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Kubernetes-Observability 📈

I designed and implemented a secure Kubernetes platform automated through a Jenkins CI/CD server with security scans embedded into the pipeline. Integrating a shift-left security and runtime validation

CI/CD Orchestration (Jenkins) ⚙️

  • Automated build, scan, and deployment pipeline

  • Enforced security gates before workload deployment

  • Integrated container and cluster validation into delivery lifecycle

Container Security (Shift-Left) 🔐

  • Trivy (Image vulnerability HIGH/Critical)

  • SNYK (Dependency and container security analysis, prevents images with vulnerabilities from reaching the cluster)

Dynamic & Runtime security ⚡️

  • OWASP ZAP (DAST scanning for exposed endpoints)

  • Validates application layer security risk

Kubernetes Security and Compliance 📋

  • Kubescape (Cluster hardening and compliance checks)

Benchmarked against:

MITRE ATT&CK framework NSA Kubernetes Hardening Guide OWASP top 10

Observability Stack

Prometheus and Grafana the primary observability and metrics tools used within the a Kubernetes cluster. These work well together in production but carry out different task. Grafana give you direct visualization of metrics while prometheus acts as a metrics engine database.

Grafana 📊

Grafana is metrics observability platform that can be integrated with many other tools.

  • prometheus
  • loki
  • CloudWatch
  • ElastiSearch

http://localhost:3000

Prometheus 🧰

Prometheus is a metrics engine database that scrapes metrics at scheduled intervals and sends metrics to Time Series Database (TSDB) and uses PromQL as a query language to send queries to Grafana for visualization

http://localhost:9090

About

This Systems uses a Jenkins CI/CD pipeline with automated security scanning for Kubernetes workloads using Trivy, SNYK, OWASP Zap and kubescape. Grafana dashboards are used for metrics visualization and Prometheus scraping metrics every few seconds and sending the PromQL queries to Grafana

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