GitLab Data + Project Metrics = Real Pipeline Visibility
Enhance development pipeline visibility and gain more context than GitLab reports alone can provide–all in minutes. GitLab metrics are generally more accurate than project management services—like Jira—but they still aren’t enough. Real insight into engineering health comes from correlating the two data sources. When engineering leaders combine GitLab analytics with project data they can:
- See the big picture
- Confidently report on project progress
- Identify bottlenecks and areas to improve
- Tie engineering metrics to business outcomes
Enhance development pipeline visibility and gain more context than GitLab reports alone can provide–all in minutes. GitLab metrics are generally more accurate than project management services—like Jira—but they still aren’t enough. Real insight into engineering health comes from correlating the two data sources.
By correlating Jira activity & GitLab metrics, LinearB gives you a consolidated GitLab dashboard and provides a new depth of insights
By correlating Jira activity & GitLab metrics, LinearB gives you a consolidated GitLab dashboard and provides a new depth of insights
Join the next wave of modern engineering organizations
Easily Identify Bottlenecks Using GitLab Data
What does “In Progress” really mean to your team? Unfortunately the definition isn’t standardized for every team. And that’s where a lot of work gets lost.
Jira can show you cycle time–the time from initial commit to deployment–in the control chart, but it’s based on issue status, not actual GitLab activity.
LinearB calculates cycle time using GitLab analytics. Git (and the IDE) is where your devs actually work, so the calculation is always accurate–and not dependent on data hygiene.
Plus, LinearB enables you to understand your cycle time far more deeply than the control chart. LinearB breaks cycle time down into four phases–which gives leaders a big clue as to where the problem is. With one click you can then drill into cycle times phases and see the leading indicators (like PR size for a single branch) that are causing bottlenecks and driving the metrics up.
With context like this, all on a single project and GitLab metrics dashboard, you can find root causes—and solutions—to improve cycle time (and value delivery) in seconds.
Jira can show you cycle time–the time from initial commit to deployment–in the control chart, but it’s based on issue status, not actual GitLab activity.
LinearB calculates cycle time using GitLab analytics. Git (and the IDE) is where your devs actually work, so the calculation is always accurate–and not dependent on data hygiene.
Plus, LinearB enables you to understand your cycle time far more deeply than the control chart. LinearB breaks cycle time down into four phases–which gives leaders a big clue as to where the problem is. With one click you can then drill into cycle times phases and see the leading indicators (like PR size for a single branch) that are causing bottlenecks and driving the metrics up.
With context like this, all on a single project and GitLab metrics dashboard, you can find root causes—and solutions—to improve cycle time (and value delivery) in seconds.
GitLab Reporting Tools Align Teams to Business Priorities
Answer “When will feature X be ready?” with confidence…and more importantly, correctly.
Engineering leaders need to know where their devs’ time is being invested and when features are going to ship. GitLab reports—like lines of code, number of commits, open issues or merge requests—can’t answer that. In addition to not being helpful for seeing engineering’s impact on the business, these metrics can lead to a “big brother” culture, and can negatively affect quality.
Think about it like this: If lines of code equals productivity, devs will write lots of it, regardless of whether it’s good or not.
Enhance GitLab reporting with metrics like planning accuracy, people effort, investment profile, added work, and GitLab CI dashboard KPIs to gain a more complete picture of your development pipeline and potential bottlenecks. This dashboard provides the necessary context to promote healthy discussion around how to balance competing priorities and finite resources.
Engineering leaders need to know where their devs’ time is being invested and when features are going to ship. GitLab reports—like lines of code, number of commits, open issues or merge requests—can’t answer that. In addition to not being helpful for seeing engineering’s impact on the business, these metrics can lead to a “big brother” culture, and can negatively affect quality.
Think about it like this: If lines of code equals productivity, devs will write lots of it, regardless of whether it’s good or not.
Enhance GitLab reporting with metrics like planning accuracy, people effort, investment profile, added work, and GitLab CI dashboard KPIs to gain a more complete picture of your development pipeline and potential bottlenecks. This dashboard provides the necessary context to promote healthy discussion around how to balance competing priorities and finite resources.
Discover the real impact of data-driven engineering
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Improve GitLab Analytics with WorkerB for Slack & MS Teams
Merging devs are happy devs. Unfortunately, half of all merge requests (MRs) are idle for 50% of their lifespan. Even worse, after 4+ days of sitting idle, these MRs (even really big ones) have a single comment on them: “LGTM.” This isn’t only a recipe for poor quality and lots of churn–it’s a really bad developer experience.
Using automated notifications in Slack or MS Teams, WorkerB helps reduce project idle time between hand-offs with functionality to help devs prioritize their day, automate annoying tasks, and review small MRs directly from their WorkerB notifications.
Reduced idle time translates to improved GitLab statistics, faster feedback loops, more frequent merges, a better developer experience, and ultimately more value delivered.
Using automated notifications in Slack or MS Teams, WorkerB helps reduce project idle time between hand-offs with functionality to help devs prioritize their day, automate annoying tasks, and review small MRs directly from their WorkerB notifications.
Reduced idle time translates to improved GitLab statistics, faster feedback loops, more frequent merges, a better developer experience, and ultimately more value delivered.
We correlate data across your tools to identify
bottlenecks and automate developer workflow optimization.
