DevOps Posts

You can use Amazon Elastic File System (EFS) as a shared file system between your Amazon EC2 instances to benefit from its scalability and durability. You can simply deploy your files to an Amazon EFS file system and mount it on dozens of Amazon EC2 instances in the same VPC. Then, you only need to deploy to your EFS file system when you have an update.

Now, what about automating your deployments to Amazon EFS? AWS CodePipeline does not have a deploy action integrated with Amazon EFS file systems. However, your AWS CodeBuild containers can mount EFS file systems. So you can copy your files and folders directly to your EFS file system after building them. In this post, I will talk about creating CI/CD pipelines using AWS CodePipeline and CodeBuild to build and automate your content to Amazon EFS file systems. Read more at Deploying to Amazon EFS With AWS CodeBuild & AWS CodePipeline post.

AWS CodePipeline is the AWS service to build and orchestrate your CI/CD workflows on AWS. Using CodePipeline with other AWS developer tools, you can model, visualize, and automate your software release process without maintaining any build or deploy servers.

Today, I am excited to announce the launch of my new course AWS CodePipeline Step by Step on Udemy! In this post, I will talk about what you will learn in this course section by section. Besides, I will also share a discount coupon special to launch in the end. Read more at Announcing My AWS CodePipeline Step by Step Course post.

Whether you have a static website like this blog or a front-end application developed using a framework like Angular, React, or Vue.js, you can follow similar steps to create a continuous deployment pipeline on AWS using AWS CodePipeline. In this post, I will share the AWS services you can use while creating this type of pipelines to achieve fast and frequent deployments. Read more at AWS CodePipeline for Your Static Websites & Frontend Apps: A Complete CI/CD Approach post.

In addition to API development, AWS Lambda has many use cases. One of them is running some background jobs in scheduled intervals. Besides, if you need a chain of sequential or parallel AWS Lambda functions, the ideal way to orchestrate them is using AWS Step Functions.

In this post, I will talk about how to schedule your AWS Lambda functions or Step Functions state machine executions using AWS CloudWatch and EventBridge consoles as well as AWS Serverless Application Model (SAM) and CloudFormation templates. Read more at 3 Ways to Schedule AWS Lambda and Step Functions State Machine Executions post.

Where do you keep your DB credentials in your AWS Lambda functions that you use to access your Amazon RDS databases? Hardcoded? No! Environment variables? Well, you might be using AWS Secrets Manager, right? It would be great! But did you know that you can also use the IAM role of your AWS Lambda function and its temporary credentials to do this?

Yes, there are different ways to manage your database credentials in your AWS Lambda functions. In this post, I will talk about one of the most secure methods, using IAM authentication of Amazon RDS, with an example of an AWS Lambda function developed in Python. I will use an Amazon RDS - MySQL DB instance, but IAM authentication is also supported on PostgreSQL DB instances as well. Read more at AWS Lambda IAM Authentication for Amazon RDS With Python: Secure, But Limited post.