Grafana on DevOps Engineer & CloudAdmin

CI/CD & Production Infrastructure for a Web Application

Mon, 01 Jan 0001 00:00:00 +0000

Production Infrastructure & CI/CD for a Company Website

Client

A manufacturer of branded research products that needed a website to present its product catalog to customers

Challenge

The developers had written the code of a conventional web application (NestJS backend + Next.js frontend), but infrastructure was completely missing: manual deployments, no CI/CD, no server setup, no monitoring, no backups and no separation between test and production environments. The goal was to build a complete DevOps stack from scratch: GitLab CI/CD, a self-hosted server, two isolated environments, HTTPS, monitoring, alerting and automated backups.

Geo-Distributed Blockchain Node Cluster in Kubernetes

Mon, 01 Jan 0001 00:00:00 +0000

Geo-Distributed Blockchain Node Cluster in Kubernetes

Client

Cryptocurrency platform (Web3 / DeFi)

Challenge

The client needed fault-tolerant infrastructure to run ETH and BSC full nodes across four regions (EU, US, AP, LatAm) with minimal latency for end users, DDoS and RPC spam protection, secure HSM-based transaction signing, and centralized observability. Cold node sync takes 2–3 weeks — a fast-bootstrap solution was required.

Solution

1. Infrastructure & IaC (Terraform + EKS)

Terraform modules: VPC, subnets, security groups for 4 regions (Frankfurt, Virginia, Singapore, São Paulo)
Managed Kubernetes (EKS 1.29+) per region with dedicated node pools: full nodes, archive nodes, signing service
NVMe StorageClass (gp3) via CSI driver for high-performance chaindata storage
Helm charts for geth / bsc-node with per-region custom values

2. GitOps: Flux CD Multi-Cluster

Flux CD v2 with Kustomization per region — single source of truth for all clusters
Secrets management: HashiCorp Vault + External Secrets Operator (ESO)
All infrastructure changes applied via git push — no direct cluster access required

3. Load Balancing & Anti-Spam

HAProxy 2.8: sticky sessions, health checks via eth_syncing — traffic routed only to fully synced nodes
Nginx Ingress: rate limiting, IP reputation filtering (Lua-based, fail2ban-style)
Cloudflare Workers: geo-routing + L7 DDoS protection
Custom Go sidecar: health endpoint returns ready only when node is fully synced

4. HSM Integration for Transaction Signing

AWS CloudHSM (prod) / YubiHSM2 (staging) for private key storage
Go microservice with PKCS#11 abstraction — swap HSM vendor without rewriting code
Isolated K8s namespace + NetworkPolicy: no egress except to HSM endpoint
gRPC API for backend: sign tx, get pubkey
Full audit log of all signing operations → Loki

5. Monitoring & Alerting

Custom Prometheus exporter (Go): eth_blockNumber, eth_syncing, peer count per node
Grafana dashboards: sync lag, block height per region, RPC latency, SLO 99.9%
Alertmanager → PagerDuty: alerts on block lag > N blocks, node down, peer count below threshold
Loki + Promtail: structured logs from all nodes with region/pod correlation

6. Operations & Disaster Recovery

Snapshot bootstrap: chaindata from S3 via rclone — node ready in hours instead of weeks
DR playbook: step-by-step runbooks for regional recovery
Chaos Engineering (Chaos Mesh): node kill, network partition, pod failure tests
Architecture Decision Records (ADR) for all key design choices

Technologies

Kubernetes

Terraform

Helm

Flux CD

Prometheus

Grafana

Results

✅ Geo-routing: latency reduced by routing users to the nearest region
✅ Fast bootstrap: node ready in hours via S3 snapshot instead of 2–3 weeks of sync
✅ Anti-spam: rate limiting + IP reputation — public RPC handles bot load without degradation
✅ HSM: private keys never leave the hardware module
✅ GitOps: every infrastructure change goes through git with a full audit trail
✅ SLO 99.9%: tracked in Grafana, PagerDuty alerts on any degradation

Prometheus + Grafana Monitoring Stack

Mon, 01 Jan 0001 00:00:00 +0000

Observability Stack for Microservices Architecture

Client

Early-stage startup

Challenge

After migrating to a microservices architecture (15+ services), the team had no centralized monitoring in place. Issues were only discovered through user complaints — typically 30+ minutes after they occurred. A full observability stack was needed to detect and diagnose problems proactively.

Solution

1. Monitoring Architecture

Prometheus for metrics collection
Grafana for visualization
Loki for centralized log aggregation
Jaeger for distributed tracing
Alertmanager for notifications

2. Metrics Collection

Automatic service discovery in Kubernetes
Application-level custom metrics
System metrics via node-exporter
Database metrics via postgres-exporter and redis-exporter

3. Grafana Dashboards

Per-service dashboards for each microservice
Unified infrastructure overview dashboard
SLA/SLO tracking metrics
Business metrics (RPS, conversion rate)

4. Centralized Logging (Loki)

Log aggregation across all services
Full-text log search via Grafana
Log-to-metric correlation

5. Distributed Tracing (Jaeger)

HTTP request tracing across services
Call chain visualization
Bottleneck identification
Per-service latency analysis

6. Alerting

Alerts delivered to Slack / PagerDuty / custom webhooks
Critical issue escalation
On-call rotation support
Automatic incident creation

Technologies

Prometheus

Grafana

Kubernetes

Docker

Helm

Linux

Results

✅ MTTD: reduced from 30 minutes to under 1 minute
✅ MTTR: recovery time reduced by 60%
✅ Alerts: proactive notifications before users are impacted
✅ Visibility: full observability across all services
✅ Capacity planning: data-driven resource forecasting