The moment Dynatrace flags a real problem, six AI specialists find the cause in your live data, open the fix in GitLab, and prove your service recovered. You approve every change. They handle the rest.
Checkout latency jumped to ~1,204ms, past the 300ms goal, because payment-service got slow.
Davis opened problem P-26065 on checkout. Grail shows 1,271 error events and a peak latency of 1,206ms. The payment-service deploy added a 1,200ms delay.
A real incident, start to finish. It plays on its own. Hover to pause.
When Dynatrace flags a real issue on your service, HiveMind wakes up on its own. No polling, no setup. It pulls the cause and the evidence straight from your data.
It reads your live logs and traces, finds the one thing that broke, and opens the fix as a GitLab merge request. It even tells you which customers and how much revenue are at risk.
Once you approve, it merges and redeploys. Then a Dynatrace Site Reliability Guardian confirms the service is healthy again. The proof comes from Dynatrace, not from us.
Six specialists, each plugged into a real system. One alert and they all jump in. A single coding agent cannot see your production, your customers, or your revenue. This team can.
You do not have to take its word for anything. Each step links to the real thing behind it. The Dynatrace problem, the exact query it ran, the merge request, and the recovery check. A script cannot fake any of it.
Every change stops at an approval step. HiveMind writes the fix. You decide if it goes out.
A Dynatrace Site Reliability Guardian checks the service recovered. We do not say it worked. Dynatrace does.
It runs on Vertex AI in your own cloud. Your telemetry is never used to train models.
Connect your Dynatrace and GitLab in two minutes, then watch your first real incident get fixed from start to finish.