Elasticsearch Consulting & Support for Enterprises

Our Elasticsearch consulting covers cluster architecture and sharding design, ILM policy design, mapping and analyzer strategy, security hardening, performance tuning, and migration planning. Every engagement is staffed by a named senior engineer with production Elasticsearch experience across self-managed and Elastic Cloud deployments.

Yes, we support Elastic Cloud and self-managed Elasticsearch clusters directly. If you're running OpenSearch — the Apache 2.0 fork — we cover that on a dedicated OpenSearch consulting track, since the two platforms have diverged in security plugin architecture and lifecycle management tooling. If you're evaluating a move between them, we help you make that call.

Yes — this is one of the most common incidents we see. It's usually caused by shard allocation rules, disk watermark flood-stage settings blocking replica assignment, or awareness attributes preventing rebalancing. We start with the shard allocation explain output to isolate the exact blocker rather than guessing.

Yes. We translate Solr schema definitions into Elasticsearch mappings, rebuild query logic from Solr query syntax into the Elasticsearch Query DSL, and validate relevance scoring parity before cutover so your search results don't quietly get worse in production.

We use an alias-based reindex strategy: build the new index under a new name with the corrected mapping, backfill data with the reindex API, validate against production traffic in parallel, then atomically swap the alias. Your application never points directly at a physical index, so the swap is invisible to consumers.

A structured review of shard allocation and replication, node role balance, ILM policy coverage, mapping and index template drift, and security configuration. We deliver a written report with findings ranked by production risk, not a generic scorecard. Most teams run this quarterly or after a major version upgrade.