CI/CD Control Tower
A cost-aware DevOps command centre joining pipelines, deployments, and pull-request risk to their cost consequences.
At a glance
| Route | /ci-cd-control-tower |
| Group | Operate |
| Page permission | intelligence |
What it is
A cost-aware DevOps command centre. It joins CI/CD pipeline execution, deployments, pull-request risk, approvals, and release incidents to the cost consequences of each — so a release can be evaluated on quality and spend at the same time.
Who it is for
DevOps and platform engineering teams, release managers, and engineering leaders who own both delivery velocity and the cost of what is delivered.
How it works
Failure analysis at log level, not status level
The platform reads job logs, classifies the failure, and feeds that evidence to a narrative model — producing a root-cause explanation and deterministic fix hints.
Flakiness detection is attempt-aware, so a test that passes on retry is distinguished from one that is genuinely broken.
Cost attribution to releases
Deployment events are ingested and correlated with the cost ledger, which is what makes it possible to say that a specific release changed spend.
Release memory
A release graph tracks active and recent releases, DORA metrics are computed for delivery quality, and release memory retains what happened previously — so recurring failure patterns are recognised rather than rediscovered.
Features
- Pipeline run visibility across connected CI systems, with job-level insight
- Log-level root-cause analysis with failure classification and deterministic fix hints
- Attempt-aware flakiness detection distinguishing retry-passing tests from genuine failures
- DORA metrics and release quality tracking, including change failure rate
- Active and recent release graph with a release timeline
- Service-level release health
- Cost delta per deployment, attributing spend changes to specific releases
- Pull-request risk assessment surfaced alongside cost impact
- Action queue with approval-required gating and owner assignment
- Release memory retaining prior incidents and resolutions
- Open incident tracking tied to releases
- Agentic follow-up chips proposing the next diagnostic step
- Rollback support and readiness checks
How to use it
Connect GitHub
Through the GitHub App in Integrations, and confirm the permission check on this page passes.
Point CI webhooks at the workspace ingestion endpoint
So pipeline runs appear here.
Confirm deployment events are being ingested
Cost attribution depends on them. Without deployment events you get delivery metrics but no cost correlation.
Review the release timeline
Identify releases carrying a material cost delta.
For failing pipelines, read the job insight — not the raw log
The log-level root cause and fix hints are the point of the module.
Use flakiness detection before assigning engineering time
Separate infrastructure noise from real regressions first.
Track DORA metrics as a delivery-health baseline
Watch change failure rate against release cadence.
Work the action queue
Assigning owners and approving where gated.
Escalate cost regressions formally
Into Apex → Incidents for tracked root-cause analysis.
Why it matters
The core insight
Cost regressions and reliability regressions are usually caused by the same events — releases — but are almost always investigated by different teams, using different tools, days or weeks apart.
Putting deployment quality and deployment cost on one surface makes the connection immediate.
And log-level root-cause analysis removes the most expensive part of incident response: reading logs to work out what broke.
Connects to
- Shares GitHub integration with PR Cost Review and Deploy & Migration
- Cost attribution feeds regression analysis in Intelligence
- Incidents escalate to Apex → Incidents
- Approvals route through Approvals
- Configuration lives in Integrations