DrDroid Observability Stack Implementation by Shaid TDrDroid Observability Stack Implementation by Shaid T

DrDroid Observability Stack Implementation

Shaid T

Completed work

Backend Engineer

DevOps Engineer

Grafana

PostgreSQL

Slack

Electronics

🚀 DrDroid Observability Stack

Author: Shaid T

🎯 Overview

This project demonstrates a comprehensive observability stack integrating:

15 microservices (Google's microservices-demo)

Full monitoring (Prometheus, Grafana, Loki, Jaeger)

Chaos engineering (Chaos Mesh)

Multi-channel alerting (Slack, AlertManager)

AI-powered incident management (DrDroid platform)

Database persistence (PostgreSQL)

✨ Features

Feature Description Status 📊 Microservices Demo 11-service e-commerce application ✅ Production 🔍 Prometheus Metrics Real-time metrics collection & alerting ✅ Active 📈 Grafana Dashboards Business & technical metrics visualization ✅ Live 📝 Loki Log Aggregation Centralized logging with Promtail ✅ Streaming 🎯 Jaeger Tracing Distributed request tracing ✅ Bonus Feature 💾 PostgreSQL Database Persistent order data storage ✅ Integrated 🌪️ Chaos Engineering 4 fault injection scenarios ✅ Active 🚨 Multi-Channel Alerts Slack + DrDroid integration ✅ Connected 🤖 DrDroid AI Platform Intelligent incident analysis ✅ Integrated

🏗️ Architecture

┌─────────────────────────────────────────────────────────┐
│              k3d Cluster (3 nodes)                      │
├─────────────────────────────────────────────────────────┤
│                                                         │
│  Microservices Layer                                    │
│  ├─ frontend                                           │
│  ├─ cartservice                                        │
│  ├─ checkoutservice                                    │
│  ├─ productcatalogservice                              │
│  └─ 7 more services...                                 │
│                                                         │
│  Data Layer                                            │
│  └─ PostgreSQL (Order persistence)                     │
│                                                         │
│  Observability Stack                                   │
│  ├─ Prometheus → Metrics & Alerting                    │
│  ├─ Grafana → Dashboards & Visualization              │
│  ├─ Loki → Log Aggregation                            │
│  ├─ Jaeger → Distributed Tracing                      │
│  └─ AlertManager → Alert Routing                       │
│                                                         │
│  Chaos Engineering                                     │
│  └─ Chaos Mesh → Fault Injection                      │
│                                                         │
└─────────────────────────────────────────────────────────┘

🚨 Alert Pipeline

Chaos Experiment
      ↓
Metrics Spike (CPU/Memory/Errors)
      ↓
Prometheus Scrapes (every 15s)
      ↓
Alert Rule Evaluates (2min threshold)
      ↓
AlertManager Routes Alert
      ↓
  ┌───┴────┐
  ↓        ↓
Slack   DrDroid
(Team)  (AI Analysis)

Alert Rules

Alert Condition Severity Action HighPodCPU CPU > 80% for 2min Warning Slack notification HighPodMemory Memory > 500MB Warning Slack notification PodNotRunning Pod not in Running state Critical Slack + Investigation PodFrequentRestarts >3 restarts in 5min Warning Auto-remediation trigger

🌪️ Chaos Engineering Scenarios

1. CPU Stress Test

Purpose: Test high resource utilization handling Target: Frontend service Expected Behavior:

CPU spikes above 80%

Prometheus alert fires after 2 minutes

Slack notification sent

DrDroid correlates with metrics

kubectl apply -f manifests/chaos/cpu-stress-chaos.yaml

2. Pod Kill Test

Purpose: Test Kubernetes self-healing Target: Cart service Expected Behavior:

Pod terminated

Kubernetes restarts pod automatically

Brief service disruption

Alert fires for pod downtime

kubectl apply -f manifests/chaos/pod-kill-chaos.yaml

3. Network Latency Test

Purpose: Test degraded network performance Target: Checkout → Payment communication Expected Behavior:

500ms latency injected

Request timeouts increase

User experience degrades

Tracing shows bottleneck

kubectl apply -f manifests/chaos/network-chaos.yaml

4. HTTP Error Injection

Purpose: Test error handling & logging Target: Product catalog service Expected Behavior:

HTTP 500 errors injected

Error rate spikes in metrics

Logs capture exceptions

Alert fires for high error rate

kubectl apply -f manifests/chaos/http-chaos.yaml

Stop any chaos experiment:

kubectl delete -f manifests/chaos/<chaos-file>.yaml
# Or delete all
kubectl delete podchaos,networkchaos,stresschaos,httpchaos --all -n default

🚀 Quick Start

Prerequisites

Docker

kubectl

helm

k3d

Installation

# 1. Clone the repository
git clone https://github.com/OpShaid/drdroid-observability-stack.git
cd drdroid-observability-stack

# 2. Run setup script (installs dependencies)
./setup.sh

# 3. Deploy everything
./s.sh

# 4. Wait for all pods to be ready (2-3 minutes)
kubectl get pods --all-namespaces -w

Manual Setup

# 1. Create k3d cluster
k3d cluster create drdroid-demo --agents 2

# 2. Deploy microservices
kubectl apply -f https://raw.githubusercontent.com/GoogleCloudPlatform/microservices-demo/main/release/kubernetes-manifests.yaml

# 3. Install monitoring stack
helm repo add prometheus-community https://prometheus-community.github.io/helm-charts
helm install kube-prometheus prometheus-community/kube-prometheus-stack \
  --namespace monitoring --create-namespace \
  --set grafana.adminPassword=drdroid2024

# 4. Install Loki for logs
helm repo add grafana https://grafana.github.io/helm-charts
helm install loki grafana/loki-stack -n monitoring \
  --set grafana.enabled=false \
  --set promtail.enabled=true

# 5. Deploy Jaeger for tracing
kubectl apply -f manifests/tracing/jaeger-all-in-one.yaml

# 6. Install Chaos Mesh
curl -sSL https://mirrors.chaos-mesh.org/v2.6.3/install.sh | bash

# 7. Deploy PostgreSQL database
kubectl apply -f manifests/database/postgres.yaml

# 8. Apply Prometheus alert rules
kubectl apply -f manifests/alerting/prometheus-rules-patch.yaml

# 9. Configure AlertManager for Slack
kubectl apply -f manifests/alerting/alertmanager-config.yaml

🌐 Access Services

Local Access

Service URL Credentials Grafana http://localhost:3000 admin / drdroid2024 Prometheus http://localhost:9090 - AlertManager http://localhost:9093 - Jaeger http://localhost:16686 - Microservices Frontend http://localhost:8080 -

Port-forward commands:

# Grafana
kubectl port-forward -n monitoring svc/kube-prometheus-grafana 3000:80 &

# Prometheus
kubectl port-forward -n monitoring svc/kube-prometheus-prometheus 9090:9090 &

# AlertManager
kubectl port-forward -n monitoring svc/alertmanager-operated 9093:9093 &

# Jaeger
kubectl port-forward -n default svc/jaeger-query 16686:16686 &

# Frontend
kubectl port-forward -n default svc/frontend 8080:80 &

External Access (via ngrok)

# Expose Grafana externally
ngrok http 3000

# Expose Prometheus
ngrok http 9090

# Use these URLs in DrDroid integrations

🔗 DrDroid Integrations

Connected Integrations

Integration Status URL/Configuration Kubernetes 🟢 Active Agent deployed via proxy token Grafana 🟢 Active https://xxx.ngrok-free.app Prometheus 🟢 Active http://xxx.ngrok-free.app Slack 🟢 Active #drdroid-alerts channel GitHub 🟢 Active Repository connected

Integration Setup

Kubernetes Agent:

cd drd-vpc-agent
./deploy_k8s.sh <PROXY_TOKEN>

Grafana + Prometheus:

Use ngrok URLs or IP-based endpoints

Add in DrDroid platform under Integrations

Slack:

Webhook URL configured in AlertManager

Channel: #drdroid-alerts

📊 Monitoring & Dashboards

Pre-configured Dashboards

Kubernetes Cluster Overview

CPU, Memory, Network across all nodes

Pod count and status

Resource utilization trends

Microservices Performance

Request rate per service

Latency percentiles (p50, p95, p99)

Error rates

Business Metrics (Custom)

Total orders processed

Order success rate

Revenue per hour

Checkout conversion funnel

Alert Dashboard

Active alerts by severity

Alert frequency over time

MTTD and MTTR metrics

Key Metrics

# CPU Usage
rate(container_cpu_usage_seconds_total[5m])

# Memory Usage
container_memory_usage_bytes

# Request Rate
rate(http_requests_total[5m])

# Error Rate
rate(http_requests_total{status=~"5.."}[5m])

# Pod Restarts
kube_pod_container_status_restarts_total

💾 Database Integration

PostgreSQL Setup

Connection Details:

Host: postgres-service.default.svc.cluster.local

Port: 5432

Database: orders

User: postgres

Schema:

CREATE TABLE orders (
    id SERIAL PRIMARY KEY,
    user_id VARCHAR(255),
    order_total DECIMAL(10,2),
    items JSONB,
    created_at TIMESTAMP DEFAULT NOW()
);

Query Orders:

kubectl exec -it <postgres-pod> -n default -- psql -U postgres -d orders -c "SELECT * FROM orders LIMIT 10;"

🧪 Testing Scenarios

End-to-End Test

# 1. Trigger chaos
kubectl apply -f manifests/chaos/cpu-stress-chaos.yaml

# 2. Monitor in Grafana
# Open: http://localhost:3000
# Navigate to: Kubernetes / Compute Resources / Cluster

# 3. Wait for alert (2-3 minutes)
# Check: http://localhost:9090/alerts

# 4. Verify Slack notification
# Check #drdroid-alerts channel

# 5. Check DrDroid incident
# Open: https://aiops.drdroid.io/incidents

# 6. Clean up
kubectl delete -f manifests/chaos/cpu-stress-chaos.yaml

📈 Production Considerations

What's Production-Ready

✅ High availability deployments ✅ Resource limits and requests configured ✅ Health checks and readiness probes ✅ Structured logging with correlation IDs ✅ Metrics instrumentation ✅ Alert rules with proper thresholds

What Would Be Added for Production

Persistent Storage: Thanos for long-term Prometheus metrics, S3 for Loki

High Availability: Multi-replica AlertManager, Grafana, Prometheus

Security: Vault for secrets, RBAC policies, network policies, mTLS

Disaster Recovery: Velero for cluster backups, cross-region replication

Cost Optimization: OpenCost integration, resource right-sizing

Distributed Tracing: Full service instrumentation with OpenTelemetry

Incident Management: PagerDuty/Opsgenie integration with on-call rotations

CI/CD: ArgoCD for GitOps deployments

Service Mesh: Istio for advanced traffic management and security

🛠️ Troubleshooting

Common Issues

Pods not starting:

kubectl get pods --all-namespaces
kubectl describe pod <pod-name> -n <namespace>
kubectl logs <pod-name> -n <namespace>

Grafana not accessible:

kubectl port-forward -n monitoring svc/kube-prometheus-grafana 3000:80
# Access: http://localhost:3000

Alerts not firing:

# Check Prometheus targets
kubectl port-forward -n monitoring svc/kube-prometheus-prometheus 9090:9090
# Open: http://localhost:9090/targets

# Check AlertManager
kubectl logs -n monitoring alertmanager-kube-prometheus-kube-prome-alertmanager-0

Slack notifications not working:

# Verify webhook URL
kubectl get secret -n monitoring alertmanager-kube-prometheus-alertmanager -o yaml

# Test webhook manually
curl -X POST -H 'Content-type: application/json' \
  --data '{"text":"Test alert"}' \
  https://hooks.slack.com/services/YOUR/WEBHOOK/URL

Like this project

Completed work

Posted Nov 7, 2025

Developed an observability stack with monitoring, alerting, and incident management etc for DrDroid.

Likes

Views

Timeline

Nov 3, 2025 - Nov 5, 2025

DrDroid Observability Stack Implementation

Shaid T

Completed work

Backend Engineer

DevOps Engineer

Grafana

PostgreSQL

Slack

Electronics

🚀 DrDroid Observability Stack

Author: Shaid T

🎯 Overview

This project demonstrates a comprehensive observability stack integrating:

15 microservices (Google's microservices-demo)

Full monitoring (Prometheus, Grafana, Loki, Jaeger)

Chaos engineering (Chaos Mesh)

Multi-channel alerting (Slack, AlertManager)

AI-powered incident management (DrDroid platform)

Database persistence (PostgreSQL)

✨ Features

🏗️ Architecture

┌─────────────────────────────────────────────────────────┐
│              k3d Cluster (3 nodes)                      │
├─────────────────────────────────────────────────────────┤
│                                                         │
│  Microservices Layer                                    │
│  ├─ frontend                                           │
│  ├─ cartservice                                        │
│  ├─ checkoutservice                                    │
│  ├─ productcatalogservice                              │
│  └─ 7 more services...                                 │
│                                                         │
│  Data Layer                                            │
│  └─ PostgreSQL (Order persistence)                     │
│                                                         │
│  Observability Stack                                   │
│  ├─ Prometheus → Metrics & Alerting                    │
│  ├─ Grafana → Dashboards & Visualization              │
│  ├─ Loki → Log Aggregation                            │
│  ├─ Jaeger → Distributed Tracing                      │
│  └─ AlertManager → Alert Routing                       │
│                                                         │
│  Chaos Engineering                                     │
│  └─ Chaos Mesh → Fault Injection                      │
│                                                         │
└─────────────────────────────────────────────────────────┘

🚨 Alert Pipeline

Chaos Experiment
      ↓
Metrics Spike (CPU/Memory/Errors)
      ↓
Prometheus Scrapes (every 15s)
      ↓
Alert Rule Evaluates (2min threshold)
      ↓
AlertManager Routes Alert
      ↓
  ┌───┴────┐
  ↓        ↓
Slack   DrDroid
(Team)  (AI Analysis)

Alert Rules

🌪️ Chaos Engineering Scenarios

1. CPU Stress Test

Purpose: Test high resource utilization handling Target: Frontend service Expected Behavior:

CPU spikes above 80%

Prometheus alert fires after 2 minutes

Slack notification sent

DrDroid correlates with metrics

kubectl apply -f manifests/chaos/cpu-stress-chaos.yaml

2. Pod Kill Test

Purpose: Test Kubernetes self-healing Target: Cart service Expected Behavior:

Pod terminated

Kubernetes restarts pod automatically

Brief service disruption

Alert fires for pod downtime

kubectl apply -f manifests/chaos/pod-kill-chaos.yaml

3. Network Latency Test

Purpose: Test degraded network performance Target: Checkout → Payment communication Expected Behavior:

500ms latency injected

Request timeouts increase

User experience degrades

Tracing shows bottleneck

kubectl apply -f manifests/chaos/network-chaos.yaml

4. HTTP Error Injection

Purpose: Test error handling & logging Target: Product catalog service Expected Behavior:

HTTP 500 errors injected

Error rate spikes in metrics

Logs capture exceptions

Alert fires for high error rate

kubectl apply -f manifests/chaos/http-chaos.yaml

Stop any chaos experiment:

kubectl delete -f manifests/chaos/<chaos-file>.yaml
# Or delete all
kubectl delete podchaos,networkchaos,stresschaos,httpchaos --all -n default

🚀 Quick Start

Prerequisites

Docker

kubectl

helm

k3d

Installation

# 1. Clone the repository
git clone https://github.com/OpShaid/drdroid-observability-stack.git
cd drdroid-observability-stack

# 2. Run setup script (installs dependencies)
./setup.sh

# 3. Deploy everything
./s.sh

# 4. Wait for all pods to be ready (2-3 minutes)
kubectl get pods --all-namespaces -w

Manual Setup

# 1. Create k3d cluster
k3d cluster create drdroid-demo --agents 2

# 2. Deploy microservices
kubectl apply -f https://raw.githubusercontent.com/GoogleCloudPlatform/microservices-demo/main/release/kubernetes-manifests.yaml

# 3. Install monitoring stack
helm repo add prometheus-community https://prometheus-community.github.io/helm-charts
helm install kube-prometheus prometheus-community/kube-prometheus-stack \
  --namespace monitoring --create-namespace \
  --set grafana.adminPassword=drdroid2024

# 4. Install Loki for logs
helm repo add grafana https://grafana.github.io/helm-charts
helm install loki grafana/loki-stack -n monitoring \
  --set grafana.enabled=false \
  --set promtail.enabled=true

# 5. Deploy Jaeger for tracing
kubectl apply -f manifests/tracing/jaeger-all-in-one.yaml

# 6. Install Chaos Mesh
curl -sSL https://mirrors.chaos-mesh.org/v2.6.3/install.sh | bash

# 7. Deploy PostgreSQL database
kubectl apply -f manifests/database/postgres.yaml

# 8. Apply Prometheus alert rules
kubectl apply -f manifests/alerting/prometheus-rules-patch.yaml

# 9. Configure AlertManager for Slack
kubectl apply -f manifests/alerting/alertmanager-config.yaml

🌐 Access Services

Local Access

Port-forward commands:

# Grafana
kubectl port-forward -n monitoring svc/kube-prometheus-grafana 3000:80 &

# Prometheus
kubectl port-forward -n monitoring svc/kube-prometheus-prometheus 9090:9090 &

# AlertManager
kubectl port-forward -n monitoring svc/alertmanager-operated 9093:9093 &

# Jaeger
kubectl port-forward -n default svc/jaeger-query 16686:16686 &

# Frontend
kubectl port-forward -n default svc/frontend 8080:80 &

External Access (via ngrok)

# Expose Grafana externally
ngrok http 3000

# Expose Prometheus
ngrok http 9090

# Use these URLs in DrDroid integrations

🔗 DrDroid Integrations

Connected Integrations

Integration Setup

Kubernetes Agent:

cd drd-vpc-agent
./deploy_k8s.sh <PROXY_TOKEN>

Grafana + Prometheus:

Use ngrok URLs or IP-based endpoints

Add in DrDroid platform under Integrations

Slack:

Webhook URL configured in AlertManager

Channel: #drdroid-alerts

📊 Monitoring & Dashboards

Pre-configured Dashboards

Kubernetes Cluster Overview

CPU, Memory, Network across all nodes

Pod count and status

Resource utilization trends

Microservices Performance

Request rate per service

Latency percentiles (p50, p95, p99)

Error rates

Business Metrics (Custom)

Total orders processed

Order success rate

Revenue per hour

Checkout conversion funnel

Alert Dashboard

Active alerts by severity

Alert frequency over time

MTTD and MTTR metrics

Key Metrics

# CPU Usage
rate(container_cpu_usage_seconds_total[5m])

# Memory Usage
container_memory_usage_bytes

# Request Rate
rate(http_requests_total[5m])

# Error Rate
rate(http_requests_total{status=~"5.."}[5m])

# Pod Restarts
kube_pod_container_status_restarts_total

💾 Database Integration

PostgreSQL Setup

Connection Details:

Host: postgres-service.default.svc.cluster.local

Port: 5432

Database: orders

User: postgres

Schema:

CREATE TABLE orders (
    id SERIAL PRIMARY KEY,
    user_id VARCHAR(255),
    order_total DECIMAL(10,2),
    items JSONB,
    created_at TIMESTAMP DEFAULT NOW()
);

Query Orders:

kubectl exec -it <postgres-pod> -n default -- psql -U postgres -d orders -c "SELECT * FROM orders LIMIT 10;"

🧪 Testing Scenarios

End-to-End Test

# 1. Trigger chaos
kubectl apply -f manifests/chaos/cpu-stress-chaos.yaml

# 2. Monitor in Grafana
# Open: http://localhost:3000
# Navigate to: Kubernetes / Compute Resources / Cluster

# 3. Wait for alert (2-3 minutes)
# Check: http://localhost:9090/alerts

# 4. Verify Slack notification
# Check #drdroid-alerts channel

# 5. Check DrDroid incident
# Open: https://aiops.drdroid.io/incidents

# 6. Clean up
kubectl delete -f manifests/chaos/cpu-stress-chaos.yaml

📈 Production Considerations

What's Production-Ready

What Would Be Added for Production

Persistent Storage: Thanos for long-term Prometheus metrics, S3 for Loki

High Availability: Multi-replica AlertManager, Grafana, Prometheus

Security: Vault for secrets, RBAC policies, network policies, mTLS

Disaster Recovery: Velero for cluster backups, cross-region replication

Cost Optimization: OpenCost integration, resource right-sizing

Distributed Tracing: Full service instrumentation with OpenTelemetry

Incident Management: PagerDuty/Opsgenie integration with on-call rotations

CI/CD: ArgoCD for GitOps deployments

Service Mesh: Istio for advanced traffic management and security

🛠️ Troubleshooting

Common Issues

Pods not starting:

kubectl get pods --all-namespaces
kubectl describe pod <pod-name> -n <namespace>
kubectl logs <pod-name> -n <namespace>

Grafana not accessible:

kubectl port-forward -n monitoring svc/kube-prometheus-grafana 3000:80
# Access: http://localhost:3000

Alerts not firing:

# Check Prometheus targets
kubectl port-forward -n monitoring svc/kube-prometheus-prometheus 9090:9090
# Open: http://localhost:9090/targets

# Check AlertManager
kubectl logs -n monitoring alertmanager-kube-prometheus-kube-prome-alertmanager-0

Slack notifications not working:

# Verify webhook URL
kubectl get secret -n monitoring alertmanager-kube-prometheus-alertmanager -o yaml

# Test webhook manually
curl -X POST -H 'Content-type: application/json' \
  --data '{"text":"Test alert"}' \
  https://hooks.slack.com/services/YOUR/WEBHOOK/URL

Like this project

Completed work

Posted Nov 7, 2025

Developed an observability stack with monitoring, alerting, and incident management etc for DrDroid.

Likes

Views

Timeline

Nov 3, 2025 - Nov 5, 2025