RCA Example & QA Perspective
Scenario: Timeout Error in Payment Service
Problem Description: 15% of users in the production environment are unable to complete payment transactions. Users receive "Transaction timed out" error. The issue is observed more frequently during peak hours.
Impact:
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Daily transaction loss
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Customer complaints
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Increased ticket volume to support team
5 Whys Technique Application
| Step | Question | Answer |
|---|---|---|
| 1 | Why are users unable to make payments? | Payment API returns timeout error |
| 2 | Why does the API timeout? | Database query responds late |
| 3 | Why does the query respond late? | Full table scan is performed on the Orders table |
| 4 | Why is a full table scan performed? | Index is not defined on the relevant column |
| 5 | Why is the index not defined? | Table growth was not anticipated, performance testing was not conducted |
Root Cause: user_id column lacks an index, and performance testing under load was not performed.
Fishbone Analysis (Ishikawa Diagram)
The following table categorizes the factors contributing to the payment timeout error:
| Category | Factors |
|---|---|
| PEOPLE | • Performance check was skipped during code review • DBA approval was not obtained |
| METHOD | • Load testing was not performed • DB migration checklist was incomplete |
| SYSTEM | • Index is missing • Connection pool is insufficient |
| ENVIRONMENT | • Peak hour traffic increase • Concurrent user count increased 3x |
| MEASUREMENT | • DB response time was not monitored • Alert threshold was not defined |
Main Problem: PAYMENT TIMEOUT ERROR
Actions Taken
Short-Term (Immediate Fix)
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Index added to orders.user_id column
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Connection pool size increased
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API timeout duration optimized
Medium-Term (Preventive Actions)
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Index review step added to DB migration checklist
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Load testing process integrated into CI/CD pipeline
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Monitoring and alerts defined for database response time
Long-Term (Process Improvement)
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Performance testing strategy documented
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Performance criteria added to code review checklist
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Capacity planning process established
QA's Role in the RCA Process
QA engineers should take an active role in the RCA process and ask the following questions:
Test Coverage Analysis
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Was this scenario within test coverage?
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Was load testing performed? If so, under what conditions?
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Were edge cases evaluated?
Test Strategy Assessment
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Why did the current testing approach fail to catch this bug?
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Which type of testing was missing? (Performance, Load, Stress)
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How accurately did the test environment reflect production?
Regression Strategy
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Which areas carry regression risk after this fix?
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What should be added to automation coverage?
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Should the smoke test suite be updated?
Defect Pattern Analysis
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Have similar bugs occurred before?
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Is there a common pattern?
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Which module or component is at risk?
RCA Report Template
An RCA report should include the following sections:
Summary
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Incident ID: INC-2024-0892
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Date: 2024-01-15
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Severity: P1
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Affected System: Payment Service
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Impact Duration: 3 hours 20 minutes
Problem Description
[Description of the problem and how it was detected]
Timeline
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09:15 - First alert triggered
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09:22 - Incident opened
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09:45 - Root cause identified
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10:30 - Hotfix deployed
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12:35 - Service stabilized
Root Cause
[Root cause identified through 5 Whys or other technique used]
Impact Analysis
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Number of affected users
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Number of failed transactions
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Financial impact (if any)
Actions Taken Table
| Action | Owner | Due Date | Status |
|---|---|---|---|
| Add index | DB Team | 2024-01-16 | Completed |
| Add load testing | QA Team | 2024-01-22 | In Progress |
| Set up monitoring | DevOps Team | 2024-01-25 | Planned |
| Update checklist | QA Team | 2024-01-20 | Completed |
Lessons Learned
[Conclusions drawn regarding process, system, and team]
Approval
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Prepared by: [Name]
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Approved by: [Name]
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Date: [Date]
Lessons Learned
Questions to be evaluated as a team at the end of each RCA process:
From a Process Perspective:
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Which control points were missing?
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Which existing processes should be updated?
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Is there an automation opportunity?
From a Technical Perspective:
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Is an architectural or design change required?
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Is monitoring and alerting sufficient?
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Is documentation up to date?
From a Team Perspective:
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Was there a knowledge gap?
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Was a training need identified?
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Were communication processes adequate?
Lessons learned outputs should be shared with the entire team and stored as a reference to prevent similar errors.