Scale AI Operations Without Growing Costs

Chronosphere delivers the scalability and reliability you need with the cost controls you want.

Dashboard displaying metrics for an AI agent service, including costs per request, token consumption, and LLM error rates—helping you scale AI operations and reduce costs with a sidebar for related queries, monitors, and notification settings.

Challenges
Solutions
Proven Results
Resources

Overcoming Observability Challenges in AI and LLM Environments

Traditional observability tools struggle to handle the scale, elasticity, and complexity of AI infrastructure and LLM applications, leading to increased costs, performance degradation, and slower troubleshooting.

Downtime and Latency Damage Customer Trust

Downtime or delays hurt customer trust. Many observability tools can’t meet AI workload demands, causing latency and reliability issues when it matters most.

Traditional Observability Buckles Under Data Load

AI and LLM workloads create huge, unpredictable data volumes. Training drives sustained load, while inference causes sudden spikes during real-time queries.

Runaway Costs Divert Resources From AI Innovation

Without mechanisms to optimize, shape, and filter data based on relevance and usage, companies pay for large amounts of redundant and low-value telemetry - draining budgets that could fuel AI research and development.

The Solution: Chronosphere Observability Platform

Chronosphere empowers AI companies to control observability costs and complexity in high-volume, unpredictable environments. By reducing data volumes by 84% on average, Chronosphere optimizes costs. It supports all telemetry types (metrics, events, logs, traces) from various sources (OpenTelemetry, Prometheus, Datadog, and more) at a scale necessary for AI workloads—with the ability to process over 2B data points per second. Chronosphere delivers the reliability you need with the cost control you want.

Key Use Cases

LLM Inference Monitoring

Monitor the accuracy and bias of your LLM outputs using standardized OpenTelemetry tracing SDKs integrated with Chronosphere. Get alerted instantly if your LLM service begins producing misleading or low-quality responses, protecting your brand and maintaining user trust.

GPU Profiling & Optimization

Leverage open source profiling tools built on pprof and Parca to gain visibility into GPU performance. Avoid expensive GPU black boxes and maintain high utilization during model training, maximizing your hardware investment and accelerating

Scale Seamlessly With AI Workload Demands

Handle massive data volumes from training workloads and unpredictable spikes from inference operations. Process over 2B data points per second without performance degradation.

Find Out How

An illustration of a green cloud with a circuit board, symbolizing scalable and reliable data stores.

A dashboard displays error spans by region, highlighting "us-west-1" with 90%. A tooltip shows current and previous error percentages. Bar and line charts are visible below.

Resolve Issues Faster to Maintain AI Service Quality

Empower developers of all experience levels to quickly identify the source of service issues without deep system knowledge or complex query writing. Differential Diagnosis (DDx) surfaces potential problem areas through a simple point-and-click investigation process, eliminating reliance on system experts.

Learn More About DDx

Control Observability Data Volumes and Costs

Pay only for data that provides value. Our Control Plane enables you to identify and keep only the data your team actually uses. Customers achieve an 84% reduction in telemetry data volume, on average.

Get Control of Your Data