Elasticsearch & OpenSearch Consulting

Slow queries, bad mappings, shard sprawl, indexing bottlenecks, recovery storms, cluster instability, migration risk. Across Elasticsearch, Elastic Cloud, self-managed, and OpenSearch. We have fixed all of these, more than once.

Deep Search Cluster Diagnosis

Elasticsearch and OpenSearch reward query-shaped data, deliberate mappings, controlled shard counts, and operational discipline. When teams treat them like SQL databases or generic log buckets, the problems compound — quietly, until they don't.

OpenSearch still shares a lot of operational DNA with Elasticsearch 7.x, but migrations, plugin compatibility, security models, managed-service behavior, and the diverging long-term ecosystems all need deliberate planning. We have moved clients in both directions and the answer is never "just flip the switch."

Top Elasticsearch & OpenSearch Mistakes

  1. Treating Elasticsearch like a SQL database instead of designing query-shaped documents.
  2. Creating shards, aliases, and indexes like they're free. They aren't.
  3. Letting dynamic mappings, field counts, and templates grow with nobody reviewing them.
  4. Using aggregations, wildcard searches, and deep pagination without ever measuring fan-out.
  5. Buying time with more nodes before fixing schema, retention, and the shape of the workload.

Where We Usually Start

  1. Cluster topology, node roles, heap, CPU, storage, and recovery behavior.
  2. Shard count, shard size, index count, replica strategy, and allocation rules.
  3. Mappings, templates, datastreams, ILM, retention, and field cardinality.
  4. Slow logs, hot queries, aggregation pressure, indexing pressure, and task history.
  5. Upgrade, migration, rollback, and validation constraints.

What We Do

Cluster Architecture & Design

We design Elasticsearch and OpenSearch clusters around the actual workload — not a generic reference architecture. That means looking at:

  • Cluster sizing and node configuration
  • Shard allocation strategies that match query patterns
  • Index design and data modeling
  • Network topology and data center placement
  • Multi-cluster setups for disaster recovery
  • Cloud-native deployments (AWS, Azure, GCP)
  • Elastic Cloud, Amazon OpenSearch Service, and self-managed tradeoffs — honestly

High Availability & Reliability

Make the cluster survive things that will absolutely happen:

  • Master node configuration and quorum settings
  • Replica strategies for data redundancy
  • Cross-zone and cross-region replication
  • Disaster recovery planning that's actually been tested
  • Backup and restore strategies
  • Cluster health monitoring and alerting

Performance Optimization

Find the actual bottleneck. Fix it. Don't just throw nodes at it:

  • JVM heap sizing and GC tuning
  • Thread pool configuration
  • Index settings (refresh interval, translog, etc.)
  • Shard sizing and count
  • Query performance analysis and tuning
  • Resource allocation and capacity planning

Cluster Operations & Maintenance

The unglamorous work that keeps you off the pager:

  • Cluster upgrade and migration strategies
  • Index lifecycle management (ILM)
  • Rolling restarts and zero-downtime maintenance
  • Security hardening and access control
  • Monitoring, logging, and alerting setup
  • Performance troubleshooting and root-cause analysis

Version Migration & Upgrades

Major upgrades are where teams get surprised. We plan them so you don't:

  • Pre-upgrade assessment and planning
  • Breaking changes analysis and mitigation
  • Rolling upgrade procedures
  • Full cluster restart upgrade strategies
  • Post-upgrade validation
  • Rollback plans that actually work
  • Elastic to OpenSearch (or back) compatibility assessment

Elastic Cloud & Managed Services

Managed services are great until you hit their edges. We help you avoid the edges:

  • Elastic Cloud account setup and configuration
  • Deployment sizing and capacity planning
  • Multi-region and cross-cloud deployments
  • Cloud-native features and integrations
  • Cost optimization and right-sizing
  • Migration from self-managed to Elastic Cloud
  • Hybrid architectures (on-prem + cloud)

Docker & Kubernetes Deployments

Run Elasticsearch on Kubernetes without re-learning the worst lessons publicly:

  • Docker containerization and image optimization
  • Kubernetes StatefulSets and operators (ECK)
  • Helm chart development and customization
  • Persistent volume management and storage classes
  • Service discovery and networking
  • Resource limits and pod scheduling
  • Autoscaling strategies (HPA, VPA, cluster autoscaler)
  • Multi-zone and multi-cluster Kubernetes setups
  • Monitoring and logging inside containerized environments

Index Templates & Component Templates

Templates that work the same in six months as they do today:

  • Index template design and versioning
  • Component templates for reusable config
  • Template composition and inheritance
  • Dynamic template patterns and matching
  • Mapping templates for consistent field definitions
  • Settings templates for index configuration
  • Alias management and rollover
  • Template precedence and conflict resolution

Security & Access Control

Lock it down without making the cluster unusable:

  • Elasticsearch Security (X-Pack) configuration
  • User authentication (native, LDAP, AD, SAML, OIDC)
  • Role-based access control (RBAC) design
  • Index-level and document-level security
  • Field-level security and data masking
  • API key management and rotation
  • SSL/TLS certificate management
  • Network security and firewall configuration
  • Audit logging and compliance requirements
  • Multi-tenancy and data isolation strategies

Kibana Dashboards & Visualizations

Dashboards people actually open during incidents:

  • Kibana dashboard design and development
  • Custom visualizations (Lens, Vega, Timelion)
  • Data tables and pivot configurations
  • Time series and trend analysis
  • Geographic visualizations and maps
  • Dashboard sharing and embedding
  • Saved object management and versioning
  • Dashboard performance optimization
  • Custom Kibana plugins and extensions

Why Work With Us

  • 12+ years in production: We have designed and rescued Elasticsearch, Elastic Cloud, and OpenSearch clusters across plenty of industries and workload shapes.
  • Real clusters, not slides: Our recommendations come from clusters running millions of documents and thousands of queries per second — under real failure conditions.
  • We look at the whole system: Architecture, performance, security, and operations. Fixing one in isolation usually breaks another.
  • We right-size your spend: Performance and cost aren't opposing forces if you set the cluster up right.
  • Knowledge transfer is part of the job: When we're done, your team understands every decision and can keep running the cluster without us.

Ready to Diagnose Your Cluster?

Tell us what's slow, unstable, expensive, or hard to explain in your Elasticsearch or OpenSearch environment. We'll tell you where we'd look first.