Enterprise AI Measurement Guide
CI/CD
Deployment Log
Where can we see a per-deployment record showing Status, Environment, Repository, SHA, Author, and Duration for every production deployment?
What it shows
The Deployment Log is the event-level audit trail for every production deployment, showing each deploy's status (success or failure), the environment it targeted, the repository it came from, the exact timestamp, the commit SHA, the author, and the deployment duration. This is the record layer that makes every other CI/CD metric auditable: when an aggregate metric shows a spike in failures, the Deployment Log shows which commits, which authors, and which environments were involved.
Why it matters
The Deployment Log is where AI coding governance becomes concrete. When an incident post-mortem asks "which code caused this, and who authored it?", the answer for AI-assisted deployments requires knowing not just the commit SHA and human author but whether that commit was AI-generated, AI-assisted, or human-only. The Author field in Larridin's Deployment Log captures that attribution, making the root cause analysis for AI-related production incidents traceable rather than requiring manual code archaeology. As regulators and boards begin asking for AI governance documentation, the Deployment Log is part of the audit trail that demonstrates accountability.
The Larridin angle
The SHA-level granularity of Larridin's Deployment Log enables cross-referencing with the Quality Team Level Breakdown, connecting a specific failed deployment's commit SHA to the author's AI Code Share %, Rubber Stamp Rate, and AI Slop Index score in the same investigation. That cross-tab traceability converts the Deployment Log from a record-keeping artifact into an active investigation tool.
Related CI/CD Metrics
Common questions
What information does the Larridin Deployment Log provide?
The Deployment Log provides details on each production deployment, including status, environment, repository, deployed time, SHA, author, and duration.
Why is the Deployment Log important for AI-assisted releases?
The Deployment Log is crucial for AI-assisted releases as it attributes deployments to specific authors and commits, aiding in root cause analysis and compliance with AI governance requirements.
How does the Deployment Log aid in incident post-mortems?
The Deployment Log helps by identifying which code and author were involved in an incident, distinguishing between AI-generated, AI-assisted, or human-only commits.
How does Larridin's Deployment Log enhance traceability?
Larridin's Deployment Log allows cross-referencing with other metrics like the Quality Team Level Breakdown, making it an active tool for investigating deployment issues.