Browse AWS Certification Guides

DVA-C02 Troubleshooting and Optimization Guide

Study DVA-C02 Troubleshooting and Optimization: key concepts, common traps, and exam decision cues.

This is the shortest weighted domain, but it is one of the easiest places to lose points because the stems look operationally familiar and the answer choices are all plausible. DVA-C02 expects developers to reason from evidence: logs, metrics, traces, deployment output, health checks, and performance symptoms.

Current weight in the exam guide

AWS currently weights Troubleshooting and Optimization at 18% of scored content.

What this domain is really testing

This domain is not testing generic “ops common sense.” It is testing whether a developer can:

  • start from evidence instead of intuition
  • use the right observability signal for the specific failure
  • change the narrowest useful control instead of redesigning the whole system
  • separate visibility problems, release problems, scaling problems, and code-level bottlenecks

Work this domain in order

Lesson Focus
4.1 Root Cause Analysis with Metrics, Logs & Traces Learn how to move from symptoms into evidence-based root-cause analysis.
4.2 Logging Strategy, Custom Metrics, Alerts & Health Checks Learn how observability is built into application code and runtime behavior.
4.3 Concurrency, Caching, Messaging Filters & Performance Tuning Learn the optimization choices that improve performance or reduce noisy downstream work.

Fast routing inside this chapter

If the question is really about… Go first to…
logs, traces, dashboards, deployment failure output, or debugging the cause of a production issue 4.1 Root Cause Analysis with Metrics, Logs & Traces
custom metrics, notifications, structured logs, or readiness checks 4.2 Logging Strategy, Custom Metrics, Alerts & Health Checks
Lambda concurrency, cache effectiveness, filter policies, or performance bottlenecks 4.3 Concurrency, Caching, Messaging Filters & Performance Tuning

If you keep missing questions in this domain

Symptom What is usually going wrong Fix first
you keep jumping to infrastructure changes you are not proving the root cause first rework 4.1 and force every stem into symptom, signal, cause, then fix
observability answers all look valid you are not separating logs, metrics, traces, alerts, and health checks by purpose rework 4.2 and ask what evidence each tool adds
tuning questions feel arbitrary you are not isolating the actual bottleneck rework 4.3 and decide whether the issue is concurrency, downstream pressure, cache efficiency, or noisy filtering
release issues blur into runtime issues you are not combining deployment context with runtime evidence use 4.1 first, then check whether the symptom aligns with a recent rollout

What strong answers usually do

  • start with evidence before changing architecture
  • separate visibility problems from performance problems
  • tune the narrowest resource or behavior that explains the symptom
  • use observability and rollback data together when troubleshooting releases

Common DVA-C02 traps in this domain

  • reading CloudWatch, logs, and X-Ray as interchangeable tools
  • choosing more alarms when the real issue is missing structure in logs or missing custom metrics
  • raising concurrency or capacity before proving where the bottleneck really is
  • forgetting that filter policies, cache TTLs, and event payload shape can be cheaper fixes than broad scaling changes

Before you leave this domain

Make sure you can explain:

  1. which signal you would inspect first
  2. what evidence would confirm the suspected cause
  3. which narrow control you would tune first
  4. how you would know the fix worked

Then loop back through the Cheat Sheet and Study Plan so the final review reflects how AWS actually mixes development, security, deployment, and troubleshooting inside one stem.

In this section

Revised on Sunday, May 10, 2026
3. Deploy
Study Plan