A practical guide to end-to-end serverless observability on AWS: implement distributed tracing with AWS X-Ray and OpenTelemetry, high-cardinality metrics via Embedded Metric Format (EMF), and symptom-based alerting.

Explore how AWS observability helps developers build reliable, secure, and efficient cloud applications. Learn to use Amazon CloudWatch, AWS X-Ray, AWS CloudTrail, and Amazon SNS to monitor performance, analyze logs, trace requests, detect failures, and investigate incidents. Discover practical implementation steps, architecture design, security practices, cost optimization, and a hands-on experiment to improve cloud application reliability.

Learn how to configure distributed tracing and latency tracking across AWS Lambda, DynamoDB, and Amazon Bedrock to debug complex agentic workflows.

An honest look at when it works and when it doesn’t

Learn how to troubleshoot distributed applications on AWS using CloudWatch, AWS X-Ray, OpenTelemetry, and CloudTrail. Explore a real-world latency investigation, trace requests across services, analyze logs, configure actionable alarms, and avoid common observability mistakes.

Bedrock AgentCore tutorial: deploy a support agent on AgentCore Runtime in us-east-1, invoke it, read the execute_tool span in X-Ray,...

はじめに横浜銀行アジャイル開発チームのwatariです。AWS上で、次のようなサーバーレスアプリケーションをOpenTelemetryで計装する機会がありました。これまではAWS X-Ray SDKを利用してトレースを可視化していましたが、AWSがOpenTelemetryへの移行を推奨しています。そのためOpenTelemetryを用いた計装をPoC（概念実証）として試しました。テレメトリの送

はじめに 横浜銀行アジャイル開発チームのwatariです。 AWS上で、次のようなサーバーレスアプリケーションをOpenTelemetryで計装する機会がありました。 これまではAWS X-Ray SDKを利用してトレースを可視化していましたが、AWSがOpenTelemetryへの移行を推奨しています。 そのためOpenTelemetryを用いた計装をPoC（概念実証）として試しました。 テレメトリの送信先にはNew Relicを使用します。本稿ではOTLPによる直接送信の実装に焦点を当て、New Relicのエージェントとの比較は扱いません。 WebアプリケーションやLambd...

When we work with telemetry in production environments, we need to balance the cost vs. observability trade-off. Send everything to your tracing backend, and watch your AWS bill explode. Sample too…

Surface Mount Technology (SMT) polarity programming defines how a polarity-sensitive component feeds from tape reel or tray to the pick-and-place machine, designed to help maintain correct orientation on the Printed Circuit Board Assembly (PCBA). Get it right, and boards run clean. Get it wrong by 180°, and downstream systems (Automated Optical Inspection (AOI), X-ray, In-Circuit [...]

A practical guide to cutting through the noise and diagnosing bottlenecks in cloud architectures. Discover how to leverage Amazon CloudWatch, AWS CloudTrail, and AWS X-Ray to ensure high performance and security in modern data pipelines and applications.

Our BharatBuildsTour “First Commit” journey — from spending an entire day struggling to find the right problem statement, to building a Lambda Latency/Cost Optimizer, realizing it was only “okay,” and eventually turning that idea into AWS Incident Autopilot (AWS-IP). A story about debugging, changing direction, and pushing a project beyond the first version.

A practical, ordered roadmap of AWS services for beginners — based on what I wish I'd learned first.

Descubra como estruturar uma arquitetura de monitoramento eficiente usando serviços nativos da AWS, garantindo a saúde do seu produto sem explodir o orçamento inicial da sua startup.

Version 1.0 of the Nx Plugin for AWS, an open source toolkit for scaffolding full-stack applications on AWS, is now available. AI assistants can stand up an application on AWS in minutes, but rarely get security, observability, and type-safety right in one pass. The plugin extends Nx, an open source, language-agnostic build system for monorepos, with generators that each build one part of an application on request, alongside the infrastructure to run it. Generators cover AI agents and Model Context Protocol servers on Amazon Bedrock AgentCore, plus APIs, websites, and databases, built on proven open source frameworks in TypeScript and Python. Each writes out a working, deployable piece of your application, defining infrastructure as either AWS Cloud Development Kit (AWS CDK) constructs or Terraform modules, with recommended practices in place such as AWS WAF protection, access logging to Amazon CloudWatch, and AWS X-Ray tracing. The connection generator wires projects together with type-safe clients, so a breaking API change becomes a build error instead of a failed request in production. Each generator produces the same result every time, making it a dependable foundation for an AI assistant to build on. The generated code belongs to you, with no runtime dependency on the plugin, and Nx migrations bring later improvements to workspaces you have customized. The plugin is available under the Apache 2.0 license at no additional charge; you pay only for the AWS resources your applications use. To learn more, see the launch blog post and documentation.

Cloud incidents can be difficult to troubleshoot when multiple AWS services are connected. Could Generative AI help detect incidents, identify root causes, recommend fixes, and safely automate remediation? This article explores what an AI-assisted incident response system could look like and where human approval is still essential.

この記事は「2026 Japan AWS Jr. Champions 真夏のQiitaリレー」の記事となります。 過去の投稿は以下のリンク集からご覧ください。 はじめに こんにちは。株式会社スリーシェイクの太田暢です。 今回は分散トレーシング入門として、Ru...

この記事は「2026 Japan AWS Jr. Champions 真夏のQiitaリレー」の記事となります。 過去の投稿は以下のリンク集からご覧ください。 はじめに こんにちは。株式会社スリーシェイクの太田暢です。 今回は分散トレーシング入門として、Ru...

Groups Conversations All groups and messages Sign in Machine Learning, Deep Learning and AI Conversations     X-Ray Your Agent Fleet 0 views Eyal Estrin unread, 6:12 AM (8 minutes ago)    to https://medium.com/google-cloud/x-ray-your-agent-fleet-845456633576 Eyal Estrin Author | Cloud Architect | AWS • Azure • GCP Insights Social: @eyalestrin Connect: https://linktr.ee/eyalestrin Blog: https://security-24-7.com Reply all Reply to author Forward

Learn observability best practices for AWS Lambda durable functions, including CloudWatch metrics, custom alarms, structured logging, and X-Ray tracing for debugging callback timeouts end-to-end.

This article covers observability best practices for AWS Lambda durable functions using a Stripe payment processing example, including CloudWatch metrics, structured logging, X-Ray tracing, and debugging callback timeouts.