Engineering managers need software development analytics tools, also known as git tracking tools, to measure metrics that give them insights into project processes and product deliveries.
Analytics tools also help evaluate how effective the development process is and if it needs any changes.
In this guide, we'll list some of the best development analytics tools, along with the key metrics they measure and their advantages.
What Is a Software Development Analytics Tool?
A software development analytics tool is a piece of software that keeps track of the time spent on tasks, bug reports, and overall progress during the development process. It's an essential tool for engineering managers because it gives them insights into how their projects are being carried out and if anything is hindering the workflow.
Software development analytics tools are also known as git tracking tools. They allow development teams to see the information surrounding any bottlenecks and get progress reports at the end of the day, week, or month.
Here are some of the things git tracking tools can help you do:
- Measure the number of commits and pull requests per day/week/month to track the project's velocity
- Analyze how much time is spent on the tasks compared to the set deadlines
- Identify reasons for delays and bottlenecks in real time
- Measure the amount of accumulated technical debt over time
- See who the best-performing team members are
Git tracking tools showcase trends and provide key performance indicators (KPIs), reports, and statistics. They also integrate with code repositories.
Additionally, the best git tracking tools aggregate the historical data of an engineering team in one place so that it can be used to monitor performance and progress.
Top 10 Development Analytics Tools
Haystack
Haystack is a Massachusetts Institute of Technology project that provides analytics for open-source projects. It uses Elasticsearch to store time series data, which can be used to track commits, bugs, and other events happening on an engineering team's projects.
It also provides code quality metrics like test coverage and type checking. Haystack allows teams to measure their velocity by counting the number of commits per day.
The Haystack project offers an open data model, streamlining the control and analysis of equipment and building systems. Moreover, it provides real-time alerts and resolves issues in engineering teams quickly.
The product provides daily reports to engineering managers in their inboxes and alerts them of any potential issues with instant notifications.
Haystack can determine what's normal and what's not by analyzing events that have happened over time. In this way, it notifies you in case of a potential problem.
Key Metrics
- Cycle Time: Haystack calculates cycle time by measuring the time between commits of any kind (e.g., bug fix, task) until they are merged in.
- Deployment Frequency: This metric allows teams to see how many deployments were done per day.
- Throughput: This shows the number of tasks completed per minute to help engineers identify low-performing teammates and find bottlenecks.
- Change Failure Rate: This metric helps teams measure how many errors are triggered by code changes.
- Team Health: This is a health-focused metric that helps teams identify factors like overwork and burnout.
- Time Spent in Dev: This shows the total time that developers have been coding per day/week/month.
Pros
- Sends burnout alerts
- Detects anomalies and alerts instantly
- Helps measure culture-focused metrics too
- Integrates with multiple tools
Cons
- Lacks specific filters for the exact DORA metrics
- Has functional bugs at times
Capterra & G2 Average Rating: 4.95 (8+ reviews)
LinearB
LinearB is among the best git tracking tools since it's a real-time performance analysis platform. It's mostly used to monitor rollups of a team's work, find bottlenecks, and alert engineering managers about any potential problems.
LinearB captures time spent on tasks by task category (e.g., designing, coding). As a result, it can measure the velocity of each team member and calculate the time it takes to finish a certain task.
It also gives real-time updates about project delivery dates, alerts engineering managers in cases of anomalies, and tracks repeatable tasks that can be automated in the future.
In this way, LinearB helps teams focus on what really matters when coding to deliver projects faster.
Moreover, it integrates with Slack, Shortcut, and Jira so that engineering managers and team members can easily monitor the progress of their projects in real time.
Key Metrics
- Deployment Rate: This metric lets teams measure how frequently deployments are made.
- Change Failure Rate: This metric helps track the number of functional and nonfunctional bugs introduced in changes.
- Mean Lead Time: LinearB calculates lead time by considering all delays between the development and deployment of change requests.
- Mean Time to Recovery: This metric measures team members' time spent fixing bugs introduced by changes.
- Team Metrics: LinearB tracks velocity, throughput, work in progress, cycle time per task category (e.g., design), and incomplete tasks.
Pros
- Integrates with issue tracking platforms
- Offers custom granularity (performance analysis from a single contributor to the whole organization)
- Provides Slack notifications for issues
- Has great customer service
Cons
- Has a learning curve
- Initial configuration can be tricky
Capterra & G2 Average Rating: 4.7 (31+ reviews)
Learn More: What Are the Responsibilities of a Data Engineer Manager?
Allstacks
Allstacks is a handy tool for software organizations that provides insight into team performance, trends, and project status, prioritizing development efforts accordingly.
The Value Stream Intelligence Platform on Allstacks generates guiding insights for stakeholders' engineering projects. With these insights, engineering teams can shape more effective outcomes for their customers and the business itself.
The tool also offers intelligent forecasting, which analyzes your system development life cycle activity to identify risks and create visibility. More importantly, it's one of the best development analytics tools to get reports on your teams, with more than 120 engineering metrics and shareable dashboards.
Key Metrics
- Pull Request Cycle: This metric shows you the average time required to accept or reject a pull request. Higher values could indicate inefficient code review, leading to more bugs and delayed releases.
- Cycle Time: This is another key metric indicating how long it takes your team to complete a project, from submitting a ticket for development to testing and releasing. The shorter the time, the better your team is performing.
- First Deployment Date: This important metric shows you the date when your development team first deployed code successfully in production servers. To have better release management, it's necessary to know when this was done last so you can track your team's progress.
- Revenue Impact: This is a great metric to get an idea of how much money you're losing each month after your team releases new features and bugs before time. The higher the value, the lower the customer engagement and profit growth of your business.
Pros
- Easy to integrate
- Provides impactful reports
- Offers forecasts for project completion
Cons
- Starting meaningful dashboards is tricky
- You have to wait overnight to get information from Jira projects
Capterra & G2 Average Rating: 4.7 (21+ reviews)
Waydev
Waydev is an agile method for tracking the output of engineering teams during a development process, allowing them to perfect the final outcome.
The Waydev tool can help software organizations measure market-based metrics on each of their projects. It lets engineering teams compare the return on investment (ROI) of specific products, identify which features need improvement or removal, and remain competitive in the market.
Moreover, Waydev gives software engineering teams insight into the cost and progress of deliverables and key initiatives, helping them stay on schedule. It also paves the way for resource planning by helping team managers identify the impact of bug fixes and scope creep on delivery and roadmap velocity.
Key Metrics
- Active Day: On large teams, it's hard to see which team member is struggling and who is succeeding. Waydev has proposed Active Days to counter this problem. An Active Day is a day on which a team member contributed code to the project in any way, such as writing code or reviewing someone's work.
- Code Churn: Code churn refers to the number of lines added and removed from a project's codebase during a certain period. The tool generates reports on this metric so software engineering teams can steer their efforts toward areas that need improvement, such as fixing bugs or adding new features.
- Impact: This metric measures how ''big'' the code changes are.
- Throughput: This metric measures the total amount of churned, refracted, and new code added to the project.
Pros
- Lets you see data from different angles
- Easy to digest
- Has many unique metrics unavailable elsewhere
Con
- Costly for small businesses
Capterra & G2 Average Rating: 4.6 (63+ reviews)
Codacy
Codacy is a git tracking tool that monitors and reviews code quality on every pull request and commit. It then reports back the impact of a pull request or commit.
The tool automatically runs through a number of programming languages and multiple tools to perform a comprehensive analysis of your software's overall quality, which you can then share with the team on Slack or email.
Overall, the tool identifies issues regarding security, code duplication, code complexity, code coverage, best practices, and code style.
Key Metrics
- Cyclomatic Complexity: This metric is used to measure the complexity of your code. It helps to identify methods that are too complex and need refactoring for higher readability, better maintainability, and improved extensibility.
- Duplication: This metric is used to detect code duplication. It helps you spot potential problems that are hard to catch with standard tools. The duplication can be both within files and across the project, so the tool lets you track down all duplicated code.
- Lack of Cohesion Methods (LCOM): This metric is used to find methods that are doing too much, thus making the code less modular. LCOM allows you to look into your project's architecture to spot potential issues with the design.
- Number of Overloads: This metric helps identify methods that can be reduced. It lets you assess the level of code coupling and find methods with too many dependencies, i.e., overloaded methods.
Pros
- Automatically updates the rating for your code
- Supports all major languages
- Has an intuitive user interface and a seamless dashboard
Cons
- Lacks code quality customization for projects where standards are provided
- Spots some de facto standards and nonrelevant errors
Capterra & G2 Average Rating: 4.6 (17+ reviews)
Jellyfish
Jellyfish is one of the best git tracking tools, which let you align your engineering work processes with your business properties through surface insights.
The tool is designed to provide you a complete understanding of your product. It provides insights from GitHub and Jira to help you decide what business value your application provides.
Jellyfish shows the status of each branch and pull requests and provides relevant information about the commits that will affect the branch. It gives you full visibility into how your engineering work fits in with your business objectives.
Thus, you can use the tool to scale with confidence, investing in areas that are sure to add significant value to your business. Besides Jira, Jellyfish also works with Bitbucket, GitLab, Confluence, and Google Sheets.
Key Metrics
- Cycle Time: This metric measures the time from the start of a particular task to its completion. It's a critical metric to keep track of, as it indicates the efficiency and speed at which work is done within your team.
- Deployment Frequency: Tracking the frequency of deployments helps engineering teams improve the speed at which they deliver value to customers.
- Change Frequency: Change frequency shows you how often new changes are made to the code, which helps you find areas for improvement.
- Task Resolution Rate Over Time: This metric helps determine if your team is improving. It helps you understand the time it takes for issues to be resolved on a daily basis and whether or not there has been an improvement in that metric over the past few weeks.
Pros
- Offers multiple perspectives on resource allocation
- Shows a summary for executive briefings
- Transforms data into insights for management and leadership
Cons
- Lacks user configuration for creating custom supports
- The user interface takes some time to get used to
Capterra & G2 Average Rating: 4.55 (23+ reviews)
SonarQube
SonarQube is among the best git tracking tools. It empowers developers to monitor code quality and track changes over time by evaluating the technical debt and code quality.
SonarQube provides a different set of rules that can be configured per your project or team's preferences.
It also helps you monitor coding standards, maintain consistency across the entire project, and stay updated on any new vulnerabilities in libraries and packages. With thousands of automated static code analysis rules, the tool guides engineering teams and protects the final product on multiple fronts.
This tool ensures that your codebase is maintainable and clean. To accomplish this, SonarQube catches tricky bugs and prevents undefined behavior.
Key Metrics
- Number of Classes: This is a metric that tells you how many classes are present in your project. If the number is continuously increasing, it means that the current approach to coding is not working.
- Number of Methods: This metric measures the total number of methods available in your project along with their dependencies on other methods. The more complex the dependency graph, the higher the friction and cost for understanding the code will be.
- Density of Comments: This metric refers to the percentage of comment lines in a codebase. The higher the percentage, the better. Code lines with comments make it easier to understand and resolve bugs.
- Number of Lines: This metric measures the total number of lines present in a file. In some cases, if the number is smaller, it indicates that too much code is packed into one method or class.
- Duplicate Code: Duplicate code makes your system bloated and vulnerable to bugs, which could cost you a lot on the maintenance front. It has been found that even 10% code duplication can cause a drop in performance.
- Duplicate Comments: This metric is directly related to the previous one, as comments are added to understand the code. If the same comments are repeated over and over, it makes your codebase harder to maintain.
Pros
- Allows security vulnerability scanning
- Has multisoftware language support
- Supports code analysis
Cons
- The admin portal could be more usable
- Lacks custom rule sets
Capterra & G2 Average Rating: 4.5 (50+ reviews)
Pluralsight Flow
Pluralsight Flow aggregates git data into comprehensive insights and reports that engineering teams can use to make their projects more successful. Essentially, Flow is an organizational tool that pioneers a unique way of communicating and measuring productivity in software engineering.
The tool tracks your project's cycle time, complexity, cost, risk score, work in progress (WIP) limit adherence rate, code coverage metrics, build status, and deployment frequency.
Flow is designed to give you an organized view of your work. It visualizes all the relevant information in a single dashboard to make meaningful insights easily accessible. The tool summarizes the relevant data into a single unified number that you can use to identify problem areas in your team's performance and focus on their improvement.
It also includes a code search function that lets you analyze the codebase for changes, defects, and bugs.
Key Metrics
- Coding Days: These are the days on which developers contribute code to a project. This metric provides insight into a team's performance.
- Churn: This refers to the code that's rewritten or deleted shortly after someone has written it (normally within three weeks or less). Engineering teams can use this metric to determine how often they rewrite their own work.
- New Work: This is brand new code written from scratch that isn't replacing an older code. The metric shows you the code quantity a team or individual uses to write new features.
- Team Velocity: This metric shows you what your team achieved over a particular period (or sprint cycle) and allows them to compare this to their previous performance.
Pros
- Makes it easy to quantify work
- Has metrics that can be used to incentivize team members
- Has multiple code repositories
Cons
- Doesn't have the best Jira support
- The date range is reset when switching between reports
Capterra & G2 Average Rating: 4.5 (22+ reviews)
Code Climate Velocity
Code Climate Velocity uses your repos to synthesize data that gives you full visibility into code quality, code coverage, and security vulnerabilities. In addition to Jira integration, it has Git support as well.
Velocity allows you to refine your workflows, identify development opportunities, and set concrete goals. Additionally, the tool spots bottlenecks and poor code instantly, giving you the ability to improve existing processes and workflows.
Key Metrics
- Deployment Frequency: This is the frequency at which new versions of your project are released. This metric allows you to measure how frequently new versions of your code get deployed into production environments.
- Reviews: This refers to the number of times a change is reviewed. The metric gives you a sense of how many of your team members are reviewing changes one or more times before they're deployed into production.
- WIP Limit Compliance Rate: This metric shows how often your code maintains its WIP limits requirements. In other words, it tells you how often your processes adhere to your WIP limits.
Pros
- Has custom dashboards and trends
- Uses industry benchmarks
- Provides real-time risk alerts
- Allows you to compile data on development velocity and code quality
Con
- Expensive
Capterra & G2 Average Rating: 4.5 (8+ reviews)
ZenHub
ZenHub uses agile automation to help you and your dev teams work better and smarter.
ZenHub gives developers the visibility and insights they need to ship higher-quality software faster. You can also get real-time updates on what your team is working on and who's working on what, which helps you track progress down to the task level.
With dynamic prioritization built in, this tool also gives you the power to manage requests coming from other parts of your business or even your customers directly within GitHub.
ZenHub helps engineering teams identify project bottlenecks that are slowing down their workflow. Dev teams will also get insight into blockers that are impacting their development or testing cycle times so they can quickly prioritize and address these issues.
Key Metrics
- Number of Critical Issues: This metric tells you about all the bugs and enhancement requests that are blocking project development.
- Number of Pending Pull Requests: This gives you an idea of how many pull requests remain unmerged and require your attention.
- Number of Projects: This shows you how many projects are running under ZenHub. The higher the number, the better it is for the engineering teams.
Pros
- Top-notch programmability
- Easy to set up the board and integrate it with Github
- Minimal overhead and remarkable UX
Cons
- The mobile experience isn't satisfactory
- Admin type functions aren't logically located
Capterra & G2 Average Rating: 4.4 (58+ reviews)
Final Words
With that, we have come to the end of our list of the best software development analytics tools. These tools allow the engineering team to detect issues and measure metrics to improve the final outcome and streamline work processes.
Software development analytics tools play an important role in software engineering project pipelines, and you can leverage them to get the results you desire, such as higher efficiency, productivity, or ROI.
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