We’re excited to announce the first feature in the automated engineering insights suite: Deployment Frequency. This dashboard gives you more visibility into your development environment and the flow of code in between, delivering a new level of transparency and operational efficiency to your workflow.
Let’s dive in!
Unpacking Deployment Frequency
Deployment frequency (DF) is a measure of how often code updates or changes are deployed in a specific environment. The higher the deployment frequency, the faster and more agile your process.
For a remote, globally distributed team like ours, we’ve found that keeping track of deployment frequency can help accelerate delivery velocity – without sacrificing product quality.
Here’s why:
👉 Identifying blockers: This metric provides visibility into your dev, staging, and production environments and helps you identify blockers in your workflows i.e. why it takes so long to deploy to production, or why our team isn’t shipping as often.
👉 Measuring operational efficiency: A higher deployment frequency is often correlated with a well-oiled, efficient development lifecycle.
👉Reducing risk: We’ve found that deploying smaller, frequent changes reduces the risk associated with each deployment and helps teams catch issues early.
Introducing Our New Deployment Frequency Feature
Tara AI’s Deployment Frequency dashboard is designed to help you understand how code flows between each development environment, within a repository and timeframe.
- To choose the repo, navigate to the dropdown menu on top of the dashboard.
- To change the timeframe, simply navigate to the calendar toolbar on the top right and update the dates.
- You can also choose which dev environment (dev, staging, production) to view, and compare your team’s performance against that of the previous period using the check boxes on the dashboard.
The Deployment Frequency view will allow you to answer key questions about the pace, efficiency, and frequency of code deployments and improve the overall dev process, such as:
- How often is code submitted in each environment?
- Which Continuous Integration (CI) Stage receives the most or least updates per day/week/period?
- Which dev stage is the blocker within the CI pipeline?
- How does our current deployment frequency compare to the last week or period?
- Are we delivering faster or slower than the previous period?
- Are there specific days when we deploy more than others?
For example, if changes are shipped to staging but not progressing further, this could indicate that your engineers need to improve their testing practices. If your QA team is unable to keep up with the pace of deployments, it might be time to reassess and allocate additional resources to your team.
With this feature, teams can gain an unprecedented level of granularity and visibility into their development cycle– whether you’re trying to accelerate your deployment speed, balance your resources, or simply get a clearer picture of your delivery process.
More to come as we continue to grant access to teams.
Request access today.