Coralogix

Learning Objectives

• Describe what Coralogix does and how its streaming pipeline differs from index-heavy observability tools
• Explain how AI is applied through the Olly agent for real-time troubleshooting
• Identify why analyzing data in-stream changes the economics of observability

What Is Coralogix?

Coralogix is a full-stack observability platform that analyzes logs, metrics, and traces to help teams monitor and troubleshoot their software. What sets it apart is its architecture: rather than indexing all incoming data into expensive storage before it can be queried, Coralogix analyzes telemetry in real time as it streams through the platform. This streaming approach lets teams process and derive insight from high-volume data without paying the storage and indexing cost that traditional observability tools require. Founded in 2014, Coralogix is a private company that raised a large growth round in 2026.

On top of that streaming foundation sits Olly, Coralogix's AI agent. Olly answers natural-language questions about a system's telemetry and can run troubleshooting in several modes — fully human-led, conversational, or fully automated — against the live streaming data. Because the agent operates on Coralogix's own data pipeline rather than bolting onto an external store, it is genuinely agentic on a foundation the platform controls end to end.

What Coralogix Does

• Full-stack observability — unifies logs, metrics, and traces in one platform
• Streaming analysis — processes telemetry in real time as it flows, avoiding heavy up-front indexing
• Cost control — separates insight from storage so teams can analyze high-volume data affordably
• Natural-language querying — the Olly agent lets users ask questions about their systems in plain language
• Flexible troubleshooting — Olly runs in human-led, conversational, or fully automated modes
• Alerting and dashboards — real-time alerts and visualizations built on the streaming pipeline

How AI Is Applied

Coralogix's AI is more than a chat wrapper because it sits directly on the platform's streaming data foundation. The Olly agent can interpret a natural-language question, pull the relevant logs, metrics, and traces from the live stream, and reason toward an answer or a diagnosis. Crucially, it offers a spectrum of autonomy: a human can drive every step, work conversationally with the agent, or hand it a problem to investigate fully automatically. That range lets teams calibrate how much they trust the agent to different situations.

The design is genuinely agentic on its own data foundation — the AI operates against a pipeline Coralogix builds and controls, rather than querying a separate indexed store after the fact. That tight coupling is what makes real-time, in-stream troubleshooting possible. As with any automated investigation, the fully automated mode is best applied where a human can review the reasoning and confirm any action, but the underlying capability is a real application of AI to live observability data rather than a superficial add-on.

Who Uses Coralogix

Coralogix is used by software engineering, DevOps, and site-reliability teams — particularly organizations generating high volumes of telemetry that find traditional index-based observability costly. Its streaming model appeals to teams that want full-stack visibility without runaway storage bills, and its natural-language agent lowers the barrier for engineers who are not query-language experts.

Pricing

Coralogix uses a data-based pricing model tied to the volume and type of telemetry processed, and its streaming architecture is positioned to reduce cost relative to index-heavy alternatives at high volume. Exact pricing depends on data volume, retention, and features, so larger deployments are quote-based. Organizations contact Coralogix directly for enterprise terms.

Company Details

Strengths

• Cost-efficient at scale — streaming analysis avoids the storage and indexing cost of high-volume telemetry
• Real-time insight — analyzes data in motion so problems surface without waiting on indexing
• Genuinely agentic — Olly operates on Coralogix's own data foundation, not as a superficial add-on
• Flexible autonomy — human-led, conversational, or fully automated troubleshooting modes
• Full-stack coverage — logs, metrics, and traces in a single platform

Limitations and Considerations

• Architectural shift — the streaming model is different from index-first tools and may require rethinking how teams query and retain data
• Automated mode needs oversight — fully automated troubleshooting is best used where a human can review the agent's reasoning
• Data-based pricing — cost tracks telemetry volume, so teams should monitor usage
• Newer AI capability — as with any agent, real-world results depend on data quality and coverage

Key Takeaways

• Coralogix is a full-stack observability platform built on a streaming data pipeline that analyzes logs, metrics, and traces in real time without heavy indexing
• Its Olly AI agent answers natural-language questions and runs human-led, conversational, or fully automated troubleshooting against that live pipeline
• Operating on its own data foundation makes the AI genuinely agentic rather than a superficial add-on, and the streaming model changes the cost economics of high-volume observability
• Best for engineering and SRE teams generating large telemetry volumes who want real-time insight without index-heavy storage costs