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aws-observability

Configure CloudWatch Logs, Metrics, Alarms, and X-Ray tracing for AWS observability.

6|1|Updated Mar 30, 2026
Search Tags:#aws#observability#terraform#alerting#lambda#cloudwatch#x-ray
One-click install
npx skills add https://github.com/wesleyosantos91/multi-agents --skill aws-observability-wesleyosantos91
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: aws-observability
Source: https://github.com/wesleyosantos91/multi-agents/tree/main/devin/.devin/skills/aws-observability
Command: npx skills add https://github.com/wesleyosantos91/multi-agents --skill aws-observability-wesleyosantos91

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

AWS workloads often fail silently or degrade gradually, making it hard to detect incidents early, understand root causes, and prove system health with actionable evidence.

Core Features & Use Cases

  • CloudWatch Logs that scale: Structured JSON logging for better searchability, plus Log Insights queries to quickly pinpoint errors, cold starts, latency distributions, and recurring failure patterns.
  • Metrics-driven alerting: Practical alarm thresholds for Lambda, API Gateway, SQS, and DynamoDB, including Terraform examples for repeatable, environment-specific setup.
  • Distributed tracing with X-Ray/ADOT: Enable tracing for Lambdas and instrument code to correlate requests across services, accelerating time-to-diagnosis.

Quick Start

Configure CloudWatch log groups with retention, enable X-Ray tracing for your Lambda, and create metric alarms for Lambda errors, throttles, and SQS DLQ using Terraform for the service and environment you specify.

Frequently Asked Questions about aws-observability

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I set up CloudWatch alarms for Lambda errors and SQS dead-letter queues using Terraform?▼

You can set up CloudWatch alarms for Lambda and SQS by applying Terraform-ready alarm definitions that specify practical thresholds for errors, throttles, and DLQ message counts to enable environment-specific alerting.

How do I enable AWS X-Ray tracing for Lambda functions to diagnose performance regressions?▼

To enable AWS X-Ray tracing for Lambda, you activate tracing in your function configuration and instrument the code, allowing distributed traces to correlate requests across services for faster diagnosis.

What is the best way to query CloudWatch Logs for cold starts and latency distributions in AWS?▼

The best way to query CloudWatch Logs for cold starts and latency is by using structured JSON logging combined with practical CloudWatch Log Insights queries to pinpoint errors and recurring failure patterns.

Can I use this approach to monitor API Gateway and DynamoDB performance across multiple environments?▼

Yes, you can monitor API Gateway and DynamoDB by configuring metric-driven alarms and a dashboard template, using Terraform examples to ensure repeatable, environment-specific visibility across your services.

Why do I need structured JSON logging for AWS observability instead of standard log outputs?▼

Structured JSON logging is needed for AWS observability because it improves searchability and allows Log Insights queries to quickly pinpoint specific errors, cold starts, and latency distributions during incident analysis.

Does this observability setup work without existing Terraform infrastructure modules?▼

The setup provides Terraform-ready alarm definitions and dashboard templates, but you will need a Terraform workflow to apply these configurations and provision the CloudWatch and X-Ray resources for your specified service.

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