v1.4.1
Release v1.4.1
openai:gpt-4.1
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Release Notes
Overview
This release focuses on improving the accuracy and clarity of status reporting in Gogios, particular
ly in how stale checks are handled in both HTML and text reports. It also includes minor bug fixes a
nd version updates to ensure a smoother monitoring experience.
Improvements
More Accurate Status Reporting
-
Stale Check Handling Refined:
Previously, stale checks (checks that haven't reported in a while) were excluded from non-stale re
ports, regardless of their status. Now, only stale checks with a non-OK status are excluded from non
-stale reports.
Why this matters:- Ensures that checks which are stale but healthy (OK) are still visible in regular status reports
. - Reduces confusion by only hiding stale checks that are not OK, making it easier to focus on acti
onable issues.
- Ensures that checks which are stale but healthy (OK) are still visible in regular status reports
-
Consistent Logic in HTML and Text Reports:
The logic for filtering stale checks is now consistent across both HTML and text status reports.
Why this matters:- Users will see the same information regardless of the report format, improving reliability and t
rust in the monitoring output.
- Users will see the same information regardless of the report format, improving reliability and t
Bug Fixes
-
Suppressed Checks Handling:
No changes were made in this release, but the code continues to ensure that OK checks are never su
ppressed, maintaining transparency in reporting. -
Version Update:
The internal version string is updated to v1.4.1 to reflect these changes.
Other Changes
- Code Clean-up:
Minor formatting and whitespace improvements for better maintainability.
Migration Notes
- No Breaking Changes:
This release is fully backward compatible. No configuration changes or migrations are required.
Summary
Gogios v1.4.1 enhances the clarity of monitoring reports by ensuring that healthy, stale checks rema
in visible and that reporting is consistent across formats. These improvements help users quickly id
entify and focus on real issues, making system monitoring more effective and less noisy.