Amazon OpenSearch Service is AWS's managed service for running OpenSearch clusters. It is used for full-text search, log analytics, observability, security analytics, and real-time dashboards without operating all cluster infrastructure manually.
Who is Amazon OpenSearch for?
Amazon OpenSearch is suitable for teams already using AWS that need scalable search and analytics for application logs, website search, event data, or monitoring pipelines. It is especially relevant for DevOps, data engineering, security, and backend teams.
Key features
- Managed OpenSearch clusters with AWS infrastructure.
- Full-text search, filtering, aggregations, and dashboards.
- Integration with CloudWatch, Kinesis, Lambda, IAM, and other AWS services.
- Security features such as encryption, access policies, and fine-grained access control.
- Scalable storage and compute options for changing workloads.
Pros and cons
Pros
- Fits naturally into AWS-based architectures.
- Reduces operational work compared with self-managed clusters.
- Good for log analytics, search, and observability use cases.
- Supports familiar OpenSearch and Elasticsearch-style workflows.
Cons
- Costs can rise quickly with large indexes, high ingest, or overprovisioned clusters.
- Tuning shards, mappings, and queries still requires expertise.
- AWS dependency may be a drawback for multi-cloud teams.
Pricing and costs
Amazon OpenSearch is usage-based. Costs usually include instance hours, storage, data transfer, optional features, and backups. Teams should estimate ingest volume, retention, query load, and dashboard usage before choosing a cluster size.
FAQ
Is Amazon OpenSearch the same as Elasticsearch?
No. OpenSearch is a fork of Elasticsearch, but many concepts and APIs are similar.
Is it only for logs?
No. Logs are common, but the service is also used for application search, security analytics, and dashboards.
Does AWS manage everything?
AWS manages infrastructure, but teams still need to design indexes, retention, security, and query patterns.