Kubernetes Hosted ELK SIEM

Kubernetes Hosted ELK SIEM – for Centralized, Scalable Security and Visibility

A Kubernetes-hosted ELK-based SIEM centralizes log collection, processing, detection, and investigation at scale while providing elastic storage, automated operations, and cloud-native resilience.

Client Background

A global Enterprise struggled with fragmented logs, slow threat detection, and spiraling storage costs as services multiplied across cloud and on‑prem environments. Security analysts spent hours stitching together investigations while operations wrestled with brittle ELK deployments that failed under peak ingest. The board demanded faster detection, consistent compliance, and predictable operating costs.

Business Challenges

High Volume Ingestion: Handling 10 TB/day of log data from multiple pods across environments.

Tiered Storage Management: Efficient management of hot, warm, and cold data tiers for cost and performance balance.

Scalability & Performance: Ensuring Elasticsearch can scale with 5 secondary replicas while maintaining performance.

Centralized Monitoring: Aggregating logs from all pods across namespaces and clusters into a single pane of glass.

Resource Optimization: Efficient compute, memory, and storage utilization across nodes to avoid overprovisioning or bottlenecks.

Centralized Monitoring: Aggregating logs from all pods across namespaces and clusters into a single pane of glass.

Solutions Delivered

A. Kubernetes Cluster on AWS

Deployed using EKS with autoscaling node groups.

Implemented a Hot-Warm-Cold Architecture with Index Lifecycle Management.

B. ELK Stack Deployment

Elasticsearch: Deployed Elastic Cloud on Kubernetes (ECK) using Helm chart.

Logstash: Parsing and enriching logs before indexing.

Kibana: Dashboards for real-time visualization, alerting, and monitoring.

C. Fluent Bit DaemonSet

Deployed on all nodes to collect pod logs.

Enriched logs with Kubernetes metadata and forwarded to Logstash.

D. Snapshot Management

Automated index snapshots to Amazon S3 using Elasticsearch snapshot lifecycle policies.

Cold data restored on-demand for compliance or audit requirements.

E. Index Lifecycle Management (ILM)

Hot tier: 1–7 days on high-performance SSDs for frequent access.

Warm tier: 7–30 days on cost-effective storage for medium access.

Cold tier: >30 days on S3 archived snapshots, searchable as needed.

Key Highlights

StatefulSets with dedicated master, data, ingest, and coordinator roles plus anti‑affinity for high availability.

Kubernetes autoscaling and Helm deployments enable elastic handling of bursty security telemetry and EPS spikes.

Hot‑warm‑cold node architecture and Index Lifecycle Management optimize query performance and storage costs.

mTLS, encryption at rest and in transit, Kubernetes RBAC, Elastic RBAC, and secret management for compliance and least privilege.

Prometheus and built‑in Elastic metrics monitor cluster health, JVM, ingest backpressure, and query latency.

Business Impact

Centralized monitoring of logs across all pods and clusters.

10 TB/day ingestion handled efficiently with high reliability.

Elastic scalability with optimized resource utilization.

Tiered storage reduced cost while maintaining performance.

Automated backups ensured compliance and DR readiness.

Real-time visualization & alerting improved operational awareness.

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