DORA Metrics Tools: ULTIMATE Guide to Choose the Best Option

You're on the right page if you’re looking for the best DORA metrics tools.

After we share our five-step framework, which includes metrics measurement, developer friendliness, integrations, and more, we'll analyze six top contenders.

Feel free to use it if you’re doing your own shortlist.

Here’s a sneak peak:

What Are DORA Metrics?

DevOps Research and Assessment (DORA) metrics are performance indicators. You can use them to gain valuable insights into your software development lifecycle.

Following DORA metrics allows engineering teams, leaders, and other stakeholders to make data-driven decisions based on team performance. The end goal, of course, is to improve operational efficiency.

1. Deployment Frequency

Deployment frequency measures the number of times a team successfully releases to production over a given period. Frequent deployments indicate a smooth and efficient deployment process, which can lead to faster feedback and improvement cycles.

• Good averages: Elite DevOps performers typically deploy on-demand, often multiple times a day, while medium performers have weekly or monthly deployment events.
• Challenges in measurement: One challenge is having multiple sources of deployment data across different environments, such as different teams, tools, or automated systems. All this can make it challenging to get a unified view of all deployments. Additionally, tracking the production environment can be harder for on-premise applications or mobile apps, where deployments may occur differently from cloud-based systems.

2. Lead Time for Changes

Lead time for changes measures the period it takes for a committed code change to reach production. 

Shorter lead times indicate a more efficient development process because teams respond quickly to changes and feedback. That improves user and developer experience.

• Good averages: Elite teams often have lead times of less than a day, while medium performers might take one to two weeks.
• Challenges in measurement: A key challenge is standardizing the starting point for measurement, such as defining when the first commit is published. Additionally, supporting various Git workflows, including trunk-based development, rebasing, and long-lived branches, can complicate matters further.

3. Change Failure Rate

Change failure rate measures the percentage of changes to production that result in a failure requiring remediation (e.g., hotfix, rollback, patch).

This metric shows whether you have a good code quality and reliable deployment process. A lower change failure rate suggests better code and processes, which lead to higher customer satisfaction.

• Good averages: High-performing teams have a change failure rate of 0-15%, while lower-performing teams might experience rates above 30%.
• Challenges in measurement: Determining what qualifies as a failure and accurately tracking these incidents can be complex, especially if you don’t have a standardized incident management system. Additionally, it’s challenging to capture all incidents because they have many different sources to account for. Another challenge is attributing the failure to the correct deployment or team. 

4. Failed Deployment Recovery Time

This metric measures the time it takes for a team to recover from a production failure and restore service to users. It helps you understand the effectiveness of incident management and response workflows. 

Faster recovery times are better because they enhance operational performance and minimize customer impact.

• Good averages: Elite teams typically restore service in less than an hour, while medium performers may take up to a day.
• Challenges in measurement: Accurately tracking recovery time can be complex due to incident severity and response efficiency variability. For accurate measurement, you need consistent incident reporting and management tools. Another challenge is having different incident sources to support.

How to Choose a Good DORA Metrics Tool

As you can see, all the metrics above have their own measurement challenges. Getting an accurate read on your current situation can be difficult because of factors like inconsistent data, variability in how metrics are defined across teams, or gaps in your toolchain integration. These challenges can lead to incomplete insights and skewed results, making it harder to drive meaningful improvements.

You must select the right tool to build a comprehensive DORA metrics dashboard and avoid these mistakes. 

From our experience at Axify, we encourage you to consider the following criteria to make an informed choice.

1. Metrics Measurement

A good tool should cover all essential metrics and provide actionable insights to accurately measure your team's DevOps performance. Here are some questions to help assess a tool’s metrics measurement capabilities:

• Does the tool cover all four DORA metrics? Ensure the tool provides comprehensive coverage of the four indicators we discussed above.
• How are the metrics visualized and reported? Look for intuitive dashboards that make it easy to interpret data and make informed decisions.
• Does the tool provide organization-wide insights? Some tools, like Axify, offer features that allow you to view DORA metrics across the entire organization. This lets you see performance metrics for all projects or teams simultaneously, making monitoring and comparing performance across your organization easier.
• Can we trust the data’s accuracy? Check if the tool allows you to quickly drill down into the data, view historical data, and validate its accuracy. A tool that can do this is more reliable because it helps you make data-driven decisions based on accurate insights.

2. Developer Friendliness

A developer-friendly tool ensures your team adopts and uses it effectively. Consider the following questions:

• Is the tool easy to use and understand? The interface should be intuitive, allowing developers to quickly access the information they need without a steep learning curve.
• Does it provide valuable insights without overwhelming users? Look for a balance between detail and simplicity. You need actionable insights that aren’t overly complex.
• How does the tool support continuous improvement? Ensure the DORA metrics tool facilitates a culture of continuous integration and improvement by providing feedback loops and highlighting opportunities for improvement.

3. Integrations

The tool should offer flexible integrations to fit seamlessly into your existing workflows. Here are some questions to consider:

• Does it integrate with our existing tools and platforms? Check for compatibility with your code repository, project management tools, incident management systems, and other DevOps tools.
• How easy is it to set up and maintain integrations? Assess the tool’s setup process and ongoing maintenance requirements to ensure it won’t burden your engineering teams.
• How customizable is it to fit your workflow? Look for a tool that seamlessly integrates with your team's workflow without requiring your team to adapt.
• Does it support multiple sources? Ensure the tool can handle numerous repositories, deployment, and incident sources.
• Can you filter views by teams or repositories? Check if the tool allows you to filter and customize views, enabling you to focus on specific teams or repositories as needed.
• How does the tool handle incident tracking? Many tools naively track incidents solely through issue trackers like Jira, but a solid tool should support multiple impact sources. Look for solutions that go beyond bug tracking and support a variety of incident sources to provide a more complete picture of your production issues. As a side note, this is an area where tools like Axify outperform competitors like LinearB.

4. Data Reliability and Performance

Consider how reliable the tool is for syncing data and performance. Here are key questions to evaluate.

• How reliable is the data? Ensure the tool syncs regularly and consistently with minimal delays or issues.
• How long does it take to synchronize for the first time? Investigate how quickly the tool can sync your data from when it's connected. Fast and efficient syncing is crucial, especially for teams managing large codebases.
• Does the tool ensure data security? Some tools, like LinearB, clone repositories to calculate metrics, which raises security concerns. Look for solutions that extract only the necessary metadata, such as pull request metadata, to reduce security risks without compromising performance.

5. Support and Community

Reliable support and a tight user community can significantly impact your experience with the tool. Here’s what to look for:

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• What support options are available? Check for available support channels like chat, email, or phone and whether there’s a dedicated support team.
• Are there comprehensive resources available? Look for documentation, tutorials, and other learning resources to help your team get the most out of the tool.

Best DORA Metrics Tools

Let’s jump into the part you’re here for.

1. Axify: Best for Tracking Metrics that Matter

Axify is a powerful platform designed to provide teams with a comprehensive view of their software development process. Axify helps engineering teams enhance their performance and deliver reliable software efficiently by tracking key metrics – from DORA to resource allocation and team morale.

Axify is an intuitive tool for different roles: engineering leaders and managers, product managers, and product operations professionals.

Key Features

• DORA metrics dashboard: This dashboard provides real-time insights into all four DORA metrics, allowing teams to measure software delivery performance and make data-driven decisions. Pair this with Axify’s Value Stream Mapping and objective tracking to track all essential metrics related to your business goals.
• Value Stream Mapping: Axify helps you visualize and optimize the flow of value from development to delivery, providing a clear picture of bottlenecks and areas for improvement.
• Organization-wide insights: Axify enables you to track DORA Metrics across all teams and projects, offering a comprehensive view of your organization's performance. This feature allows you to compare performance metrics across different teams and identify areas for improvement.
• Integration with DevOps tools: Axify seamlessly integrates with popular DevOps tools, such as code repositories and project management systems. This ensures smooth data flow and streamlined processes across all your metrics. However, other tools allow more integrations.
• Software delivery forecast: Axify calculates precise delivery estimates based on your historical data. Predictable software delivery is essential for maximizing your budget and offering top-notch solutions for your customers.

What Makes Axify Different

Axify offers a holistic view of DORA and additional development metrics like flow metrics and software delivery forecasts. It can also accommodate different teams, making it a versatile choice for organizations looking to optimize their software delivery process.

2. LinearB: Best for Workflow Automation and Developer Productivity

LinearB is a software engineering intelligence platform that offers deep insights into workflows and automates routine tasks. 

LinearB allows for team-level rather than individual metrics, which people see as more reasonable and practical. Users appreciate that LinearB can help identify trends or bottlenecks without micromanaging individual developers.

However, LinearB has limitations in incident management. It relies mostly on issue trackers like Jira, which many users feel doesn’t provide a complete picture. Axify, in contrast, handles incident tracking more comprehensively because it supports multiple incident sources, giving teams deeper visibility into production issues.

Moreover, LinearB clones the entire repository to calculate its metrics, which raises significant security concerns. Axify only extracts the necessary pull request metadata, providing a secure and streamlined process. Users may question why a tool would need to scan the entire codebase, as it increases the risk of exposing sensitive code.

Key Features

• Workflow automation: LinearB’s key strength lies in its ability to automate daily tasks, reduce manual effort, and allow developers to focus on high-impact work. The platform offers programmable workflows that optimize PR reviews and other key processes.
• DORA metrics tracking: LinearB integrates DORA metrics into its broader performance analytics, providing teams with actionable insights to streamline their software delivery.
• Resource allocation and project forecasting: The platform offers tools to track resource utilization and predict project outcomes. This helps teams manage risks and costs effectively.

What Makes LinearB Different

LinearB stands out due to its strong focus on automating workflows and enhancing developer productivity. Using tools like WorkerB and gitStream for policy-as-code allows teams to optimize their processes and significantly reduce cycle time and PR review time.

3. Swarmia: Good for Aligning Engineering Work with Business Objectives

Swarmia is a work management tool that bridges the gap between engineering work and business goals. It focuses on helping teams prioritize their tasks to deliver business value more effectively.

Axify offers similar capabilities with its Executive Dashboard, helping leadership measure the ROI of engineering efforts while maintaining a holistic view of the entire value stream. However, Axify goes a step further, providing tools for the whole team so that everyone, from software engineers to product managers and CTOs, can access valuable, actionable insights.

As for Swarmia, many users are concerned metrics can be misused by management to unfairly compare team performance or punish developers, especially if the metrics are applied rigidly or without context.

There’s a worry that focusing too much on metrics like time from the first commit to merge might lead to gaming the system, where developers might delay commits or merge code without proper review to meet metrics.

Besides, Swarmia only supports a few integrations (e.g., Jira/Linear and GitHub). By contrast, Axify offers more flexibility and integrations.

Key Features

• Healthy team-level metrics: Swarmia tracks DORA and SPACE metrics, giving teams the insights they need to identify and eliminate bottlenecks while maintaining a healthy work environment.
• Automated feedback loops: The platform enhances collaboration and code quality by integrating with tools like Slack for real-time notifications and feedback. This helps teams adopt and maintain best practices.
• Developer experience and productivity: Swarmia combines system metrics with developer feedback to offer a comprehensive view of the development process. Therefore, it ensures that both quantitative data and qualitative insights drive improvements.

What Makes Swarmia Different

Swarmia stands out for its focus on aligning engineering tasks with broader business objectives. Axify is better for teams looking for a holistic approach with unique metrics like team morale and advanced software delivery forecasts. Besides, our Executive Dashboard gives leadership valuable insights.

4. Jellyfish: Best for Engineering Management and Alignment

Jellyfish is designed to help engineering leaders manage their teams and ensure that their work aligns with company strategy. It provides deep insights into how resources are being used and where improvements can be made.

However, Jellyfish is unsuitable for other roles, especially those directly involved in creating the software. Besides, you need organizational-wide admin configuration to install Jellyfish. You may need to change your Jira practices to accommodate this new dashboard.

Key Features

• Resource allocation: Jellyfish offers a comprehensive view of how engineering resources are utilized. Therefore, leaders can ensure their teams are focused on the highest-priority initiatives that maximize business impact.
• Engineering metrics and reporting: The platform integrates data from various tools and contextualizes it with business data. Engineering leaders can track progress, forecast delivery timelines, and communicate effectively with stakeholders.
• Scenario planning and delivery management: Jellyfish allows teams to model different delivery scenarios. You can identify potential risks and ensure projects stay on track and within budget.

What Makes Jellyfish Different

Jellyfish is tailored for engineering leadership and finance teams. By comparison, Axify can help other team members beyond the C-suite.

5. Allstacks: Best for Predictive Analytics in Software Delivery

Allstacks is a predictive forecasting and risk management platform for software delivery. It integrates with the tools your team already uses to provide insights into potential risks and delays.

However, Allstacks offers a wide range of metrics to select from in a customizable dashboard, which can create unnecessary noise. In contrast, Axify focuses on delivering only the most valuable metrics, eliminating the clutter and linking engineering performance to business outcomes.

Key Features

• Forecast and estimations: Uses historical data to predict software delivery estimates and identify risks before they become issues.
• Risk management: Helps teams proactively manage risks, reducing the likelihood of delays and other problems.
• Comprehensive dashboards: Offers customizable dashboards that provide visibility into the health and progress of projects.

What Makes Allstacks Different

Allstacks excels in its predictive analytics capabilities, allowing teams to manage risks more effectively than most other tools. By comparison, Axify’s more streamlined dashboard links performance metrics to business outcomes.

6. Sleuth: Best for Deployment Tracking and Automation

Sleuth is a deployment tracking tool designed to help engineering teams measure and improve their performance, mainly through DORA metrics. It provides real-time insights into the software delivery process and leverages AI and automation to enhance efficiency.

Instead of primarily relying on ticketing systems or git data, Sleuth focuses on deploys and impact metrics, then connects these to issues, git data, builds, and more. This method ensures a more accurate representation of what is being shipped and its impact. 

Key Features

• DORA metrics tracking: Sleuth excels at monitoring the four key DORA metrics—deployment frequency, lead time for changes, change failure rate, and failed deployment recovery time. These metrics help teams understand and optimize their software delivery performance.
• Automations marketplace: Sleuth offers a good set of no-code automations that can be easily integrated into existing workflows to reduce manual tasks, improve consistency, and enable faster deployments.
• Real-time deployment insights: The platform provides detailed insights into each deployment, helping teams identify and address bottlenecks before they impact delivery timelines.

What Makes Sleuth Different

Sleuth helps teams optimize their DevOps practices without extensive manual intervention. It offers various engineering review templates and AI summaries for each metric. You can also write your edits and reviews on the dashboard for extra visibility. Finally, you can track action items and meeting outcomes straight from the platform.

Look Beyond DORA Metrics

If you’ve read this far, you know the best DORA metrics tools. Each platform has its pros and cons, though, so choose wisely. 

Of course, DORA metrics aren’t the only metrics that count. 

Your team may also need to follow Agile metrics, like daily sprints, or you may want to track team morale. 

In that case, Axify offers solutions for different teams and stakeholders. 

If you’re a CIO, use Axify’s new executive dashboard to gain a high-level view of engineering performance and make informed decisions to drive strategic improvements. If you’re a software project manager, Axify is excellent for monitoring real-time project progress and team health. That’s how you can maintain both product delivery and team wellbeing.

While DORA metrics provide critical insights into your team’s DevOps performance, you need to integrate them with other key performance indicators and holistic metrics.

That’s the best way to better understand your team’s effectiveness and health and to work toward your business goals.

Book a virtual tour today and see how Axify can help.