Managed OpenSearch
Assistance-operated OpenSearch for search, log analytics, dashboards, and indexed operational data
Managed OpenSearch is for teams that need search, log indexing, or analytics over operational data without building a specialist search operations function. Assistance operates the OpenSearch platform while your team owns the application data, relevance requirements, and business dashboards.
Best-fit use cases#
| Use case | Why OpenSearch fits |
|---|---|
| Application and product search | Full-text search, filtering, facets, autocomplete, and relevance tuning workflows |
| Log analytics | Centralized searchable logs with retention and dashboards |
| Security and audit data | Indexed event data with access controls, retention, and investigation views |
| Operational analytics | Near real-time exploration of events, metrics-derived records, and activity streams |
| Migration from self-hosted Elasticsearch/OpenSearch | Improve operations, lifecycle policies, backups, and support coverage |
What Assistance operates#
| Area | Included managed service responsibility |
|---|---|
| Provisioning | Cluster topology, node roles, storage sizing, network placement, secure defaults, and endpoint details |
| Reliability | Cluster health, shard allocation, snapshots, restore process, failover expectations, and runbooks |
| Lifecycle | Index templates, rollover, retention, hot/warm/cold guidance, snapshot policies, and deletion controls |
| Maintenance | Version lifecycle guidance, patch planning, maintenance windows, upgrade execution, and rollback planning |
| Security | TLS, authentication, role-based access, tenant separation where appropriate, audit logging options, and credential rotation support |
| Observability | Dashboards and alerts for cluster health, storage, JVM pressure, shard count, indexing rate, query latency, and snapshot health |
| Support | Severity-based support for platform incidents and escalation for covered production clusters |
Search relevance and data semantics stay customer-owned
Assistance operates OpenSearch. Your team owns which data should be indexed, mapping semantics, relevance expectations, dashboard meaning, and application behavior. We advise on safe index and query patterns but do not own product search semantics unless scoped separately.
Ownership boundary#
| Responsibility | Assistance owns | Customer owns |
|---|---|---|
| Cluster runtime | Nodes, shards, upgrades, snapshots, monitoring, and platform incident triage | Applications and ingestion clients that write/read data |
| Index lifecycle | Templates, rollover, retention implementation, and operational guardrails | Data retention requirements, index purpose, mapping semantics |
| Search behavior | Query performance advice and capacity guidance | Relevance tuning, ranking rules, product search acceptance criteria |
| Logs and dashboards | Platform availability and shared dashboard infrastructure | Which logs matter, field meaning, operational/business interpretation |
| Access | Roles, tenants, service accounts, rotation procedure | User approval, identity ownership, internal access reviews |
Deployment options#
| Option | When to use it |
|---|---|
| Assistance physical servers | Development search, staging logs, internal analytics, and predictable log/search workloads |
| Customer cloud account | Production search/log clusters close to applications or inside existing compliance/network boundaries |
| Cloud-managed service operations | Assistance operates Amazon OpenSearch Service or equivalent where provider-managed data plane is preferred |
| Hybrid | Development and test clusters on Assistance infrastructure with production in cloud |
Reliability and support model#
| Topic | Managed OpenSearch approach |
|---|---|
| Availability | Target availability scoped by cluster topology, node roles, provider dependencies, and support plan |
| Snapshots | Snapshot frequency and retention defined by data criticality and recovery needs |
| Retention | Lifecycle policies prevent unbounded growth and uncontrolled shard counts |
| Performance | Query latency, indexing pressure, JVM, storage, and shard allocation are monitored for covered clusters |
| Response | P1 response targets scoped in support agreement; 24/7 critical response available for covered production services |
Onboarding#
1. Search and data assessment#
We review use case, data sources, retention, query patterns, dashboards, ingest rates, compliance requirements, and current cluster health if migrating.
2. Managed cluster design#
Assistance proposes topology, node roles, shard strategy, templates, lifecycle policies, snapshot approach, access model, monitoring, and support tier.
3. Ingestion and migration#
We configure endpoints and access, support migration or reindexing strategy, and connect ingestion tools such as Fluent Bit, Logstash, Data Prepper, Beats, or application clients where scoped.
4. Operate and review#
After go-live, we monitor cluster health, growth, shard pressure, indexing errors, query latency, and snapshots. Retention and capacity are reviewed before data growth affects availability.
Supported capabilities#
- OpenSearch clusters for search and log analytics
- OpenSearch Dashboards access and dashboard operations
- Index templates, rollover, retention, and snapshot policies
- Ingest pipelines and common log shipping patterns
- Role-based access control and tenant separation where appropriate
- Migration planning from Elasticsearch or OpenSearch deployments
Not included by default#
- Designing product search relevance from scratch
- Owning application ingestion code or data correctness
- Unlimited retention, storage, shard count, or dashboards outside the plan
- Guaranteeing performance for unreviewed high-cardinality mappings or expensive queries
- SIEM process ownership unless a security operations scope is added
Related products#
- Managed Kafka — Stream events into OpenSearch
- Managed Prometheus — Metrics and alerting alongside logs/search
- Managed MongoDB — Document data source often paired with OpenSearch for search
- SRE as a Service — Incident and observability operating model
Getting started#
Request an OpenSearch assessment. We will inspect data sources, retention, query behavior, cluster health, access needs, and support requirements before proposing a managed design.
Request OpenSearch assessment →Frequently asked questions#
Can OpenSearch handle both application search and logs? Yes, but they should be separated by index lifecycle, retention, access, and sometimes clusters. We design the boundary based on risk and workload shape.
Do you migrate from Elasticsearch? Yes, subject to version compatibility, plugin usage, data volume, and downtime tolerance. Some migrations are reindex-based rather than in-place upgrades.
Who owns retention rules? Your organization owns legal and business retention requirements. Assistance implements lifecycle policies and monitors storage/shard health.
Can you operate Amazon OpenSearch Service? Yes. We can operate provider-managed OpenSearch services in your account when that deployment model fits better than self-managed clusters.
What SLA applies? Availability and response targets are scoped by topology, provider dependency, support tier, and what Assistance controls operationally.