Managed OpenSearch

Assistance-operated OpenSearch for search, log analytics, dashboards, and indexed operational data

Managed OpenSearch is the logs, search, and indexed-data companion to Managed Prometheus in the docs-level observability set. Use OpenSearch for search, log indexing, dashboards over operational data, and investigation workflows; use Prometheus for metrics, alerting, and SLO evidence. Assistance operates the OpenSearch platform inside an agreed consulting or services boundary 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; 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

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.