1) Read about AWS RDS, DynamoDB and AWS lambda and write a post on linkedIn with example in your own words
Here's a draft for your LinkedIn post:
🌟 Understanding AWS RDS, DynamoDB, and AWS Lambda 🌟
As a DevOps enthusiast, I constantly explore cloud solutions to simplify workflows and enhance scalability. Today, I want to share insights about three powerful AWS services: RDS, DynamoDB, and Lambda – and how they can work together seamlessly.
AWS RDS (Relational Database Service)
AWS RDS is a managed relational database service. It supports popular database engines like MySQL, PostgreSQL, and SQL Server. RDS simplifies database administration tasks such as backups, scaling, and updates.
Example: Suppose you have an e-commerce platform that requires you to store structured data such as orders for customers. RDS is a good way of maintaining this relational data with high reliability and scalability.
DynamoDB
It's a fully managed NoSQL database designed for high performance and scalability, ideal for storing key-value and document-based data with millisecond latency. For example, in building a real-time leaderboard for a gaming application, low latency and auto scaling of DynamoDB can ensure it is the one needed to handle rapid updates to data.
⚡ AWS Lambda
AWS Lambda lets you run code without provisioning servers. Your code executes in response to events such as HTTP requests, database changes, or file uploads, through an event-driven model.
For example, in serverless architecture, you would use Lambda to process a user upload, validate the data, or trigger the notifications on the addition of a new item in DynamoDB.
2) You are part of a team responsible for migrating the database of an existing e-commerce platform to Amazon RDS. The goal is to improve scalability, performance, and manageability. The current setup uses a self-managed MySQL database on an on-premises server.
Migration Plan: Moving to Amazon RDS for MySQL
Migrating a self-managed MySQL database to Amazon RDS for MySQL can significantly enhance scalability, performance, and ease of management. Here's a high-level breakdown of the steps:
Assessment and Planning
Understand the current setup:
Analyze the on-premises database structure, storage size, queries, and performance metrics.
Define requirements:
Identify RDS instance type, storage capacity, backup requirements, and security settings.
Plan downtime:
Decide on a migration window to minimize impact on the e-commerce platform.
2️⃣ Preparation
Set up Amazon RDS:
Launch an RDS instance with the required configuration (engine version, instance type, and security groups).
Enable replication:
Ensure that RDS allows replication from your MySQL version to minimize downtime during migration.
Backup the database:
Take a full backup of the on-prem database just in case.
3️⃣ Data Migration
Use AWS Database Migration Service (DMS):
DMS streamlines transferring data to RDS. Set up a replication instance and connect source (on-prem) and target (RDS).
Full Load:
Transfer all of the data to the RDS instance
Ongoing replication:
Enable CDC to synchronize changes from the on-premises database during the migration period.
4️⃣ Testing
Data integrity checking
Compare sample data between the two databases for consistency
Performance testing
Evaluate query performance and application response times on the new RDS setup
Application testing
Validate the e-commerce application works as expected with the RDS database
5️⃣ Cutover and Optimization
Cutover
Switch the application to point to the RDS database as the source of data
Monitor performance:
Use Amazon CloudWatch to monitor database metrics such as CPU usage, query performance, and connections.
Optimize
Apply indexing, caching, and scaling (vertical or horizontal) based on usage patterns.
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