DeepFlow

DeepFlow

DeepFlow

软件

软件描述

通过零代码 eBPF、高级分析和 10 倍存储效率,统一您的云原生监控。

官方网站

访问软件的官方网站了解更多信息

官方认证

deepflow.io

安全链接HTTPS

什么是 DeepFlow?

Instant observability for cloud-native applications. Universal Map for Any Service DeepFlow provides a universal map with Zero Code by eBPF for production environments, including your services in any language, third-party services without code and all cloud-native infrastructure services. In addition to analyzing common protocols, Wasm plugins are supported for your private protocols. Full Stack golden signals of applications and infrastructures are calculated, pinpointing performance bottlenecks at ease. Distributed Tracing for Any Request Zero Code distributed tracing powered by eBPF supports applications in any language and infrastructures including gateways, service meshes, databases, message queues, DNS and NICs, leaving no blind spots. Full Stack network performance metrics and file I/O events are automatically collected for each Span. Distributed tracing enters a new era: Zero Instrumentation. Continuous Profiling for Any Function DeepFlow collects profiling data at a cost of below 1% with Zero Code, plots OnCPU/OffCPU function call stack flame graphs, locates Full Stack performance bottleneck in application, library and kernel functions, and automatically relates them to distrubuted tracing data. DeepFlow can even analyze code performance through network profiling under old version kernels (2.6+). Seamless Integration with Popular Stack DeepFlow can serve as storage backed for Prometheus, OpenTelemetry, SkyWalking and Pyroscope. It also provides SQL, PromQL and OLTP APIs to work as data source in popular observability stacks. It injects meta tags for all obervability signals including cloud resource, K8s container, K8s labels, K8s annotations, CMDB business attributes, etc., eliminating data silos. Performance 10x ClickHouse SmartEncoding injects standardized and pre-encoded meta tags into all observability data, reducing storage overhead by 10x compared to ClickHouse String or LowCard method. Custom tags and observability data are stored separately, making tags available for almost unlimited dimensions and cardinalities with uncompromised query experience like BigTable.

主要功能

下载与相关链接

安全提示
⚠️

安全提醒

点击下方链接将跳转到第三方网站,请确保来源安全,建议优先从官方网站下载。