ELK Stack — Portfolio Projects

Build these projects to demonstrate real skills to employers. Each project is designed to be interview-worthy — something you can walk through in detail.

Project 1: Production-Grade ELK Stack Setup

Level: Beginner | Time: 1-2 days

Set up a complete, production-ready ELK Stack environment from scratch with proper configuration, security hardening, and monitoring.

Steps

1.Plan your ELK Stack architecture and document requirements

2.Install and configure ELK Stack following official best practices

3.Apply security hardening (restrict access, disable defaults)

4.Set up basic monitoring and alerting

5.Write a README documenting the setup

6.Add to GitHub with .gitignore and proper structure

Skills Demonstrated

•ELK Stack installation and configuration

•Security hardening

•Documentation

GitHub Repo Name

elk-stack-production-setup

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Project 2: End-to-End Log Pipeline with Grok Parsing and ILM

Level: Intermediate | Time: 2-3 days

Ship real application + Nginx logs through Filebeat → Logstash → Elasticsearch, with proper grok parsing, a dead-letter queue for failed matches, and an ILM policy that actually rotates and expires data.

Steps

1.Run a small app that produces both structured (JSON) and unstructured (Nginx access log) output

2.Configure Filebeat to ship both log types with distinguishing fields/tags

3.Write a Logstash pipeline: grok-parse the Nginx logs, json filter the structured logs, geoip enrich by client IP

4.Route grok parse failures to a logs-parse-failures-* index instead of silently dropping fields

5.Define an ILM policy (hot → warm → delete) and prove it actually rolls indices over on a size/age trigger, not just on paper

6.Build a Kibana dashboard with an error-rate-over-time panel and a top-error-messages table

Skills Demonstrated

•Logstash grok parsing and pipeline design

•ILM policy configuration and verification

•Kibana dashboard building

GitHub Repo Name

elk-log-pipeline-ilm

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Project 3: High-Volume ELK on Kubernetes with Kafka Buffering

Level: Advanced | Time: 4-5 days

Deploy Filebeat as a DaemonSet across a Kubernetes cluster, buffer through Kafka to absorb ingestion spikes, and run a multi-node Elasticsearch cluster with hot/warm tiering — the architecture actually used at real log volume, not the single-node dev setup.

Steps

1.Deploy Filebeat as a DaemonSet with Kubernetes autodiscovery so it picks up every pod's logs automatically

2.Stand up Kafka as a durable buffer between Filebeat and Logstash so a slow/down Elasticsearch doesn't cause log loss

3.Run multiple Logstash consumers reading from Kafka in parallel; tune pipeline.workers and batch size

4.Deploy a multi-node Elasticsearch cluster with dedicated master nodes and hot/warm data node roles

5.Load-test with a realistic log volume and watch JVM heap, indexing rate, and disk watermarks under load

6.Document what breaks first as volume increases, and how the architecture absorbs it

Skills Demonstrated

•Kubernetes-native log collection at scale

•Kafka as a durable ingestion buffer

•Elasticsearch cluster topology and capacity planning

GitHub Repo Name

elk-kubernetes-kafka-scale

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Tips for Great Projects

Make it real. Solve an actual problem, even a small one. "Built a Kubernetes cluster to deploy my personal blog" is more impressive than a tutorial clone.

Document everything. A repo with a great README beats one with better code but no explanation. Include: what it does, why you built it, how to run it, what you learned.

Show your thinking. In interviews, you'll be asked: "Why did you choose X over Y?" Have a reason. Architecture decisions matter.

Iterate publicly. Make commits regularly. Employers look at commit history. 10 commits over a week shows real work; 1 commit with everything shows you copied it.

Portfolio Checklist

•[ ] 3+ projects on GitHub with clear READMEs

•[ ] At least 1 project with a working ILM policy you can prove rotates/deletes data

•[ ] At least 1 project that solves a real problem

•[ ] Each project has an architecture diagram

•[ ] Projects are pinned on your GitHub profile

ELK Stack — Projects

ELK Stack — Portfolio Projects

Project 1: Production-Grade ELK Stack Setup

Steps

Skills Demonstrated

GitHub Repo Name

Project 2: End-to-End Log Pipeline with Grok Parsing and ILM

Steps

Skills Demonstrated

GitHub Repo Name

Project 3: High-Volume ELK on Kubernetes with Kafka Buffering

Steps

Skills Demonstrated

GitHub Repo Name

Tips for Great Projects

Portfolio Checklist