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Duration 21 hours
Course Outline
Fundamentals of OpenSearch Scaling
- Overview of OpenSearch architecture and core components
- Understanding scaling approaches: vertical vs. horizontal
Cluster Architecture and Design Strategies
- Designing large-scale, multi-node clusters
- Shard allocation, replication, and fault tolerance mechanisms
- Cross-cluster search and replication strategies
Scaling Indexing and Data Management
- Building efficient data ingestion pipelines
- Managing hot, warm, and cold storage tiers
- Index lifecycle management and rollover policies
Performance Optimization and Benchmarking
- Measuring and enhancing query latency and throughput
- Configuring heap size, thread pools, and circuit breakers
- Utilizing Rally and Performance Analyzer for benchmarking
Monitoring, Observability, and Alerting
- Tracking metrics via OpenSearch Dashboards
- Integrating with Prometheus, Grafana, and CloudWatch
- Configuring automated alerts for critical performance thresholds
Security and Access Control at Scale
- Implementing granular role-based access control
- Managing certificates and securing communication channels
- Best practices for auditing and compliance
Cloud Scaling via AWS OpenSearch Service
- Automated cluster scaling using AWS
- Integrating IAM, VPC, and CloudFormation
- Federating hybrid on-premises and AWS OpenSearch environments
Disaster Recovery, Backup, and Maintenance
- Snapshot and restoration strategies
- Managing node failures and cluster instability
- Automated cluster maintenance and upgrade processes
Conclusion and Future Directions
Requirements
- Knowledge of distributed database principles.
- Practical experience with Linux or cloud infrastructure administration.
- Proficiency in REST APIs and JSON data exchange.
Intended Audience
- DevOps and site reliability engineers.
- Data engineers and backend developers.
- Cloud architects responsible for large-scale search infrastructures.
Testimonials (1)
the trainer was very good and made the training perfect for my needs
