AWS DevOps

Introduction AWS Elastic Beanstalk simplifies the process of deploying and scaling web applications. You upload your code, and Elastic Beanstalk handles capacity provisioning, load balancing, auto scaling, and application health monitoring. Elastic Beanstalk now offers AI Analysis to help troubleshoot environment health issues. When you request an analysis, Elastic Beanstalk triggers a script on the

This is a guest post written by Jasdeep Singh Bhalla from GoDaddy. AWS Cloud Development Kit (CDK) Aspects are a powerful mechanism that allows you to apply organization-wide policies, like security rules, tagging standards, and compliance requirements across your entire infrastructure as code. By implementing the Visitor pattern, Aspects can inspect and modify every construct

AWS DevOps Agent is your always-available operations teammate that resolves and proactively prevents incidents, optimizes application reliability and performance, and handles on-demand SRE tasks across AWS, multicloud, and on-premises environments. It integrates with your existing observability tools to correlate telemetry, code, and deployment data to reduce Mean Time To Repair (MTTR) and drive operational excellence.

Introduction Teams running distributed workloads face a persistent operational challenge: when something breaks, the information needed to resolve it is scattered across logs, deployment pipelines, configuration histories, and third-party monitoring tools. A Site Reliability Engineer (SRE) responding to a 2 AM page must manually correlate telemetry from multiple sources, trace dependencies across services, and form

Standardizing CDK construct properties across a large organization requires repetitive manual effort that scales poorly as teams and repositories grow. Development teams working with AWS Cloud Development Kit (AWS CDK) must apply the same configuration properties across similar resources to meet security, compliance, and operational standards but manual configuration leads to drift, maintenance burden, and

Introduction Organizations carry a growing burden of technical debt — aging codebases, outdated runtimes, and legacy frameworks that slow innovation, increase security risk, and inflate maintenance costs. Addressing this debt requires tackling a wide range of code transformation challenges: version upgrades, runtime migrations, framework transitions, and language translations, all of which must be repeated across

March 2026: This post has been updated to reflect that Amazon ECS now supports canary and linear deployment strategies natively as of October 2025. The recommendation has been updated accordingly to reflect ECS-native as the default choice for new deployments. Blue/green deployments on Amazon Elastic Container Service (Amazon ECS) have long been a go-to pattern

Introduction Software maintenance and modernization is a critical challenge for enterprises managing hundreds or thousands of repositories. Whether upgrading Java versions, migrating to new AWS SDKs, or modernizing frameworks, the scale of transformation work can be overwhelming. AWS Transform custom uses agentic AI to perform large-scale modernization of software, code, libraries, and frameworks to reduce

In today’s rapidly evolving software landscape, maintaining and modernizing Java applications is a critical challenge for many organizations. As new Java versions are released and best practices evolve, the need for efficient code transformation becomes increasingly important. Organizations today face significant challenges when modernizing their Java applications. Legacy codebases often contain outdated patterns, deprecated APIs,

Root cause analysis during incidents is one of the most time-consuming and stressful parts of operating cloud applications. Engineers must quickly correlate telemetry data across multiple services, review deployment history, and understand complex application dependencies—all while under pressure to restore service. AWS DevOps Agent changes this paradigm by bringing autonomous investigation capabilities to your operations

AWS CloudFormation enables you to model and provision your cloud application infrastructure as code-base templates. Whether you prefer writing templates directly in JSON or YAML, or using programming languages like Python, Java, and TypeScript with the AWS Cloud Development Kit (CDK), CloudFormation and CDK provide the flexibility you need. For organizations adopting multi-account strategies, CloudFormation

At re:Invent 2025, Matt Garman announced AWS DevOps Agent, a frontier agent that resolves and proactively prevents incidents, continuously improving reliability and performance. As a member of the DevOps Agent team, we’ve focused heavily on making sure that the “incident response” capability of the DevOps Agent generates useful findings and observations. In particular, we’ve been

The AWS SDK for Java v2 represents a fundamental shift in how Java applications interact with AWS services, addressing critical security requirements while delivering measurable performance improvements. For organizations still operating on v1, this transition extends beyond a routine version upgrade—it’s a strategic imperative for maintaining secure, efficient cloud operations. With v1 reaching end-of-support on December 31, 2025,

This post was contributed by Adi Ziv, Senior Platform Engineer at Kaltura, with collaboration from AWS. Kaltura, a leading AI video expirience cloud and corporate communications technology provider, transformed CI/CD infrastructure by migrating to AWS CodeBuild-hosted runners for GitHub Actions. This migration reduced DevOps operational overhead by 90%, accelerated build queue times by 66%, and

This post was co-written with Muthuvelan Swaminathan (Principal Partner Engineer) and Ruchika Bakolia (Software Engineer) from New Relic. Modern distributed systems that generate massive volumes of metrics, traces, and logs are inherently complex. The process of correlating logs, comparing configurations and switching between tools during incident management makes manual root cause analysis a bottleneck that

This post was co-written with Omri Sass (Director of Product Management), Cansu Berkem (Director of Product Management), and Mohammad Jama (Product Marketing Manager) from Datadog. On-call engineers spend hours manually investigating incidents across multiple observability tools, logs, and monitoring systems. This process delays incident resolution and impacts business operations, especially when teams need to correlate

The AI-Driven Development Life Cycle (AI-DLC) methodology marks a significant change in software development by strategically assigning routine tasks to AI while maintaining human oversight for critical decisions. Amazon Q Developer, a generative AI coding assistant, supports the entire software development lifecycle and offers the Project Rules feature, allowing users to tailor their development practices

AI-Driven Development Life Cycle (AI-DLC) holds the promise of unlocking the full potential of AI in software development. By emphasizing AI-led workflows and human-centric decision-making, AI-DLC can deliver velocity and quality. However, realizing these gains hinges on how organizations effectively integrate AI into their engineering workflows. Through our work with engineering teams across industries, we

Streamline your AWS infrastructure development with AI-powered documentation search, validation, and troubleshooting Introduction Today, we’re excited to introduce the AWS Infrastructure-as-Code (IaC) MCP Server, a new tool that bridges the gap between AI assistants and your AWS infrastructure development workflow. Built on the Model Context Protocol (MCP), this server enables AI assistants like Kiro CLI,

Back in July 2024, we announced plans to de-emphasize AWS CodeCommit based on adoption patterns and our assessment of customer needs. We never stopped looking at the data or listening to you, and what you’ve shown us is clear: you need an AWS-managed solution for your code repositories. Based on this feedback, CodeCommit is returning