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Duration 21 hours (3 days)
Course Outline
Foundations of OpenSearch Scaling
- Overview of OpenSearch architecture and core components
- Exploring scaling dimensions: vertical versus horizontal
Cluster Architecture and Design Patterns
- Architecting large-scale, multi-node clusters
- Managing shard allocation, replicas, and fault tolerance
- Strategies for cross-cluster search and replication
Large-Scale Indexing and Data Management
- Building efficient data ingestion pipelines
- Managing hot-warm-cold storage tiers
- Index lifecycle management and rollover policies
Performance Optimization and Benchmarking
- Measuring and enhancing query latency and throughput
- Configuring heap sizing, thread pools, and circuit breakers
- Utilizing Rally and Performance Analyzer for benchmarking
Monitoring, Observability, and Alerting
- Tracking metrics using OpenSearch Dashboards
- Integration with Prometheus, Grafana, and CloudWatch
- Creating automated alerts for critical performance thresholds
Security and Access Control at Scale
- Implementing granular role-based access control
- Managing certificates and encrypted communications
- Best practices for auditing and compliance
Cloud Scaling with AWS OpenSearch Service
- Automating cluster scaling with AWS
- Integrating IAM, VPC, and CloudFormation
- Federating hybrid on-premises and AWS OpenSearch environments
Disaster Recovery, Backup, and Maintenance
- Developing snapshot and restore strategies
- Mitigating node failures and cluster instability
- Automating cluster maintenance and upgrades
Summary and Future Directions
Requirements
- A solid grasp of distributed database concepts
- Practical experience in Linux or cloud infrastructure administration
- Proficiency 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
