Turbinia
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Turbinia is an open-source framework for deploying, managing, and running distributed forensic workloads to automate common forensic processing tools in the cloud.
turbiniactl status -g <group id>
Summary
Turbinia is an open-source framework, free to use, for deploying, managing, and running distributed forensic workloads such as Plaso, TSK, and strings across cloud or local machines. It runs as separate client, server, and worker components, with the server scheduling and parallelizing tasks that workers pick up continuously, making it suited to incident response and DFIRDFIRDigital forensics and incident response, investigating what happened during a security incident and containing it. The work includes preserving evidence, reconstructing activity and restoring systems. teams processing large volumes of evidence under time pressure rather than analysts working case-by-case by hand. The README itself points users toward OpenRelik, noting that Turbinia is in maintenance mode and will not receive new features, though it still sees occasional commits and releases from its long-running contributor base dating back to 2015.
Turbinia is an open-source framework for deploying, managing, and running distributed forensic workloads to automate common forensic processing tools in the cloud.
How Turbinia helps
How do I get several terabytes of disk images through Plaso and TSK without waiting on one machine to finish each in turn?
the server splits incoming evidence into tasks and hands them to workers that pick jobs up continuously, so many images or files are processed in parallel instead of one at a time
Where has this piece of evidence gotten to, and is it done yet?
the client can query the server for the status of submitted tasks, showing which are still queued, running, or finished
How much can I throw at processing before I need to add another worker?
because workers pull tasks from the server continuously, adding a worker increases parallel capacity without changing how evidence is submitted
Can I process evidence on a local machine and in the cloud with the same setup?
client, server, and worker components run independently and can each be deployed in the cloud, on local machines, or as a hybrid, so the same request path handles either
What happened during a specific worker's run when a task looked stuck?
the client can pull a bounded number of log lines back from a worker to inspect its recent activity without logging into the machine directly
Did evidence discovered mid-processing get picked up automatically?
any new evidence a task creates or uncovers is fed back into Turbinia so it re-enters the same scheduling and processing pipeline rather than being left for manual handling
Languages
Command line
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Score card
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Shipping velocity releases a month, last 12 months
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Documentation quality release-notes rubric, 0–100
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Breaking-change discipline how rarely a release breaks users, and notice given
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Maintenance risk quiet time against its own cadence, maintainers
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Innovation & surface new capabilities, API and MCP surface
- Community health
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Contributor trend distinct committers, this year against last
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Maintainer concentration bus factor now against a year ago
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Issue backlog trend issues closed per issue opened, 12 months
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Responsiveness median time to a maintainer’s first reply
Nine scores for Turbinia, each built from the releases, notes and API history this site tracks — and, on Researcher and Business, where it stands among every measured tool in its category and how that has moved.
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Blank means never measured; nothing here is a filled-in zero.
Peer standings are included with Researcher and Business. See how this tool ranks against its competitors, using data we don't publish anywhere else.
See plans →Each score is 0–100 on a published rubric, derived from data this site already shows. A dimension we cannot measure says so — it is never scored 0 and never enters a rank.
How this is scored
- Shipping velocity — releases a month over the last 12 months, on a log scale where 16 a month scores 100. Needs 3 releases in the window.
- Documentation quality — the release-notes rubric published on the analytics page, unchanged.
- Breaking-change discipline — the share of releases carrying a breaking change (none scores 100, half or more scores 0). Only projects that label breaking changes are measured: a clean record cannot be told from an unlabelled one.
- Maintenance risk — quiet time measured against the tool's own release cadence (quiet longer than 90 days and three typical gaps scores 0), plus the number of active maintainers and whether contributors are growing, where known. Higher is lower risk.
- Innovation & surface — new capabilities in the feature ledger this year, API and MCP operations added, and the share of commits that are features: the mean of whichever we hold.
- Community health (open-source tools only) — each is a direction, not a size: contributors this year against last, the bus factor now against a year ago, and issues closed per issue opened, where steady scores 50, doubled 100 and halved 0; plus the median time to a maintainer's first reply (an hour scores about 100, a month or more 0). A commercial card has no repository and carries none of the four.
- Documented delivery (commercial tools) — when a vendor's documented new capabilities have slowed against its own baseline, that counts against the overall standing as heavily as two low dimensions. Steady delivery, or too little history to judge, leaves the standing alone; it is never a sixth score.
- Open-source tools are scored on repository signals; commercial tools on their published changelog. Ranks compare tools within one category and one profile and need at least five measured peers; the overall standing needs three ranked dimensions. Best-in-breed or consolidator is a shape, not a quality, and is never scored.
Release-note detail over time
See how much detail Turbinia puts in its release notes, quarter by quarter, and compare it with tracked tools in the same category. This history uses up to ten retained, reviewed notes per tool; sparse or blank older quarters may reflect that limit.
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Releases
13 entries
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- February 20251
- October 20241
- August 20241
- March 20241
- November 20231
- July 20231
- February 20231
- November 20221
- September 20221
- July 20221
- February 20221
- January 20221
- October 20211
Project health
Issue, contributor and maintainer activity in google/turbinia, 2023-10 – 2026-09, as of 2026-09-25. Twelve-month figures first; the trend lines run the whole window.
- Contributors 9 +2 vs prior 12 months
- Maintainers 0 +0 joined · −3 left, last 12 months
- Bus factor 0 committers behind half the commits
- Community-filed 100% of issues opened, last 12 months
- Median time to close 2.2 years first maintainer reply 2.7 days
- Open backlog 98 of 569 issues ever filed
- Issues opened / month 0 · 0 communitymaintainers
- Open backlog 98
- Contributors / month 1
- Commits / month 1
- Stars 794
- bugs 100%
Counts from the project's public repository and git history; no individuals are identified. Maintainers are the committers covering 80% of the last year's commits. how we measure this
Libraries its release ships
What its latest release locks, checked against known advisories.None of its release's images build from a lockfile we can read.
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