Beginner’s Guide to AWS DevOps Best Practices

Overview of DevOps

DevOps integrate developers and operations teams to improve collaboration and productivity by automating workflows and continuously measuring application performance.

It focuses more on automation – automating code, testing workflows, and infrastructure. The software can be integrated, tested, monitored, and deployed.

It also enables the adoption of an iterative process to monitor, measure, and improve the code and operation every day by improvising the ability to increase the market needs and other things to impact the software.

Here are two blogs to refresh your memory on the Importance of DevOps and 5 popular DevOps Tools.

DevOps Practices

The best practices help organizations to deliver faster, more reliable updates to their customers by automating and optimizing the software development and infrastructure management process.

Here are the top 5 DevOps best practices to follow:

Continuous Integration

Continuous integration is a practice where the workflows are integrated frequently, leading to multiple integrations. Each integration is verified by an automated build, including a test, to detect integration errors. This method greatly reduces integration issues, according to many teams, and speeds up the development of software that works well. Jenkins is one of the tools and can be deployed in the cloud through the AWS EC2 service to achieve continuous integration with the help of plugins. Plugins allow integration of various DevOps stages.

Continuous Delivery

One of the software development practices called “continuous delivery” automatically prepares code updates for production deployment. Continuous delivery, a cornerstone of contemporary application development, builds on continuous integration by deploying any code alterations to testing and/or production environments following the build step. When properly implemented, developers will always have a build artifact that is prepared for deployment and has undergone a set of tests.

Continuous integration and Continuous delivery (CI/CD) workflow orchestration can be achieved by AWS CodePipeline, which builds a workflow that builds code in AWS CodeBuild every time we commit a change.

CodePipeline

CodePipeline is a continuous delivery service, it can be used to model, visualize, and automate the steps required to release the software. It lets to monitor the processes in real-time.

CodeBuild

CodeBuild is an entirely managed continuous integration service CodeBuild compiles source code, runs tests, and creates software packages that are prepared for deployment. The builds won’t be kept in a queue because CodeBuild scales constantly and handles several builds at once. Using pre-packaged build environments or making your build environments with your build tools will allow you to get going quickly.

Microservices

Microservice addresses by breaking apart the monolithic into several smaller loosely coupled marker services. The Microservices model is a single distinct business function that when combined with other microservices provides a complete application as exposed by the user interface, and communication between microservices. It is often performed using APIs where each microservice shows its functionality as well-defined interface communication. It is often allowed to happen between any two microservices as required by the overall system to work. Each microservice can be developed independently of every other microservice allowing scaling per microservice. Finally, each microservice can be paired with its flavor of database which is best suited to the microservices specific needs.  Each microservice in an application can be built on any best-suited language.

AWS Processing power for microservices is provided through container services like Amazon Elastic Container Service and Serverless services like AWS Lambda.

Amazon Elastic Container Service

Scalable container management service that supports Docker containers and runs applications on a managed EC2 cluster.

AWS Lambda

AWS Lambda runs code without provisioning or managing servers.  It runs applications of any kind or backend service virtually.

Infrastructure-as-Code

Infrastructure as code (IaC) by incorporating it into software development practices can help teams and organizations improve automation and throughput without sacrificing quality and uptime. It makes managing cloud applications and their resources more repeatable and safer.

AWS offers a DevOps-oriented approach to building and managing infrastructure. Similar to how programmers create application code. It offers services that permit the creation, deployment, and maintenance of infrastructure in a programmatic, descriptive, and declarative way, it also provides multiple options for infrastructure as code, including CloudFormation, OpsWorks, System Manager, and Config.

• CloudFormation: Provides an easy way to create and manage the collection of AWS resources.
• OpsWorks: Configuration management service that uses Chef, an automation platform that treats server configs as code.
• System Manager: Management service that helps to collect software inventory, apply OS patches, and create system images.
• Config: Provides AWS resource inventory, configuration history, and configuration change notifications to enable security, and governance.

If you want to know more about Continuous Integration to Automate Terraform Modules With GitHub Actions here. 

Monitoring and Logging

In monitoring and logging, the three pillars of observability are critical for DevOps to provide elastic, resilient services. External monitoring helps to check the health of applications and websites to check the digital experience of user metrics. Metrics and distributed tracing help trace communication between applications distributed across systems or containers that identify errors and exceptions from apps. Events and logs are data that help to provide contextual information about events, it enables the identification of issues in the code when combined with information from external monitoring and metrics.

AWS monitoring and logging tools are CloudWatch, X-Ray, and CloudTrail.

• CloudWatch: Helps to collect and track metrics, collect, and monitor log files, set alarms, and automatically react to changes.
• X-Ray: It Helps developers analyze and debug production, and distributed applications, such as those built using a microservices architecture.
• CloudTrail: It Records AWS API calls including the identification of the caller, the time, the source IP, the request parameters, and the response.

Conclusion

DevOps practices on AWS are supportive and very important to create, store, and provide a wide range of tools for developing and deploying applications in the cloud, as technology is needed to ensure a simple, effective, and smooth transition to the cloud.

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