kubev2v/forklift-must-gather

Forklift Must-Gather Extenstion

Owned by Red Hat · part of IBM

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kubev2v/forklift-must-gather has 20+ forks on GitHub, is written in Shell, and was last pushed on Oct 17, 2026. Data as of . Signed-in members get hourly updates — create a free account.

Summary Information

Updated 2 hours ago
Added to GitGenius on October 12th, 2026
Created on November 26th, 2020
Open Issues & Pull Requests: 10 (+0)
GitHub issues: Enabled
Number of forks: 20
Total Stargazers: 3 (+0)
Total Subscribers: 13 (+0)

Repository Insights (GitGenius)

Median issue/PR response: 25.8 days
Mean response time: 32.1 days
90th percentile: 67.3 days
Tracked items: 3

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Issue Activity (beta)

Open issues: 1
New in 7 days: 0
Closed in 7 days: 0
Avg open age: 67 days
Stale 30+ days: 0
Stale 90+ days: 0

Recent activity

Opened in 7 days: 0
Closed in 7 days: 0
Comments in 7 days: 0
Events in 7 days: 0

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Detailed Description

Forklift must-gather is a diagnostic collection tool that extends OpenShift must-gather to capture Forklift-specific resources and logs.

The tool addresses the challenge of gathering relevant diagnostic data from Forklift deployments by collecting logs and custom resources in a structured format. It works by hooking into the OpenShift must-gather framework and filtering for Forklift-related artifacts, allowing operators to obtain a complete snapshot of the Forklift system state for troubleshooting and analysis.

Adoption makes sense for teams running Forklift migrations who need to diagnose issues or collect data for support. The tool is particularly valuable when dealing with long-running operations where only recent logs matter, as it supports time-based filtering to reduce data volume. Targeted gathering by namespace, migration plan, or virtual machine name allows operators to focus collection on specific resources rather than capturing everything, which saves time and storage when investigating particular migration failures. The tool can output results as an unpacked directory tree for direct inspection or as a compressed tarball for faster transmission to support systems.

The project maintains active development with regular commits addressing bug fixes and feature enhancements. Pull requests receive timely review and integration, indicating responsive maintenance. The codebase shows consistent attention to user-reported issues and incorporates feedback into updates.