Gitlab hero border pattern left svg Gitlab hero border pattern right svg

Product Vision - Telemetry

On this page

Telemetry manages a variety of technologies that are important for GitLab's understanding of how our users use our products. These technologies include but are not limited to; Snowplow Analytics,, an in-house tool called Usage Ping which is hosted on and also includes a separate service called Version Check .

If you'd like to discuss this vision directly with the Product Manager for Telemetry, feel free to reach out to Luca Williams via e-mail, Twitter, or by scheduling a video call.

Category Description
🧺 Collection The structure(s) and platform(s) of how we collect Telemetry data
πŸ” Analysis Manages GitLab's internal needs for an analysis tool that serves the Product department

Improving how we collect and work with product usage data is the first and most crucial stepping stone to visualizing and analyzing our data so we can make the best decisions for our users and therefore our business.

The overall vision for the Telemetry group is to ensure that we have a robust, consistent and modern telemetry data framework in place to best serve our internal Product, Sales, and Customer Success teams. The group also ensures that GitLab has the best visualization and analysis tools in place that allows the best possible insights into the data provided through the various collection tools we utilize.

Our users should feel safe and protected while opting-in to sending GitLab Telemetry data and feel comfortable trusting GitLab with that data. They should know that their data is being used respectfully and only to further improve our products and make them more lovable. We truly value and respect the privacy of our users and we carefully consider and prioritize privacy in every decision we make. One of GitLab’s core values is transparency. It is important that we are transparent about the way we collect data, why we collect it and how we use it.

πŸ€” Why is Telemetry important?

Telemetry is an automated communications process by which measurements and other data are collected at remote or inaccessible points and transmitted to receiving equipment for monitoring. The word is derived from Greek roots: tele = remote, and metron = measure. In software, Telemetry data records clicks, counts, time spent on tasks, webpages, growth in the usage of a feature over time, and trends of all these things.

Telemetry data is essential to building a successful product. It provides insights into how users interact with and use a product and allow many functions within a company to make educated decisions. To build an efficient, well-considered product with a great user experience, Product Managers need insights on how the decisions they previously made are impacting users. These insights allow them to understand what matters to users and what doesn't, and helps to deliver high quality, low effort interactions that users love. ❀️

Telemetry is often viewed through a negative lens. Privacy is becoming more and more of a serious topic in recent years due to the rise in social media, GDPR and the increasing need for more secure applications to protect users. However, Telemetry is not just a term used in software, it is commonly used in medicine, science, meteorology and other similar areas. There is even such a job as a Telemetry Nurse, which is a specialized role in the medical field where Nurses monitor patients vitals, record and interpret the data and provide this to Doctors to show how a patient is recovering, allowing the Doctor to prescribe a more effective and care-driven treatment plan.

Telemetry data doesn't just make Product Managers lives easier; It's also hugely beneficial to Customer Success teams by allowing them to see where users may need additional help or support. It enables Customer Success Managers and Technical Account Managers to proactively reach out and make sure that users are happy with what they've purchased. It's equally beneficial to teams such as Product Marketing and Sales by helping them know what story to tell future users of the product and what might be useful to current users to keep them up to date and well informed.

πŸš€ Collection Priorities

πŸ”₯ Current focus

Priority Focus Why?
1️⃣ Define and measure monthly active users, overall and per-stage After this epic is closed, we should have an internally consistent view of MAU and SMAU across and self-managed. We should be able to measure active use in a Periscope dashboard, enabling us to improve MAU and SMAU. We can then tackle improving this further with SMAU/MAU v2.0.

πŸŽ‰ Next up

Priority Focus Why?
2️⃣ SMAU/MAU v2.0. As our organization grows, we require better data to inform our product, marketing, and sales team as they make decisions to grow the business and realize our strategic goals. This epic will serve as the aggregation of issues required to improve our monthly active user metrics, so we can have a world-class data platform at GitLab.
3️⃣ Improve telemetry data collection from self-managed instances Currently we have little to no visibility into how many of our largest and most valuable customers are using GitLab. We need to understand how we can collect data more consistently from our Self-Managed users in order to better serve them.
4️⃣ Telemetry Documentation It is important that as we roll out new changes and develop processes and workflows, we clearly and transparently document everything in a way that is easily discoverable and digestible by both GitLab team members and users/customers.

πŸš€ Analysis Priorities

πŸ”₯ Current focus

Priority Focus Why?
1️⃣ Pendo Implementation for GitLab hosted services is an wildly popular, industry standard data collection and analysis tool widely used by many organisations to gain insights into how their users are using their products. GitLab has decided to subscribe to and implement Pendo whilst we improve our in-house data collection and analysis options and develop the overall vision for the Telemetry group.

πŸŽ‰ Next up

Priority Focus Why?
2️⃣ Product Team Dashboards Parallel to improving SMAU/MAU v2.0., it's important that we roll out the process defined by the Telemetry working group to all of the other stages so that each Product Manager has visibility into how users are using their stage and stage categories.

How we prioritize

We follow the same prioritization guidelines as the product team at large. Issues tend to flow from having no milestone, to being added to the backlog, to a directional milestone (e.g. Next 3-4 releases), and are finally assigned a specific milestone.

Our entire public backlog for Telemetry can be viewed here, and can be filtered by labels or milestones. If you find something you are interested in, you're encouraged to jump into the conversation and participate. At GitLab, everyone can contribute!