DeepFlow

DeepFlow is an advanced observability platform designed for cloud-native and AI applications, offering zero-instrumentation, full-stack visibility to help developers and operations teams monitor, troubleshoot, and optimize complex distributed systems. Leveraging eBPF (extended Berkeley Packet Filter) technology and WebAssembly (Wasm), DeepFlow enables zero-code data collection of application performance metrics, distributed tracing, continuous profiling, and network performance monitoring across any language and infrastructure. Its SmartEncoding and AutoTagging mechanisms provide efficient storage and rich metadata tagging of observability data, reducing overhead while eliminating data silos. DeepFlow integrates seamlessly with popular observability stacks such as Prometheus, OpenTelemetry, SkyWalking, and Pyroscope, supporting SQL, PromQL, and OTLP APIs for data querying.

Key Features

• Universal service map built with zero code instrumentation, covering application, third-party, and cloud-native infrastructure services across all languages.
• Zero-intrusion distributed tracing for any request with full-stack metrics and detailed file I/O event collection.
• Continuous profiling with less than 1% system overhead, generating detailed flame graphs to identify performance bottlenecks at application, library, kernel, and hardware levels.
• SmartEncoding and AutoTagging for efficient, scalable storage and correlated observability data with rich contextual metadata.

Use Cases

• Real-time application monitoring and troubleshooting of microservices architectures in production environments without code changes.
• Performance profiling and root cause analysis across cloud-native infrastructure and AI workloads for DevOps and SRE teams.
• Integration as a backend data source for comprehensive observability platforms, enabling advanced querying and visualization in existing tech stacks.