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implementation_details|

Prometheus Configuration

Used the official kube-prometheus-stack Helm chart with custom retention, multi-cluster federation, and ServiceMonitor CRDs for application metrics.

  • Custom retention policies (30 days for high-priority, 7 days for standard)
  • Multi-cluster federation for centralized metric aggregation
  • ServiceMonitor CRDs for Kubernetes-native service discovery
  • Recording rules for pre-computed aggregations and performance
  • High availability setup with Thanos for long-term storage

Grafana Dashboards

Deployed via ArgoCD Helm release, using pre-baked dashboards from JSON templates stored in Git. Integrated with SSO for RBAC access.

  • Infrastructure monitoring dashboards for CPU, memory, and network metrics
  • Application performance metrics with custom business KPIs
  • Custom alerting rules with severity-based routing
  • Multi-environment views (dev, staging, production)
  • Role-based access control (RBAC) with OAuth integration
  • Dashboard versioning via GitOps workflows

Loki + Promtail

Configured via Helm, ingesting EKS container logs and storing compressed logs on S3 for long-term retention and cost optimization.

  • Container log ingestion from EKS pods via Promtail DaemonSet
  • Log compression and indexing for efficient querying
  • S3 backend for long-term log retention (90 days)
  • Label-based log filtering and routing
  • Integration with Grafana for unified log visualization

Jaeger Distributed Tracing

Deployed using the Jaeger Operator chart, integrated with application traces through OpenTelemetry SDK for end-to-end request visibility across microservices.

  • Jaeger Operator deployed via Helm chart
  • OpenTelemetry SDK integration in application code
  • Trace sampling configuration (10% for production, 100% for staging)
  • Service dependency mapping and performance analysis
  • Integration with Grafana for trace visualization

AlertManager Configuration

Set up with routing rules for severity levels, notifying Slack channels and PagerDuty for critical incidents with proper escalation policies.

  • Severity-based alert routing (critical, warning, info)
  • PagerDuty integration for on-call escalation
  • Slack webhook notifications for team awareness
  • Alert grouping and deduplication to reduce noise
  • Silence rules for planned maintenance windows

Results Achieved

Operational Improvements

  • 80% MTTR Reduction - Faster incident resolution
  • 99.9% Uptime - Proactive monitoring
  • 50+ Dashboards - Comprehensive visibility
  • 100+ Alerts - Automated issue detection

Business Impact

  • Reduced Downtime - Proactive issue detection
  • Improved Performance - Data-driven optimization
  • Better User Experience - SLA monitoring
  • Cost Optimization - Resource utilization insights
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