Use cases / Steering execution (SLOs, observability, FinOps)
Steering execution (SLOs, observability, FinOps)
Argy standardizes run practices: observability, routines, and improvement loops are packaged and tracked.
Context
Lack of steering loops: reliability, costs, incidents. Rituals are not standardized.
Argy solution
Runbooks and SRE/FinOps baselines in the catalog, with indicators and ownership.
Key challenges
- • Inconsistent SLOs and alerts
- • Runbooks are not shared
- • Costs are hard to control
Argy approach
- • Reusable observability baselines
- • Automated runbooks and routines
- • Shared KPIs with ownership
Building blocks
- • SRE/FinOps modules
- • Notifications and alerting
- • Dashboards and traces
Governance & sovereignty
- • Traceability for run actions
- • Versioned standards
- • Approvals for sensitive actions
KPIs to track
- • MTTR
- • Incident rate
- • Cost per service
Related automations
Example workflows you can assemble for this use case.
Industrialize run operations
Steps
- • SRE baselines
- • Alerting
- • Runbooks
Outcomes
- • Fewer incidents
- • Reduced MTTR
Governed AI analysis via MCP
Steps
- • Collect logs & metrics
- • Call AI agent via MCP server
- • Root-cause summary
Outcomes
- • Faster diagnosis
- • Standardized routines
Explore more in automatable actions.
Related solutions
How leaders frame this use case across teams.
Platform / SRE team
Build the AI OS on top of your existing platform.
FinOps
Control AI and cloud costs without slowing teams down.
Next step: request a demo or explore solutions.