How to Set Up a Software Engineering Dashboard [+Key Metrics]

If your engineering team isn’t using a software engineering dashboard, you’re probably flying blind.

A solid dashboard gives you real-time data, key metrics, and clear visualizations—all in one place—so you can make smarter decisions, ship faster, and keep your team aligned. Instead of digging through Git logs, issue trackers, or spreadsheets, you get a single source of truth that helps you track progress, spot bottlenecks, and optimize workflows.

In this guide, we’ll break down exactly what an effective software engineering dashboard should include, how to set one up, and how to use your dashboard to manage continuous improvement.

From PR cycle time and deploy frequency to collaboration insights, we’ll cover the essential metrics that drive real impact. Whether you’re optimizing for speed, quality, or efficiency, the right dashboard ensures your team stays on top of their game.

What your software engineering dashboard should include

You should be able to review all of these important aspects.

1. Code quality metrics

High-quality code is the backbone of stable, maintainable software. A strong software engineering dashboard must track key metrics that highlight potential risks and areas for improvement. By monitoring these indicators, teams can enforce better coding practices, reduce defects, and improve long-term software health.

Key metrics to track:

• Change failure rate (DORA metrics): Measures how often deployments result in failures, indicating code stability.
• PRs merged without review: Identifies gaps in the review process that could lead to undetected issues.
• Issues caught in reviews: Reflects the effectiveness of peer code reviews in catching bugs early.
• Rework and refactor (work breakdown): Tracks the time spent refining existing code, ensuring maintainability.

By integrating these metrics, teams gain actionable insights to improve code quality and reduce long-term technical debt.

2. Engineering velocity metrics

Engineering velocity is a critical measure of how efficiently a team delivers software. A well-structured dashboard provides insights into bottlenecks, identifies inefficiencies, and guarantees a smooth workflow across the development pipeline. By monitoring these key metrics, teams can optimize processes and accelerate time-to-market without sacrificing quality.

Key metrics to track:

• PR cycle time (coding, review, deployment): Tracks how long it takes for pull requests to progress from creation to deployment.
• Deploy frequency in days: Measures how often code is shipped to production, ensuring rapid iteration.
• Daily work in progress (WIP) tasks: Identifies workload distribution and potential bottlenecks in development.
• Issue cycle time per task type: Highlights delays in resolving different types of work, such as features, bugs, and enhancements.

3. Technical debt management

Technical debt is the silent killer of engineering teams. If left unchecked, it drags down velocity, increases failures, and turns simple fixes into nightmares. Keeping an eye on rework and refactoring trends helps teams see where time is being spent fixing past mistakes instead of building new features. A rising change failure rate signals fragile deployments that need attention before they derail productivity.

Technical debt creates long-term instability in your codebase. If a team is spending more time fixing old issues than developing new features, it’s a red flag. Code reviews should catch problems early, but without tracking refactoring trends and issue resolution times, technical debt can spiral out of control.

Key metrics to track:

• Rework and refactoring trends: Avoid excessive fixes by addressing root causes early.
• Change failure rate: High numbers here mean unstable deployments and poor testing.
• Issue cycle time for bugs and hotfixes: Faster resolution keeps users happy and teams focused.
• Best practices to prevent technical debt: Regular refactoring, solid testing, and disciplined development keep debt under control.

4. Productivity and collaboration metrics

Productivity isn’t just about speed—it’s about sustainable, high-quality output. A solid dashboard gives teams visibility into their workload and collaboration habits, ensuring no one is overloaded or disengaged. Tracking these metrics helps balance efficiency with team well-being, preventing burnout while maintaining a strong development pace.

Key metrics to track:

• PRs merged vs. PRs opened (throughput): A widening gap suggests bottlenecks in the review process.
• Days with commits: Consistent commits indicate steady progress, while gaps may signal blockers.
• Comments per review: Fewer comments could mean rushed or shallow reviews, affecting code quality.
• Tracking engagement and preventing burnout: Monitor workload distribution to check that developers aren’t overwhelmed.

5. Deployment and reliability metrics

Reliable deployments are the backbone of a high-performing engineering team. Frequent, stable releases mean faster feedback loops and fewer fire drills. If your deployment frequency is low or failure rates are high, it's time to fine-tune your processes. Tracking the right metrics helps teams ship code with confidence while minimizing downtime.

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Key metrics to track:

• Deploy frequency: More frequent deployments lead to faster iteration and reduced risk per release.
• Change failure rate: A high failure rate signals poor testing or rushed code merges.
• Best practices for tracking deployments and minimizing risk: Automate testing, enforce code review standards, and implement rollback strategies.

How to build a software engineering dashboard

A well-built software engineering dashboard is critical for data-driven decision-making, allowing teams to track performance, identify bottlenecks, and drive continuous improvement. Follow these steps to set up a high-impact dashboard that keeps your engineering team aligned, efficient, and focused on delivering value.

Step 1: Choose an engineering analytics platform

tart by selecting a robust engineering analytics platform like DevStats. A powerful tool offers seamless integration with your existing development workflow and provides accurate, real-time insights. Once you've set up DevStats or an equivalent platform, configure it according to your organization’s needs, connect repositories, and import historical data. The more data available, the better the insights.

Step 2: Connect to data sources

Your dashboard must pull data from multiple sources to provide a comprehensive view of engineering performance. To get the most out of your engineering analytics dashboard, you need to connect it to multiple data sources for a complete and accurate picture. Without solid integrations, you’re left piecing together insights manually, which is time-consuming and prone to errors.

• Integrate DevStats with GitHub, GitLab, or Bitbucket: Make sure all repositories are linked.
• Use API integrations as needed for real-time data updates: Automate data collection to eliminate manual tracking.

Step 3: Visualize your data

Now that your data sources are connected, it’s time to explore your dashboard and get comfortable with the layout. Start clicking around to see how data is organized and which reports are available. A few key metrics to check right away include PR Cycle Time, which shows how long pull requests take to move through the pipeline, Deploy Frequency, which tracks how often new code is shipped, and Issue Cycle Time, which highlights how quickly tasks are completed. As you navigate, look for trends, bottlenecks, or unexpected patterns to get a quick sense of your team’s workflow.

Step 4: Identify bottlenecks and issues

A dashboard is only useful if it leads to action. Use it to detect inefficiencies, such as slow PR cycles, high change failure rates, or inconsistent deployment frequencies.

Here are some ideas to get you started:

• Analyze PR cycle time to spot delays
• Monitor issue cycle time to uncover blockers in development
• Track daily WIP to prevent team overload, too much unplanned work, and context switching

Step 5: Plan realistic benchmarks

Continuous improvement starts with setting achievable, data-backed goals, and your dashboard provides the foundation for defining and tracking performance benchmarks. Begin by comparing your current metrics against industry standards, using frameworks like DORA and SPACE as a baseline to understand where your team stands. From there, set improvement targets for key areas such as code quality, development velocity, and team collaboration. Focus on making realistic, incremental gains rather than sweeping changes, ensuring steady progress without overwhelming your team​.

Step 6: Execute necessary changes

Once problem areas are identified and benchmarks are set, implement changes to optimize team efficiency and code quality. Start by prioritizing the most impactful adjustments, focusing on bottlenecks that slow down development. You should be regulary monitoring progress to check that changes are producing the desired results and be ready to iterate if needed.

Here are some ideas:

• Reduce PR cycle time by streamlining reviews and automating tests
• Increase deployment frequency by improving CI/CD practices
• Enhance collaboration by enforcing review processes and balancing workloads

Step 7: Review your results

An engineering dashboard should grow and adapt as your development team evolves, so it’s important to regularly check in on key metrics and make adjustments as needed. Use DevStats to track progress against your benchmarks and see if the changes you’ve implemented are making a real impact​. If things start to plateau, take a step back, reassess your processes, and tweak your approach. Continuous improvement is a cycle of identifying, planning, executing, and reviewing​​. Stay flexible, keep an eye on trends, and refine your strategy to ensure long-term success.

Now you know how to use a software development dashboard to make informed decisions.

It’s time to set one up for your team. The good news is that it only takes a few minutes to get started. Learn more about DevStats.