Archives: FAQs

 Answer: Start with enabling analysis only for key components (e.g. Lambda + API Gateway) to limit cost and noise Ensure your application generates sufficient metrics, logs, and trace data for ML models to establish a baseline Keep function versions and performance stable initially, then introduce changes to test detection Use DevOps Guru recommendations as guidance, […]

 Answer: You pay for: Resource analysis — how many and which AWS resources DevOps Guru is monitoring API / insight calls — how many insights or API interactions are generated There is no minimum commitment. Only the resources marked for analysis and the operations done by DevOps Guru count.

Answer: Some example issue types: Resource configuration issues (e.g. insufficient provisioned concurrency, misaligned memory allocation) Resource exhaustion (e.g. memory, CPU, or IO usage trends that approach limits) Underutilized resources (over-provisioning) Runtime errors or sudden deviations in invocation patterns Anomalous latencies or error rates DevOps Guru correlates metrics, logs, and events to present contextual insights.

 A: Amazon DevOps Guru is a fully-managed operational insights service that uses machine learning to analyze logs, metrics, traces, and configurations across AWS resources, with the goal of surfacing anomalies and suggesting corrective actions. In a serverless context, DevOps Guru can detect issues specific to AWS Lambda (e.g. concurrency limits, cold starts, misconfiguration) and integrate […]

A: Insights may take time (hours) to appear, because the system needs baseline data If your traffic is sparse, anomalies may not be sufficiently distinct False positives or noise can happen, so inspect recommendations carefully DevOps Guru is not a replacement for alerting — you may still want CloudWatch alarms for critical thresholds Pricing: you […]

A: DevOps Guru shows an insight (e.g. “Ongoing reactive insight”) in its dashboard. You can click to see details: aggregated metrics graphs, anomaly timelines, relevant events, and a set of recommendations on how to address the issue (e.g. increase concurrency, optimize function code). The blog describes navigating into the insight view and reviewing anomalies vs […]

 A: In the tutorial, they configure multiple CloudWatch Event rules (six rules scheduled every minute) that invoke either the default Lambda or a versioned Lambda with “provisioned concurrency.” This intentional variation is designed to provoke anomalies in invocation patterns, concurrency usage, or resource limits, which DevOps Guru can then pick up.

 A: You need: An AWS account in a region where DevOps Guru is supported A Lambda function deployed (in this tutorial, Node.js runtime) Permissions to enable DevOps Guru, access CloudWatch, configure event rules Ability to schedule triggers (e.g. via CloudWatch Events / EventBridge) to invoke the Lambda repeatedly Enough invocation data (over time) so DevOps […]

 A: The tutorial shows how to automatically detect operational anomalies in AWS Lambda functions using Amazon DevOps Guru in a serverless context. The idea is that DevOps Guru monitors metrics, logs, and events, uses ML to detect anomalies (e.g. function performance issues, resource exhaustion), and surfaces insights/recommendations so you don’t manually comb through logs.

A: You create a middleware function (e.g. checkLogin) that checks whether req.session (or req.session.userId or a flag like req.session.loggedIn) is set. If not, redirect to login or return a 401/403 response. Use this middleware on routes that require authentication (e.g. app.get(‘/welcome’, checkLogin, (req, res) => {…})). In logout route, destroy the session (req.session.destroy(…)) and redirect. […]