Project Overview
A high-growth SaaS platform suffered from frequent production outages caused by manual deployment errors. Each release took two weeks of planning and execution, which stalled their product innovation.
GryphalCode implemented a GitOps-based CI/CD pipeline using GitLab CI, ArgoCD, and Kubernetes. We also set up a full observability stack (Prometheus, Grafana, ELK) to monitor system health and detect issues before they impact users.
The Challenge
- Fragile, manual deployment process.
- No visibility into application metrics or performance.
- High MTTR (Mean Time To Recovery) after failures.
The Solution
We automated everything. From unit tests to staging deployments, every commit is now verified. The new observability stack provides real-time alerting, and automated rollbacks ensure that a "bad" commit never stays in production.
Key Results
Deployment failures dropped by 89% , and release cycles were slashed from 2 weeks to daily releases . The engineering team now spends 50% more time on features rather than firefighting.
DevOps & Observability Q&A
What tools do you use for observability?
We primarily use Prometheus and Grafana for metrics, coupled with the ELK stack (Elasticsearch, Logstash, Kibana) for log aggregation and distributed tracing with Jaeger.
How do you measure CI/CD success?
We track the DORA metrics: Deployment Frequency, Lead Time for Changes, Change Failure Rate, and Time to Restore Service (MTTR), aiming for "Elite" performer status for all our clients.