- Ensure high-quality telemetry data collection with minimal noise
- Configure intelligent alerting using baselines and anomaly detection and Reduce alert fatigue through alert tuning and deduplication strategies
- Implement event correlation to group related incidents
- Use AIOps features to identify patterns and predict failures and Continuously improve signal-to-noise ratio in monitoring systems
- Investigate production incidents using logs, metrics, and traces
- Perform root cause analysis (RCA) and document findings
- Collaborate with application teams to resolve critical issues
- Improve MTTR (Mean Time to Resolution) through better observability and maintain incident response runbooks
- Work with containerized environments (Docker, Kubernetes)
- Ensure observability coverage for APIs
- Apply basic ML/statistical techniques for anomaly detection and Query and analyze telemetry data using SQL-like languages (e.g., NRQL)
- Identify trends and capacity issues using time-series analysis
- Provide insights and recommendations to improve system reliability
Maintain data retention and governance policies
