Cortex XCOR Operator is a chat interface that guides domain-specific AI agents. Operational Fabric grounds autonomous operations in real-time system topology, operational memory, past user behavior and human knowledge.
"Cortex XCOR has already reduced our MTTR by 25%. We're now using its AI capabilities to run complex, multi-dependency root cause analyses in minutes that used to take hours or days."
Chronosphere has long been your trusted partner for protecting uptime. Now, we’re introducing XCOR, the next-generation observability platform, built on Chronosphere’s foundation and powered by Palo Alto Networks. If you're an existing Chronosphere customer, you can continue to use the platform as you always have. You'll just notice a new logo and design. You can also gain access to new capabilities like XCOR Operator, Synthetics and Consumption Budgets.
Cortex XCOR aligns observability spend with operational value by evaluating incoming telemetry against actual usage. The Utility Analyzer inspects data streams to identify low-utility metrics, logs and traces across active workflows. Teams then apply central Optimization Rules to drop, roll up or sample data upstream without code modifications. To prevent cost overruns, Consumption Budgets enforce team caps and automatically shed low-priority data during spikes. On average, customers reduce data by 90% while preserving key diagnostic signals.
Cortex XCOR has several ways to streamline observability migration. Automated migration tooling programmatically translates existing queries, dashboards, monitors and SLOs into XCOR formats. A validation engine then executes side-by-side visual checks to confirm data parity and highlight translation gaps. The Platform teams manage the transition through the Migration Hub, which tracks real-time status and locks verified configurations. For telemetry collection, XDOT Collector serves as a drop-in OpenTelemetry replacement for proprietary vendor agents.
Cortex XCOR accelerates root cause analysis through two primary AI capabilities. XCOR Operator provides a natural language interface that lets engineers investigate issues, construct queries, draft dashboard panels and explore telemetry using plain-English prompts without syntax friction. AI Investigations is an AI SRE capability that analyzes standard and custom telemetry across the architecture, automatically correlating disparate signals to isolate probable root causes, streamline triage and reduce mean time to resolution (MTTR).
Cortex XCOR prevents vendor lock-in through the XCOR Distribution of OpenTelemetry (XDOT) Collector. XDOT Collector uses standard OpenTelemetry YAML configurations and semantic conventions instead of proprietary formats. Built as an open-standard, drop-in agent, XDOT Collector standardizes telemetry across logs, events, metrics and traces using uniform data models without requiring application code reinstrumentation. By grounding data collection in open standards, teams retain long-term flexibility and full control over their telemetry pipeline.
We define AI-driven observability as the integration of conversational interaction with domain-specific AI agents, grounded in live architectural context. Within Cortex XCOR, the Operational Fabric powers this approach by anchoring autonomous operations in real-time system topology, operational memory, past user behavior and human knowledge. This ensures AI-driven analysis and root cause workflows remain continuously informed by actual system state and historical incident data.
Yes, Cortex XCOR supports real user monitoring (RUM) across both web and mobile applications. The platform efficiently stores high-fidelity frontend data at scale, eliminating the need to sample user sessions. Engineering teams retain complete, unsampled visibility into real user interactions, page loads and errors without incurring prohibitive storage costs or losing diagnostic context during troubleshooting.
Cortex XCOR operates on a flexible, credit-based consumption model. Billing is governed by two levers: A nominal rate for total Data Processed before optimization and a rate for Data Persisted after data-shaping rules apply. Your credit pool draws down based on active usage throughout the contract period. Built-in Consumption Budgets allow platform teams to partition allocations and set automated caps to prevent unexpected drawdowns.
Cortex XCOR in Action
See how Cortex XCOR optimizes observability at enterprise scale. Cut data noise and slash incident resolution times without slowing your engineers down.
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