Enterprise Observability Platform

Production-ready, cloud-native observability platform built with professional tooling and best practices.

Architecture Overview

┌─────────────────┐    ┌─────────────────┐    ┌─────────────────┐
│   APPLICATIONS  │    │  OTEL COLLECTOR │    │    BACKENDS     │
│                 │    │                 │    │                 │
│ • OTLP          │───▶│ Agent (DaemonSet│───▶│ Mimir (Metrics) │
│ • Jaeger        │    │ Gateway (Deploy)│    │ Loki (Logs)     │
│ • Zipkin        │    │ + 6 Exporters   │    │ Tempo (Traces)  │
│ • Prometheus    │    │ + Unified Proc. │    │                 │
└─────────────────┘    └─────────────────┘    └─────────────────┘
                                │
                       ┌─────────────────┐
                       │   SLI/SLO       │
                       │   MONITORING    │
                       │                 │
                       │ Sloth + 23 SLOs │
                       │ Error Budget    │
                       │ Burn Rate Alert │
                       └─────────────────┘

Components

Unified Telemetry Collection

• OpenTelemetry Collector: Agent + Gateway deployment pattern
• Multi-Protocol Support: OTLP, Jaeger, Zipkin, Prometheus
• Advanced Processing: Sampling, correlation, transformation
• 6 Specialized Exporters: Node, KSM, Blackbox, NGINX, Redis, CloudWatch

Three-Pillar Storage

• Mimir: Long-term metrics storage with S3 + DynamoDB
• Loki: Log aggregation and search
• Tempo: Distributed tracing with correlation

SRE & Monitoring

• Sloth: SLI/SLO operator with 21 comprehensive SLOs
• Professional Tooling: Official Helm charts, GitOps-ready
• AWS Integration: S3, DynamoDB, IRSA, KMS encryption

Key Features

✅ Enterprise Architecture: Production-ready with HA, scaling, security ✅ Unified Collection: Single telemetry pipeline for all signals ✅ Cloud Integration: Native AWS S3/DynamoDB with proper IAM ✅ SLO-Driven: Comprehensive error budget and burn rate monitoring ✅ Professional Tooling: Official Helm charts, no custom resources ✅ GitOps Ready: Declarative deployment with Helmfile

🚀 Quick Start

Complete Stack Deployment

# 1. Deploy infrastructure
cd terraform/envs/dev
terraform init && terraform apply

# 2. Deploy platform services
cd ../../../
helmfile sync

# 3. Deploy Grafana + dashboards
kubectl apply -k k8s/base/grafana/

# 4. Access services locally
./scripts/port-forward.sh

Access Points

• Grafana: localhost:3000 (admin/admin)
• Mimir: localhost:8080/prometheus
• Loki: localhost:3100
• Tempo: localhost:16686
• OTel Gateway: localhost:4317

📊 Monitoring & SLOs

Service Level Objectives (7 categories)

• Mimir: Availability 99.9%, Latency P99 <1s, Ingestion 99.5%
• Loki: Query success 99%, Ingestion success 99.5%, Latency P95 <5s
• Tempo: Query success 99%, Ingestion success 99.5%, Latency P95 <2s
• OTel Collector: Processing success 99.9%, Export success 99.8%
• Infrastructure: Node availability 99.5%, Storage performance 99%
• Prometheus Agent: Scrape success 99.5%, Remote write 99.9%

Dashboards (7 organized dashboards)

📁 Infrastructure/
  • Kubernetes Cluster Overview
  • AlertManager Overview

📁 Observability Platform/
  • OpenTelemetry Collector
  • Mimir Metrics Storage
  • Loki Log Storage
  • Tempo Trace Storage

📁 Reliability/
  • SLO Monitoring

🔧 Configuration

Terraform + Helm Integration

Infrastructure (Terraform):

• S3 buckets with lifecycle policies
• DynamoDB tables for indexing
• IAM roles with IRSA
• KMS encryption keys

Platform (Helmfile + Kustomize):

• OpenTelemetry Collector (agent + gateway)
• Mimir, Loki, Tempo backends
• Grafana Operator + dashboards
• 6 specialized exporters

Template System

Dynamic configuration from Terraform outputs:

# Templates are populated during deployment
values.template.yaml → values.generated.yaml
${aws_region} → us-west-2
${mimir_s3_bucket_name} → observability-dev-mimir
${kms_key_id} → arn:aws:kms:...

🗂️ Project Structure

observability-platform/
├── terraform/               # Infrastructure as Code
│   ├── modules/             # Reusable modules (s3-kms, iam, dynamodb)
│   └── envs/               # Environment configs (dev, prod)
├── k8s/base/               # Kubernetes manifests
│   ├── grafana/            # Grafana Operator + dashboards
│   ├── otel-collector/     # Telemetry collection
│   └── exporters/          # Specialized metric exporters
├── helmfile.yaml           # Declarative Helm deployment
├── deploy.sh              # Automated deployment script
└── scripts/               # Utility scripts (cleanup, port-forward)

🛠️ Operations

Troubleshooting

# Check component health
kubectl get pods -n observability

# Verify metrics ingestion
curl "http://localhost:8080/prometheus/api/v1/query?query=up"

# Check SLO status
kubectl get prometheusrule -n observability

# View logs
kubectl logs -n observability -l app.kubernetes.io/name=mimir

Cleanup

# Remove entire platform
./scripts/cleanup.sh

# Remove infrastructure
cd terraform/envs/dev && terraform destroy

📚 Documentation

• docs/ - Architecture guides and cost optimization
• k8s/base/grafana/README.md - Grafana Operator setup
• scripts/README.md - Utility scripts documentation
• terraform/modules/README.md - Infrastructure modules guide

💰 Cost Estimates

Development: ~$10-35/month Production: ~$150-700/month

Costs depend on data volume and retention policies. Includes lifecycle management for cost optimization.

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Enterprise-grade observability stack with comprehensive monitoring, SLO tracking, and professional tooling. Ready for production deployment!