Case Study: Diagnosing problems and implementing solutions with Enterprise customers

A case study on the process of how Izymes worked with the world’s largest on-demand streaming company to diagnose problems within the Workzone app, and bring forth a solution.

About the company

The company is a globally renowned on-demand streaming company that revolutionized the way people consume television shows and movies.

The Problem

Within the Workzone plugin for BItbucket, you will find pull request workflow automation such as adding targeted reviewers and groups, entirely customizable merge-checks and automatic merge ability.

When pull request auto-merges takes place and subsequently fails, the team’s release pipeline stops, as features and bugfixes are not propagated. The team needed a diagnostic tool within the Workzone plugin to identify the cause of the merge failure and investigate quickly.

Their large enterprise Bitbucket instance consists of 8+ nodes. This makes it difficult to quickly identify the node that produced the auto-merge failure based on TBytes of backend logs.

The Solution

We met with the company’s head of Engineering at the Atlassian’s Team’23 event over in Las Vegas. We invited him to our expo booth to touch base and learn more about how they are using Workzone in their Bitbucket instance.

As our conversion continued, a problem they have been facing casually surfaced: “We use Workzone for our pull request workflow automation. Sometimes it gets stuck with automatic merges, and it takes us some time to figure out what may have gone wrong.”

We brainstormed a few possible solutions and discussed options right then and there. Having his instant feedback was invaluable. We were able to craft a feature request in real time and get his OK.

The Result

A new solution within the Workzone plugin was implemented. Users are now able to add comments to the pull request history with a unique identifier and context information, including the Bitbucket node ID. This, in turn, will help teams to find the cause for any auto-merge failure directly on the pull request page. If more investigation is required, they can match the unique identifier and node ID with the corresponding Bitbucket server logs.

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