OpenSearch Architecture & Query
- OpenSearch vs Elasticsearch: what changed, what is compatible, where they diverge
- OpenSearch Service (managed): domain configuration, instance types, UltraWarm, Cold storage
- Index management: ISM (Index State Management) — the OpenSearch equivalent of ILM
- Query DSL: compatible with Elasticsearch — differences and additions
- OpenSearch Dashboards: Kibana fork — discover, visualize, dashboards
- Security plugin: fine-grained access control, encryption in transit and at rest
- k-NN search: vector similarity search for ML embeddings
- Anomaly detection plugin: real-time anomaly detection on time-series data
- Alerting plugin: monitor definitions, triggers, destinations
- Observability: trace analytics, log analytics, piped processing language (PPL)
Migration, Ingestion & Production
- Migrating from Elasticsearch to OpenSearch: API compatibility, breaking changes checklist
- Data ingestion: Logstash OpenSearch output plugin, Fluent Bit, Firehose
- OpenSearch Ingestion (managed Logstash): pipeline configuration
- Integration with AWS services: CloudWatch Logs, S3, Lambda, Kinesis
- OpenSearch cross-cluster replication
- Snapshot management: manual and automated snapshots to S3
- Sizing and performance tuning for OpenSearch Service
- Cost optimization: UltraWarm and Cold storage for long-term log retention
Teams who can operate OpenSearch confidently — whether migrating from Elasticsearch or building new on AWS — understanding the plugin ecosystem and AWS-native integration points.
- Configure and operate OpenSearch Service domains with correct sizing and storage tiers
- Use ISM policies for cost-effective index lifecycle management
- Set up fine-grained access control with the security plugin
- Ingest data from AWS services and apply anomaly detection and alerting
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Particularly relevant for teams running on AWS who want the Elasticsearch query model with tighter AWS service integration.
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