For the past 12 years, we’ve been engineers and then managers of teams of 5 to 150 in several types of companies - startups and big tech. We’ve seen the dev experience being affected by the same problems everywhere: maybe it’s a slow build on your local machine, too many meetings and interviews, or inefficient code review practices that force you to open 10 PRs in parallel to make progress on a given week. We personally struggled with automated tests suites that would take 4 hours to complete and we saw teammates become so desensitized to heavy oncall load that they would stop complaining and just give up.
We also learned that the discussion about engineering metrics always falls into a false dichotomy: don’t measure anything because engineering is creative work (it is!) or measure engineers in intrusive ways along meaningless dimensions like lines of code. We believe that the way to overcome this false dichotomy is to apply quantitative measurements empathetically, that is, with a clear understanding of the human impacts of what's being measured on the people doing the actual work - for example, by measuring how noisy on-call pages disrupt an engineer’s life after hours. The key is to focus on bottlenecks instead of output, and on the team level rather than on individuals. So we set out to build a product where you can see all the data from all your dev tools, query it, make sense of trends, and build alerts for when things go wrong.
At its core, Okay is an end-to-end analytics platform focused on engineering data. First, we ingest data from tools like Google Calendar, Github, Pagerduty, etc. We join it with the team structure that we find in services like Workday. In addition to pre-built integrations, you can also use a tracing-like API to capture e.g. how long local builds are taking. Then, we clean up and enrich the signal: tagging interviews correctly, rebuilding the full history of a PR as a connected chain of review events, inferring dimensions like tenure (which can e.g. help capture new hire experience). Finally, we expose all this data in a query builder UI that closely maps to the underlying SQL query, and we enable users to choose from visualizations we built specifically for representing engineering work: time series of course, but also calendars (e.g. to understand the life of a PR) or heatmaps (e.g. to identify a painful on-call rotation quickly). The opinionated part of Okay is all in the data modeling we do on behalf of users - we aim to reflect our values (team-based vs individuals) and to retain a lot of expressiveness so that users can ask questions like “what is the code review experience of our new hires in our NYC office compared to the SF office?”.
You can check how Okay works by going to our website (https://www.okayhq.com) or checking our product video (https://www.youtube.com/watch?v=jzzo3m4280k). We don’t have free trials because once you identify bottlenecks and set the right alerts to create new habits, it usually takes several weeks to see the changes happen - we’re talking about humans working together after all, so it does require a little bit of upfront investment. We price based on the number of users and engineers on the team.
If you are interested or have specific questions for your use-case, we’d love to connect with your team directly in the comments. Thanks!
by Andrey
Azimov