Engineering teams struggle with fragmented access requests and approvals across Slack and Jira, causing delays and inefficiency. A DevOps service catalog centralizes services with clear ownership, dependencies, and documentation—transforming tribal knowledge into self-service capabilities that reduce MTTR.
This approach standardizes workflows, automates provisioning, and establishes clear ownership. Engineers gain self-service tools, incident commanders access dependencies instantly, and compliance remains intact without slowing delivery.
The seven-step framework below creates a sustainable service catalog that engineering teams readily adopt.
Step 1: Audit Your Engineering Requests
Slack pings about database restarts, Jira tickets for access, and incident notes on "missing dashboards" all point to the same bottleneck—repeat work that dilutes your team's velocity.
- Surface the high-volume, high-friction requests to convert them into catalog items and cut average handling time by double-digit percentages.
- Export the past 90 days of Slack, Jira, and post-incident data. Aggregate, then classify each entry by request type, environment, urgency, and effort. Scattered records across multiple tools are inevitable—a disciplined audit reconciles them into a single truth set.
- Inspect content patterns next. Search Slack for verbs like provision, grant, deploy. In Jira, sort by label or component to identify "frequent flyers." For postmortems, tag any delay that lists "waiting on X" as a potential service candidate. Quantify frequency (requests per week) and friction (average resolution hours) to rank importance.
- Consider what engineers typically ask your team for in Slack, which Jira issues recur more than twice a sprint, what incident reviews flagged as delayed or manual, and where approvals or provisioning consistently stall. Document these patterns to build your baseline.
Sample findings often look like this:
, for instance, surface inline Approve / Decline buttons in Slack or Microsoft Teams, eliminating context-switching. Status updates thread back to original requests so participants track progress without portal refreshes.
| Request Type | Approval Required | Approver | SLA |
| Production deployment | Single | Release manager | 30 min |
| New cloud database | Multi-level | Team lead → FinOps | 2 h |
| Sandbox environment | Auto-approved | — | Immediate |
| AWS spend > $5 000 | Parallel | Eng manager & Finance | 4 h |
Configure timeouts to prevent approval limbo. Escalate to the next authority tier or auto-rollback changes when SLA clocks expire. Notify approvers at submission and T-10 minutes. Additional pings add noise and erode compliance.
Step 6: Track SLA & Resolution Performance
Service catalogs without performance measurement become abandoned documentation repositories. Implement real-time tracking across four core timestamps to convert operational data into continuous improvement actions.
Instrument each service request with creation, first response, resolution, and final closure timestamps. From these events derive the DevOps "Four Keys" (deployment frequency, lead time, change failure rate, MTTR) recommended by DORA and Atlassian.
Calculate automation coverage as the ratio of requests closed without human intervention to total requests over the past 30 days. Run this calculation nightly and expose the figure on an "Automation Metrics Dashboard" alongside manual outliers to identify workflows ready for scripting.
Present quarterly to management using a single slide: metric, previous value, current value, delta, planned remediation. Stakeholders see an accountable, numbers-driven operation; practitioners gain a clear mandate to optimise.
Inline CTA: Time to benchmark your ops health? Download the “Automation Metrics Dashboard Template” and track SLA compliance, MTTR, and more—all in one page.
Step 7: Publish and Maintain Your Catalog
Successful service catalog deployment requires strategic implementation where engineers already work. Follow these five steps to ensure adoption and maintenance:
- Publish your catalog where engineers work daily—pin URLs in Slack channels, embed tabs in Microsoft Teams, and integrate links within CI/CD pipelines to establish it as the single source of truth.
- Integrate with existing documentation systems by embedding service pages in Confluence and mirroring metadata in Notion to prevent version conflicts and keep runbooks synchronized.
- Demonstrate time savings during sprint reviews by showcasing common workflows like database provisioning that bypass ad-hoc requests and route directly to automation.
- Review catalog content quarterly with service owners to maintain accuracy while implementing automated drift detection for runtime versions and deployment status.
- Collect systematic feedback through post-fulfillment surveys to track satisfaction and identify improvement opportunities for continuous refinement.
Ensure your catalog is:
- Reviewed and signed off by all service owners
- Linked in relevant Slack and Teams channels
- Has quarterly accuracy audits scheduled
- Has automated CI/CD syncs running nightly
- Displays ownership and escalation paths on every service page
How to Launch a DevOps Catalog in Siit
Implement a DevOps service catalog in just five working days with Siit's platform to transform scattered communication into structured workflows. Follow these steps to achieve 90% auto-routing of requests with zero custom code:
- Day 1: Configure Siit's Service Catalog builder. Import each high-volume service—provisioning, deployment, access management—then assign owners, SLAs, and dependencies. The interface mirrors industry-standard metadata schema, capturing ownership, runtime specifications, and documentation links in validated formats. Siit syncs changes through API calls rather than manual edits, ensuring governance consistency across automated catalogs.
- Day 2: Deploy Dynamic Forms directly to Slack or Microsoft Teams. Each form renders fewer than five fields, auto-fills requester context, and hides irrelevant inputs through conditional logic. Production-level requests route to appropriate queues while eliminating repetitive data entry.
- Day 3: Configure AI Triage routing rules. Siit classifies intake by environment, cost impact, and urgency, then applies attribute-based routing. Critical production incidents reach on-call SRE channels within 60 seconds; non-urgent staging tasks flow to backlog queues. Escalation timers enforce predefined SLA targets automatically.
- Day 4: Activate Rapid Approvals to eliminate manual bottlenecks. Approvers clear or reject requests inline within chat interfaces. Unresolved items escalate automatically after two hours, maintaining compliance without introducing additional tools.
- Day 5: Observe analytics dashboard tracking. Monitor request volume, resolution time, and SLA attainment in real time—metrics essential for catalog health assessment. A single engineer with Slack admin rights, Jira API access, and Siit credentials can complete this end-to-end deployment.
Sign up for Siit today and join hundreds of leading organizations that have cut MTTR while boosting developer productivity. Our 14-day free trial gives you full access to all features, dedicated onboarding support, and proven implementation templates.
You can also schedule a personalized demo and see how your team can deploy a complete DevOps service catalog in less than a week.
