The Top 5 Tools to Track DORA Metrics (2026 Buyer’s Guide)

Tracking DORA metrics sounds simple until you try to do it. Then you’re knee-deep in GitHub exports, Jira queries, and a spreadsheet that breaks every time someone changes the CI configs.

Scroll through any engineering subreddit, and you’ll find some version of this question:

(Source: Reddit)

The framework makes sense on paper. Four metrics, clear definitions, and plenty of research backing them up. But then, you try to implement it and spend weeks wiring together systems that were never meant to share data.

This guide walks through five tools that handle DORA measurement without the DIY overhead. We’ll cover how each one works, what makes them different, and which is the best fit depending on your stack and team size.

Why DORA Metrics Are Hard to Measure Accurately

Getting accurate numbers is harder than it looks. Most teams figure this out within the first few weeks of trying to set up DORA tracking on their own.

Here are a few common problems that show up:

• Teams define “deploy” differently: Some count every merge to main, others only count production releases, and teams running microservices might track each service as a separate deployment. None of these approaches is wrong, but the numbers become hard to compare when everyone measures differently.
• Your stack doesn’t share data: Pull requests in GitHub, tickets in Jira, deploys in CircleCI, incidents in PagerDuty. To get a single number like lead time, you need to trace a path across all of these systems. That’s possible to do manually for a while, but it doesn’t scale, and it breaks the moment someone changes a workflow.
• Microservices make tracking harder: A single feature might touch five different repos and trigger a dozen separate deployments before it reaches users. Calculating lead time for that feature means tracing all of those changes back to a single starting point, which most tools aren’t built to do automatically.
• Failures and rollbacks blend together: A quick rollback that fixes an issue in two minutes might count as a failure on one team and a successful recovery on another. The same goes for partial outages, degraded performance, or errors that only affect a subset of users.
• Clean data needs consistency that most teams don’t have: Accurate measurement depends on clean data, which means every deploy, every incident, and every release needs to be labeled the same way. In practice, that rarely happens. One team tags everything carefully, another skips it when deadlines get tight, and a third uses slightly different conventions that don’t match anyone else.

What to Look for in a DORA Metrics Tool

Not every platform approaches DORA tracking the same way. Some give you raw numbers and leave the interpretation to you, while others provide the context and drill-down you need to improve.

A few things are worth paying attention to before you commit to a platform:

• Native integrations with your existing stack: The tool should connect directly to your version control, issue tracker, CI/CD platform, and incident management system without any custom scripts or middleware. The fewer manual connections you have to build and maintain, the more reliable your data will be over time.
• Second-order metrics that explain the “why”: The four DORA numbers tell you what’s happening, but not why. A good tool will also outline metrics like cycle time, PR review time, and flow efficiency so you can trace a slow lead time back to its root cause.
• Ready-to-use dashboards from day one: You shouldn’t need to spend weeks building views before you see your first metric. The best platforms come with DORA dashboards already configured so you can start tracking immediately and adjust things later.
• Multi-level views that match your org structure: A platform should let you see metrics at the team level, the department level, and the org level without rebuilding dashboards from scratch. This makes it easier to roll up insights for leadership while keeping granular data available for team leads.
• Full visibility across the software delivery lifecycle: DORA metrics alone don’t show you everything. The best tools track work from ticket creation through code review, deployment, and production, so you can see where time gets lost at every stage.
• Threshold alerts that find issues early: Most teams don’t have time to monitor dashboards every day. The better platforms let you define acceptable ranges and push alerts to Slack or email when something falls outside them.

5 Best Tools to Track DORA Metrics in 2026

With those criteria in mind, here are five platforms that handle DORA tracking well.

Each one takes a slightly different approach, so the right choice depends on your stack, team size, and how deep you want to go with engineering analytics:

1. Plandek

Plandek is a software engineering intelligence platform that combines real-time DORA tracking with predictive analytics and AI-driven insights.

The platform connects to your existing DevOps toolchain and tracks metrics across the full software delivery lifecycle, from ticket creation through deployment and production. Plus, it comes with an AI assistant that interprets your data and pushes actionable insights directly to Slack.

Key Features

• Dekka, an AI-powered virtual engineering pro: Plandek includes Dekka, an AI assistant that analyzes your delivery data and pushes daily summaries of risks, blockers, and recommended actions to Slack or email.
• Native integrations across the DevOps stack: The platform connects directly to Jira, GitHub, GitLab, Azure DevOps, Bitbucket, Jenkins, CircleCI, PagerDuty, and more. It handles both cloud and on-prem instances, and normalizes data across different configurations.
• North Star dashboards for leadership: The platform includes executive-level views that let tech leaders define and track the KPIs that matter most to stakeholders. These dashboards make it easier to communicate engineering performance to the C-suite without dumbing down the data.
• SmartView for predictive delivery analytics: SmartView analyzes ticket history across your teams to calculate risk scores at the sprint and epic level. It flags stalled tickets, PR delays, and QA bottlenecks as they happen, and recommends specific actions to get things back on track.
• GenAI impact measurement: Most teams have adopted AI coding assistants, but have no way to measure whether they’re helping. Plandek tracks how tools like GitHub Copilot, Cursor, and Devin are affecting cycle time, merge frequency, and quality metrics across your org.

What Are Real-World Users Saying about Plandek

• Day-to-day sprint visibility: The sprint breakdowns are detailed enough to check multiple times a week, whether you’re tracking mid-sprint progress or monitoring how a larger project is trending across cycles. [Read Full G2 Review]
• Automated reporting through native integrations alternatives: Plandek connects directly to Jira, GitHub, and Azure DevOps, which means reporting happens in the background. No manual data pulls or spreadsheet wrangling needed. [Read Full G2 Review]
• Clean setup with minimal learning curve alternatives: Navigation is clean, and the setup process stays out of your way. You don’t need a dedicated admin or extensive training to get things working. [Read Full G2 Review]

What Are Customers Saying about Plandek

DORA tracking delivers the most value when it leads to measurable improvement. Secret Escapes, a fast-growing UK travel company, needed to scale its engineering org without sacrificing delivery speed.

After rolling out Plandek across their teams, they reduced cycle time by 75%, cut production hotfixes by 54%, and doubled commit frequency — all within 24 months.

Visibility gaps create a different kind of problem. PEI Group was stuck with manual, Excel-based reporting that ate up hours and still produced outdated numbers.

They implemented Plandek to automate metric collection and gain full SDLC visibility across Jira, PRs, builds, and deployments. Engineering metrics now go straight into board-level reporting, and the platform has become the default for every new team that joins.

Sprint predictability is another common pain point. Lucanet struggled with scope creep and oversized stories that kept spilling into future sprints.

They used Plandek to track target completion and relative velocity, which helped teams spot where they were underestimating capacity. The result was tighter planning, fewer delays, and a clearer picture of what was causing delivery to slip.

2. Sleuth

Sleuth is an engineering intelligence tool that takes a deploy-first approach to DORA tracking. Instead of inferring deployments from commits or merges, it treats each deploy as a discrete event and connects it to the issues, builds, and incidents around it.

Key Features

• 100+ no-code automations: The platform includes pre-built automations for pull request hygiene, traceability between issues and deploys, and Slack-based workflows.
• Full cycle time visibility: Tracks work from the moment an issue comes up through code commits, pull requests, deployments, and rollbacks. This gives teams a complete picture of where time gets spent across the delivery process.
• AI-powered engineering reviews: Sleuth offers templated reviews for standups, sprint retrospectives, and executive check-ins that pull in relevant metrics automatically.

Limitations

• Some gaps with trunk-based setups: Sleuth works best with branching workflows, and teams using trunk-based development may need to do extra work to get accurate metrics. [Read Full G2 Review]
• Limited guidance for complex setups: The platform offers technical documentation, but teams with less common development or deployment workflows may spend extra time figuring out how to adapt Sleuth to their process. [Read Full G2 Review]
• Cost scales with team size: Per-user pricing means the total spend grows as your team grows, which can make Sleuth a harder sell for companies watching their software budget closely. [Read Full G2 Review]

Pricing

Sleuth charges per user per month:

• The Standard plan runs $35 per user and includes DORA metrics and automations
• The Enterprise plan costs $45 per user and brings features like SAML SSO, on-premise GitHub support, and dedicated customer success.

A 30-day free trial is available for both tiers.

3. Swarmia

Swarmia is a software engineering intelligence platform that combines quantitative metrics with qualitative developer feedback.

It integrates with GitHub, Jira, Linear, and Slack to track the standard DORA numbers, but also includes a built-in survey framework to measure developer satisfaction and team health.

Key Features

• DORA metrics with team-level drill-down: Swarmia tracks all four DORA metrics and lets you filter by team, repository, or time period. You can view deployment frequency, change lead time, change failure rate, and MTTR across your entire org or for specific groups.
• Developer experience surveys: The platform includes a 32-question survey framework based on research into developer productivity and satisfaction. You can run recurring surveys and compare results across teams.
• Slack notifications that push data to engineers: Swarmia sends relevant updates directly to Slack. This includes PR reminders, CI failure alerts, and team-level notifications that keep work moving without context switching.

Limitations

• Custom CI/CD setups need workarounds: Swarmia doesn’t automatically detect every deployment method. Teams with non-standard GitHub Actions for deploys may find the configuration less straightforward than expected. [Read Full G2 Review]
• Limited customization for metrics and tagging: Users who want to build their own metrics or tag issues in specific ways may find the platform restrictive. [Read Full G2 Review]
• Scope creep detection can be too aggressive. The platform sometimes flags small, legitimate changes made during code review as scope creep. There’s no easy way to mark certain additions as minor, which can make the metric feel less accurate for teams with fluid workflows. [Read Full G2 Review]

Pricing

Swarmia has a modular pricing structure. You can start with a single module (Business outcomes, Developer productivity, or Developer experience) at €28 per developer per month, or get all three with the Standard plan at €49 per developer per month.

A free tier covers companies with up to 9 developers and includes most features. Enterprise pricing is available for larger orgs and adds on-premise integrations and volume discounts.

4. Code Climate Velocity

Code Climate Velocity is an engineering management platform built for mid-sized to large engineering teams with complex team structures and workflows.

The platform connects to GitHub, Jira, and your incident management stack to track DORA metrics and over 60 other indicators in one place.

Key Features

• DORA metrics with real-time deployment and incident data: Velocity connects to your CI/CD and incident management tools via API to pull actual deployment and incident records. Teams with complex release processes get more accurate metrics than platforms that rely on commit or merge data alone.
• Deep metric coverage in one place: The platform tracks over 60 metrics spanning delivery speed, code quality, and team activity. You can combine DORA data with metrics like PR size or cycle time in the same dashboard.
• Filtering by team, repo, and application: The platform supports grouping and filtering data by team, repository, or application, which is useful for large organizations that need to compare performance across different groups or track specific delivery pipelines.

Limitations

• Integration and documentation gaps: Setting up new repositories is not always straightforward, and the API can behave inconsistently when queries don’t match expected filters. [Read Full G2 Review]
• Limited options for fixing data issues: Process inconsistencies, like a PR that skipped a step, can distort results in ways that are hard to clean up later. Teams may need to manually verify any metrics that look unusual before acting on them. [Read Full G2 Review]
• Team assignments can be hard to keep current: If people move between teams frequently, keeping Velocity’s team structure in sync becomes a chore. Users have also noted that tighter integrations with other products and engineering tools would help paint a fuller picture of team health. [Read Full G2 Review]

Pricing

Code Climate Velocity does not list public pricing on its website. According to third-party sources, pricing for larger organizations can run around $700 per user per year, though exact costs depend on team size and feature requirements.

You’ll need to contact sales for a quote.

5. LinearB

LinearB is a software engineering intelligence platform that connects to your Git repositories and project management tools to track DORA metrics alongside deeper workflow analytics.

It also breaks down cycle time into four different phases (coding time, pickup time, review time, and deploy time), which helps teams figure out exactly where work is getting stuck.

Key Features

• DORA metrics with industry benchmarks: LinearB tracks all four DORA metrics and compares your performance against benchmarks built from over eight million pull requests across thousands of engineering teams.
• Team working agreements and goal tracking: Engineering managers can set targets for metrics like PR size, review time, and pickup time. LinearB tracks progress against these goals and notifies teams when work risks falling behind.
• GitStream workflow automation: This policy-as-code engine automates repetitive PR tasks like routing reviews to the right people, applying contextual labels based on code changes, and auto-approving low-risk modifications.

Limitations

• Executive reporting takes extra effort: LinearB provides granular data, but some users find it difficult to roll that detail into simple summaries for senior leadership. A streamlined scorecard view with built-in benchmarks would make upward reporting easier. [Read Full G2 Review]
• Setup is team-by-team: Configuration happens at the team level, so organizations with multiple squads need to repeat the process for each one. LinearB supports quick-start setups with room to refine later, but training across teams takes time. [Read Full G2 Review]
• Takes time to learn the full feature set: The range of metrics and settings means there’s a learning curve before teams feel comfortable. [Read Full G2 Review]

Pricing

LinearB offers two plans billed per contributor per month:

• Essentials at $29/contributor/month: Includes 1,000 monthly credits, AI code reviews, auto-PR descriptions, programmable workflows, and developer satisfaction surveys. Supports GitHub Cloud only, and a free trial is available.
• Enterprise at $59/contributor/month: Adds 1,500 monthly credits, developer productivity insights, project tracking and forecasting, resource allocation, R&D cost capitalization, and Slack/Teams automations. Custom pricing for large deployments.

How to Choose the Right DORA Metrics Tool for Your Team

The right tool depends on where your team is today and where you’re headed. A platform that works for a 10-person startup will feel different from one built for a 500-engineer organization with multiple business units.

Here’s how the options break down by team stage:

No tool will be perfect out of the gate. The goal is to pick one that covers your core needs today and gives you room to grow. Most platforms offer trials or demos, so you can test a couple before locking in.

Plandek – The #1 Tool to Track DORA Metrics in 2026

Plandek is ideal if you’re past the point of just wanting to know your DORA numbers. It’s for teams that want to understand why lead time crept up last quarter, where cycle time is getting eaten, and which sprints are at risk of missing their goals.

Here’s what you get with Plandek:

• Dekka, an AI assistant that monitors your delivery data and pushes daily summaries of risks, blockers, and recommended actions to Slack or email
• SmartView predictive analytics that assign risk scores to sprints and epics, and flag issues while there’s still time to course-correct
• A library of 50+ configurable metrics other than DORA, so you get the second-order indicators needed to understand what’s driving each number
• Out-of-the-box integrations with the tools you already use, including Jira, GitHub, GitLab, Azure DevOps, Jenkins, CircleCI, and PagerDuty
• GenAI impact tracking that measures how tools like Copilot and Cursor affect velocity, quality, and delivery predictability across your org

If your current DORA setup isn’t giving you the depth you need, it’s worth seeing what Plandek can do.

Book a demo to see the platform in action.