Forem: amlan

How to Develop and Deploy an AWS metrics Slack bot using Bedrock Agents and Terraform

amlan — Tue, 16 Sep 2025 00:38:41 +0000

As cloud environments grow more complex, real-time observability becomes crucial. Developers and DevOps teams rely heavily on timely metrics to monitor system performance, troubleshoot issues, and ensure uptime. But jumping into dashboards or digging through CloudWatch logs every time an alert fires can be time consuming. That’s where a conversational interface—like a Slack bot—comes in.

In this blog post, you’ll learn how to build a Slack bot that can fetch and respond with AWS metrics on demand. We’ll leverage Amazon Bedrock Agents to provide intelligent, natural language responses powered by foundation models, and use Terraform to provision and manage the infrastructure. By the end, you’ll have a smart, Slack bot that understands questions like “What the highest CPU usage for my EC2 instance?”—and can answer in plain English with live AWS data.

For more details:
https://amlana21.medium.com/how-to-develop-and-deploy-an-aws-metrics-slack-bot-using-bedrock-agents-and-terraform-8eefae1b3deb

How to deploy a multi Task AI agent via CDK on AWS using Bedrock and Bedrock Knowledgebase

amlan — Thu, 05 Jun 2025 00:27:43 +0000

Artificial Intelligence (AI) agents are transforming the way we interact with software, enabling intelligent automation, natural language understanding, and real-time decision-making. AWS Bedrock and Bedrock Knowledge Base provide powerful tools to build and enhance AI-driven applications without managing infrastructure or complex model training. By leveraging the AWS Cloud Development Kit (CDK), developers can deploy AI agents in a scalable, repeatable, and infrastructure-as-code (IaC) manner.

In this blog, we will walk through deploying a multi-function AI agent on AWS using CDK and using services like Bedrock, and Bedrock Knowledge Base. This agent will be capable of handling multiple tasks, such as answering questions based on a documentation and perform some other task as needed. We will cover the architecture, CDK setup, and key components necessary to build and integrate the AI agent into your AWS environment.

For more details:

https://amlana21.medium.com/how-to-deploy-a-multi-task-ai-agent-via-cdk-on-aws-using-bedrock-and-bedrock-knowledgebase-caa85e920500

How to use SSM port forwarding to access a Private AWS ECS service from your local machine

amlan — Thu, 21 Nov 2024 01:21:25 +0000

In this post, we’ll explore how to leverage SSM port forwarding to seamlessly connect to a private ECS service. We’ll cover prerequisites, configuration steps, and best practices, so you can integrate this powerful capability into your workflow and enhance your troubleshooting steps.

https://amlana21.medium.com/how-to-use-ssm-port-forwarding-to-access-a-private-aws-ecs-service-from-your-local-machine-8aae3de0247a

How to Deploy MongoDB on AWS using Terraform: as a Service on ECS or on DocumentDB

amlan — Tue, 22 Oct 2024 01:28:23 +0000

In today’s cloud-first world, managing and deploying databases efficiently is crucial for maintaining high-performance applications. MongoDB, known for its flexibility and scalability, is a popular choice for developers and enterprises alike. When combined with the power of AWS, you can leverage robust infrastructure and services to ensure your MongoDB deployments are secure, scalable, and cost-effective.

This blog post will guide you through deploying MongoDB on AWS using Terraform, an Infrastructure as Code (IaC) tool that allows you to manage and automate your cloud resources. Whether you’re looking to run MongoDB as a service on Amazon Elastic Container Service (ECS) or leverage Amazon DocumentDB (a fully managed, MongoDB-compatible database service), this tutorial has you covered.

By the end of this guide, you’ll have a step-by-step walkthrough to get your MongoDB deployment up and running on AWS. Whether you’re a DevOps engineer, a cloud architect, or a developer looking to automate your infrastructure, this blog post will equip you with the knowledge to deploy MongoDB efficiently on AWS using Terraform.

For more details:

https://amlana21.medium.com/how-to-deploy-mongodb-on-aws-using-terraform-as-a-service-on-ecs-or-on-documentdb-a62b2bda2132

How to add RAG & LLM capability to Amazon Lex using QnA Intent and Amazon Bedrock models

amlan — Sun, 15 Sep 2024 21:10:41 +0000

Conversational AI has rapidly evolved, offering more dynamic and personalized interactions between users and applications. Amazon Lex, a powerful service for building conversational interfaces, already provides robust capabilities for creating chatbots. However, as user demands grow, the need for more sophisticated and contextually aware responses becomes essential.

This is where Retrieval-Augmented Generation (RAG) comes into play. RAG enhances a bot’s ability to provide accurate and relevant answers by leveraging large-scale knowledge bases and retrieval systems. By integrating RAG with Amazon Lex, you can create chatbots that not only understand user queries but also retrieve and generate information from vast document sets.

In this blog post, we’ll explore how to add RAG capability to Amazon Lex using the QnA Intent, a feature designed to handle questions and answers effectively.

For more details:
https://amlana21.medium.com/how-to-add-rag-llm-capability-to-amazon-lex-using-qna-intent-and-amazon-bedrock-models-2d4a454aefcb

Talk to My Document: A Serverless RAG approach using Huggingface, Amazon Lex and Amazon DynamoDB

amlan — Sun, 28 Jul 2024 17:48:52 +0000

In this Post I demonstrate a RAG approach using Amazon Lex and DynamoDB and Hugging Face llm. This approach enables the use of a Lex bot and LLM to answer questions based on knowledge context from a document. This approach uses LlamaIndex for the whole RAG pipeline.
I have uploaded the whole code for the solution to Gumroad if anyone is interested to follow this.

💡 Post
https://amlana21.medium.com/talk-to-my-document-a-serverless-rag-approach-using-huggingface-amazon-lex-and-amazon-dynamodb-9361da3694fc

🗒 Full code
https://achaklan.gumroad.com/l/serverlessrag

📃 Demo of the Doc ingestion
https://youtu.be/G79vO7Lavww

🤖 Demo of the Lex Chatbot
https://youtu.be/Q7TtIM1jRmM

How to add memory to LLM Bot using DynamoDB

amlan — Thu, 11 Jul 2024 03:41:59 +0000

In the realm of artificial intelligence, the capability to remember past interactions is pivotal for creating personalized and engaging user experiences. For any chatbots, to answer questions effectively and keep up with a conversation, it becomes essential to have its own memory.

There are many solutions available using which memory capability can be added to a chatbot, based on a LLM or anything else. In this post I am explaining one of the methods of providing memory using AWS DynamoDB.

I will walkthrough the steps to provision a DynamoDB table and convert it to a memory store for a LLM chatbot.

For more Details:

https://amlana21.medium.com/how-to-add-memory-to-llm-bot-using-dynamodb-670dfd5e4594

https://youtu.be/WkbXjCywLeo

How to Deploy a Next JS App on IPFS (InterPlanetary File System) and automate using Fleek

amlan — Thu, 06 Jun 2024 14:15:18 +0000

In todays’ AI era, where running a model for inference on GPU is a costly affair, it becomes important to find cost effective alternatives to at least deploy the app frontends. One such alternative I came across is IPFS. It provides you the decentralized storage flavor to your application at a fraction of cost. And when it comes to deploying web applications, its always better if we can automate the process.

In this post I will walkthrough the process of automating the deployment of a NextJS frontend to IPFS using Fleek.

More details: https://medium.com/@amlana21/how-to-deploy-a-next-js-app-on-ipfs-interplanetary-file-system-and-automate-using-fleek-5637c792b7a3

How to stream LLM responses using AWS API Gateway Websocket and Lambda

amlan — Fri, 10 May 2024 06:05:38 +0000

Nowadays LLMs are everywhere. Many tasks are getting automated using AI (LLM) models. Most of these use cases are chat based where you chat with the LLM and it responds back with answers. In these scenarios it becomes useful to have a streaming mechanism where the LLM can stream responses back to the user. In such cases, the client can connect to the LLM and the LLM can stream responses back to the client as and when they are ready. This is where Websockets come into play. Websockets provide a full-duplex communication channel over a single TCP connection. This allows the LLM to stream responses back to the client. In this post, I will explain how to stream LLM responses using AWS API Gateway Websockets and Lambda. We will use AWS API Gateway to create a Websocket API which will be used to stream responses from a backend LLM inference service , to the client. We will use AWS Lambda to process the LLM responses and send them to the client over the Websocket connection. Finally we will automate the deployment of the infrastructure using Terraform.

For more details:

https://amlana21.medium.com/how-to-stream-llm-responses-using-aws-api-gateway-websocket-and-lambda-ba2fc9c348cc

How to have AWS Lambda assume a role dynamically and get permissions on the fly

amlan — Thu, 02 May 2024 04:05:22 +0000

During a recent work on one of my projects, I came across a scenario where I needed to have a AWS Lambda function assume a role dynamically and get permissions conditionally. When we create an AWS Lambda function, we always associate a single role to the function. To achieve my need I had to come up with a solution where I could have the Lambda function assume a role dynamically and get permissions which is different than the associated role. I wanted to share my experience of this method and hopefully it will help someone who is looking for a similar solution.

In this post, I will show you how to have a Lambda function assume a role dynamically and give the functions permissions which are not present in the associated role.

https://amlana21.medium.com/how-to-have-aws-lambda-assume-a-role-dynamically-and-get-permissions-on-the-fly-715e8642ab8a

Perform blue green deployment on AWS ECS using CodePipeline and CodeDeploy

amlan — Fri, 05 Apr 2024 02:15:44 +0000

In this post I explain the process to perform a blue green deployment using CodeDeploy and CodePipeline, to an application deployed on AWS ECS cluster.

https://medium.com/@amlana21/perform-blue-green-deployment-on-aws-ecs-using-codepipeline-and-codedeploy-f1f60e31673a

Deploying an AWS ECS Cluster with AWS CDK (in GoLang) and Deploying a Streamlit-OpenAI App to the cluster

amlan — Sat, 05 Aug 2023 16:29:00 +0000

In this post I walk through steps to use CDK as an IAAC framework for deploying to AWS. The steps in this post follow CDK using Golang. Here we will see how we can use CDK to not only deploy an ECS cluster but the whole infrastructure to support a Streamlit app which uses OpenAI API.

https://amlanscloud.com/cdkapppost/