I like how all the data is already integrated into the dashboard with DX and that I don't need to do anything extra as an engineering manager to access it. The fact that it's easy and pain-free to use is a big plus. Its integration with GitHub and Jira is very useful, and the connection with Backstage is nice since it aligns all our platform data on team services. I really appreciate the AI adoption metrics, especially when it comes to seeing which team members are utilizing skills the most. Also, setting up DX was straightforward for me, as I just had to sign in through SSO while my platform team handled all the connections and third-party integrations. I also really love the fact that there is an MCP for DX, it's been such a big unlock - this makes annual reviews much easier and helps me create realtime dashboards about my engineers performance through Claude Code directly. Review collected by and hosted on G2.com.

I find that metrics like true throughput and PRs often need more nuance. The way DX currently looks at PRs - just by their size or number - doesn't fully capture the value added by an engineer. There are instances when engineers work on PRs for migrations or batch processes, which may not be as valuable as more complex, high-cognitive-load tasks. It should consider factors like code complexity and duplication for a more accurate measure of true throughput. Additionally, it was frustrating that when our company used AWS Bedrock instead of a Claude Enterprise account, we couldn't integrate or measure AI usage on DX from that source. Review collected by and hosted on G2.com.