Monitoring and Operations
Description
Comprehensive monitoring, logging, and operational practices for data engineering pipelines using CloudWatch, CloudTrail, and other AWS monitoring services.
Learning Objectives
Learners will master operational monitoring of data pipelines, implement comprehensive logging strategies, create automated alerting systems, troubleshoot data engineering issues, and establish operational excellence for production data systems.
Topics (7)
CloudWatch metrics, dashboards, alarms, and monitoring strategies for data processing workloads and AWS services.
Log collection, CloudWatch Logs Insights, log aggregation, and log-based alerting for data engineering systems.
Pipeline monitoring, data quality checks, SLA monitoring, and automated health assessment for data workflows.
CloudWatch alarms, SNS notifications, automated response systems, and escalation procedures for data incidents.
Troubleshooting methodologies, root cause analysis, debugging techniques, and issue resolution for data systems.
Operational frameworks, automation strategies, documentation practices, and continuous improvement for data operations.
Performance analysis, bottleneck identification, resource optimization, and cost optimization for data processing systems.