@aws-devops-blog
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Introduction Automated incident remediation – turning investigation findings into deployed fixes without manual toil – is the next frontier for operations teams running distributed workloads on AWS. Today, when an incident fires at 2 AM, the on-call engineer must correlate telemetry across Amazon...
AWS CloudFormation helps you model and provision cloud infrastructure as code using JSON or YAML templates, or through tools like the AWS Cloud Development Kit (CDK) and AWS Serverless Application Model (SAM). Whether you create stacks directly, use change sets for preview, or deploy through CI/C...
AWS CloudFormation helps you model and provision cloud infrastructure as code using JSON or YAML templates, or through tools like the AWS Cloud Development Kit (CDK). Whether you create stacks directly, use change sets for preview, or deploy through CI/CD pipelines and AI agents, fast feedback on...
Custom code transformations are the work that no off-the-shelf migrator covers for you. Moving your services off an internal library, enforcing your team’s error-handling conventions, standardizing logging across your fleet of services: that work piles up on your backlog because general-purpose t...
Introduction Organizations that use feature flags alongside incident response tooling often connect the two manually. When an outage occurs, engineers must identify which flags are relevant, decide whether to disable them, and coordinate the change across teams. This manual process adds latency a...
When an alarm fires at 2 AM, the first thing most engineers do is grep logs, check recent deployments, and trace code paths. However, the context they need — metrics, traces, topology, configurations — lives in a separate browser tabs and applications. What if your IDE could bring that cloud inte...
When something breaks in production, you find out fast. Understanding why it broke, before the damage spreads, is the hard part. That is where Site Reliability Engineering (SRE) teams lose the most time. Think about the last time you got paged at 2 a.m. The alert said something broke, not why. Yo...
This post was co-written with Bharadwaj Tanikella (AI/ML Product Engineering Leader) and Mohammad Jama (Product Marketing Manager) from Datadog. In December 2025, we showed how AWS DevOps Agent and Datadog MCP Server could work together to autonomously correlate monitoring data with the infrastru...
AWS DevOps Agent can investigate a growing range of production incidents autonomously. It diagnoses CrashLoopBackOff failures, traces ConfigMap deletions through audit logs, and correlates Amazon CloudWatch metrics with cluster events — all without human intervention. But AWS DevOps Agent has a v...
Introduction When a deployment fails, finding the root cause often means piecing together information from multiple sources. You wait for the deployment to finish, request a log bundle, download it, and then search through files like eb-engine.log and cfn-init.log to find the error. If you’re not...
Confirmation bias is one of the most common reasons incident investigations take longer than they should. An on-call engineer gets alerted, forms a theory based on initial triage and experience, finds one piece of supporting evidence, and stops looking. The actual root cause — buried in a differe...
Modern distributed systems route business transactions through dozens of microservices, message queues, and event streams. When a message fails to process or processing exceeds SLA thresholds, troubleshooting requires correlating logs from tools like Elasticsearch, metrics from Datadog, and infra...
We are excited to announce CDK Mixins, a feature of the AWS Cloud Development Kit (CDK) that fundamentally changes how you compose and reuse infrastructure abstractions. In this post, you will learn how to use CDK Mixins to apply sophisticated features to any construct – whether L1, L2, or custom...
Learn how to build CLI tools that extend themselves through natural language using Amazon Bedrock, the Strands Agents SDK, and Model Context Protocol. This post walks through a meta-tooling pattern where generated CLIs can create, refine, and version new commands at runtime—turning days of manual...
Learn how AWS Transform custom can help migrate Excel VBA applications to modern Python code while overcoming context window limitations, preserving functional equivalence, and enabling cloud-native deployment—turning weeks of manual rewriting into hours of AI-guided transformation. Introduction...
Authors: Sourav Kundu and Joyson Neville Lewis. In today’s cloud-native landscape, ensuring the integrity and authenticity of your serverless functions is critical for maintaining security and compliance. Organizations face increasing challenges in preventing the execution of tampered or maliciou...
AWS CloudFormation makes it easy to model and provision your cloud application infrastructure as code. CloudFormation templates can be written directly in JSON or YAML, or they can be generated by tools like the AWS Cloud Development Kit (CDK). Resources are created and managed by CloudFormation...
Introduction Modernizing applications by upgrading language runtimes, migrating SDKs, and refactoring frameworks is important for cloud adoption but can be labor-intensive at scale. Each repository requires analysis of dependencies and transformation needs; custom transformation logic must be bui...
Introduction As modern applications evolve into complex ecosystems of serverless functions, microservices, and event-driven architectures, incident response becomes increasingly challenging. DevOps and SRE teams spend hours manually correlating data across observability tools and troubleshooting...
When we launched Amazon Q Developer, our goal was to bring AI assistance directly into the developer workflow. Customers adopted Q Developer across VS Code, JetBrains, Eclipse, and Visual Studio, using it for code generation, debugging, and chat-based guidance. Q Developer proved that AI belongs...
Enterprise modernization has reached an inflection point. You can transform one repository easily. Existing tools, including AWS Transform custom, work well for individual repositories, and the process is understood. But what about 50 repositories? 100? 200? When you need to modernize at enterpri...
