Chronosphere
Chronosphere
Observability at Scale
Gartner Magic Quadrant Leader in observability — bringing cloud-native telemetry, AI-powered analysis, and real-time cost control to the Palo Alto Networks platform.
Acquisition
Chronosphere Joins Palo Alto Networks
A $3.35B acquisition bringing Gartner MQ Leader observability to the platform.
Strategic rationale: Observability is the missing link between infrastructure operations and security operations. By integrating Chronosphere's telemetry capabilities with Cortex and XSIAM, Palo Alto Networks connects "what's happening" (observability) with "is it safe" (security) — enabling faster detection, root-cause analysis, and automated remediation.
Capabilities
What Chronosphere Brings
Cloud-native observability designed for modern, ephemeral infrastructure.
Cloud-Native Observability
Built for Kubernetes, microservices, and serverless from the ground up. Chronosphere collects, stores, and analyzes metrics, traces, and logs across distributed architectures without the cardinality explosions that plague legacy monitoring tools.
Metrics
High-cardinality time series at scale
Traces
Distributed tracing across services
Logs
Structured and unstructured log analysis
Telemetry Pipeline
Chronosphere's Telemetry Pipeline is the game-changer. It intelligently routes, aggregates, and filters telemetry data before it hits storage — dramatically reducing costs and noise while preserving the signals that matter.
Real-Time Cost & Value Control
Unlike legacy observability tools that charge by data volume with no controls, Chronosphere gives teams real-time visibility into observability costs and the value each data stream delivers. Set quotas by team or service, identify low-value high-cost metrics, and optimize spend without sacrificing coverage. This addresses the #1 pain point with tools like Datadog and Splunk Observability — unpredictable and escalating costs.
Deep Dives
Capability Deep Dives
Explore each observability pillar in detail — click to expand.
100% Prometheus and PromQL compatible with native OpenTelemetry ingestion. Handles hundreds of millions of data points per second with high cardinality management that identifies and controls cardinality explosions — the #1 scaling challenge for cloud-native metrics.
High-Cardinality Handling
Aggregate, downsample, remove high-cardinality labels without code changes
Query Accelerator
Auto-pre-aggregation for faster dashboards and alerts — import Grafana dashboards directly
Metrics Usage Analyzer
Utility scoring, cost identification, optimization recommendations per metric stream
Announced at Open Source Summit 2025 to address the 250% YoY log growth problem. Filter low-value logs, remove whitespace, convert logs to metrics in clicks.
- Logs Usage Analyzer — usage and cost tracking with proactive volume growth anticipation
- PII Redaction — redact sensitive data from logs in-flight before leaving your environment
- Flexible Routing — route to low-cost object storage with rehydration capability; JSON normalization from raw text
Distributed tracing with span-level analysis and dynamic head-and-tail sampling with flexible rate adjustments.
Differential Diagnosis (DDx)
Guided, queryless troubleshooting that takes high-level metric anomalies and drills into detailed trace analysis. Reveals what's changing, what's not, and where to focus — correlating across metrics, logs, and traces. Repeatable and scalable: lets any developer troubleshoot like a seasoned expert on day one. 50% reduced troubleshooting time (customer-reported).
Built on the Fluent Bit foundation (CalyPtia/Fluent Bit acquisition). Stream-process, transform, enrich, and reduce telemetry data in-flight before it hits any destination. Remains available as a standalone solution post-PANW acquisition.
Collect From
- • Prometheus, OpenTelemetry, FluentD
- • Splunk HEC, Telegraf, Okta, Mandiant
- • HTTP API, TCP, Vercel
Route To
- • Chronosphere, Datadog, CrowdStrike
- • Splunk, Amazon S3, Azure Blob
- • ClickHouse, Apache Kafka
Speeds up SIEM/observability migrations by up to 50% • Redacts PII from logs before leaving environment • Requires 20x less infrastructure than legacy alternatives
The Control Plane is Chronosphere's core differentiator. Containerized workloads generate 10–100x more data than traditional VMs — the Control Plane solves the resulting cost and noise problem with a four-phase cycle:
1. Analyze
Auto-assigns utility scores to all incoming data based on usage frequency and consumer identity
2. Refine
Aggregates, downsamples, drops non-valuable metrics, filters logs, converts logs to metrics
3. Operate
Query Accelerator pre-aggregates data; Query Scheduler prevents query crowding
4. Govern
Capacity allocation via quotas by team or service; prevents cardinality and log volume spikes
84%
Average data volume reduction after Control Plane deployment
Customer Evidence:
- • DoorDash: Automated 14,000 SLOs with full endpoint coverage without manual SLO creation
- • Robinhood: 5x improvement in reliability, 4x faster issue resolution
- • Fintech customer: 70% reduction in observability costs, 14,000 engineering hours saved annually
Forrester TEI Study: $7.9M benefits over 3 years • 165% ROI • <6 month payback • 75% fewer reliability incidents • 84% average data volume reduction
Cortex XSIAM Integration: Chronosphere's Telemetry Pipeline becomes the data ingestion/preprocessing layer for XSIAM — filtering low-value noise before it reaches XSIAM, reducing data ingestion costs by 30%+. Requires 20x less infrastructure, enabling customers to scale security posture without scaling spending. Long-term vision: observe AI workloads (models, agents, pipelines) → detect anomalies → autonomously remediate via AgentiX.
AI-Powered
AgentiX Integration
Autonomous AI agents that find and fix issues before they impact users.
From Detection to Resolution — Autonomously
By integrating Chronosphere observability with Palo Alto Networks' AgentiX agentic AI framework, the platform can automatically detect anomalies in application behavior, correlate them with security telemetry, and initiate remediation — all without human intervention.
Anomaly detected in metrics/traces
AI agent investigates root cause
Cross-references security telemetry
Automated fix deployed
Leadership
Martin Mao
SVP, General Manager — Observability
Chronosphere co-founder Martin Mao joins Palo Alto Networks to lead the observability business unit. His experience scaling observability at Uber and building Chronosphere ensures continuity of vision and execution.
Scoping
Sizing the Observability Opportunity
Key dimensions to scope a Chronosphere engagement.
Current Tools
What are they using today? Datadog, Splunk Observability, New Relic, Grafana/Prometheus, Dynatrace? Pain points typically center on cost and scale.
Log Volume
Daily log/metric volume in GB or TB. What percentage is useful vs. noise? Telemetry Pipeline can cut 30%+ of noise immediately.
Monitoring Scope
What's monitored? Cloud infrastructure, K8s clusters, microservices, databases, CI/CD pipelines? How many services and hosts?
Discovery
Observability Discovery Questions
Uncover cost pain and operational gaps.
Why ask: Observability cost overruns are the #1 pain point. Datadog bills have doubled or tripled year-over-year for many enterprises. Chronosphere's Telemetry Pipeline and cost controls directly address this.
Listen for: "It keeps going up" or "We got surprise bills" — strong Chronosphere play. "We've had to cut data to stay on budget" — Telemetry Pipeline preserves signal while cutting cost.
Why ask: Most organizations estimate only 30-50% of their telemetry is actionable. Chronosphere's Telemetry Pipeline automatically identifies and routes low-value data to cheaper storage tiers.
Listen for: "We collect everything just in case" — classic over-collection. "We don't know" — opportunity for a pipeline assessment.
Why ask: Mean time to root cause (MTTRC) reveals operational maturity. AgentiX integration enables AI-driven root cause analysis that drastically reduces investigation time.
Listen for: "Hours" or "It depends on who's on call" — strong case for AI-assisted investigation. "We war-room it" — expensive human-intensive process.
Why ask: This is the PAN differentiator. Most observability tools exist in a silo from security. Chronosphere + XSIAM bridges the gap between "the app is slow" and "the app is under attack."
Listen for: "No, those are separate teams and tools" — platform consolidation opportunity. "We send alerts to our SIEM" — show the native integration advantage.