Elasticsearch · OpenSearch · KibanaElasticsearch / OpenSearch, indexed, secured, sub-second.
In short: Elasticsearch is a distributed, document-oriented search and analytics engine built on Apache Lucene. It stores JSON documents in an inverted index for fast full-text search, log analytics, and observability at scale. Elasticsearch ships under the Elastic License 2.0 / SSPL (with AGPLv3 re-added in 2024), while OpenSearch is the Apache 2.0-licensed fork the community maintains after Elastic's 2021 licence change.
Expert search and analytics solutions with Elasticsearch and OpenSearch. From log analytics pipelines to security hardening and performance optimization.
JUSDB_ELASTICSEARCH_PRODElasticsearch 8 · 3-node cluster
Lucene index · shards + replicas
0.00k
8ms
40%
0.0k/s
Search Throughput
0.00k QPS[OK] cluster: health GREEN, 24 shards allocated
[INF] shard: rebalance complete, even distribution
[OK] merge: segments 18 → 6 on logs-000042
[INF] ilm: rollover hot → warm on metrics-*
Representative cluster view · illustrative metrics
0+
Clusters Managed
0.99%
Uptime SLA
0k+
Searches / sec Served
0TB+
Index Size Managed
What we do
Search & analytics engineering
Specialized in both Elasticsearch and OpenSearch deployments for enterprise search and analytics.
Index & Shard Strategy
Optimize shard sizing, replica counts, and rollover policies (ILM/ISM) to prevent mappings explosion and split-brain.
Security & Role-Based Access
Implement fine-grained Document/Field level security plugins, RBAC, SAML integrations, and TLS encryption.
JVM & Garbage Collection Tuning
Prevent OutOfMemory (OOM) errors and long GC pauses by optimizing heap sizes and circuit breakers.
Query Profiling & Relevance
Improve search speed using query caching, avoiding costly wildcard/regex patterns, and tuning BM25 relevance.
Cross-Cluster Replication (CCR)
Design multi-region active-active architectures and snapshot-based disaster recovery strategies.
Log Analytics Hot/Warm/Cold
Implement multi-tier data architectures to dramatically reduce expensive ingest nodes and storage costs.
Search performance
Search & analytics expertise
Specialized in both Elasticsearch and OpenSearch deployments for enterprise search and analytics.
Search Performance
After tuning12×
Median query speedup
55%
Cluster cost reduction
Real cases
Queries we've transformed
5,100ms
210ms
Terms agg over high-cardinality field, no doc_values
The fix
Updated mapping with doc_values + keyword sub-field
OOM
Stable
Dynamic fields exploded mapping to 12k fields
The fix
Disabled dynamic mapping; defined explicit mapping
Uneven
Balanced
1 node held 70% of primaries — CPU pinned
The fix
Shard routing + allocation awareness, rebalanced
0.00%
Cluster Uptime
<0s
Reallocation RTO
0
Active Shards
High availability
Always on. Cluster-engineered.
Dedicated master-eligible nodes, replica shards across availability zones, and cross-cluster replication — tested with failover drills. Real 99.99% search availability, not a theoretical SLA.
Incident response
A red-cluster P1, handled in under 15 minutes.
When unassigned shards turn the cluster red or a GC pause stalls ingest, a named search engineer responds — not a ticket queue. Shard reallocation and heap fixes applied online, with a blameless postmortem after.
Query latency p99 > 5s — search degrading
Named search engineer in under 15 min, not a ticket queue
Unbounded terms aggregation, no doc_values on field
Updated mapping + doc_values, reindexed online
Aggregation p99 5.1s → 210ms — total 14 min
Pre-Migration Assessment
SQL full-text / Solr → Elasticsearch 8
Estimated cutover window: < 15 minutes
Migration
Move to OpenSearch without the downtime
Elasticsearch → OpenSearch, or self-managed → Elastic Cloud. We pre-validate mappings and plugins, reindex or snapshot/restore, replicate live, and cut over with zero search downtime.
Technology stack
Technologies We Work With
Complete search and analytics ecosystem support
FAQ
Elasticsearch & OpenSearch questions, answered
What Elasticsearch services do you provide?
We provide cluster architecture design, index lifecycle management, performance tuning, shard optimization, security configuration, log pipeline setup (Logstash, Beats, Fluentd), and migration services for Elasticsearch and OpenSearch.
How do you optimize Elasticsearch cluster performance?
We optimize through proper shard sizing, index lifecycle management, JVM heap tuning, bulk indexing optimization, search query caching, and hardware configuration. We typically achieve 2-10x performance improvements.
Do you support both self-hosted and Elastic Cloud?
Yes, we support self-hosted Elasticsearch, Elastic Cloud, AWS OpenSearch Service, and hybrid deployments. We help you choose the right deployment model based on your requirements and budget.
Get started
Ready to Power Your Search & Analytics?
Whether you need log analytics, full-text search, or real-time monitoring dashboards, our search experts will help you build scalable and secure solutions.
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