Elastic Observability
Claim this toolFull-stack observability solution built on a Search AI Platform, enabling faster troubleshooting with agentic AI.
Paid plans only, free trialVisit WebsiteReviews on G2 Capterra
130 reviews trackedThe Bottom Line
- Price
- Paid plans only, free trial. Compare plans
Key facts
- Unifies full-stack observability with AI-driven insights for faster troubleshooting.
- Ingests any data, including OpenTelemetry, with AI-powered analysis and anomaly detection.
- Offers cost-efficient storage and high-performance querying for petabytes of data.
Pros
- Fixes problems in seconds, not hours, using AI-driven insights.
- Supports petabytes of data with cost-efficient storage and high performance.
- Open source and standardized on OpenTelemetry for flexibility and extensibility.
- Provides comprehensive full-stack visibility from bare metal to cloud and GenAI apps.
- Offers zero-config, always-on analysis with machine learning to proactively identify issues.
Cons
- Reviewers consistently report a steep learning curve, since getting real value out of the platform requires comfort with Kibana and query languages like KQL and ES|QL that new teams do not already know.
- Running it well is resource-intensive on compute and storage, so self-managed deployments carry significant infrastructure overhead and cost-management burden as data volumes grow.
- The pricing and licensing structure is widely described as confusing to decipher for large-scale deployments, and premium capabilities such as AI-powered APM sit behind expensive subscription tiers.
- Compared with competitors like Datadog, users note weaker out-of-the-box automation and predictive AI features, leaving more manual configuration and setup work to the team.
What is Elastic Observability?
Elastic Observability is a comprehensive, full-stack observability solution built on Elastic's Search AI Platform. It helps SREs and development teams troubleshoot problems faster, often in seconds, by unifying application and infrastructure visibility. The platform ingests any data, including OpenTelemetry-compliant telemetry, and provides instant dashboards, always-on anomaly detection, and pattern analysis. It leverages AI Assistant and agentic AI workflows to dive deeper into root causes, moving beyond just alerts to provide actionable answers.
The solution is designed to store more data, spend less, and troubleshoot faster, integrating log analytics, application performance monitoring (APM), infrastructure monitoring, AIOps, LLM observability, and digital experience monitoring (DEM). It supports petabytes of data with cost-efficient storage and high-performance querying, making it suitable for organizations needing to manage and analyze large, long-term datasets across cloud, on-prem, Kubernetes, and serverless environments. Its open-source foundation and standardization on OpenTelemetry ensure flexibility and extensibility.
Available on: Web
Louis Corneloup Source elastic.co ↗
Ratings Across the Web
4.3 (130 reviews)
Elastic Observability holds an aggregate rating of 4.3 out of 5 from 130 reviews across G2 and Capterra, last checked September 17, 2026.
Ratings aggregated from independent review platforms. Learn more
Preview
Key Features
- Log analytics with Discover, prebuilt dashboards, and ES|QL
- Application Performance Monitoring (APM) with native OpenTelemetry support
- Infrastructure monitoring across cloud, on-prem, Kubernetes, and serverless
- AIOps with zero-config anomaly detection, pattern analysis, and correlation
- LLM observability for tracking GenAI app latency, errors, prompts, and costs
- Digital Experience Monitoring (DEM) with RUM, synthetic testing, and uptime monitoring
- AI-driven log processing with Streams for automatic data organization
- AI Assistant for natural language root cause insights and context
Pricing Plans
Free TrialPricing checked Oct 8, 2026
| Plan | Price | Details |
|---|---|---|
| Hosted | Resource based pricing |
+2 more Show less
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| Serverless | Usage based pricing |
+3 more Show less
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| Self-managed | License based pricing |
+1 more Show less
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Is Elastic Observability worth the price?
Good value
Elastic Observability's pricing is complex, relying on resource-based, usage-based, or license-based models rather than transparent fixed monthly costs.
It's best for organizations with varying scales of observability requirements, from those needing full control to those preferring a fully managed serverless experience.
Reviews
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4.3/5
Across 130 verified user reviews on G2, Capterra
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Elastic Observability FAQ
How does Elastic Observability leverage agentic AI to improve troubleshooting?
Elastic Observability uses agentic AI workflows and an AI Assistant to analyze data, dive deeper into issues, and pinpoint root causes. This allows users to get answers and insights rather than just alerts, significantly speeding up problem resolution.
What specific OpenTelemetry (OTel) capabilities does Elastic Observability offer for application performance monitoring (APM)?
Elastic Observability provides production-grade pure OTel support, allowing users to stream native OTel data without proprietary agents. It also offers broad language support with sampling capabilities for comprehensive APM.
How does Elastic Observability help manage and analyze logs from various sources?
Elastic Observability uses AI-driven log processing with Streams to automatically organize data, apply parsing, partitioning, field extraction, and lifecycle policies. It also highlights 'Significant Events' to draw attention to important features within petabytes of logs for instant clarity.
Can Elastic Observability provide visibility into Generative AI applications?
Yes, Elastic Observability offers LLM observability features to remove blind spots for GenAI apps. It tracks latency, errors, prompts, responses, usage, and costs across all major LLM services.
What are the benefits of using Elastic Observability with the new Search AI Lake architecture?
When combined with Search AI Lake, Elastic Observability enables faster analytics with near-instant queries, even on petabytes of data. This allows for rapid insights by analyzing all data at unprecedented speed and scale, benefiting from the decoupled compute and storage of Search AI Lake.
Source: elastic.co