PipelineIQ
An AI-powered CI/CD failure-analysis platform that ingests pipeline logs, classifies failures, estimates severity and recommends resolutions asynchronously through Apache Kafka.
- Java 21
- Spring Boot
- Spring Security
- Apache Kafka
- PostgreSQL
- Redis
- Docker
- GitHub Actions
- Swagger/OpenAPI
- OpenAI API
- Prometheus
- Grafana
CI/CD failures are noisy and slow to investigate. Engineers spend time reading raw logs to find root causes that an automated system can surface more quickly.
Pipeline log events stream through Kafka into an analysis service. AI-assisted log analysis identifies a likely root cause, classifies the failure, estimates severity and proposes a resolution.
Log analysis must not become a bottleneck or slow down the pipeline it observes.
Kafka decouples ingestion from analysis. Producers publish log events and the analysis service consumes them asynchronously, allowing the platform to process work without blocking builds.
Asynchronous communication
Log events are published to Kafka topics and consumed asynchronously, decoupling ingestion from analysis.
- 01Asynchronous Kafka messaging to decouple log ingestion from analysis.
- 02AI log analysis for root cause, failure classification, severity and resolutions.
- 03JWT authentication and RBAC to secure the API surface.
- 04Prometheus + Grafana for operational visibility (metrics & dashboards).
- 05Containerized services with Docker and automated GitHub Actions builds.
Automated failure triage that turns raw build logs into a likely root cause, severity classification and recommended resolution.
Role — Sole developer — event-driven architecture, AI integration and platform development.
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