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Cloud & DevOps · Major Project
Centralised Logging with the ELK Stack
Logs from many services shipped, parsed and searched in one place
3-4 weeks build
Overview
Every service writes logs; this puts them somewhere you can ask questions of them. Filebeat ships logs from an Nginx proxy and a set of app containers, Logstash parses them into structured fields, Elasticsearch indexes them with a retention policy, and Kibana dashboards show errors, slow requests and traffic by endpoint. The whole stack runs locally in Docker on a laptop with 8 GB of RAM.
What makes it stand up
- 01Filebeat shipping from Nginx and several app containers
- 02Grok and JSON parsing that turns raw lines into queryable fields
- 03Index lifecycle policy that rolls over and deletes old logs
- 04Kibana dashboards for errors, latency and top endpoints
- 05Threshold alerts on error spikes through ElastAlert 2
Module breakdown
- 01
Shipping
Filebeat inputs, modules and back-pressure handling.
- 02
Parsing
Logstash pipelines with grok, date and GeoIP filters.
- 03
Storage
Index templates, mappings and lifecycle retention.
- 04
Dashboards
Kibana visualisations and saved searches for common incidents.
- 05
Alerting
Error-rate rules with email or Slack notifications.
After this, you will be able to
- Explain why centralised, structured logs beat SSH and grep
- Defend your field mappings and retention policy
- Demo tracing a failing request through the logs live
Technology stack
- Elasticsearch
- Logstash
- Kibana
- Filebeat
- Docker
- Level
- Major Project
- Domain
- Cloud & DevOps
- Build time
- 3-4 weeks
- Difficulty
You receive
- Complete, commented source code
- 60-90 page project report (IEEE format)
- Editable presentation deck
- Architecture, ER and UML diagrams
- Local setup and deployment guide
- Sample dataset or seed data
- Viva question bank with answers
- One 45-minute walkthrough call
- 30 days of doubt-clearing support