Building an AIOps Pipeline with Open Source Tools Training Course

Designing an Open-Source AIOps Architecture

• Overview of essential components in open AIOps pipelines
• Data lifecycle from ingestion to alert generation
• Strategies for tool comparison and integration

Data Collection and Aggregation

• Processing time-series data using Prometheus
• Capturing logs via Logstash and Beats
• Standardizing data for cross-source correlation

Creating Observability Dashboards

• Visualizing key metrics with Grafana
• Developing Kibana dashboards for log analysis
• Leveraging Elasticsearch queries for operational insights

Anomaly Detection and Incident Forecasting

• Transferring observability data into Python workflows
• Training machine learning models for outlier detection and prediction
• Integrating models for real-time inference within the pipeline

Alerting and Automation with Open-Source Tools

• Configuring Prometheus alert rules and Alertmanager routing
• Automating responses via scripts or API integrations
• Utilizing open-source orchestration platforms (e.g., Ansible, Rundeck)

Integration and Scalability Strategies

• Managing high-volume ingestion and long-term data retention
• Implementing security and access controls in open-source stacks
• Scaling individual layers: ingestion, processing, and alerting

Practical Applications and Extensions

• Case studies on performance optimization, downtime avoidance, and cost reduction
• Expanding pipelines with tracing tools or service mapping
• Best practices for sustaining AIOps in production environments

Summary and Future Directions