Enterprise OpenSearch Consulting & Support Services | Nextbrick

Achieve Unbreakable Search, Analytics, and Observability with Expert OpenSearch Solutions

We architect, deploy, secure, and optimize production-grade OpenSearch clusters that deliver sub-second search, petabyte-scale log analytics, and mission-critical observability—with zero vendor lock-in and predictable total cost of ownership.

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Why OpenSearch is the Modern Enterprise Standard for Search, Analytics & Observability

The fragmentation of the Elastic Stack created a critical decision point for enterprises: remain on a proprietary path with escalating costs and reduced control, or embrace a truly open, community-driven future. OpenSearch—the open-source fork of Elasticsearch and Kibana—has emerged as the definitive choice for organizations demanding transparency, scalability, and freedom from licensing uncertainty.

The Strategic Business Imperative Driving OpenSearch Adoption:

• Escape Vendor Lock-in & Cost Surprises: Enterprises report 40-60% annual cost increases on proprietary Elastic licensing after achieving scale. OpenSearch eliminates license fees and provides predictable, linear scaling economics.

• Consolidate Silos into a Unified Data Platform: Most organizations run separate clusters for application search, security analytics (SIEM), and infrastructure monitoring—triplicating costs and complexity. A well-architected OpenSearch deployment can unify these workloads.

• Meet Stringent Compliance & Data Sovereignty Requirements: Proprietary solutions often restrict where and how data can be processed. With OpenSearch, you maintain full control over data residency, encryption standards, and access governance—critical for GDPR, HIPAA, FedRAMP, and financial regulations.

• Future-Proof Your Data Stack: The vibrant, vendor-neutral OpenSearch community (including AWS) ensures rapid innovation in vector search for AI, advanced security features, and performance optimizations without roadmap restrictions.

  

The Nextbrick Difference: Enterprise-Grade Operations for Your Most Critical Data Workloads

We are more than consultants; we are OpenSearch reliability engineers. We ensure your cluster isn’t just running—it’s thriving under load, secured against threats, and evolving with your business. We deliver:

• Uncompromising Performance: Guarantee P99 search latencies under 100ms and ingest throughput of 100,000+ documents/second even during unpredictable traffic surges.

• Ironclad Security & Compliance: Implement end-to-end security with fine-grained role-based access control (RBAC), node-to-node encryption, audit logging, and integrations with SAML/OIDC providers—turning OpenSearch into a compliant enterprise platform.

• Radical Cost Efficiency: Achieve 30-50% lower total cost of ownership versus managed Elastic services through expert data tiering, index lifecycle management (ILM), and right-sized infrastructure planning.

• Proactive Resilience: Our 24/7 OpenSearch managed services include predictive anomaly detection, automated healing procedures, and disaster recovery drills—transforming your cluster from a reactive liability to a proactive asset.

Comprehensive OpenSearch Consulting & Managed Services

Our full-spectrum services are designed by core OpenSearch contributors and battle-tested SREs to cover every stage of the cluster lifecycle.

1. OpenSearch Strategy, Architecture & Production Deployment

We design resilient, multi-zone architectures on AWS, Azure, GCP, or on-premises. This includes capacity modeling for 3-year growth, hot-warm-cold-frozen data tiering strategies, security-first configuration (OpenSearch Security Plugin), and detailed disaster recovery runbooks with RPO/RTO targets.

2. OpenSearch Performance Tuning & Scaling Optimization

Poor performance often stems from deep configuration issues. We conduct JVM heap pressure analysis, optimize thread pool and queue configurations, tune index refresh intervals and merge policies, and implement shard strategy optimization to eliminate overhead and ensure linear scalability.

3. Advanced Data Ingestion & Pipeline Engineering

Efficient data flow is critical. We architect and implement robust ingestion pipelines using OpenSearch Data Prepper, Logstash, or Vector, with custom processors for parsing, enrichment, and routing. We ensure back-pressure handling, guaranteed delivery semantics, and seamless integration with Kafka, Kinesis, or database change-data-capture (CDC) streams.

4. OpenSearch Security Hardening & Compliance Implementation

Security is non-negotiable. We go beyond basics to implement certificate-based node authentication, field-level security, document-level security, audit log analysis, and integrations with Active Directory, Okta, or Auth0. We conduct penetration testing and deliver frameworks for SOC 2, HIPAA, or PCI-DSS compliance.

5. Migration from Elasticsearch, Splunk, or Other Platforms

Execute low-risk, zero-downtime migrations. Our methodology includes comprehensive feature gap analysis, dual-write/dual-read migration patterns, data validation frameworks, and application client (SDK) transition plans to move from Elasticsearch 7.x/8.x, Splunk, or Solr without business disruption.

6. 24/7 OpenSearch Managed Services & Proactive Support

Your insurance policy against midnight pages. Includes 24/7/365 monitoring with custom Grafana dashboards, alerting on 50+ critical metrics, automated index lifecycle management, patch and version upgrade management, and direct Slack/phone access to Senior OpenSearch SREs.

7. OpenSearch Observability & SIEM Implementation

Transform logs, metrics, and traces into actionable insights. We deploy and customize the OpenSearch Observability plugins (Trace Analytics, Piped Processing Language) or implement a scalable, cost-effective SIEM using the OpenSearch Security Analytics plugin, replacing costly commercial tools.

8. Vector Search & AI Integration for Generative AI Workloads

Prepare for the AI era. We implement OpenSearch’s Neural Search plugin, design hybrid search systems (combining BM25 and k-NN), build Retrieval-Augmented Generation (RAG) pipelines, and optimize HNSW algorithm parameters for high-recall, low-latency similarity search.

9. OpenSearch Health, Diagnostic, and Cost Optimization Audit

Our signature assessment provides an X-ray of your cluster. We deliver a report covering cluster stability, security posture, shard efficiency, query performance bottlenecks, and cloud cost waste analysis, complete with a prioritized 90-day optimization roadmap.

10. OpenSearch Training & Developer Enablement

Empower your team for long-term success. We offer customized training for developers (REST API, query DSL), administrators (day-2 ops, troubleshooting), and architects (scaling, security), along with runbooks and hands-on incident simulation labs.

Download Our “Production OpenSearch Operations Playbook” | Request a Detailed Managed Services SLA

Enterprise Outcomes & Quantifiable ROI: Data-Driven Impact

For Financial Leaders (CFOs, VPs of Finance):

• Radically Reduce Software & Infrastructure Spend: Achieve 40-60% savings versus Elastic Cloud or Splunk Cloud through open-source licensing and expert resource optimization. Typical ROI on consulting services is 3-5 months.

• Convert CAPEX to Predictable OPEX: Our managed services provide a fixed, predictable monthly cost, eliminating six-figure unexpected license true-ups and overprovisioning waste.

• Demonstrate Compliance & Risk Reduction: Our security frameworks provide auditable evidence for regulatory requirements, reducing insurance premiums and risk exposure.

For Technology Leaders (CTOs, VPs of Engineering):

• Eliminate Search & Observability Bottlenecks: Guarantee P99 search latency under 100ms and ingest pipeline stability during 10x traffic events, directly improving application performance and developer velocity.

• Achieve Enterprise-Grade Resilience: Design for 99.99%+ availability with multi-AZ/multi-region architectures and automated recovery, protecting revenue and brand reputation.

• Consolidate & Simplify Your Stack: Unify application search, log analytics, and APM onto a single, governed OpenSearch platform, reducing operational overhead by 30-50%.

For Security & DevOps Leaders (CISOs, Directors of Platform):

• Implement a Cost-Effective, Powerful SIEM: Deploy a full-featured security analytics platform at 20-30% of the cost of Splunk Enterprise Security, with comparable ingestion scale and query power.

• Enable Real-Time, Full-Fidelity Observability: Correlate metrics, logs, and traces in a single pane of glass, reducing mean-time-to-resolution (MTTR) by 60-80% for production incidents.

• Proactively Secure Your Data Layer: Implement defense-in-depth security with fine-grained access controls, encryption-in-transit/at-rest, and comprehensive audit trails, significantly shrinking your attack surface.

For Product & Data Leaders (CPOs, Heads of Data):

• Ship Search & Analytics Features Faster: Provide developers with a golden-path, self-service OpenSearch platform with built-in guardrails, reducing time-to-market for data-intensive features from quarters to weeks.

• Power Next-Generation AI Applications: Build RAG pipelines and semantic search capabilities on a proven, scalable foundation, unlocking new ML-driven user experiences.

• Improve Data Democratization & Insights: Enable business teams with secure, performant dashboards and ad-hoc query capabilities without taxing engineering resources.

Use Our OpenSearch TCO Comparator: Benchmark Your Costs Against Managed Services

Our Proven OpenSearch Consulting Methodology: The Reliability Engine Framework

Phase 1: Immersive Discovery & Benchmarking (1-2 Weeks)

• Automated collection of existing cluster metrics, logs, and configurations.

• Analysis of data schemas, query patterns, and client application performance.

• Establishment of business SLAs and technical SLOs (Service Level Objectives).

Phase 2: Target Architecture & Security Design (2-3 Weeks)

• Threat modeling and failure mode analysis for the proposed architecture.

• Creation of detailed, implementable architecture diagrams (VPC, networking, node roles).

• Data lifecycle and security policy design (index templates, ILM policies, RBAC roles).

Phase 3: Implementation, Migration & Optimization (Timeline Varies)

• Infrastructure-as-Code deployment (Terraform, Ansible, Crossplane) of the new environment.

• Data migration execution using logstash, snapshot/restore, or custom ETL with validation.

• Iterative performance testing & tuning against real-world workloads.

Phase 4: Validation, Cutover & Knowledge Transfer (1-3 Weeks)

• Load, failure, and disaster recovery testing in staging with stakeholder sign-off.

• Phased production cutover with comprehensive rollback checkpoints.

• Hands-on workshops and delivery of complete operational runbooks.

Phase 5: Managed Operations & Continuous Evolution (Ongoing)

• Weekly performance & cost reports, monthly security reviews.

• Quarterly architecture reviews to align with business growth and new OpenSearch features.

• Proactive roadmap planning for upgrades, scaling events, and new use cases.

Deep Technical Expertise Across the OpenSearch Ecosystem

Our team includes contributors to the OpenSearch project and maintainers of key related open-source tools.

Core Platform & Deployment Expertise:

• OpenSearch & OpenSearch Dashboards: Deep specialization in v2.x performance, Security Plugin, Observability Plugin, and Anomaly Detection.

• Deployment Models: AWS OpenSearch Service (Managed), Self-Managed on Kubernetes (OpenSearch Operator, ECK), On-Premise (VM/Bare Metal), Multi-Cloud Hybrid.

Performance & Observability Stack:

• Monitoring: Prometheus exporters (opensearch-prometheus-exporter), OpenSearch Performance Analyzer and Root Cause Analysis (RCA) Framework, Custom Grafana dashboards for per-tenant insights.

• Profiling: Java Flight Recorder (JFR) for hotspot analysis, eBPF for kernel-level observability on data nodes, query profiling via the _profile API.

Orchestration & Infrastructure as Code:

• Kubernetes: OpenSearch Operator, ECK (Elastic Cloud on Kubernetes) for OpenSearch, Helm charts for auxiliary services.

• Cloud Automation: Terraform modules for AWS OpenSearch Service, Azure DevOps/GitLab CI pipelines for blue-green deployments.

• Configuration Management: Ansible playbooks for on-premise node provisioning and configuration.

Integration & Data Pipeline Ecosystem:

• Ingestion: OpenSearch Data Prepper, Logstash, Fluentd, Vector, Apache NiFi.

• Streaming & Analytics: Apache Kafka, Amazon Kinesis, Apache Spark (with Spark-OpenSearch connector).

• Security & Identity: Integration with Okta, Azure AD, Keycloak, HashiCorp Vault for secret management.

Vector Search & AI/ML Integration:

• OpenSearch Neural Search Plugin: Implementation of BERT, sentence-transformers, and custom model deployment.

• RAG Pipeline Architecture: Integration with LangChain, LlamaIndex, and LLM APIs (OpenAI, Anthropic).

• Algorithm Tuning: Optimization of HNSW parameters (ef_construction, M), FAISS indexes, and hybrid score fusion.

Evidence of Impact: OpenSearch Transformation Case Studies

Global Media & Streaming Platform

Challenge: Proprietary Elasticsearch cluster costs escalating by 50% yearly ($2M+ annually) with unpredictable performance during live events. Needed a path off vendor lock-in.
Our Solution: Executed a zero-downtime migration to a self-managed OpenSearch cluster on AWS. Implemented index lifecycle management (ILM) with cold tiering to S3 and performance-tuned for mixed media metadata and user behavior analytics workloads.
Quantifiable Results:

• Achieved 55% reduction in annual platform costs ($2.1M to $950K).

• Improved 95th percentile search latency by 40% (from 250ms to 150ms).

• Successfully handled 8x normal traffic during a premiere event with no degradation.

• Full migration completed in 12 weeks with zero user-facing downtime.

Financial Services RegTech Company

Challenge: Needed a compliant, secure SIEM/audit log analytics platform to process 5 TB/day of financial transactions for fraud detection and regulatory reporting. Commercial SIEM quotes exceeded $3M/year.
Our Solution: Designed and deployed a multi-tenant OpenSearch-based SIEM with the Security Analytics plugin. Implemented field-level security, immutable audit logs, and PCI-DSS compliant architecture.
Quantifiable Results:

• Deployed a full-featured SIEM at 25% of the cost of commercial alternatives.

• Reduced time to run compliance reports from hours to seconds.

• Achieved ingestion scale of 200,000 events/second sustained.

• Passed stringent external PCI-DSS audit on first attempt.

E-commerce Marketplace with AI-Driven Search

Challenge: Legacy keyword search resulted in 35% search abandonment. Needed to implement semantic and vector search for product discovery without sacrificing scale or latency.
Our Solution: Implemented OpenSearch with the Neural Search plugin. Built a hybrid search system combining BM25 (keywords) and k-NN (vector) for 10 million product embeddings. Created a continuous learning pipeline to update embeddings from user behavior.
Quantifiable Results:

• Reduced search abandonment by 48%.

• Increased product discovery click-through rate (CTR) by 32%.

• Maintained sub-100ms P99 latency for hybrid search queries.

• Enabled “similar items” and visual search features that drove 15% incremental revenue.

Client Endorsements: Trusted for Mission-Critical Search & Analytics

“When we faced a 300% license renewal bill from Elastic, panic set in. Nextbrick architected and executed our migration to OpenSearch with surgical precision. Not only did we escape the cost spiral, but our observability platform performance actually improved. Their OpenSearch consulting expertise saved our budget and upgraded our capabilities.”
– VP of Infrastructure, SaaS Unicorn Company

“Our previous OpenSearch cluster was a constant source of firefighting—slow queries, nodes dropping out, constant tuning. Nextbrick’s managed services team took over operations and transformed it into a set-and-forget utility. We get weekly performance reports and have had zero incidents in 9 months. They deliver true operational serenity.”
– Director of Platform Engineering, Digital Media Company

“Implementing a compliant SIEM seemed like a multi-year, multi-million dollar project. Nextbrick delivered a production OpenSearch Security Analytics platform in 16 weeks that processes all our security logs and meets our regulatory requirements at a fraction of the expected cost. They understand both the technology and the compliance landscape deeply.”
– CISO, Financial Technology Firm

Critical Questions for Enterprise Leaders Evaluating OpenSearch

1. What is the true total cost of ownership (TCO) comparison between OpenSearch and Elasticsearch?

The TCO advantage for OpenSearch is significant and structural. While Elasticsearch licensing costs scale aggressively with features (like alerting, ML) and deployment size, OpenSearch includes all features in its open-source Apache 2.0 license. For a 500-node cluster processing 50 TB/day, enterprises typically see: Elasticsearch Cloud: $1.8M-$2.5M/year. Self-Managed OpenSearch (with our managed services): $600K-$900K/year—a 60-70% savings. This excludes the strategic cost of avoiding vendor lock-in.

2. How mature and enterprise-ready is OpenSearch compared to Elasticsearch 8.x?

OpenSearch 2.x is highly mature and battle-tested. It contains all the core features of Elasticsearch 7.10 (the last open-source version), plus significant improvements developed by the OpenSearch community: a new security plugin with improved RBAC, a revamped observability plugin with Piped Processing Language (PPL), and vector search capabilities built-in. It powers Amazon’s AWS service logs, Adobe’s experience platform, and thousands of other enterprises. The 2.x release line has proven stability at petabyte scale.

3. What does your 24/7 OpenSearch managed service include, and how is it priced?

Our comprehensive managed service includes: 24/7 cluster monitoring & alerting, performance tuning, security patch management, index lifecycle management, backup verification, and direct access to Senior SREs. We typically price as a percentage of your cloud infrastructure spend for OpenSearch (15-25%) or a fixed monthly fee for on-premise. This compares favorably to Elastic Cloud’s 30-40% premium over infrastructure costs and includes far more hands-on expertise. We provide clear SLAs for response (P1: <15 min) and resolution times.

4. We’re currently on Elasticsearch 7.x or 8.x. What’s involved in migrating to OpenSearch?

Migration is a well-trodden path. The process involves: 1) Feature & API Compatibility Analysis (most REST APIs are identical), 2) Client SDK Updates (minor changes to Java High-Level REST Client), 3) Data Migration (using snapshot/restore or reindexing—we prefer snapshot/restore for large clusters), and 4) Testing (functional, performance, regression). For a typical 50-node cluster, the migration project takes 8-12 weeks. We use dual-write strategies during cutover to ensure zero data loss and immediate rollback capability.

5. Can OpenSearch truly replace Splunk for security and observability use cases?

Yes, for the vast majority of enterprise use cases. The OpenSearch Observability Plugin provides robust log analytics, metrics, and distributed tracing. The OpenSearch Security Analytics Plugin delivers SIEM capabilities: threat detection, alerting, correlation rules, and dashboards. The key advantages are: 1) Cost (20-30% of Splunk’s), 2) Integration (tight integration with your existing data in OpenSearch), and 3) Flexibility (open source, no data ingestion caps). For organizations requiring extremely niche Splunk SPL commands or specific third-party threat intelligence integrations, we conduct a detailed gap analysis first.

6. How do you approach performance tuning for high-throughput log analytics vs. low-latency application search?

These are fundamentally different workloads requiring different configurations:

• Log Analytics (High Ingest, Batch Queries): We optimize for write throughput: higher refresh_interval, bulk queue depth, optimized JVM GC for large heaps, and indexing-heavy instance types (high I/O, moderate CPU).

• Application Search (Low Latency, Real-Time Queries): We optimize for read latency: lower refresh_interval, more aggressive caching, search-heavy instance types (high CPU, memory), and potentially separate dedicated coordinator nodes.
  Often, we implement multiple data tiers or even separate clusters to isolate these workloads, then use cross-cluster search to unify querying when needed.

7. What is the implementation timeline and engagement model for a new OpenSearch deployment?

Engagements typically begin with a fixed-price Health Check or Architecture Design ($7,500-$20,000). Implementation projects range from $50,000 for a straightforward migration to $200,000+ for a greenfield, multi-use case platform with advanced security. Ongoing managed services are typically 15-25% of annual infrastructure costs. A typical enterprise deployment timeline is 10-16 weeks from kickoff to production cutover, followed by a 30-day hypercare period.

Begin Your Journey to OpenSearch Excellence

Don’t let proprietary lock-in constrain your innovation or budget. Partner with the foremost experts in open-source search, analytics, and observability.

Contact Our Search & Analytics Practice
Phone: +1-408-4090-256 | Email: shrey@nextbrick.com

Transform your data layer from a costly, complex burden into a scalable, open, and high-performance asset with expert OpenSearch consulting and managed services.

Nextbrick OpenSearch Consulting | OpenSearch Managed Services | Elasticsearch to OpenSearch Migration | OpenSearch SIEM Implementation | Vector Search & AI Integration