Changes
Learn how to track and manage changes in SRE.ai
Overview
A Change is SRE.ai's core unit of work.
It tracks everything associated with a feature or fix, from the initial description through code commits, pull requests, and deployment across environments.
Changes support every metadata type supported by the Metadata API.
Usually, developing a new feature in Salesforce involves updating a range of metadata types and data.
Tasks, Apex scripts, and manual steps may also be involved.
You can import changes directly if your source environment is enabled for Source Tracking.
Core capabilities
Change lifecycle
A Change moves through your deployment pipeline as work progresses.
SRE.ai tracks the current stage automatically based on deployment history.
If new commits have been added since the last successful deployment, the change is flagged as needing re-deployment.
Each change has a status:
Active: The change is in progress
Archived: The change has been completed or closed
What a Change tracks
Commits
Every git commit associated with a change is linked and visible in the change view.
Commits are scoped to a specific branch, which SRE.ai creates automatically if one is not provided.
Pull requests
Pull requests created from a change branch are automatically associated with the change. For each PR, SRE.ai tracks:
Review status: Pending, Approved, Changes Requested, or Commented
Merge state: Open, Merged, or Closed
Who last reviewed it and when
Who merged it and when
Data queries
Changes can include SOQL queries that define data to retrieve alongside the metadata.
When present, these queries are saved as reusable templates and appear as selectable options in the commit tool, so the same query can be applied across multiple commits without re-entering it.
How it works
Deployments
Each deployment of a change to a Salesforce environment is recorded, including which commit was deployed, which stage it targeted, and whether it succeeded.
Code quality
SRE.ai runs code analysis on the files modified by a change and surfaces findings directly in the change view.
Finding types:
Static code analysis
Rule-based violations (e.g., PMD, ESLint) with severity and rule name
AI analysis
AI-generated observations about code quality, patterns, and risks
Dependency reference check
Checks for broken or missing references across metadata components
Finding severity: Critical, High, Medium, Low, Info
Finding statuses:
Open: New or unresolved
In progress: Being worked on
Resolved: Fixed and closed
Dismissed: Marked as not applicable
Users can provide feedback on findings (positive or negative) and leave comments. Findings can also be marked as implemented once a fix has been deployed.
PR and MR comments
When a pull request or merge request is linked to a change, SRE.ai automatically posts code findings as inline comments so reviewers see them without leaving the code review.
GitHub: Findings are submitted as a single pull request review with one inline comment per finding, anchored to the specific file and line number.
GitLab: Findings are posted as MR discussions. Each comment includes the file path and line number in the body.
Which findings are posted:
Severity: Critical, High, and Medium only. Low and Info are not posted
Status: Open and In Progress only. Resolved and Dismissed findings are excluded
Cap: Up to 50 comments per PR/MR
Deduplication: Findings that were already commented on are not reposted when a PR is updated
Findings are only posted for files that appear in the pull request diff. If a finding references a file not changed in the PR, that comment is skipped.
Test coverage
For Apex code, SRE.ai tracks test coverage at the class level. Each change shows:
Overall coverage percentage vs. the required threshold
Which lines are covered and which are not
A per-class breakdown with test method detail
Activity timeline
The timeline logs every significant event in a change's lifecycle:
Change created or updated
Commit added
Deployment completed
Pull request created, reviewed, or merged
Each entry includes a timestamp and the user who performed the action.
External issues
Changes can be linked to Jira or Linear issues.
When a change is updated, SRE.ai automatically syncs the relevant fields back to the linked issue, keeping your issue tracker up to date without manual updates.
Links to external issues are visible in the change header and can be added or removed at any time.
Setup
The Changes page lists all changes in your workspace.
Each change row displays a component count badge (e.g., "3 components") so you can gauge the scope of a change at a glance without opening it.
The view can be filtered and adjusted:
Status filter: Active or Archived
Visible columns: Status, Source Org, Stage, Created, Last Updated
Rows per page: 10, 20, 30, 50, or 100
Click on any change to expand its details and adjust the Change.
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