Deckgauge is a source-available engineering-intelligence application that brings work-tracking and code-activity data into shared views for engineering leaders. The project says it connects Jira, GitHub, GitLab and Azure DevOps, with dashboards for delivery, roadmaps, team activity and organizational context. Those are advertised capabilities, not independently verified evidence that the metrics are accurate or that using the product improves performance.
What Deckgauge is designed to show
Deckgauge is intended to help leaders understand what work is planned, where teams are focused and how engineering activity is distributed. Its creator, Yaniv Zalevas, says he built it after seeing new consulting engagements begin with weeks of meetings to understand an engineering organization. He believed existing work data could answer some of those questions faster; that is his rationale, not a measured result.
The project describes Deckgauge as an engineering-intelligence cockpit, combining information from connected development and project systems. Its repository lists engineering dashboards, roadmaps, contribution insight, team management and review notes. Zalevas’s original feature pitch also names DORA metrics, roadmap focus, per-engineer workload, CapEx/OpEx and organizational views. Treat these as product claims rather than independently tested capabilities.
What the views do—and do not—establish
A dashboard can make patterns in delivery and work allocation easier to inspect, but a metric is not a complete account of engineering quality or individual contribution. Context matters: work differs in complexity, interruptions and dependencies, and activity counts can be misleading when used as a proxy for productivity. Deckgauge’s repository describes its approach as “Decision support with a human in the loop — never an automated performance rating.” That is the project’s stated intent, not independent evidence about how customers use the software.
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Which systems it connects
The documented sources are Jira, GitHub, GitLab and Azure DevOps. Before adopting Deckgauge, confirm that the connectors cover the systems and configurations your teams actually use. The project’s connector list does not establish that every data type, workflow customization or historical record in those platforms is supported.
Deckgauge is aimed at leaders looking for a consolidated view across work tracking and code activity. It is not, on the available product description, proof of a team’s health or a substitute for conversations with engineers.
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Self-hosting, demos and data handling
The repository documents deployment with Docker. The project presents self-hosting as a way to run the application on infrastructure the customer controls, and its creator says this keeps development data within the user’s infrastructure. That describes the intended architecture; it is not an independent security, privacy or data-flow audit.
The project’s demo is populated with fictional or synthetic information. The site labels its illustrative dashboard data synthetic, so displayed figures should not be read as customer outcomes or published performance statistics. The repository also says not to enter real data into the shared demo.
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Rank #3
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Secure the deployment before exposing it
The repository warns that the common demo account, test@test.com, has a publicly known password. It also says the default published Docker Compose ports may listen on all interfaces. Do not leave those defaults exposed on a network.
- Remove the sample account before using a deployment with real organizational data.
- Restrict host binding and network access before exposing the service beyond a trusted environment.
- Use the current repository’s installation, backup and upgrade instructions; commands and migration details can change between releases.
License and commercial options
The repository identifies Deckgauge as source-available under the Functional Source License, FSL-1.1-Apache-2.0. Its summary permits commercial use but restricts offering Deckgauge as a competing substitute product or hosted service. The Apache-2.0 grant takes effect on the second anniversary of each release, not on one shared date for all versions. The repository says version 2.0.0 was published September 11, 2026 and converts on September 11, 2028. Check the LICENSE file for the exact release you plan to use and for the terms that apply to your use case.
Rank #4
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The project describes its Community edition as free, with no developer cap or feature gate on metrics, boards, dashboards or connectors. It describes Enterprise as a hosted and operated service or as a commercial license for a customer’s environment, with support. These are current project descriptions; confirm availability and terms directly with the project before making a decision.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.How to evaluate Deckgauge for your team
Compare it with other engineering-intelligence tools against your actual requirements rather than relying on feature labels alone. The repository positions Deckgauge alongside products such as Jellyfish and LinearB, and the project site names Swarmia as a nearby alternative; the available information does not establish a like-for-like comparison.
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- What You Get: Anker 332 USB-C Hub (5-in-1), welcome guide, our worry-free 18-month warranty, and friendly customer service.
- Integration fit: Check the documented connectors against your trackers, code hosts and specific workflows.
- Deployment and control: Decide whether a self-hosted deployment or a hosted service fits your operational and data-control needs.
- Metric transparency: Ask how each measure is calculated, what data it omits and whether teams can challenge interpretations.
- Use of individual-level data: Set clear limits on whether workload or contribution views can be used for rankings or performance decisions.
- Edition and license: Separate Community features from paid hosting, support or commercial licensing, and review the license for the exact release in use.
Zalevas also says the application was largely built by AI agents using Claude Code with an agent workflow, with human review on every merge. That is the author’s account of the development process, not an independently audited history.
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