Cloud Native Application Observability

Automate triage, compress MTTR, and control spend with AI-driven observability.

Challenges

The Complexities of Cloud-Native Application Monitoring

Dynamic microservices and rapid code updates degrade system visibility, complicate incident triage, and drive up telemetry bills.
Inflexible sampling leaves debugging to chance
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Inflexible sampling leaves debugging to chance

Traditional monitoring relies on rigid trace sampling to cut costs, frequently dropping the critical traces needed to debug production failures.
AI-generated code accelerates system drift
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AI-generated code accelerates system drift

AI coding tools speed up deployments but erode developer system context. Manually correlating metrics, logs, and traces in unfamiliar code inflates MTTR.
Noisy alerts mask actual user experience
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Noisy alerts mask actual user experience

Traditional monitoring triggers alerts for minor service faults that don't impact end users, creating fatigue and masking critical regressions.
Solutions

Take Control of Application Performance and Telemetry Costs

Cortex® XCOR™ combines AI workflows with comprehensive service views to streamline troubleshooting while keeping spend predictable.

Automate complex triage using AI Investigations

AI Investigations reasons across system topology, operational context, and incident signals to pinpoint likely root causes and compress MTTR.

Streamline daily operations with Operator

Replace static dashboards with conversational AI. Operator lets teams query telemetry, troubleshoot issues, and execute tasks fast.

Unify telemetry with Service Views

Cortex XCOR normalizes custom business-centric telemetry into core Service Views, giving engineers and AI complete operational context.

Filter telemetry noise using Optimization Engine

The Optimization Engine filters low-value logs, metrics, and traces at ingestion, capturing only valuable data to control telemetry spend.

Protect user experience with native SLOs

Track real-time error budget burn rates and SLOs directly in telemetry workflows to prevent noisy alerts and page only when targets are at risk.

Key Capabilities

Capabilities Built for DevOps and SRE Teams

Cortex XCOR simplifies complex operational workflows, streamlines telemetry collection, and prevents cost overruns.
AI Operator

AI Operator

Tune alerts, query data, build dashboards, and more — all using natural language. The AI Operator is embedded throughout Cortex XCOR.
Auto Service Discovery & Views
Auto Service Discovery & Views

Auto Service Discovery & Views

Cortex XCOR automatically discovers APIs, dependencies, and microservices. Curated views seamlessly map custom telemetry alongside RED metrics.
Real-User Monitoring (RUM) & Synthetics
Real-User Monitoring (RUM) & Synthetics

Real-User Monitoring (RUM) & Synthetics

Capture user sessions to monitor web vitals. Unify frontend events with distributed traces to pinpoint bottlenecks across browser, network, or app.
Differential Diagnosis (DDx)
Differential Diagnosis (DDx)

Differential Diagnosis (DDx)

Compare degraded telemetry against healthy baselines across metrics and traces to surface exact state changes and isolate root causes.
Native Service Level Objectives (SLOs)
Native Service Level Objectives (SLOs)

Native Service Level Objectives (SLOs)

Build, track, and maintain SLOs automatically. Cortex XCOR calculates error budget burn rates in real time, alerting only when reliability is at risk.
Telemetry Optimization Engine
Telemetry Optimization Engine

Telemetry Optimization Engine

Filter out unused and low value of telemetry before storage. Manage ingestion across logs, traces, and metrics with custom rules and unified budgets.
Benefits

Strategic Value for DevOps and SRE Teams

Accelerate incident resolution, slash telemetry overhead, and maintain system reliability without vendor lock-in.
Compress MTTR and Reduce Downtime
Compress MTTR and Reduce Downtime

Compress MTTR and Reduce Downtime

AI Investigations correlate signals automatically to isolate root causes in minutes, not hours.
Control Ingestion and Storage Costs
Control Ingestion and Storage Costs

Control Ingestion and Storage Costs

Optimize telemetry data based on value delivered to keep spend in check and predictable.
Eliminate Tool Silos and Reduce Alert Fatigue
Eliminate Tool Silos and Reduce Alert Fatigue

Eliminate Tool Silos and Reduce Alert Fatigue

Unify telemetry on one platform and use SLOs to alert only when error budgets are threatened.
Future-Proof Stack with Open Standards
Future-Proof Stack with Open Standards

Future-Proof Stack with Open Standards

Ingest OpenTelemetry natively to ensure vendor-neutral flexibility as your operations scale.

Frequently Asked Questions

Operator is an embedded AI operational engine that replaces static dashboards with conversational operational assistance. It interprets natural language requests and directs specialized agents to execute operational tasks and complex troubleshooting workflows, lowering operational toil for SRE and IT teams.
When an alert triggers, Investigations launches automatically and reasons over XCOR’s Operational Fabric—combining system topology, custom and standard telemetry, and operational knowledge—to deliver evidence-based root cause analysis to compress MTTR.
We offer an easy-to-deploy Cortex XCOR XDOT Collector built entirely on OpenTelemetry standards, while fully supporting the standard upstream OTel collector.
Because Cortex XCOR is fully compatible with OpenTelemetry, it natively supports all major programming languages and frameworks—including Java, Go, Python, Node.js, .NET, and Rust. It automatically auto-discovers dependencies, APIs, and microservice connections out of the box.