Summary
Harvester provides a support bundle for its cluster to resolute incidents. However support bundle contains endless logs with complex naming patterns. This epic target to build a lightweight CLI tool that helps SREs quickly debug issues by analyzing Harvester support bundles. The tool will parse support bundle contents, surface relevant errors, and provide actionable insights to accelerate incident resolution.
Problem
Harvester generates support bundles to resolve cluster incidents. But these archives contain thousands of log files with cryptic naming conventions and unstructured data. SREs currently spend hours manually grepping through logs, correlating timestamps across services, and identifying error patterns. The complexity of support bundle structures makes it difficult to quickly pinpoint root causes, especially during production outages where every minute matters. Without a standardized analysis approach, debugging efficiency varies widely across team members, leading to inconsistent resolution times and increased cognitive load during critical incidents.
Solution
Build a lightweight CLI tool that automates Harvester support bundle analysis, enabling SREs to debug incidents in seconds rather than hours. The tool will:
- Parse & Extract: Automatically read support bundle archives, interpret file structures, and surface relevant logs, configs, and metrics
- Detect Errors: Identify critical errors, correlate patterns across services, and prioritize issues by severity and impact
- Provide Actionable Insights: Generate human-readable summaries with root cause suggestions, runbook references, and recommended next steps
By transforming thousands of chaotic log files into structured, prioritized diagnostics, the tool empowers SREs to resolve incidents faster, reduces human error, and ensures consistent debugging practices across the team.
Goal
- Simple, fast debugging for SREs
- Validate the cluster health
Child Issues / Tasks
Design Document
No response
Summary
Harvester provides a
support bundlefor its cluster to resolute incidents. However support bundle contains endless logs with complex naming patterns. This epic target to build a lightweight CLI tool that helps SREs quickly debug issues by analyzing Harvester support bundles. The tool will parse support bundle contents, surface relevant errors, and provide actionable insights to accelerate incident resolution.Problem
Harvester generates support bundles to resolve cluster incidents. But these archives contain thousands of log files with cryptic naming conventions and unstructured data. SREs currently spend hours manually grepping through logs, correlating timestamps across services, and identifying error patterns. The complexity of support bundle structures makes it difficult to quickly pinpoint root causes, especially during production outages where every minute matters. Without a standardized analysis approach, debugging efficiency varies widely across team members, leading to inconsistent resolution times and increased cognitive load during critical incidents.
Solution
Build a lightweight CLI tool that automates Harvester support bundle analysis, enabling SREs to debug incidents in seconds rather than hours. The tool will:
By transforming thousands of chaotic log files into structured, prioritized diagnostics, the tool empowers SREs to resolve incidents faster, reduces human error, and ensures consistent debugging practices across the team.
Goal
Child Issues / Tasks
Design Document
No response