Apache SkyWalking

Pinpoint Service Mesh Critical Performance Impact by using eBPF

Introducing performance analysis in production with SkyWalking Rover.

Background

Apache SkyWalking observes metrics, logs, traces, and events for services deployed into the service mesh. When troubleshooting, SkyWalking error analysis can be an invaluable tool helping to pinpoint where an error occurred. However, performance problems are more difficult: It’s often impossible to locate the root cause of performance problems with pre-existing observation data. To move beyond the status quo, dynamic debugging and troubleshooting are essential service performance tools. In this article, we’ll discuss how to use eBPF technology to improve the profiling feature in SkyWalking and analyze the performance impact in the service mesh.

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Apache SkyWalking application performance monitoring tool
Apache SkyWalking, Open Source, Tetrate

SkyWalking 8.4 provides infrastructure monitoring for VMs

Apache SkyWalking– the APM tool for distributed systems–  has historically focused on providing observability around tracing and metrics, but service performance is often affected by the host. The newest release, SkyWalking 8.4.0, introduces a new feature for monitoring virtual machines. Users can easily detect possible problems from the dashboard– for example, when CPU usage is overloaded, when there’s not enough memory or disk space, or when the network status is unhealthy, etc.

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SkyWalking service topology
Apache SkyWalking, Observability, Open Source

Observability at scale: SkyWalking it is!

SkyWalking, a top-level Apache project, is the open source APM and observability analysis platform that is solving the problems of 21st-century systems that are increasingly large, distributed, and heterogenous. It’s built for the struggles system admins face today: To identify and locate needles in a haystack of interdependent services, to get apples-to-apples metrics across polyglot apps, and to get a complete and meaningful view of performance. 

SkyWalking is a holistic platform that can observe microservices on or off a mesh, and can provide consistent monitoring with a lightweight payload.

Let’s take a look at how SkyWalking evolved to address the problem of observability at scale, and grew from a pure tracing system to a feature-rich observability platform that is now used to analyze deployments that collect tens of billions of traces per day. 

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Apache SkyWalking application performance monitoring tool
Apache SkyWalking, Observability, Open Source

3X performance improvement in SkyWalking’s recent 6.1 release

Apache SkyWalking, the observability analysis and application performance monitoring (APM) tool, shattered its own performance record with its recent 6.1 release.

Designed especially for microservices, cloud native and container based architecture, SkyWalking provides distributed tracing, service mesh telemetry analysis, metric aggregation and workload visualization.

Following SkyWalking’s integration with Istio and Envoy-based Service Mesh at the end of 2018, our colleague, Hongtao Gao, set a performance baseline with his blog post SkyWalking performance in Service Mesh scenario.

Using an 8 CPU, 16GB VM test environment, SkyWalking was found to support 25K telemetry data per second, or 100K data per second in a 3-node cluster using elasticsearch as storage.

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