Building an AIOps Pipeline with Open Source Tools Training Course

Structuring a Transparent AIOps Framework

• Introduction to essential elements within open AIOps workflows
• Data trajectory from intake through to notification
• Evaluating tools and defining integration strategies

Data Acquisition and Consolidation

• Importing temporal data via Prometheus
• Logging data capture using Logstash and Beats
• Standardizing inputs for multi-source analysis

Creating Monitoring Dashboards

• Displaying metrics through Grafana
• Constructing Kibana interfaces for log examination
• Utilizing Elasticsearch searches to derive operational value

Deviation Identification and Outage Forecasting

• Transferring monitoring data into Python workflows
• Developing ML models for identifying outliers and predicting trends
• Implementing models for real-time inference within the monitoring stack

Notifications and Automation with Free Tools

• Defining Prometheus alert criteria and Alertmanager routing
• Initiating scripts or API processes for automated reactions
• Employing open-source orchestration utilities (e.g., Ansible, Rundeck)

Integration and Expansion Considerations

• Managing high-throughput intake and extended data retention
• Security and permission management in free software stacks
• Scaling individual layers independently: intake, processing, notification

Practical Use Cases and Extensions

• Examples: performance refinement, outage avoidance, and expenditure control
• Expanding workflows with tracing utilities or service mapping
• Recommended practices for sustaining AIOps in live production

Recap and Future Directions