AWS for DevOps:
tools, benefits & best practices

AWS for DevOps: tools, benefits & best practices

February 27, 2024

AWS DevOps architecture components

The architecture and tools for DevOps on AWS can vary depending on the project’s requirements and specifics. For example, here are the components used when deploying software on Amazon EC2, a popular cloud infrastructure service used by millions of businesses globally.

CodeCommitCodePipelineСodeBuild CodeDeployArtifactsS3 Bucket Application load balancerBlue environmentAppWebGreen environmentAppWebBlue/green deploymentCloudFrontCode changesDevelopers

Amazon CloudFront

Amazon CloudFront is a content delivery network that allows companies to deliver web content, live and on-demand videos, and software updates to users faster by using a globally distributed AWS data center infrastructure. The integration with AWS Web-Application Firewall enables DevOps teams to protect their web apps and APIs from common cyber threats, including DDoS and account creation fraud, with just one click in CloudFront’s console.

Amazon Simple Storage Service (S3)

Amazon S3 is a scalable cloud storage that is used for data management and backup, disaster recovery, high-performance computing, and machine learning training data. Amazon S3 provides multiple classes of highly available cloud storage (99.5% availability and more), which helps companies ensure seamless operations for their websites and apps.

Elastic Load Balancing

With this AWS service, IT teams can effectively distribute traffic between virtual servers, as well as monitor server, container, and service health. For example, teams can use Application Load Balancer to run health checks to quickly identify and resolve issues such as the inability to communicate data between EC2 instances, S3 bucket misconfigurations, or enabled legacy metadata endpoints on Kubernetes clusters.

Amazon Relational Database Service (RDS)

Amazon RDS is a managed SQL database service that allows teams to manage, migrate, and back up data by using the AWS Management Console or the AWS Command Line Interface. One of the main advantages of Amazon RDS is the automation of data management routine tasks, including data backups and replication, issue discovery, or resource allocation.

Amazon DynamoDB

DynamoDB is a NoSQL database service that can handle millions of queries simultaneously and automatically scale database capacity based on the on-demand or provisioned capacity pricing models. In the case of on-demand scaling, a company pays per request its app performs for reading or writing data. The second option implies that IT specialists specify the number of data writes and reads that are expected to be executed by an app’s backend.

Amazon Auto Scaling

This tool monitors AWS solutions and automatically scales the required cloud computing resources on demand, including Amazon DynamoDB tables and Amazon EC2 instances. IT teams can create comprehensive scaling plans based on a company's unique goals and easily monitor the average consumption of all scalable resources via a unified user interface, getting overall visibility into AWS DevOps architecture.

Amazon Route 53

Amazon Route 53 is a DNS service that helps automatically redirect end users to web applications, including those outside of the Amazon Web Services infrastructure. Latency-based routing is one of the tool’s core features that allows it to automatically avoid any network issues when redirecting end-users to apps, thus helping companies mitigate customer churn due to high latency.

AWS security groups

A security group is a charge-free AWS firewall service that regulates and tracks incoming and outgoing traffic among EC2 instances based on predefined security rules. Teams can easily create new security groups via AWS Management Console, AWS CLI (Command Line Interface), or AWS SDK and switch them off when they’re no longer needed.

DevOps best practices

To understand the essence of DevOps better, let us explore its best practices that can be used in AWS and other cloud infrastructures.

DevOps best practices

Conventionally, developers commit changes to a central repository only when a substantial part of the work is done. In turn, continuous integration implies that development teams should routinely submit code changes into a central repository to be able to identify and fix bugs much faster and update software more frequently. Following the continuous integration practice, developers merge their work regularly, which results in fewer bugs and improved software quality.

Continuous delivery goes hand in hand with continuous integration. This is a practice where the code changes are developed in short iterations, automatically built and tested, and prepared to be deployed to the production environment at any time. Since standardized testing ensures its reliability, issues are identified timely and the code is always ready to be deployed. Continuous integration is often challenging in on-premises deployments due to limited scalability and resource constraints, while the cloud allows for almost unlimited testing environments.

Microservices architecture is a software development method that splits an application into a series of small services that typically communicate with each other through APIs. Each microservice serves a single purpose, is typically managed by a separate development team, and can be modified and scaled up independently. Compared to the monolithic architecture, microservices provide better scalability, enabling IT teams to deliver new features more easily.

Essentially, the infrastructure as code (IaC) approach implies that developers should treat infrastructure the same way they treat code. Instead of relying on scripts and manual processes, engineers should use familiar code-based tools, a version control system, and highly standardized practices. This would allow IT teams to easily change and distribute infrastructure configurations and ensure that each configuration is properly documented.

With DevOps in place, IT teams should monitor user experience after the application is released to the production environment. Thoroughly analyzing the data generated by applications, DevOps specialists can quickly resolve issues and accurately assess how software updates impact user experience.

Communication and collaboration are essential cultural components of the DevOps philosophy. By establishing a knowledge management strategy and company-wide standards for information exchange, businesses can ensure effective communication between traditionally siloed units like development, marketing, and operations teams.

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AWS DevOps tools

Choosing the right tools is critical for establishing an effective AWS DevOps architecture. Here are key AWS DevOps tools classified based on their roles in the SDLC:

AWS for CI/CD

AWS CodePipeline

AWS CodePipeline is a continuous delivery service that allows organizations to model and automate every stage of the application release process by building CI/CD pipelines. It enables companies to update applications faster and timely address the ever-changing customer demands. With AWS CodePipeline, companies can easily test frequent and incremental code updates, which prevents bug escalation and reduces the amount of time and resources needed for fixing issues. Importantly, AWS CodePipeline is easily adaptable to a company’s specific needs. For example, it allows teams to use such repositories as Github and Atlassian Bitbucket or the company's own third-party Git source repositories.

AWS CodeBuild

AWS CodeBuild is a continuous integration service that streamlines code compilation and testing. AWS CodeBuild scales build servers depending on companies’ current needs and can compile multiple builds at the same time. What’s more, companies can use their existing build tools in AWS CodeBuild environments, so the integration requires minimal effort and becomes more cost-effective.

AWS CodeDeploy

AWS CodeDeploy allows companies to introduce application changes in small steps and thus significantly reduce downtime and solve challenges commonly associated with software deployments. Regardless of the deployment platform (EC2, Lambda, or on-premises), CodeDeploy easily integrates with organizations’ existing DevOps tools like GitHub and Jenkins. With AWS CodeDeploy, IT teams can automate software deployment across multiple test and production environments and have a full view of the software’s deployment status.

Benefits of AWS DevOps

AWS DevOps practices help companies mitigate the drawbacks of the traditional development approach and gain tangible business advantages.

Benefits

Faster delivery
DevOps allows organizations to iterate and develop software at a much faster pace.

Increased reliability
With continuous testing as an essential component, AWS DevOps promotes software quality and reliability.

Improved collaboration
DevOps encourages collaboration, so more employees end up participating in the creation of the end product.

Streamlined innovation
DevOps allows organizations to easily adapt to fluctuating customer needs by delivering updates and new features continuously.

Enhanced transparency
With continuous monitoring practices, teams can identify software errors in almost real time and fix them faster.

Advanced automation
Since AWS DevOps optimizes many manual software development tasks like testing or deployment, teams can focus on coding.

Revamp your SDLC with AWS DevOps tools

Revamp your SDLC with AWS DevOps tools

When implemented properly, AWS DevOps architecture can bring tangible improvements to software development by streamlining aspects like code deployment, infrastructure provisioning, and app monitoring. From a business perspective, AWS DevOps helps companies reduce testing, designing, and maintenance costs and proactively cater to customer needs by accelerating product and service delivery. However, decision-makers should remember that DevOps implementation is often disruptive for IT teams working with the traditional software delivery model, as they have to adapt to new workflows implying more frequent releases and automation. A transformation that is too rapid or inconsistent can negatively impact IT teams’ productivity, reducing the overall ROI of DevOps implementation. So companies should turn to certified AWS consultants such as Itransition to ensure successful implementation of AWS DevOps architecture.

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