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Duration 21 hours
Course Outline
Introduction to OpenSearch Scaling Concepts
- Review of OpenSearch architecture and core components
- Understanding scaling dimensions: vertical versus horizontal
Cluster Architecture and Design Patterns
- Designing large-scale multi-node clusters
- Shard allocation, replicas, and fault tolerance mechanisms
- Cross-cluster search and replication strategies
Indexing and Data Management at Scale
- Building efficient data ingestion pipelines
- Managing hot-warm-cold storage tiers
- Index lifecycle management and rollover policies
Performance Optimization and Benchmarking
- Measuring and improving query latency and throughput
- Configuring heap sizing, thread pools, and circuit breakers
- Utilizing Rally and Performance Analyzer for benchmarking
Monitoring, Observability, and Alerting
- Monitoring key metrics using OpenSearch Dashboards
- Integrating with Prometheus, Grafana, and CloudWatch
- Building automated alerts for critical threshold breaches
Security and Access Control at Scale
- Implementing fine-grained role-based access control
- Managing certificates and securing communication channels
- Auditing and compliance best practices
Scaling in the Cloud with AWS OpenSearch Service
- Automating cluster scaling with AWS
- Integrating IAM, VPC, and CloudFormation
- Hybrid on-premises and AWS OpenSearch federation
Disaster Recovery, Backup, and Maintenance
- Developing snapshot and restore strategies
- Handling node failures and cluster instability
- Automating cluster maintenance and upgrades
Summary and Next Steps
Requirements
- A solid grasp of distributed database concepts
- Experience in Linux or cloud infrastructure administration
- Familiarity with REST APIs and JSON data exchange
Target Audience
- DevOps and Site Reliability Engineers
- Data Engineers and Backend Developers
- Cloud Architects overseeing large-scale search infrastructures
Testimonials (1)
the trainer was very good and made the training perfect for my needs