Best Engineering Metrics and DORA Tools in 2026
Every eng leader eventually gets asked some version of 'why is this taking so long?' Engineering metrics tools pull data from Git, CI/CD, and issue trackers to answer it with evidence instead of anecdotes: where pull requests wait, how long deploys take, how often changes fail, and how work is split between new features, maintenance, and unplanned work.
These tools can also be misused as surveillance, which destroys trust quickly. We evaluated them on metric coverage (DORA, cycle time, investment allocation), data quality, developer experience features, how they frame team versus individual data, and ease of setup.
Picking a PM tool? Four questions, one straight answer.
Tell us how your team works. We’ll say where Vantage fits next to your tracker, and where it doesn’t.
LinearB
Delivery metrics with workflow automation
LinearB measures DORA metrics, cycle time, and PR workflow across Git and project tools, and adds automation through gitStream to route reviews, label PRs, and enforce policies. Benchmarks help teams compare their metrics against industry ranges.
Pros
- DORA and cycle time metrics out of the box
- Workflow automation to improve PR flow
- Industry benchmarks for context
- Free tier for smaller teams
Cons
- Configuration needed to map work types correctly
- Some features require higher tiers
- Can feel metrics-heavy for small teams
Jellyfish
Engineering management platform tied to business investment
Jellyfish connects engineering activity to business priorities, showing how effort is allocated across initiatives, maintenance, and unplanned work. It is often used by eng leaders reporting to executives and finance, including for software capitalization, alongside delivery and DORA metrics.
Pros
- Strong investment allocation reporting
- Connects engineering work to business initiatives
- Supports software capitalization reporting
- DORA and delivery metrics
Cons
- Aimed at larger engineering orgs
- Requires clean issue tracker data
- Sales-led pricing
Swarmia
Developer-friendly metrics and working agreements
Swarmia combines DORA and flow metrics with features designed to help teams improve on their own terms, such as working agreements, Slack notifications for stuck PRs, and investment balance views. It deliberately emphasizes team-level insights over individual rankings.
Pros
- Team-first framing builds trust with engineers
- Working agreements and Slack nudges drive improvement
- Investment balance and DORA metrics
- Developer experience surveys
Cons
- Fewer executive reporting features than Jellyfish
- Best with GitHub; other integrations vary
- Per-developer pricing
DX
Developer experience measurement combining surveys and system data
DX measures developer experience and productivity using a combination of research-backed surveys and system data from tools such as GitHub, Jira, and CI. Its frameworks focus on identifying friction that slows developers down, and it is widely used to measure the impact of AI coding tools.
Pros
- Research-backed developer experience surveys
- Combines perception data with system metrics
- Useful for measuring AI tooling impact
- Strong benchmarking
Cons
- Survey participation is required for full value
- Aimed at mid-size and larger orgs
- Sales-led pricing
Sleuth
Deployment tracking and DORA metrics
Sleuth focuses on deployments as the unit of measurement, tracking what shipped, when, and with what impact to calculate accurate DORA metrics. It also supports team rituals such as reviews and planning with metrics included.
Pros
- Accurate deploy-based DORA metrics
- Tracks change impact after deploys
- Integrations with CI/CD, monitoring, and trackers
- Supports recurring team reviews
Cons
- Narrower scope than full engineering management platforms
- Setup depends on deployment tooling
- Smaller vendor
Faros AI
Engineering intelligence with an open data model
Faros AI connects data across source control, CI/CD, incident, and planning tools into a unified model for DORA, productivity, and AI adoption metrics. An open-source community edition lets teams start without a commercial contract.
Pros
- Broad data connectors across the delivery toolchain
- Open-source community edition
- Flexible custom metrics
- AI coding assistant impact analysis
Cons
- More setup than turnkey tools
- Best value at larger scale
- Advanced features commercial only