Come along and meet people who have implemented and tuned Druid in situations small and large – very very large! Panelists shared some of their key tips and tricks, covering a range of topics from best practices in alerting and auto-scaling to strategies for handling ingestion and query optimization. This panel provided insights into managing Druid clusters efficiently, from Kubernetes and infrastructure management to data modeling, to ensure stable, high-performance clusters at scale.
Panelists:
– Cinto Sunny, Data Platform Engineer, Apple
– George Wu, Senior Software Engineer, Imply
– Ben Hopp, Lead Solutions Architect, Imply
[Timestamp] Table of Contents:
[00:00] Introductions
[1:00] Best Practices for Monitoring and Alerting
[3:00] Infrastructure as Code and Containerization
[5:00] Key Metrics to Monitor
[7:00] Common Mistakes in Cluster Management
[11:00] Scaling Strategies
[13:00] Metadata Backup and Restore
[15:00] Evaluating New Druid Versions
[17:00] Resource Utilization in Production
[19:00] Rolling Updates vs. Blue-Green Deployments
[21:00] Graceful Node Recycling
[23:00] Filling Feature Gaps in Druid Operators
[24:00] Educating Users on Druid’s Use Cases
[26:00] NVMe vs. Network Block Storage
[27:00] Starting Points for Performance Tuning
[29:00] Disaster Recovery and Failed Ingestion
[30:00] Mitigating Expensive Queries
[33:00] Segment-Related Troubleshooting
[34:00] Query Context for Custom Resource Settings
[36:00] Managing Segment Creation During Ingestion
[38:00] Load Balancing for Ingestion Tasks
[39:00] Closing Remarks
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