Elasticsearch Development for Fast, Relevant Search
Build search that scales with your query volume and returns relevant results, fast.
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Search infrastructure for production loads
Elasticsearch handles search and analytics well in development, but production brings index bloat, slow queries, and cluster instability. We build search infrastructure that returns relevant results under load, configure clusters for the data volumes you actually run, and tune queries before users notice performance drops.
Our capabilities include:
- Full-text search and relevance tuning
- Cluster configuration and shard optimization
- Log aggregation and observability pipelines
- Real-time analytics and dashboards
- Vector search and RAG implementations
- Elasticsearch migrations and upgrades
Who we support
We work with engineering teams where search performance degrades as data grows, observability pipelines can’t keep pace with log volume, or Elasticsearch clusters need expertise your team doesn’t have in-house.
Product Teams Scaling Search
Your search worked fine with thousands of records but slows down with millions. Users complain about irrelevant results, queries timeout during traffic spikes, and nobody on your team knows how to tune relevance or optimize index mappings.
Platform Teams Running Observability
Log volume grows faster than your cluster can handle. Queries against recent data are fast but historical searches crawl. You need pipelines that ingest at scale and retention policies that don't tank performance.
Engineering Teams Adding AI Search
You're implementing vector search or RAG but Elasticsearch's vector capabilities are new territory. Hybrid search combining keywords and embeddings requires architecture your team hasn't built before.
Ways to engage
We offer a wide range of engagement models to meet our clients’ needs. From hourly consultation to fully managed solutions, our engagement models are designed to be flexible and customizable.
Staff Augmentation
Get access to on-demand product and engineering team talent that gives your company the flexibility to scale up and down as business needs ebb and flow.
Retainer Services
Retainers are perfect for companies that have a fully built product in maintenance mode. We'll give you peace of mind by keeping your software running, secure, and up to date.
Project Engagement
Project-based contracts that can range from small-scale audit and strategy sessions to more intricate replatforming or build from scratch initiatives.
We'll spec out a custom engagement model for you
Invested in creating success and defining new standards
At Curotec, we do more than deliver cutting-edge solutions — we build lasting partnerships. It’s the trust and collaboration we foster with our clients that make CEOs, CTOs, and CMOs consistently choose Curotec as their go-to partner.
Why choose Curotec for Elasticsearch?
We’ve tuned clusters that started fast and slowed under real data volumes. Our engineers understand shard strategy, mapping design, and query optimization that keeps search responsive. You get infrastructure expertise, not just developers who read the docs.
1
Extraordinary people, exceptional outcomes
Our outstanding team represents our greatest asset. With business acumen, we translate objectives into solutions. Intellectual agility drives efficient software development problem-solving. Superior communication ensures seamless teamwork integration.
2
Deep technical expertise
We don’t claim to be experts in every framework and language. Instead, we focus on the tech ecosystems in which we excel, selecting engagements that align with our competencies for optimal results. Moreover, we offer pre-developed components and scaffolding to save you time and money.
3
Balancing innovation with practicality
We stay ahead of industry trends and innovations, avoiding the hype of every new technology fad. Focusing on innovations with real commercial potential, we guide you through the ever-changing tech landscape, helping you embrace proven technologies and cutting-edge advancements.
4
Flexibility in our approach
We offer a range of flexible working arrangements to meet your specific needs. Whether you prefer our end-to-end project delivery, embedding our experts within your teams, or consulting and retainer options, we have a solution designed to suit you.
Elasticsearch capabilities for production search
Cluster Configuration & Optimization
Relevance Tuning & Query Optimization
Observability & Log Pipelines
Vector Search & RAG Integration
Migration & Version Upgrades
Monitoring & Performance Troubleshooting
Tools and technologies for Elasticsearch
Core Elasticsearch Stack
Curotec deploys the full Elastic Stack for search, analytics, ingestion, and visualization in production environments.
- Elasticsearch — Distributed search and analytics engine for full-text search, structured queries, and real-time data analysis across large datasets
- Kibana — Visualization and dashboarding platform for exploring Elasticsearch data, building search analytics, and monitoring cluster health
- Logstash — Server-side data processing pipeline that ingests, transforms, and routes data from multiple sources into Elasticsearch indexes
- Beats — Lightweight data shippers for logs, metrics, network data, and uptime monitoring that feed directly into Elasticsearch or Logstash
- Elastic Agent — Unified agent for collecting logs, metrics, and security data with centralized management through Fleet and Kibana
- Elastic Cloud — Managed Elasticsearch service on AWS, Azure, and Google Cloud with automated scaling, upgrades, and cluster management
Data Ingestion & ETL
Our engineers build pipelines that move data from source systems into Elasticsearch with transformation, enrichment, and validation.
- Logstash Pipelines — Filter, transform, and enrich data with grok patterns, mutate filters, and conditional routing before indexing into Elasticsearch
- Apache Kafka — Distributed streaming platform for high-throughput data ingestion with Kafka Connect sinks feeding Elasticsearch indexes
- Apache NiFi — Flow-based data ingestion with visual pipeline design, data provenance tracking, and Elasticsearch processors for real-time indexing
- Fluentd & Fluent Bit — Lightweight log collectors for containerized environments with Elasticsearch output plugins and filtering capabilities
- Filebeat & Metricbeat — Purpose-built shippers for log files and system metrics with pre-configured modules for common applications and services
- Custom ETL Scripts — Python and Node.js pipelines using Elasticsearch bulk APIs for data migration, transformation, and scheduled index updates
Client Libraries & Frameworks
We integrate Elasticsearch with application backends using language-specific clients and frameworks for search and analytics features.
- Elasticsearch Python Client — Official Python library for indexing, searching, and managing clusters with support for async operations and DSL queries
- Elasticsearch Java Client — Native Java API for high-performance search applications with strongly-typed requests and connection pooling
- Elasticsearch JavaScript Client — Node.js and browser client for building search interfaces, autocomplete features, and real-time dashboards
- Spring Data Elasticsearch — Java framework integration for repository-based data access, entity mapping, and query derivation in Spring applications
- Elasticsearch PHP Client — Official PHP library for Laravel and Symfony applications with bulk indexing, scroll queries, and cluster management
- Elasticsearch DSL — High-level Python library for building complex queries, aggregations, and index mappings with readable, chainable syntax
Cluster Monitoring & Management
Our team configures monitoring tools that surface cluster health, query performance, and resource utilization before problems escalate.
- Kibana Stack Monitoring — Built-in dashboards for cluster health, node performance, index stats, and shard allocation with alerting on threshold breaches
- Elasticsearch-HQ — Open-source cluster management interface for monitoring node status, index metrics, and query performance across environments
- Cerebro — Web-based cluster administration tool for shard management, index operations, snapshot configuration, and node diagnostics
- Prometheus & Grafana — Metrics collection and visualization using Elasticsearch exporter for custom dashboards and alerting pipelines
- Elastic APM — Application performance monitoring that traces requests through search infrastructure and identifies slow query patterns
- Watcher & Alerting — Built-in Elasticsearch alerting for cluster health, query thresholds, and anomaly detection with notification integrations
Vector Search & AI Integration
Curotec implements vector storage, embedding pipelines, and hybrid search for semantic and RAG-powered applications.
- Elasticsearch Vector Search — Native dense vector storage and kNN search for semantic similarity, image matching, and embedding-based retrieval
- ELSER — Elastic Learned Sparse Encoder for semantic search without external embedding models, trained on relevance data for out-of-box accuracy
- OpenAI & Cohere Embeddings — Integration pipelines that generate embeddings from text and store vectors in Elasticsearch for RAG applications
- LangChain & LlamaIndex — Python frameworks for building retrieval-augmented generation with Elasticsearch as the vector store and retriever
- Hybrid Search — Query configurations combining BM25 keyword matching with vector similarity for results that balance precision and semantic relevance
- Inference Pipelines — Elasticsearch ingest processors that generate embeddings at index time using deployed ML models for automatic vectorization
Deployment & Scaling Infrastructure
Our engineers deploy Elasticsearch on cloud platforms and Kubernetes with autoscaling, backups, and disaster recovery.
- Docker & Docker Compose — Containerized Elasticsearch deployments for development environments, testing, and local cluster configuration
- Kubernetes & Helm — Orchestrated Elasticsearch clusters with elastic scaling, rolling upgrades, and automated failover using ECK operator
- AWS OpenSearch & Elasticsearch Service — Managed cloud deployments with automated backups, scaling policies, and VPC integration on AWS infrastructure
- Azure Cognitive Search — Microsoft cloud search service with Elasticsearch-compatible APIs, AI enrichment, and integration with Azure services
- Terraform & Ansible — Infrastructure-as-code provisioning for Elasticsearch clusters with repeatable deployments and configuration management
- Snapshot & Restore — Backup strategies using S3, Azure Blob, and GCS repositories with lifecycle policies and cross-cluster replication
FAQs about our Elasticsearch services
How do you fix search that slows down over time?
Index mappings, shard allocation, and query patterns usually reveal the bottleneck. It’s often mapping explosions, oversized shards, or unoptimized queries. We fix the root cause rather than throwing hardware at the problem.
Can you optimize our existing Elasticsearch cluster?
Cluster audits cover node resources, index configurations, and query performance to pinpoint slowdowns. Tuning often involves shard rebalancing, mapping adjustments, and query rewrites without rebuilding your entire search infrastructure.
What's involved in migrating to a newer version?
Migrations start with breaking change assessments, then reindexing with zero downtime using aliases. Testing runs against your actual query patterns, not sample data, with rollback plans ready before cutover.
How do you approach relevance tuning?
We configure analyzers, field boosting, and custom scoring based on how your users actually search. Relevance improves through iteration—analyzing failed searches, adjusting synonyms, and testing against real queries until results match expectations.
Can you help us implement vector search or RAG?
Hybrid architectures combine keyword matching with semantic similarity. This includes embedding pipelines, vector index configuration, and retrieval strategies that feed relevant context to LLMs without hallucination.
What does ongoing Elasticsearch support look like?
Support covers cluster health monitoring, performance tuning, and version upgrades as Elastic releases them. Query optimization and capacity planning happen proactively, before slow searches impact users.
Ready to have a conversation?
We’re here to discuss how we can partner, sharing our knowledge and experience for your product development needs. Get started driving your business forward.
