We Are Trusted Elastic Partners 

• Log Analytics 

Search petabytes of logs, visualize through prebuilt dashboards, and run ad hoc analysis with Elasticsearch Query Language (ES|QL). 

• Application Performance Monitoring 

Stream native OTel data, capture traces, and monitor performance across languages and frameworks. 

• Infrastructure Monitoring 

Gain visibility across infrastructure layers with 400+ integrations for hosts, containers, and cloud services. 

• AIOps & ML 

Built-in anomaly detection, pattern recognition, and forecasting across multi-signal telemetry. 

• LLM Observability 

Track latency, errors, prompts, usage, and costs for generative AI applications. 

• Digital Experience Monitoring 

Combine real user monitoring, synthetic testing, and uptime checks to improve customer experience. 

• Distributed Scalability 

Autoscales, replicates, and balances clusters across environments, supporting petabytes of data through cross-cluster search. 

• AI-Powered Search & Ranking 

Semantic and lexical queries combined with hybrid ranking and integration with LLMs for improved accuracy and intent-matching. 

• Time Series & Log Analytics 

Real-time telemetry analysis with ES|QL, snapshots, and optimized index modes for cost-efficient storage. 

• Vector Database 

Support for semantic and hybrid search across text, images, and multi-modal data. Billions of embeddings managed through a single API. 

• Geospatial Engine 

Fast location-aware queries with geo-distance, polygon mapping, and spatial analytics. 

• Integrations & APIs 

350+ connectors and open APIs for ingest pipelines, custom integrations, and automation. 

• Environment Agnostic 

Deploy Elastic clusters on bare metal, VMs, containers, or Kubernetes with identical functionality and performance. 

• Multi-Cloud and Hybrid Ready 

Operates seamlessly across AWS, Azure, and GCP, or in regulated, air-gapped, and sovereign cloud environments. 

• Cross-Cluster Search 

Execute federated queries across multiple clusters, regions, or clouds as if they were one system. 

• Elastic Vector Database 

Support for billions of embeddings, text, and multi-modal vectors with deployment in any environment, enabling semantic search and AI applications everywhere. 

• Elastic Common Schema (ECS) 

Ensures consistent indexing and interoperability across different environments, reducing integration overhead. 

• Scale to Global Reach 

Auto-scales, replicates, and rebalances workloads to match demand with zero downtime. 

• Elastic Agent: Centralized ingestion with one-click setup for observability and security data. 

• Open Crawler: Open-source indexing of web content into Elasticsearch with lightweight design and customizable options. 

• Data Connectors: Prebuilt connectors for SaaS and productivity tools to create unified search experiences. 

• APIs: Document APIs and ingest pipelines for custom ingestion logic. 

• Logstash: A processing pipeline to collect, parse, enrich, and transform data from any format. 

• Language Clients: Full-featured clients for Java, Python, Go, and more to embed Elastic directly into applications. 

• Unified Security and Observability 

Correlate logs, metrics, traces, and security events across cloud, on-prem, and hybrid environments. 

• SIEM for Real-Time Threat Detection 

Analysts can leverage enriched telemetry, automated correlation, and alert prioritization to reduce mean time to detection (MTTD) and response (MTTR). 

• AI-Powered Analytics and Anomaly Detection 

Built-in machine learning detects anomalies and unusual patterns across telemetry data, uncovering potential threats that signature-based tools may miss. 

• LLM Integration for Security Insights 

Summarize alerts, generate incident context, and get remediation steps, enhancing SOC efficiency and decision-making. 

• Automated Threat Response and Orchestration 

Trigger automated response workflows, enabling containment and mitigation actions without manual intervention, while maintaining human oversight. 

• Scalable and Flexible Deployment 

Elastic’s cloud-native architecture ensures SIEM, analytics, and AI capabilities scale across petabytes of data and multiple environments.