Search Results for "file::rsyncp"

Zipkin is a distributed tracing system. It helps gather timing data needed to troubleshoot latency problems in service architectures. Features include both the collection and lookup of this data. If you have a trace ID in a log file, you can jump directly to it. Otherwise, you can query based on attributes such as service, operation name, tags and duration. Some interesting data will be summarized for you, such as the percentage of time spent in a service, and whether or not operations failed...

... 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. DeepFlow collects profiling data at a cost of below 1% with Zero Code, plots OnCPU/OffCPU function call stack flame graphs, and locates Full Stack performance bottleneck in the application.

This repository is for active development of the Azure SDK for Python. For consumers of the SDK we recommend visiting our public developer docs or our versioned developer docs. For your convenience, each service has a separate set of libraries that you can choose to use instead of one, large Azure package. To get started with a specific library, see the README.md (or README.rst) file located in the library's project folder. Last stable versions of packages that have been provided for usage...