"payload": {
"event_type": {"name": "30-min Interview - [Job Title]",      "scheduling_url": "https://calendly.com/your-org/interview"},
"invitee": {"email": "candidate@example.com","name":"John Doe",    "questions_and_answers": [{ "question": "Phone Number", "answer": "123-456-7890" }]},
"start_time": "2024-10-27T10:00:00Z","end_time": "2024-10-27T10:30:00Z","status": "active"}}

An n8n workflow can then consume this webhook, extract invitee.email, start_time, end_time, and use it to update the corresponding candidate record in Workable or Greenhouse via their respective APIs.

Pros: Drastically reduces administrative burden, improves candidate experience, minimizes scheduling errors.

Cons: Monthly subscription costs, customization for very complex rules might be limited.

Ideal Use Case: Any recruitment agency looking to eliminate manual interview scheduling, particularly beneficial for high-volume recruitment.

6. Apollo.io / Lusha: Data Enrichment & Prospecting Automation

What it is: Apollo.io and Lusha are powerful tools for finding accurate contact information, enriching candidate profiles, and automating initial outreach sequences. They are invaluable among the best recruiting tools for sourcing.

Key Automation Features:

Contact Finder: Quickly find verified email addresses and phone numbers for prospects on LinkedIn or company websites. Data Enrichment: Augment existing candidate profiles with additional data points like job title, company, industry, and social profiles.

Automated Email Sequences: Create multi-step email drip campaigns that automatically send follow-ups based on engagement (opens, clicks, replies).

CRM/ATS Sync: Push enriched contact data and engagement activities directly into your ATS or CRM.

Intent Data: (Apollo.io) Identify companies showing buying signals for specific technologies or services, which can indirectly help in finding talent for those companies.

How it Actually Works (Sourcing Integration):
Imagine a scenario where BlinqIO identifies a potential candidate but lacks full contact details. You can pass the candidate's name and current company to Apollo.io or Lusha via n8n.

Trigger: New candidate identified by BlinqIO (Webhook to n8n).
Data Enrichment: Apollo.io/Lusha API Node: Use the candidate's name and company to retrieve their verified email and phone number.

// Conceptual Apollo.io API call to find a person   
const apiKey = 'YOUR_APOLLO_API_KEY';
const endpoint = 'https://api.apollo.io/v1/people/match';   
const payload = {"api_key": apiKey, "email": "candidate@example.com", 
// or name, organization
"first_name": "Jane","last_name": "Doe", "organization_name": "TechCorp"};
// Result includes enriched profile data, including contact info

ATS Update:
Workable/Greenhouse API Node: Update the candidate's profile with the newly enriched contact details.
Outreach Sequence:
Apollo.io API Node (or SendGrid/n8n Email Node): If you choose to use Apollo for outreach, enroll the candidate into a pre-defined email sequence. Alternatively, use n8n's email nodes to send the sequence.

Pros: High accuracy for contact data, saves immense time in manual research, powerful for scaling outbound sourcing efforts.

Cons: Subscription costs can add up, some data might still require manual verification, risk of being perceived as spam if not used carefully.

Ideal Use Case: Agencies focused on proactive outbound sourcing, headhunting, and enriching existing candidate databases.

7. RecruitCRM / Bullhorn (Automation Features within a CRM)

What it is: RecruitCRM and Bullhorn are powerful CRMs specifically designed for recruitment agencies, offering comprehensive features for managing clients, candidates, and job orders. While similar to ATSs, their CRM focus means they also help manage client relationships and broader business processes. They are among the most common ATSs used by agencies, particularly Bullhorn in larger enterprises.

Key Automation Features:

Automated Candidate Matching: AI-driven algorithms suggest best-fit candidates for open roles based on skills, experience, and past interactions.

Task & Activity Automation: Automatically create follow-up tasks (e.g., "Call client for feedback", "Send candidate update") based on stage changes or time elapsed.

Automated Reporting: Generate regular reports on pipeline health, recruiter performance, and placement metrics without manual data compilation.

Email & SMS Communication Automation: Schedule and send mass emails or individual messages directly from the CRM, leveraging templates and merge fields.

Workflow Customization: Define custom workflows for different client types or recruitment processes, automating status updates and notifications.

How it Actually Works (CRM-driven Efficiency):
The power of a recruitment CRM with strong automation lies in centralizing all your client and candidate interactions and automating routine administrative tasks.
For example: 1. Client Onboarding Workflow: When a new client is added, automatically trigger a welcome email sequence, assign a dedicated account manager, and create initial tasks.

Job Order Management: When a new job order is created, automatically generate an internal brief, notify relevant recruiters, and even kick off a BlinqIO sourcing initiative via n8n.
Candidate Re-engagement: Set up an automation to periodically re-engage passive candidates in your database who haven't been contacted in 6-12 months, sending them relevant job alerts based on their profile.

// Conceptual RecruitCRM automation for candidate re-engagement
{
  "trigger": {
    "event": "candidate_inactive_for_X_months",
    "duration": "6 months"
  },
  "conditions": [
    {
      "field": "candidate_status",
      "operator": "equals",
      "value": "passive"
    },
    {
      "field": "last_contact_date",
      "operator": "less_than",
      "value": "now - 6 months"
    }
  ],
  "actions": [
    {
      "type": "send_email",
      "template_id": "passive_candidate_re_engagement",
      "recipient": "candidate",
      "merge_tags": {
        "candidate_name": "{{candidate.firstName}}",
        "job_suggestions": "{{candidate.matchedJobs}}"
      }
    },
    {
      "type": "create_task",
      "task_name": "Follow up with {{candidate.firstName}}",
      "assignee": "original_recruiter",
      "due_date": "7_days_after_email_sent"
    }
  ]
}

Pros: Comprehensive candidate and client management, robust reporting, strong integration capabilities for a centralized tech stack.

Cons: Can be more expensive than standalone ATSs, full feature set might be overkill for very small agencies, deeper automation may require custom development or integration tools like n8n.

Ideal Use Case: Recruitment agencies of all sizes that need a centralized system for both candidate and client management, looking to automate internal operations and client communications alongside candidate flow.

Best Practices for Implementing Recruitment Automation.

To truly leverage these 7 best automation tools for recruitment agencies that actually work, consider these best practices:

Start Small, Iterate Often: Don't try to automate everything at once. Identify your biggest pain points (e.g., manual scheduling) and implement automation there first. Measure the impact, then expand.
Maintain the Human Touch: Automation should augment, not replace, human interaction. Use it for repetitive tasks, but ensure critical communication points are still human-led or thoughtfully personalized. "The five C's of recruitment" – Capability, Confidence, Concern, Command, and Communication – are still paramount and require human judgment.
Data Quality is King: Automation relies on clean, accurate data. Implement data entry standards and leverage data enrichment tools (like Apollo.io/Lusha) to ensure your candidate profiles are always up-to-date.
Security & Compliance: When connecting APIs and sharing data, prioritize security. Use environment variables for API keys, ensure data encryption, and understand GDPR/CCPA implications, especially for international recruitment.
Measure and Optimize: Track key metrics like time-to-hire, candidate response rates, and recruiter productivity. Use this data to continually refine your automation workflows.
Train Your Team: Successful adoption hinges on your team's understanding and buy-in. Provide thorough training on new tools and workflows.
Leverage Integrations: The real power comes from connecting tools. Explore the API documentation for your ATS (Workable, Greenhouse) and consider using an orchestrator like n8n for truly seamless operations.

Conclusion

The landscape of recruitment is constantly evolving, and the agencies that embrace intelligent automation are the ones that will thrive.

Moving beyond basic ATS functionality, these solutions empower recruiters to reclaim hours from manual tasks, deliver superior candidate experiences, and ultimately, secure top talent faster.

The future of e-recruiting productivity lies in these integrated, intelligent systems, allowing your agency to move from reactive to proactive, and from efficient to truly exceptional. Start exploring these tools today and build an automation strategy that truly works for your agency.

How I Built and Compared a Custom CNN vs MobileNetV2 for Boat Image Classification

Ezinne Anne😎👩🏿‍💻 — Sat, 24 May 2025 12:41:23 +0000

Hello everyone! How are you all doing?

Today, I want to share a mini story about my experience completing a deep learning assignment—part of my DeepTechReady Week 2 Challenge, where I built and compared two models: a Custom CNN and a MobileNetV2 for multiclass boat image classification.

Let’s dive in!

Background: My ML Journey

First things first—yes, I’m learning machine learning!

In February 2025, I joined a data science and machine learning training program called DeepTechReady, organized by Data Science Nigeria and 3MTT NITDA. Classes kicked off in March with foundational topics, and by April, we were neck-deep in specialization. I chose the Data Science/Machine Learning track.

During Week 2 of the Deep Learning module, we were given this assignment:

Objective:
Build and compare two CNN models—one custom and one pretrained (like MobileNetV2)—to classify a dataset of boat images into multiple classes. Evaluate and determine which performs better.

Challenge accepted.

Step 1: Understanding and Preparing the Dataset

I used Google Colab for this task and mounted my Google Drive:

from google.colab import drive
drive.mount('/content/drive', force_remount=True)

I added force_remount=True because Colab would yell at me if I ran the cell twice.

Here’s what I noticed about the dataset:

Oddly, the train folder had 4000+ images, while the test folder had 24 class folders.
In the test folder, some subfolders had hundreds of images, while others had just 5. That imbalance would become a big deal later.

Initially, I didn’t realize this was a multiclass classification problem, but the structure of the test folder made that clear quickly.

To make things work, I used the 24-class test folder and split it into training and validation sets:

 train_ds = tf.keras.utils.image_dataset_from_directory(
        data_path,
        validation_split=0.2,
        subset="training",
        seed=123,
        image_size=(img_height, img_width),
        batch_size=batch_size
    )

  val_ds = tf.keras.utils.image_dataset_from_directory(
        data_path,
        validation_split=0.2,
        subset="validation",
        seed=123,
        image_size=(img_height, img_width),
        batch_size=batch_size
    )

class_names = train_ds.class_names
num_classes = len(class_names)

Output:

Found 4774 files belonging to 24 classes.
Using 3820 files for training.
Using 954 files for validation.

Step 2: Building a Custom CNN from Scratch

Next, I created my own Convolutional Neural Network.

custom_model = models.Sequential([
        layers.Conv2D(32, (3,3), padding='same', activation='relu', input_shape=(224, 224, 3)),
        layers.Conv2D(64, (3,3), padding='same', activation='relu'),
        layers.MaxPooling2D(),
        layers.Dropout(0.25),
        layers.Conv2D(64, (3,3), padding='same', activation='relu'),
        layers.MaxPooling2D(),
        layers.Dropout(0.25),
        layers.Conv2D(128, (3,3), padding='same', activation='relu'),
        layers.MaxPooling2D(),
        layers.Dropout(0.25),
        layers.Flatten(),
        layers.Dense(128, activation='relu'),
        layers.Dropout(0.5),
        layers.Dense(num_classes, activation='softmax')
    ])

I compiled and trained the model:

custom_model.compile(
        optimizer='adam',
        loss='sparse_categorical_crossentropy',
        metrics=['accuracy']
    )

custom_model.fit(train_ds, validation_data=val_ds, epochs=5)

This lasted for more than one hour sadly and I found out from my colleagues that it was because I used CPU instead of GPU. I learned something valuable there

Model Summary: Custom CNN

Here’s what the architecture looked like:

Total params: 38,935,370 (148.53 MB)
Trainable params: 12,978,456 (49.51 MB)
Non-trainable params: 0 (0.00 B)
Optimizer params: 25,959,914 (99.02 MB)

My custom CNN was decently deep and had about 38 million parameters in total when flattened out. It handled the task okay but definitely had some overfitting issues, especially with the imbalanced classes.

Step 3: Transfer Learning with MobileNetV2

Next, I turned to MobileNetV2, a lightweight pretrained model.

base_model = MobileNetV2(
      input_shape=(224, 224, 3),
      include_top=False,
      weights='imagenet'
 )
 base_model.trainable = False

Then I added my custom classification head:

mobilenet_model = models.Sequential([
      base_model,
      layers.GlobalAveragePooling2D(),
      layers.Dense(128, activation='relu'),
      layers.Dropout(0.5),
      layers.Dense(num_classes, activation='softmax')
 ])

 mobilenet_model.compile(
      optimizer='adam',
      loss='sparse_categorical_crossentropy',
      metrics=['accuracy']
 )

 mobilenet_model.fit(train_ds, validation_data=val_ds, epochs=5)

Initially, I used 180x180 for the custom model and 224x224 for MobileNetV2. This caused issues when comparing performance, so I retrained the custom CNN using 224x224 for consistency.

Results: Comparing Custom CNN vs MobileNetV2

I evaluated both models using classification reports.

Here’s a summary of what I observed:

Custom CNN:

Performed better on high-frequency classes.
Struggled heavily on minority classes (many zero precision/recall).
Had more parameters and took longer to train.

MobileNetV2:

Generalized better across classes—even minority ones.
Faster to train.
Thanks to ImageNet pretraining, it handled even subtle boat differences better.

Verdict: Transfer learning wins here. MobileNetV2 outperformed the custom CNN in both accuracy and generalization—especially on imbalanced datasets.

Final Reflections

Here’s what I learned:

GPU matters—always check your runtime!
Transfer learning is powerful for real-world datasets, especially when you have class imbalance or limited compute.
Building custom CNNs is still a great learning experience and gives you full control over architecture.
It’s okay to experiment, make mistakes, and iterate—because that's where deep learning actually clicks.

Here is my notebook link: https://github.com/ezinneanne/DeepTechReady-Work/blob/main/DSML%20Notebooks/Week2_Assignment.ipynb

Thanks for reading my deep learning adventure! If you’re starting out, don’t be afraid to break things and learn from them—that’s the real magic.

Got questions or suggestions? I’d love to hear your thoughts!

Most Profitable Tech Careers You Should Know

Ezinne Anne😎👩🏿‍💻 — Thu, 09 Jan 2025 03:15:08 +0000

If you are aiming to build a career in tech and want to explore lucrative fields, this guide is for you. The tech industry values skills and experience over formal degrees, making it possible to succeed with self-learning and dedication. While finding a job in tech can be challenging, the potential for career growth and high earnings makes it worth the effort. When we say, "profitable tech careers," we mean not just the pay but also careers that provide opportunities for personal growth and advancement.

The most profitable tech career paths you could build, in no particular order, include:

Data Analyst
Software Engineer
Cloud Computing
Artificial Intelligence
Cybersecurity
Product Management

Data Analyst

Data analysts earn competitive salaries, often working remotely. Their primary role is to collect, organize, and analyze data to help companies make informed decisions. There is a career demand for data scientists in industries like marketing/sales, healthcare, software/IT, and finance. With focused learning, you could become a data analyst in a year.

Certifications:

Salary Range: $120,000 to $240,000 annually

Software Engineer

Software engineers design, build, test, and deploy applications, making them essential in the tech space. Mastery of at least one programming language and problem-solving skills is key to success in this role.
There are many programs offering courses on these languages that you could use to become a software engineer.

Some of them are:

Salary Range: $75,000 to $150,000 annually

Cloud Computing

With organizations adopting cloud technologies, the demand for cloud skills is rising. Career paths include cloud engineering, site reliability engineering, DevOps, and more, with opportunities to advance to cloud architect roles.

Certifications:

Salary Ranges:

Annual salary for cloud engineer ranges from $73,000 to $120,000
Annual salary for site reliability engineer ranges from $80,000 to $135,000
Annual salary for DevOps engineer ranges from $85,000 to $140,000

Artificial Intelligence

The AI boom has created a high demand for machine learning engineers, AI researchers, computer vision specialists, and natural language processing experts. These roles involve developing and deploying AI-powered solutions.

Certifications:

Salary Range: $100,000 to $150,000 annually

Cybersecurity

Cybersecurity offers a stable and diverse career path, with specializations in cloud security, application security, data security, and more. As technology advances, the need for cybersecurity experts continues to grow.
There are organizations offering security programs such as Cisco Networking Academy.

Some of them are:

Salary Range: $90,000 to $130,000 annually

Product Management

Product managers lead teams to build and launch products. They handle team coordination, task delegation, and progress reviews. If you enjoy organizing and managing projects, this career might be ideal for you.

Certifications:

Salary Range: $80,000 to $150,000 annually

By choosing any of these career paths, you can be on a journey to a rewarding and financially secure future in tech. Now, there are certain steps you can follow to achieving your tech career dream.

Steps to Build Your Tech Career

1. Learn the Basics
The tech industry has a low entry barrier, making it accessible to many. Start by learning the fundamentals of computer science and software architecture, especially if you are pursuing programming-intensive fields. A firm foundation will help you grasp advanced concepts more easily.

2. Attend Training Programs or Bootcamps
Consider enrolling in boot camps or training programs, either online or in-person. These courses, like the ones mentioned earlier, provide structured learning and practical knowledge to help you build projects and gain relevant skills.

3. Build a portfolio
A portfolio is your gateway to showcasing your skills to potential employers. To create an interesting portfolio:

Build projects that solve real-world problems.
Participate in hackathons.
Contribute to open-source projects.

With these activities, you can gain real world experience while boosting your portfolio for employment opportunities.

4. Network with people
Your network can be a powerful asset. Join tech communities, attend events, and take part in competitions. Connecting with your peers and industry experts will provide opportunities for collaboration, learning, and mentorship.

Summary

There are other fields in software tech, such as design, blockchain development, writing/documentation, animation, and community management, which are also profitable.
No matter the field, being skilled at what you do is crucial. Focus on mastering core concepts by taking tutorials and applying what you learn through projects. These projects serve as your practical resume, showcasing your ability to solve problems.

How to Write Accessible Technical Documentation – Best Practices with Examples

Ezinne Anne😎👩🏿‍💻 — Mon, 15 Apr 2024 11:56:06 +0000

When you’re writing technical documentation for a project or a tool you’re working on, you’ll want it to be accessible. This means that it will cater to and be usable by the diverse global audience on the web.

Web accessibility aims to make it possible for anyone to access web content. There are common accessibility best practices for designers, developers, and writers. This article will cover some best practices for creating technical content.‌

What is Web Accessibility?

Web accessibility is the practice of making it possible for anyone to consume or create content on the web, regardless of any health, economic, geographic, or language challenges they may have.

Why is Web Accessibility Important?

It is important to apply web accessibility best practices in your projects for a number of reasons.

First, it’ll help you reach a wider audience. When a person who may have different abilities comes across some data on the web — say on your website — they’ll want to learn more or use the data. But if they are not able to access it, you will not be happy or have a good experience.

Imagine how many people are unable to utilize the web because they are not considered when devs and designers are making decisions about how the product, website, or tool will be built.

Another important thing about accessibility is that it improves your brand’s quality. Letting people know you are an accessibility-oriented person or company by implementing it in your work shows that you want your information to be available t everyone. It also displays your versatility in your craft and your ability to improve and adapt with changing times and trends.

Also, as an individual, applying accessibility best practices benefits you as well. There are possible employment opportunities for developers and designers with great accessibility skills.

Good accessibility practices mean good SEO practices too, which can result in more visibility for your work.

Finally, accessibility is enforced by law in certain countries around the world, and web accessibility strategies are implemented by certain countries. There could be legal consequences if you overlook accessibility on your websites and apps.

How to Write Accessible Technical Documentation

Software engineers have a key role in making the web accessible. But when it comes to writing documentation, technical writers also have a role to play in improving web accessibility.

Technical writers help write various types of content, like user guides, tutorials, API references, code documentation, and so on.

Now, let’s look at some of the best practices for implementing web accessibility in technical writing. These strategies will help improve your documentation and make it more user-friendly and accessible to everyone.

Use clear headings and paragraphs

When writing content, you should make sure to use headings — along with the proper heading hierarchy (H1 for the title of the page/article, H2 for major headings, H3 for subheadings, and so on).

Also, make sure to break your content up into paragraphs so it’s easier to read and understand.

When you introduce a new topic, use a heading to call that out. When you talk about smaller topics within that section, use subheadings to alert the reader.

Headings are also important to help screen readers understand a page’s contents and how to navigate through them. So use headings to help guide readers through the text in a logical manner.

You denote headings in markdown with hashes.

Here’s an example of headings in hierarchical order.‌

# Use H1 for the page title

## Use H2 for major headings 
This heading is a main heading for the main section content. 

### Use H3 for subheadings 
This heading is a subheading that goes deeper into one of the main section's points.

Make your content clear and concise

Overall, try to keep your sentences quite short in your docs. This makes them easier to read and understand (for everyone). You can also use images or videos to provide more details if needed.

Make sure you give the full meanings of any acronyms you are using for the first time. Also, always use simple sentences, and try not to use ambiguous words.

Here’s an example of an overly complex, long sentence with difficult vocabulary:

The web3 running on the Blockchain structure which is transparent, secure, immutable, decentralized would require the processes of artificial intelligence, where it would read data, process, and store information.

This is better:

Web3 is built on the transparent, secure, unchangable, and decentralized structure of the blockchain. It uses artificial intelligence processes to read, process, and store information.

Your content should contain the main points you’re trying to make, removing all forms of ambiguity.‌ ‌

Use informative link text

All your in-line links should use clear, detailed, and descriptive text. You can describe the link’s purpose or the company’s name if it is a brand, for example.

Links are important for improving the ranking of a page. And using links like “Click here” or “Read More” is not all that helpful, as they don’t tell the reader much about what they’ll find at that link.

For instance, if I wanted to link a W3C (World Wide Web Consortium) accessibility tutorial to this article, I could use the following format: Check out these resources for content writers by W3C.

Add alt text and captions to media content

Images
Adding descriptive text to the alt text attribute allows screen readers to be able to read out the alt text associated with an image. Alt text also helps search engine bots that crawl the page know how to classify that content.

When you’re adding alt text, describe the purpose of the image and not what the image is. For instance, let’s say you’re using an image that shows some shipping containers in a section that is about containerization.‌

Instead of writing alt text like “various containers on a ship in motion”, you could write “various containers on a ship in motion to illustrate the packaging structure and process of a digital container.”

While alt text serves as an alternative for the image, captions give more details about the image. You can use HTML to insert image captions. Markdown does not support image captions, but markdown documentation sites usually have a way around it (for example, through plugins — ReadTheDocs, MkDocs — or inserting HTML via a custom component -Docusaurus).

As an example, I’ll show you how to add image captions in Docusaurus.

How to add image captions in a Docusaurus .md file:

Create a folder components in the src folder.
Create a file named figure.jsx.
Add this line of code to it:

import React from "react"; 
import useBaseUrl from "@docusaurus/useBaseUrl"; 
export default function Figure({ src, caption }) {
  return ( 
  <figure> <img src={useBaseUrl(src)} alt={caption} /> 
  <figcaption>{`Figure: ${caption}`}</figcaption> </figure> 
  ); 
}

Go to the .md file where you have the image and import the code.

import Figure from '@site/src/components/figure'; 
import figure1 from 'path-to-image';

Add it to the file.

<Figure caption="This is a caption for the image" alt="This is alt text" src={figure1} />

The image will now display with a caption.

‌Videos
To caption videos, HTML is a great option. But if you are using markdown, you can embed videos from YouTube and Vimeo using the <iframe> tag. These apps offer in-built caption support so you can enable captions before adding the embed code.

You could also install third-party plugins for this purpose.

Here’s another tip: avoid flashing content in your videos as it could lead to seizure triggers. If your video has flashing bright colours, ensure that it does not exceed two times within a second.

Add transcripts to audios and videos

It’s a good idea to add transcripts to your audio and video content. Not everyone will want to watch or listen to the content. But they may be curious to know what it is about.

By adding a transcript, you make it easier for anyone to navigate through the content and get the information that they need.

Transcript for audio
For audio content, you can insert transcripts using HTML.

Here’s an example:

<audio controls muted><!--Always set your audios to muted--> 
  <source src="ringtone.mp3" type="audio/mpeg"></source> 
</audio> 

<code> 
  <p>Here is a transcription of the text</p> 
  00:03 = I am going to be productive today<br><br> 
  00:05 = I am going to be productive today<br><br> 
  00:08 = I am going to be productive today<br><br> 
  00:10 = I need to be productive today<br><br> 
  00:11 = I have to be productive today<br><br> 
  00:13 = I should be productive today<br><br> 
  00:16 = I am going to be productive today<br><br> 
  00:18 = I ought to be productive today<br><br> 
  00:21 = I have to be productive today<br><br> 
  00:23 = Productivity matters to me <br><br> 
</code>

For markdown documentation sites like Docusaurus, you can create a custom component.‌

In your src/components folder, create a file named transcript.jsx.
Insert this code:

import React, { useState } from 'react'; 
export default function Transcript({ }) { 
  const [showTranscript, setShowTranscript] = useState(false); 
  const toggleTranscript = () => { 
    setShowTranscript(!showTranscript); 
  }; 
  return ( 
    <div> <a href="#" onClick={toggleTranscript}> { 
    showTranscript ? 'Hide transcript' : 'View transcript'
    } 
    </a> {showTranscript && ( <div id="transcriptText"> (insert your transcript text here) </div> )} 
    </div> 
  ); 
}‌

Go to your markdown file and import it.

import Transcript from '@site/src/components/transcript'; 

<Transcript />

Note: I added some tweaks to the code to make transcript display optional. You can edit it if you want the transcript to show as the page loads.

Transcript for video
Now for videos, YouTube is a great option. It provides inbuilt transcripts for your videos. So, you can always embed YouTube videos in your docs.

The transcript is in the video description after the main details. The transcript will display with the timestamps when you click the “Show Transcript” button.

Add code snippets and use the colour contrast technique

How to add code snippets
Use code blocks within the text to explain code instead of images. You could also use code snippets to showcase the output of your code. Unless it is necessary to add an image, you should use code snippets.

For instance,

index.html

<!DOCTYPE html> 
  <html> 
   <head> 
    <meta http-equiv="content-type" content="text/html; charset=utf-8" /> 
    <title>A calculator app</title> 
    <link rel="stylesheet" href="styles.css"/> 
   </head> 
   <body> 
   </body> 
  </html>

This will allow screen readers to read through the code, which they are not able to do with screenshots.

Colour contrast technique
The colour contrast technique implies using colours that are opposite or heavily contrasting.

For example, using black text on a white background has a high contrast, as opposed to using light brown text on a brown background.

When combining colours, you could use an accessible colour palette like Color Safe.‌

Add translation options

There are documentation sites that provide translation options where you can build your docs in multiple languages, websites like Jekyll. This is an example.

Docusaurus is also another doc site that provides multilingual options using Crowdin or Git.

Use accessibility testing tools

There are tools you can use to check for errors in accessibility in your docs. Some examples are WAVE (Web Accessibility Evaluation Tool) and AXE (Accessibility Engine).

Also, you can get the NVDA(NonVisual Desktop Access) screen reader to test out your content. This software will let you know how the content of your documentation will be perceived by a user using a screen reader.‌

Set up an improvement or suggestion box

Finally, it may not be possible to cover the needs of every user. So you could add a suggestion or improvement box, allowing users to send feedback about how you could further improve the content. Hearing firsthand from users can help you know how best to make the docs accessible for them.

To add an improvement box, you could use an external form link that stores the users’ inputs or you could set up the suggestion box in the docs.

How to add an external form link in Docusaurus

You would need to create a custom component for that.

Go to src/components folder and create a file feedback.jsx.
Add this code:

import React from 'react'; 

export default function FeedbackButton({ href }) {
  return ( <a href={href} target="_blank" rel="noopener noreferrer" > Give Feedback </a> ); 
};

In your markdown file import it:

import FeedbackButton from '@site/src/components/feedbackbutton';

Insert the link

<FeedbackButton href="https://forms.google.com" />

When you run it on your docs, it should showcase a link to Google forms. Google Forms is an example, you could add the link to your company website or server.

Here’s what it’ll look like:

Summary

To follow and implement these accessibility best practices, you can consider creating or using an already made style guide. This can help you consistently implement these practices and make it easier for you and other technical writers on your team.

There are style guides focused on accessibility for technical writers, such as the following:

That sums up my tips about web accessibility practices in writing. I’m a technical writer, and you can reach out to me on Instagram or hire me via Upwork. Thank you for reading.‌

My Experience With OneEntryCMS - A Headless CMS

Ezinne Anne😎👩🏿‍💻 — Wed, 13 Dec 2023 19:09:47 +0000

We use content management systems to render web content pages, such as blogs, portfolios, e-commerce sites, and so on.
Traditional CMSs like WordPress have been in use over the years for these functions.
With the need for more flexibility and customization arising, headless CMS came to be. With a headless CMS, you can build more customized systems to your taste.

According to WPEngine, there has been tremendous growth in the number of companies adopting the headless approach.

There are lots of headless CMS in the market with their features.
Recently, I came across a Headless CMS that lets you have flexibility and customization with admin access and more during the Gitex Global Devslam 2023.

It is called OneEntryCMS and I think it is pretty cool. This CMS provides users with an admin access page where they can assign more admins who would manage the application and collaborate in executing tasks seamlessly.
Apart from the admin access functionality, other features come with this CMS and I would love to share them with you.

This article will cover:

Getting Started With OneEntryCMS
- Practical Step
Features Of OneEntryCMS
- For personal account
- For the admin dashboard
OneEntryCMS Pricing And Support
Benefits Of OneEntryCMS
OneEntryCMS Alternatives
How OneEntryCMS Stands Out

Getting Started With OneEntryCMS

OneEntryCMS has an easy start which requires your email and phone number. You will receive an email with the login and password details to use for the project.
This would give you access to your administrative dashboard where you can create content.

Practical Step

Open oneentry.cloud
First, there is a prompt to share an email address, phone number and name.

This would create a personal account for you, after which you can create a project.

After you name your project, next is to select a pricing plan. You would see the pricing plans on the screen. Since I was using this for the first time, I chose the basic plan.

Click on Create. This would create a project.

Afterwards, you get an email from OneEntry which gives you your login details for that project.

With those login details, you can click on the new domain page you have created.

After you log in, you will gain access to the admin dashboard which you could use to set up your webpage.

Features Of OneEntryCMS

For the personal account

How OneEntryCMS works is that you would need to create a personal account and set up a project. With this project, you would have access to other features for your application.

In your account, you should have these options:

Profile - this section will contain the details which you used for registration.
History - this records your payment and action history in the application.
Projects - This houses all the projects that you create.
Technical support - This is where you ask questions or make a request.
Public offer - This contains the license agreement and privacy policy.
Materials - This is where you find the mTLS certificate.
API - This contains details and code snippets for integrating the Headless CMS API.
NPM - This contains the code snippets for installing, setting up, and using OneEntry headless CMS SDK integration.

For the admin dashboard

In the admin dashboard, there are a couple of features, which include:

Menu
Journal
Administrators
Content management
Catalog
Managing forms
Settings
Menu - In the Menu, it contains name and marker fields to create a new menu for the page.

Journal - The Journal section contains a record of all content changes.

Administrators - This section lets you set up administrators with the permissions you want them to have.

Content management - This is where you set up the system. With this feature, you can create context such as text, catalog, forms, and so on, depending on your desired system.

Catalog - This is where you create and configure the items for your page, such as images, products, and so on.

Managing forms - In this section, you can add details and set up forms for user interaction.

Settings - Here, you can set/adjust:

Modules - This contains all the modules.
Attributes - this is where you set the attribute.
Templates - This contains templates which you could use.
Preview templates - As the name implies, this is used to view templates.
Content languages - Here you can decide which language to use.
App tokens - This contains tokens you generate for the application.
General settings - This is where you can change other use cases.

OneEntryCMS Pricing And Support

Pricing

For pricing, OneEntryCMS offers a 30-day free trial.

Study plan: $4.99/month
Basic plan: $29.99/month
Standard plan: $49.99/month
Premium plan: $199.99/month

The cool thing about the pricing is that irrespective of the plans, you would get access to the mTLS certificate ensuring maximum security.
Also, all the plans provide the option to add an administrator.

Support

OneEntryCMS has a fast-response customer service. They also have a YouTube channel where they create content with detailed guides on how to use the functionalities of the application.

Benefits Of OneEntryCMS

Full Admin Access
OneEntryCMS provides full admin access to build a web page. This differs from other CMS. As with this admin portal, you can set up and customize your webpage as you would wish. Other CMS options present a template code without access to improve that functionality. However, with OneEntryCMS, you can gain access to improve your admin functionalities via modules, forms, and so on.
Flexibility
Another benefit of OneEntryCMS is flexibility. Headless CMS came to be as a need for flexibility. OneEntryCMS makes that possible through its admin access features (flexibility to add admins). Access to assign admin permissions on a web page.
Simple User Interface
OneEntryCMS has a simple user interface with colourful themes and simple labelled buttons across the screen, which makes it easier to understand the screen and navigate through the application. Also, the interface has simple designs, and it's not complex for easy comprehension.
Multilingual Support
OneEntryCMS has support for multiple languages. This makes it easy to collaborate with people from other languages. If you are working on a webpage and some of your team members communicate with other languages. You could collaborate with them on the webpage without worrying about language barriers.
Access Rights And Forms Module
With this CMS, you could set admins which you would manage. You can also assign permissions to the admins, defining the areas they are in charge of or not.
The next benefit is in the forms. You can set up forms and modules for your webpage describing how it should work.
Security
OneEntryCMS is safe to use as it provides an mTLS certificate. With this certificate, it will prevent unauthorized access, enhance the security of your webpage and protect your privacy.
Integration
It provides API and SDK integration. This means with this CMS, your application can access the data on the CMS using the API. You can also connect your application to the CMS using an SDK. That way, you can access data on the webpage.

Note: These are the current features on the system. However, these features could change with time, as there are continuous updates on the system.

OneEntryCMS Alternatives

ButterCMS

ButterCMS is a headless CMS that supports multiple programming languages. It provides content delivery networks and webhooks. Also, it is secure, as it makes use of two-factor authentication and role-based access control.
ButterCMS provides APIs and a customizable admin page.

Strapi

Strapi is a headless CMS that allows customization and integration of an API.
The CMS has a rich intuitive interface that makes it easy to navigate through. It has a developer community with ample resources about the product and it works.

Content stack

Content stack is a CMS tailored to provide flexibility and customization. It supports the use of add-ons and API integrations. Content stack provides multilingual support for various languages. It also supports the use of modules.

How OneEntryCMS Stands Out

OneEntryCMS provides a fully functional admin dashboard with the ability to add more administrators as you would wish.
OneEntryCMS provides API and SDK integration. With OneEntry, you can get tokens to integrate your application. This would improve the functionality of your application, making it stand out.
Improved security is another top-notch benefit. By providing all of its users with an mTLS certificate which would ensure privacy protection, unauthorized access, and protection against malicious site attackers.
Finally, there is also no need to set up a server or data storage as it backs all your data up on the cloud.

Conclusion

Although relatively new in the market, OneEntryCMS is rising as a compelling option in the headless market.
As someone who uses content management systems, it was cool for me to have gotten this CMS. I used this to build a project for a client recently and soon I will release an article on it. Anticipate!

I understand OneEntryCMS has more features which they will release soon. Some of them are push notifications to keep one's users informed of any update, versioning which would ensure tracking of changes, content history, and easy rollback.
Webhooks and Web sockets to further facilitate integrations, and streamline workflows and data exchange.
They will add more modules as well, such as Blocks, Users, Orders, Discount, and more.

With these features involved, it is set to provide the actual headless CMS businesses really need.

Containers: what is containerization and container orchestration?

Ezinne Anne😎👩🏿‍💻 — Sun, 23 Apr 2023 06:36:03 +0000

Containers are formally huge iron boxes to ship items to another location.

In computing, containers are virtual "boxes." This time, you use them to package applications with all their needs and ship them to your audience or users.

This pattern of packaging and shipping applications in the cloud has been gaining momentum because of the benefits.

This article will cover,

What is containerization?
What is a virtual machine (VM)?
Containers vs virtual machines
Benefits of containerization
What is container orchestration?
Benefits of container orchestration
Tools for containerization and orchestration

Image source

What is containerization ?

Containerization is the process of running applications in an isolated environment with the necessary libraries and network processes for the application on the same operating system.

Containerization places an application on its own to run hitch-free without interference with the OS. A containerized app can run on any operating system removing set-up and compatibility issues.

Containerization is a form of virtualization, and containers are different from virtual machines. Containers have a lightweight structure, and you can containerize any application.

What is a virtual machine (VM)?

A virtual machine (VM) is an emulation, simulation, or virtual prototype of a physical computer that runs on a physical computer. The physical computer that it runs on is the host, and the VM is the guest. A virtual machine uses the CPU, memory, and space of the computer it is on to create an operating system and build applications on it.

With virtualization, you can build multiple virtual machines, each with its own operating system. This is possible with software called a hypervisor, which acts as a connection between the host and the virtual machine. The hypervisor shares computing resources with the virtual machine and inspects the machine often.

Containers vs virtual machines

Containers have their own network, memory, and processes, but they use the same operating system.

Containers contain an application with the necessary libraries, and they consume the resources they require from the operating system they are on.

Virtual machines use different operating systems for each machine. They also use networks, memory, and processes from the physical computer.

Virtual machines contain a virtual operating system and virtual hardware for the system and the application that will run on the machine with the necessary libraries.

Image source

Benefits of Containerization

Efficient use of resources

Containerization makes containerized applications use their resources properly. even though the container runs on the operating system. It uses minimal memory and space, so it does not overload the system.

Portability

Containerized applications are compatible with a wide range of platforms and operating systems. They also do not have setup constraints, as they can run in different test and production environments. This makes it portable and easy to use anywhere.

High speed

Containerized applications usually occupy little space and make little use of CPU resources. This makes them faster and able to run at high speeds.

Security

Containerization secures applications because of its isolated nature. It keeps the apps safe from possible vulnerabilities. Also, even if a container is under attack, the container host is safe from being attacked.

Streamlined deployment and management

Containerization ensures containers have a standard unit of deployment. Because of their light structure, you can deploy them easily. You can also roll back or make updates with ease because of the container's structure.

What is container orchestration?

Container orchestration is the process of deploying multiple containers and managing them using a container orchestration tool. The container orchestration tool automates the use of containers instead of running and deploying them manually. The tool takes care of it instead.

This is very useful in large organizations where they could deploy hundreds of thousands of containers in a day. So the tool comes in handy to simplify the process.

Benefits of container orchestration

Automatic deployment

Container orchestration tools automate deployments, making it easier to deploy many containers, thereby speeding up the process and eliminating the complexities involved.

Management of containers

The tools also manage the containers by running health checks, replacing failed containers, or restarting them. This makes containers easier to use and ensures the application is available to users.

Load balancing

Orchestration tools distribute workload among the containers so there is no overload on any container. Each of the containers gets to work efficiently when you are running the application.

Making Updates

With orchestration, you can make updates easily. When a team is making updates to an application, they can roll out a new version of the application across the cluster. This will reduce downtime and ensure that the application is available during the update process.

Access to and use of resources

You can access how the containers use resources on the cluster. Orchestration tools provide visibility into that, making it possible for you to optimize resource allocation. So you could distribute the necessary resources to the containers that needed them.

Tools for containerization and orchestration

Docker

Docker is an open-source containerization platform that builds, packages, and deploys applications and their dependencies using containers.

Docker can run on popular operating systems like Windows, Linux, and macOS.

Docker uses the Docker engine for containers and Docker Swarm for orchestration. The Docker engine is the host that runs on an operating system for building containers.

Kubernetes

Kubernetes, also known as K8S, is an open-source container orchestration tool. It automates deployments and distributes loads among containers. It also monitors containers and replaces failed ones.

Although originally built by Google, Kubernetes is currently under the Cloud Native Computing Foundation (CNCF).

Kubernetes has a rapidly growing population of engineers using it. Some organizations offer orchestration services using Kubernetes. Some of them are the Google Kubernetes Engine (GKE), Azure Kubernetes Services (AKS), and so on.

Apache Mesos

Apache Mesos is another orchestration tool for managing container-based applications. It uses Marathon to manage clusters and Shipworm as a network tool. It is customizable, and you can use it for large, complex applications, even virtual machines.

The Apache Mesos Project team is in charge of this orchestration tool, and they have a thriving developer community.

Nomad

Nomad is an open-source orchestration tool that manages containerized and non-containerized applications. It is cloud-agnostic, which means it can run in any cloud environment.

It has a simple installation process, is flexible, and aims to eliminate the complexities surrounding orchestration with other tools.

Nomad integrates with other tools like Consul and Vault from its parent company, Hashicorp.

You can also use it with Kubernetes and other orchestration tools.

Summary

Containers are different from virtual machines. Container orchestration takes the containerization process to a whole new level by introducing automation and simplifying the process. Many businesses have started using containers for their applications. Soon, we might have a new standard for containerized apps.

Monolithic vs. Microservices Architecture

Ezinne Anne😎👩🏿‍💻 — Sat, 08 Apr 2023 17:22:30 +0000

Monolithic and microservices architectures are patterns you could use to build software applications. The major difference between both architectures is in their structure.
Monolithic architecture is the parts of a program that make up a unit.
On the other hand,
Microservices architecture comprises different services running independently.
In this article, you will learn:

What is monolithic architecture?
How it works
What is microservices architecture?
How it works
Pros of monolithic architecture
Cons of monolithic architecture
Pros of microservices architecture
Cons of microservices architecture
Key points to note about monolithic and microservices architectures

What is monolithic architecture?

In plain English, when you say something is monolithic, it means it has a unit that is interwoven together, with large parts making up a single form.

Monolithic architecture in software development is a pattern of building a program as a unit. It has only one code base, which contains all the codes in a program.

Every part of the program is in the code base. Hence, refactoring code or even making minor updates is tedious and could break the entire application. Applications using this type of architecture could easily shut down when a developer makes an update containing a bug.

How it works

The monolithic architecture combines all the parts of the program into a single code base. These parts comprise features (packages) coined together. In a monolithic application, all the parts interact with a single database.

During updates, you could stop the system and afterwards deploy the entire stack. But this happens to applications that are big. New applications are relatively easier until they keep growing up to that point.

Image source

What is Microservices architecture?

Microservices architecture is a pattern of software development where software splits into separate services. They connect these services with APIs and operate independently from the code base.

Developers work in teams, and each team is in charge of a service. They can deploy their updates without affecting the code base or other microservices in the network. Microservices architecture is ideal for companies building large, complex applications.

How it works

In a microservices architecture, each service runs independently with its own memory space. APIs connect these services. The connection is in a light structure to allow each service to deploy and scale according to demand.

Microservices are small-sized and meant to handle certain operations. If any of them goes down, it will not have much effect on the entire system.
Also, teams work on each service, focusing on their specific areas without being overwhelmed.

Microservices architecture is a modern pattern in system design. Some startups begin with a monolithic design, and as the software grows, they move to microservices. However, there are fast-paced start-ups that start with microservices right away. This is a good decision, as refactoring monolithic applications to microservices is difficult. It would require skilled expertise, leading to higher costs.

Pros of monolithic architecture

Simplicity

Monolithic architecture has a simple design as it is a single structure. It is simple to code and run, especially when building a new application.
It is not overly complex like microservices, and it does not require complex processes for security.

Low cost of operations

Monolithic applications do not require extra funding for maintenance. A small team can manage the simple processes involved with little cost. There is no need for an excess workforce.

Easier testing

Their applications do not require complex tests. Because of their design, they have an easy mode of development. This applies to testing too; they involve simple series of tests, unlike microservices.

Cons of monolithic architecture

It is too rigid and does not have a flexible structure

Monolithic architecture does not support the use of different technologies. Making tweaks or changes to it would involve the entire application. This can cause it to shut down easily if there are harmful bugs.

Difficult updates

It does not have singular deployments. Because of the design, it cannot accommodate multiple deployments. It can also have slower build generation, making the deployment stage tedious.

Bugs in production

In monolithic architecture, bugs in production could affect the entire application. These bugs are usually noticeable even by users. If they are severe, it will cause the entire application to shut down.

Pros of microservices architecture

Easy to deploy updates

The microservices architecture has an easy mode of deployment. Companies using microservices can make up to 500 deployments in a day. This makes the applications fast and easier to implement changes regarding market trends.

Scalable

The applications are scalable. This means they can handle complex demands without slowing down when such applications have a large volume of demands to handle. They can attend to these requests quickly while maintaining their run time.

Reliable

This is another benefit of microservices. They are reliable as they can continue running even when there are bugs that could shut down the application. Because of the microservices nature of the applications, a particular service could be down if there are bugs in it, but the entire architecture would still be running.

Cons of microservices architecture

Making APIs compatible

Microservices require the use of APIs to connect the services. In most cases, using APIs that are compatible with these services could be an issue. Sometimes, developers would need to design new APIs for services since the APIs were not compatible with the service infrastructure.

Complex series of tests

Microservices require a long series of tests because of their complex structure. Each service would need to undergo all kinds of tests, including security ones, because of the potential security hazards it could cause.

Security vulnerabilities

Microservices use APIs, and these APIs could be a vulnerable point for hackers. Since APIs have always been an easy target for attackers, potential attacks could endanger the entire system. Hence, the need for optimal security in microservice systems.

Key points to note about monolithic and microservices

Monolithic architecture is ideal for small businesses building simple applications. As they have a single codebase, they do not require multiple resources. They have low-security concerns, unlike microservices.
Microservices are ideal for large, complex applications. APIs connect microservices, and these APIs could be a security concern. Hence, it requires security experts on the ground. It also requires teams across the board to work on a particular feature.
Both architectures are great for building, but microservices appear to be the full switch for companies.
Most of the companies that are using microservices architecture began with a monolithic architecture. As their business grew, they had to look for other options to contain their workload, which made them opt for microservices.
Netflix started with a monolithic structure and moved to microservices as their product grew into a large, complex structure.
Some companies use both architectures. For instance, appwrite uses both monolithic and microservices architectures.

Resources

Microservices
Microservices vs monolithic architecture

Continuous Integration, Delivery, and Deployment: Best Practises, Benefits, and Tools

Ezinne Anne😎👩🏿‍💻 — Sat, 25 Mar 2023 21:17:27 +0000

Continuous Integration (CI), Continuous Delivery (CD), and Continuous Deployment (CD) are three important practices in software development that aim to improve the speed and quality of software delivery.

This article will cover:

What is Continuous Integration (CI)?
What is Continuous delivery (CD)?
What is Continuous Deployment (CD)?
Stages of CI/CD
Best practices for CI/CD
Benefits of Continuous Integration
Benefits of Continuous Delivery
Benefits of Continuous Deployment
Common tools for CI/CD

What is Continuous Integration (CI)?

Continuous Integration (CI) is a process where team members push changes they make to the software to a central repository. Before they merge those changes, they run a series of tests to find out whether there are errors.
When a team member makes updates to the software and submits it for merging, it goes through a review by the team lead. The continuous integration tools run automated tests to cross-check the update before merging it.

What is Continuous Delivery (CD)?

Continuous Delivery is a process where you set changes in a staging environment for further testing awaiting deployment. It continues where continuous integration stops.

Continuous delivery ensures that the software update you send to the production environment is ready by conducting further tests and validating the release process. To make deployments, you will need to write a deployment script or click a button.
You could choose when you want to deploy your changes in this case.

What is Continuous Deployment (CD)?

Continuous deployment is the next automated process that occurs after continuous integration.
When you use continuous deployment, it means automatic deployment after integration. So after your changes pass through tests and you merge them, it gets deployed immediately.

Continuous delivery differs from continuous deployment in the sense that companies could choose to apply continuous delivery or continuous deployment.
In continuous delivery, deployment is manual. You could do that by pressing a button, but in continuous integration, deployment happens immediately after continuous integration without further delay.

Stages of CI/CD

Continuous Integration

Code commit: This is the first step. Team members commit their changes to a shared repository, triggering the pipeline to begin.
Build: The pipeline generates a build of the software, including the changes made to it.
Test: The next step is to run a series of tests on the build to find out if there are errors.
Review: After running the tests, a review takes place by the team lead and other stakeholders to view the changes made to the application and how these changes look. CI usually generates a preview site so this review can take place.
Merge: After the review, if the changes pass the checks, merging takes place into the repository.

Continuous Delivery

Continuous delivery takes a step further by staging the updates for deployments.

Release: After team members have added all the expected changes needed, Then the pipeline runs further tests on it before making a release and awaiting deployment.
Deployment: This is when they deploy the release to production and end-users can operate the new deployment. Most times, the team could send the deployed software to a specific set of users for further review. Deployment is manual.
Operate: In this stage, they would operate the application and also inspect all the previous operations for backward compatibility. Just to ensure that it works properly.
Monitor: This is the last stage; it involves monitoring the site to inspect how the application runs on every device and watch out for user complaints.

Continuous Deployment

Code commit like in previous processes.
Build, test, and review
After merging takes place,
Release - Generate a release by staging it in the test environment. Deployment is automatic in this process; it happens immediately after the release stage.
Operate and monitor - Like in continuous delivery, this is the next step that follows suit where users operate the application and you monitor it to notice if there is any harm, in which case you can recall the changes.

Best practices for CI/CD

Here are some practices you could use to apply these processes in your organisation.

Have a documented plan: Set up documentation that details the steps team members are to follow in applying any of the processes.
Versioning: Version control is essential for managing code changes and ensuring that all team members are working on the latest version of the code. There are many version control options, like Git, SVN, Mercurial, and so on. You could use any of them to track changes and team collaboration.
Automation: Automation is an important step in CI/CD. Ensure you apply automation by using tools for CI/CD. With automation, you can run tests on changes, generate previews of changes to share with team members and make fast deploys.
Communication and collaboration: Break down tasks among members to promote communication and knowledge sharing. DevOps promotes participation across all fields, so set up workflows in a way that everyone gets to contribute and partake in the processes.
Intermittent deployments: Make deployments as soon as possible. This would help you monitor the minor updates you pushed to production to avoid complex bugs. Some organisations make 50 deployments daily, and some make 100 deployments daily. That way, they can roll back updates if something goes wrong.
Monitoring: After you make deployments, monitor your updates and user engagements to observe if the updates are great for the software. Use monitoring tools to monitor and measure the performance of your application and infrastructure.

By implementing these best practices, you can build a reliable and efficient software delivery process for your application.

Benefits of Continuous Integration

Some benefits of applying continuous integration are,

Faster software development process

Continuous integration ensures developers can code, build, and commit code within a short time frame.
With tests in place to review the code for bugs. This way, team members can have their commits done and move on to another process.
CI tools automate integration processes, which means members can focus on producing code while CI tests their input before merging it into the source repository.

Better software quality

CI runs a series of tests to ensure there are no errors. This improves the quality of the product. With that, teams could also add user feedback to improve the software. When developers push their changes, if there are any errors, they could easily work on them before making another update.
Also, continuous integration is a consistent routine that ensures that the software quality is always of a high standard.

Reduced possibility of errors in production

Continuous integration runs repetitive tests on updates before merging them. This reduces the possibility of deploying buggy software.
Also, when developers make errors in their commits, they would have to review them and correct the mistakes. This improves the chances of making bug-free updates in production.

Smooth process of communication and collaboration among teams

CI fosters communication among teams, as teams would need to work together in building the software.
With a CI pipeline in place, product managers can set product fixes, and developers can build and share their work across the team. Sometimes, other team members would need to contribute their own input to the product before pushing it to the repository, promoting collaboration.

Frequent code commits daily

With a CI pipeline in place, developers can make frequent code commits in a day. When they fix a specific issue and make a commit, the CI pipeline can take care of the testing while the developer can work on another issue, increasing their work rate.

Benefits of Continuous Delivery

In continuous delivery, some benefits you could gain from it include,

Fast-release process

Continuous delivery eliminates the long, stressful manual release process. With automation, developers can make releases easily until they are ready for deployment.
CD tools run checks to ensure the new releases are accurate and highlight possible errors.

Use of automation

Continuous Delivery uses automation in its release process, which makes the process secure and more efficient. Developers could focus on coding without worrying about the product release process. Which reduces their workload and makes the complete process faster.

Fast delivery process

With the CD pipeline, developers can meet deadlines and make as many updates as possible.
Knowing they can make updates after release, they can deploy and make more improvements for delivery.

Meeting up with market trends

When there is a trend and companies need to adjust to keep getting their checks.
Developers could make updates, and the CD pipeline would release them and make them ready for deployment.
With CD, developers are faster and better able to meet urgent market demands.
It improves developer productivity, making it possible for them to achieve so much within a short time frame.

Benefits of Continuous Deployment

Some benefits of continuous deployment are

Smooth deployment

Continuous Deployment ensures the safe and smooth deployment of code. With just a button click, you can deploy your release. Just like the other processes, continuous deployment uses automation to carry out this process, removing all forms of manual work.

Improves productivity

Continuous deployment improves developer productivity as they have less to worry about. Instead of following through with a manual process of deployment, they can use CDs continuously to deploy code whenever they want and meet their goals.

Improves workflow

Continuous Deployment tools can integrate with continuous integration tools. There are tools that perform both roles, setting up workflows that run across the entire process. After deployment, monitoring takes place in order to inspect for changes, which could be positive or negative.

Accurate monitoring

Continuous deployment involves monitoring the software after deployment to find out the state of the product or if users are unhappy with the launch. The next process that takes place would depend on the monitoring. If, from monitoring, the software is bad, they could roll back the updates. If it needs improvements, then developers would start working on a new feature.

Common tools for CI/CD

Jenkins

Jenkins is a free, open-source and popular continuous integration tool used to build and test applications. It has multiple plugins, which make it customizable and allow for continuous deployment too. It has customised packages for Windows, macOS, and Linux operating systems.

Travis CI

Travis CI is another popular continuous integration tool on the market. It has a free plan and paid plans too. It serves as a CI tool for running tests and building, and it supports a wide range of programming languages. Travis serves primarily as a continuous integration tool, but it also runs deployments of applications. It runs on major operating systems.

GitHub Actions

GitHub Actions is a CI/CD tool that works with the GitHub repository model to build, test, and deploy updates. It is customizable, as you could build your own GitHub Actions clone using their API and run and manage your application as you wish. It is available for all the plans on GitHub, including the GitHub free plan.

BitBucket Pipelines

BitBucket Pipelines is a CI/CD tool that runs on BitBucket. It automates builds and deployments and integrates tools like Jira and Trello into your workflows. It offers free plans and paid plans. BitBucket provides a seamless experience for its users, just like GitHub does.

Semaphore

Semaphore doubles as a CI/CD tool. You could use it to build and test your updates and make releases. It has a seamless deployment process, and it is fast. It has support for multiple programming languages. Like Travis CI, it has paid plans and a free trial. Semaphore cuts across the entire DevOps process, as it can handle continuous integration, delivery, and deployment with no additional integration.

Summary

CI/CD improves software development and reduces the workload on engineers. Continuous delivery involves a manual process in deployment, while continuous deployment deploys automatically.

There are a set of practices you could use to apply these processes in your organisation.

Also, there are popular CI/CD tools like Travis CI, BitBucket pipeline, Semaphore CI, and so on.