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 Duration 21 hours

Course Outline

Introduction to OpenSearch Scaling Concepts

  • Overview of OpenSearch architecture and core components.
  • Exploring scaling dimensions: vertical versus horizontal approaches.

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.

Indexing and Data Management at Scale

  • 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 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.
  • Setting up automated alerts for critical performance thresholds.

Security and Access Control at Scale

  • Implementing fine-grained role-based access control.
  • Managing certificates and encrypted communication channels.
  • Best practices for auditing and compliance.

Scaling in the Cloud with AWS OpenSearch Service

  • Automating cluster scaling within 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.
  • Automating cluster maintenance and upgrades.

Summary and Next Steps

Requirements

  • A solid understanding of distributed database concepts.
  • Practical experience with Linux or cloud infrastructure administration.
  • Familiarity with REST APIs and JSON data exchange standards.

Target Audience

  • DevOps and Site Reliability Engineers.
  • Data Engineers and backend developers.
  • Cloud architects overseeing large-scale search infrastructures.

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