Bitbucket

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Bitbucket Statistics Dashboards for Project Management in Confluence

May 26, 2020
#Confluence#Bitbucket#Reporting#Analytics#How To
9 min

In the blog post Handy Jira Dashboards for Project Management in Confluence, we told you how to use the data from Jira to create dashboards for agile project management on your Confluence pages. 

Using Confluence as the place for dashboards allows you to achieve better end-to-end visibility: it enables merging and aggregating data from different sources and makes it easily accessible to Leadership. Furthermore, you can export the reports in PDF, Word, JPG, or print them out and email them to external users, attach them to the quarterly report, or distribute them to managers and stakeholders.

Today we want to show how you can enhance your reports built with Table Filter and Charts for Confluence by adding engineering metrics from Bitbucket using the Awesome Graphs for Bitbucket app and build dashboards for PMs and stakeholders in Confluence. These metrics make up a comprehensive view of the processes and help managers make informed decisions.

Commits by User Chart

This chart is aimed to show you which developer worked on which project and their level of activity in terms of the number of commits so that you can identify the top contributors for each repository. You can also find the most active repositories in the whole instance, particularly for a specific project. This data can help you decide which repositories to target first with particular process improvement.

Hint: add the Table Filter macro before the Chart from Table to select repositories for comparison.

Check out a full guide on how to build this chart.

Commits Dynamics Chart

There may be cases when the snapshot is not enough, and it’s necessary for planning to see the actual change in progress. To examine trends over time, you can build the chart that will show the dynamics of contributions made by users over the chosen period. Using this, you can then compare the periods and answer questions like “Are we committing more code now than before?”.

Hint: you can change the grouping to daily, weekly, or monthly by changing the Date period aggregation in the Pivot Table macro settings.

Follow our guide to build this chart.

Lines of Code Chart

Another way to get a better understanding of the amount of work done across the projects and measure the activity and efficiency of the teams is to look at the number of lines of code added and deleted. On this chart, you can see the visualized statistics of the user’s activity in terms of lines of code on the project level.

Hint: use the Chart from Table macro’s feature “Chart as image” to save the chart as JPG and email it or use it in PowerPoint presentations.

Read the step-by-step instructions to build this chart.

Pull Requests Activities Charts

To complete the picture, you can use the two following graphs showing the Pull Request activities of the developers, i.e., the number of Open, Merged, and Declined Pull Requests on the project level basis.

The first chart provides you with an organizational view and allows you to visualize the statistics across multiple or all of the repositories, grouping the Pull Requests by their state. 

You can then drill down for more detailed data and build the chart to discern the output and productivity of each particular user:

Hint: You can also build the chart to see the dynamics in Pull Request activities by following the instructions from Commits Dynamics Chart, but with the Pull Requests source file.

Learn how to build these charts.

Enhance your reports

Using the charts described in this article, you can analyze engineers’ activity and productivity, evaluate the capacity to work, and make data-driven decisions to improve engineering efficiency. 

All of the charts on this page were built with the help of Table Filter and Charts for Confluence as the means of aggregation and visualization and the Awesome Graphs for Bitbucket app serving as a data provider.

The combination of these apps is capable of building much more complex structures that would allow you to aggregate all the information in a single dynamic chart, where you could choose and change the components on the go to get different visualizations each time in a few clicks.

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    How to use statistics to overcome challenges when moving to microservices

    April 30, 2020
    #How To#Confluence#Bitbucket#Analytics
    10 min

    Agile software development has been dominant in software engineering for years. Its methods have helped teams manage work and perform efficiently while delivering high-quality results. Microservice architecture is one of the approaches that implements the Agile practices:

    Microservice architecture is a style of structuring large complex products as a collection of individual services that can be developed and maintained independently, making the software more flexible and increasing its scalability.

    While microservices may seem as a silver bullet upfront, nothing comes easy. The migration can result in deployment challenges as well as make global testing and debugging more difficult. Apart from purely technical side effects, it requires a cultural shift in organizations and strong project management.

    In this article we focus on the challenges related to the management of microservices and describe the ways to overcome them using aggregated data and statistics:

    We’ll teach you how to turn your Confluence instance into a full-fledged BI tool and how to:

    • identify dependencies between teams 
    • see if there is a lack of collaboration between members
    • find pilot teams to implement new processes in
    • check if you are actually moving away from the monolith.

    Imagine now that you have a hostel marketplace application where people can find and book a stay. Recently you’ve decided to migrate to microservices, so now the whole application is split into independent services, each having its own repository, and you need to organize your teams and the processes the right way.

    Resolve dependencies and build the teams

    When done correctly, microservices work so that you can build, test and deploy them without affecting each other. To achieve that you need to recognize and then eliminate dependencies between the teams.

    For that purpose you can build the following graph and see the distribution of contributors on the project level:

    The graph shows the number of commits made by users, so you can identify service owners, see the interactions between the members of different teams, and spot deviations in terms of who does what, e.g. if there is somebody from the team A working on the team B’s service. The latter can result in delays in the development process and an increase of idle time caused by lags in communication between the developers.

    The same graph can also indicate the anti-patterns in teams’ culture. Being a member of an independent team can help developers work more effectively. But some teams just lack the concept of collaboration. So instead of having the work distributed among the developers, it happens that only the so-called “service owner” ends up working on his microservice. In addition to a drop in the morale of the developer, this may affect the quality of the code as there is nobody to review it.

    You can use this graph to find services led by one person and then make informed decisions to improve the team culture.

    Experiment without risk

    The variable development processes and independence are clear benefits of microservices architecture. Teams don’t have to align with the others and that allows you to test and implement new processes without paralyzing the workflow even if something goes wrong. This way you can try to introduce new practices to improve the quality of your software, such as unit testing, code review, pair programming, you name it.

    To start the implementation of the new processes it’s important to find the teams that have been operating efficiently and are currently active. The number of commits and pull requests can be used as an indicator of the active state.

    The two following graphs will help you to find pilot teams to hold experiments:

    The graphs show the activity of the teams by month for the last quarter, indicating the number of commits and pull requests respectively. Now you can compare the results and find the teams that have a lot of commits and none or few pull requests — those will be your perfect candidates.

    See the monolith breaking

    Moving from the monolithic systems takes a lot of effort so it’s important to keep track of where you are in this journey. Apart from staying motivated as you see the changes (or not yet), you need to make data-driven decisions to improve the processes and lend support to your teams.

    To get the full picture you may use the graph that shows the changes in the codebase:

    It displays the number of lines of code deleted and added around the project. Using this information you can see the breaking of the monolith: if the number of lines of code deleted is increasing steadily for the monolithic repo while more and more lines of code are being added to the new microservices repos, then you are going the right way.

    Make the data work for you

    While migration to microservices may seem costlier in terms of the amount of work for managers, that is the investment that will pay you back with faster development processes, increased scalability and adaptability. And we hope to make your way easier here. 

    The tips described in this article will help you gain more visibility into the current state of the processes and unleash the potential of your teams. Using the Awesome Graphs for Bitbucket app as a data provider and the Table Filter and Charts for Confluence app to aggregate and visualize the data, you will get the functionality that is on par with dedicated BI software platforms.

    Want to know how to build the graphs and charts from the article? Read our step-by-step guides and try yourself!

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      Awesome Graphs for Bitbucket: Exclude Files from Lines of Code Statistics

      March 22, 2019
      #How To#Bitbucket
      9 min

      Awesome Graphs for Bitbucket is an app visualizing statistics of Git repositories in terms of commits, pull requests, and lines of code. The Contributors graph, and the Code Frequency graph show how many lines of code were added and deleted in the repository in general and by each developer. 

      Sometimes lines of code statistics doesn’t represent correctly the actual effort and value that developers bring to the repository. For example, if a new library was added, it will bring hundreds of new lines while a task itself was easy to do and took half an hour.

      To make your data more precise and informative, there’s a feature in Awesome Graphs that allows the exclusion of files from lines of code (LOC) statistics.

      Why Exclude Files from LOC Stats

      This feature will be helpful for users, who:

      • Include source code from third-party libraries, and don’t want to count it towards individual code contributions.
      • Want automated code generated files not to be included into LOC statistics. 
      • Version a lot of configuration in very large xml files, and don’t want to count their updates as additions of thousands of LOC.
      • Want to include in LOC statistics only files with selected extensions (i.e. c, cpp, h).
      • Want to count in LOC statistics only files from the selected directory (i.e. src).

      How it works

      Repository administrators can add patterns in a gitignore format telling what files have to be excluded from LOC statistics of a repository.  

      bitbucket repository settings

      It is possible to exclude:

      • particular files
      • all files with selected extensions
      • all files from selected directories
      • everything except files with selected extensions
      • everything except files from selected directories

      When an administrator adds or modifies patterns, Awesome Graphs re-indexes the repository and displays graphs with new LOC statistics.

      Benefits Examples

      You can see examples of this feature usage in public repositories.

      Statistics for the main directory of a repository

      Let’s view the Contributors graph for the jquery repository. It shows additions of LOC in the whole repository.

      contributors bitbucket

      The repository exists since 2006, but according to the graph there was no significant activity there till 2014.

      It would be great to make the graph more informative and calculate LOC statistics only for the directory containing the main source code – src. We exclude from statistics all files except files from this directory and get a new graph showing the most important activity happened in the key folder of the repository. 

      contributors graph bitbucket

      Exclusion of files helped to get new insights:

      • There was intensive activity in 2006-2008, 2011, and 2014.
      • There was no significant activity after 2016.
      • Only two of top four contributors to the repository are also in the top four contributors to main source code.

      In the first graph there were peaks of activity showing additions of 50K and even 250K lines of code per week. In the second graph the largest peak shows addition of 25K lines of code, others – about 5K. This data represents the real work of developers more accurately.

      Exclusion of third-party libraries from statistics

      Let’s view the  graph for the kubernetes repository.

      Bitbucket Code Frequency

      There are two peaks of activity: addition and deletion of more than 300K lines of code. They represent not actual work, but operations with third party libraries. Huge peaks of additions and deletions caused a large scale of Y axis. Due to this all other activity seems to be non-significant.

      Let’s exclude from lines of code statistics files from the directory third_party.

      The graph has become more accurate. Peak values disappeared. The scale of Y axis decreased allowing to get a better understanding of the activity in the repository.

      Get more informative LOC statistics

      Using Awesome Graphs for Bitbucket, you can enrich your commits, lines of code reporting with the REST API the app provides. For example, you can easily count each pull request size to decide whether it needs to be decreased. Read more about it in our blog post.

      Try the app for free discover more benefits and unleash the potential of your teams.

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        How Engineers Analyze Code Review Practices in Bitbucket

        November 9, 2017
        #Bitbucket#Case Study#How To
        9 min

        This is a fantastic plugin, really useful to analyze code review practices, monitor individual repo activity or a developer’s activity across multiple repos. Looks and works great!

         Philip O’Gorman, JCA Electronics


        JCA Electronics specializes in designing and manufacturing electronic control systems that are used by original equipment manufacturers (OEM). Their engineering team creates embedded drivers, embedded application software, mobile application libraries, and mobile applications for many OEMs that are mainly agricultural and construction companies.

        The team uses Bitbucket for collaborating on code and extended its capabilities with the app Awesome Graphs for Bitbucket to:

        • get the history of developer activity across all projects and use it for filling in timesheets
        • browse commits of all branches of a repository
        • analyze project activity and the process of code review

        Data for billing – a click away

        JCA Electronics’ engineers can be working on many projects simultaneously. Therefore, to fill in timesheets for billing, the company needed an easy way to see the daily work log of each developer.

        They found Contributions in user profiles invaluable for this purpose, as this page shows a developer calendar of the past year. When they click a day, the activity stream shows the list of commits and pull requests across all projects for that day.

        commits and pull requests across all projects in Bitbucket

        Commits across all branches

        In addition, JCA Electronics appreciates the capability to see the activity across all branches (‘Show all’ link) on the Commits page of a repository or project. Before, they could only view the commits of each branch individually.

        all commits in Bitbucket

        In addition, there’s a commit graph that gives a visual representation of the development flow and makes the commit log easy to read.

        development flow in Atlassian Bitbucket

        Project activity – at a glance

        The team uses project graphs and reports to analyze project activity and monitor the number of contributors. The Graphs’ Activity tab provides the charts that let you compare the input (number of commits and pull requests) from the most active developers. In addition, it features the activity stream with the feed of commits and pull requests of the project.

        project activity in Atlassian Bitbucket

        The Contributors tab captures the dynamics on two levels: team efforts (green graph) on the project and contributions of individual engineers (cards with red graphs).

        analyze code review in Bitbucket

        The Contributors page can show graphs in commits, lines of code added or lines of code deleted. So a project manager can analyze the progress of development from different perspectives.

        JCA Electronics also uses Top Committers Report to see what developers worked on a project during a certain period of time, e.g. a sprint, a year, and compare the number of commits each person contributed.

        top committers report in Bitbucket

        Tracking code review practices

        The company has many projects and repositories to manage. So it is very important for them to make sure that pull requests and code reviews are utilized on each project. Activity in project graphs and Created vs Merged Pull Requests Report help the team ensure that the correct practices are being used.

        Activity shows:

        • how many pull requests were created, merged, and declined in the project within a chosen time period
        • who made those pull requests, including whose pull requests were declined
        • what developers were more active than others

        pull requests chart in Bitbucket

        Created vs Merged Pull Requests Report visualizes the dynamics of pull requests’ creation and merging that tells the team:

        • pull requests are used a lot (the curve is rapidly heading away from the Time axis) or not
        • more pull requests are being created than merged (red parts of the graph) or vice versa
        • how many pull requests were created and merged in each period

        created vs merged in Bitbucket

        Conclusion

        The Awesome Graphs for Bitbucket app provides JCA Electronics with the capabilities that enrich and facilitate their experience with Bitbucket. The company benefits from graphs and reports that give insights into project activity and code review practices. The graphs also provide data for billing and evaluation of contributions made by teams and individual developers.

        Read more case studies to see how our customers benefit from using Awesome Graphs for Bitbucket in their work:

        Try Awesome Graphs for Bitbucket for free

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          5 New Add-ons to Boost Dev Tools – Second Quarter 2017

          August 3, 2017
          #News#Bitbucket
          8 min

          As usual, we have reviewed all new products for Bitbucket and Bamboo for the past quarter and would like to share five add-ons that we liked the most. This summer is a hot season on the Atlassian Marketplace with Atlassian Codegeist Hackathon 2017 inviting developers to create the next great add-on for one of the Atlassian platforms. While waiting for the news about hackathon winners, let’s see what new add-ons for Atlassian Dev Tools on the Marketplace won our appreciation.

          Check out the previous post in this series if you missed it.

          Top 5 new add-ons for Bitbucket and Bamboo released in the second quarter of 2017:

          LFS Converter for Bitbucket Server

          This tool allows you to transfer files to Large File Storage (LFS). If you don’t use LFS, you can experience performance issues while working in a repository with large binary files, such as video, audio, graphics, large data sets. In addition, cloning such a repository means downloading data that weighs a lot. With LFS, large files are replaced with text pointers inside Git and the file contents is stored on a remote server.

          LFS Converter for Bitbucket Server lets you scan a repository for large files in repository settings and transfer the selected files to LFS.

          You can track the history of transfers and revert the last transfer.

          Pricing: LFS Converter for Bitbucket Server is available for Bitbucket Server. Its commercial license costs 245$ for 25 users; 495$ for 50 users; 1,500$ for 100 users. Try it

          Watching favorite files

          You can try this add-on if you have large projects with a lot of activity and you need to be aware of only a part of it. ‘Watching favorite files’ helps you tune Bitbucket notifications and get notified on changes only in those files that are important for you. To make it work, you need to add yourself to the watchers list of files and directories of your choice. After you do that, you will start receiving only those notifications, which mention files that you watch.

          You get to choose how to be notified – via email or Slack. And each user can see and manage the list of files they watch in a user profile.

          Pricing: Watching favorite files is available for Bitbucket Server and is free at the moment. Try it

          File Viewer for Bitbucket Server

          Even though this add-on is developed by our team, we are not being biased by including it in this review. We believe it’s a really useful tool for many of Bitbucket users.

          File Viewer enables viewing 3D models, geographic data structures, PDF and CSV files directly in Bitbucket without downloading.

          Included viewers:

          • 3D Viewer – STL files are rendered as interactive 3D models
          • Map Viewer – GeoJSON files are shown as maps that you can zoom
          • Table Viewer – CSV and TSV files are presented as tables with sorting by column
          • PDF Viewer – PDF files can be viewed on your Bitbucket pages

          The add-on doesn’t need to be configured. You can start using the viewers right after installing the add-on.

          To view a file in Bitbucket:

          1. Navigate to the Source section on the left-hand sidebar in your repository
          2. Select a file you would like to view in Bitbucket
          3. If the format of a selected file is supported by File Viewer, the file will automatically be displayed in a suitable viewer

          Pricing: File Viewer for Bitbucket is available for Bitbucket Server and Cloud. The Server commercial license costs 75$ for 25 users; 150$ for 50 users; 300$ for 100 users. The Cloud version of this add-on was released earlier, in 2015 (it is a winner of Atlassian Codegeist 2015 – Best Bitbucket add-on), and is free at the moment. Try it

          Build Comments task for Bamboo

          This add-on adds a Bamboo task that makes it possible to automate posting of comments to builds or releases. You can configure the contents of a comment that needs to be added. Besides text, you can use Bamboo variables.

          For example, you can configure a task that will automatically add a comment to build’s results in case a build fails. This comment will tell what agent was used and what its working directory is. It will save you time – you won’t need to look for these details in logs.

          Here’s the value for the Comment filed to configure such a task:

          Build failed on ${bamboo.agentId} and it’s working directory is ${bamboo.agentWorkingDirectory}

          Pricing: Build Comments task for Bamboo is available for Bamboo Server and is free at the moment. Try it

          Bamboo Announcement Plugin

          It’s a simple, but handy solution that adds a site-wide announcement banner in Bamboo. The message is customized by an administrator and displayed on the top of each page.

          You can use it to inform about a coming maintenance, some important update, etc.

          Pricing: Bamboo Announcement Plugin is available for Bamboo Server and is free at the moment. Try it

          If you have any questions, feel free to comment on this blog post. To stay tuned, subscribe for email notifications about new posts in our blog (enter your email in the ‘Newsletter’ section on the sidebar).

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            5 New Add-ons for Dev Tools at Atlassian Marketplace – First Quarter 2017

            May 18, 2017
            #News
            1 min

            The spring is in blossom and new products are blossoming at Atlassian Marketplace. We’ve already shared our selection of top 5 new add-ons for Confluence and JIRA with you. Now let’s take a look at what’s new for Dev Tools (Bitbucket and Bamboo). We reviewed the add-ons that were launched at the Marketplace during January-March this year and chose 5 that we thought might be especially interesting and useful for our readers. Continue reading “5 New Add-ons for Dev Tools at Atlassian Marketplace – First Quarter 2017”

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