Apache SkyWalking

1. What Is Apache SkyWalking ? ● A performance monitoring tool for distributed systems ● An open source observability platform ● Apache 2.0 license ● Collect, analyse, aggregate and visualize data ● Provides auto instrument agents for services ● Maintain a clear view of your distributed systems ● For cloud native, micro service and ● Container-based (Docker, K8s, Mesos) systems

2. SkyWalking Architecture

3. SkyWalking Architecture ● The architecture has four parts ●(1) Probes – Collect data and reformat it – For SkyWalking requirements – Different probes support different sources

4. SkyWalking Architecture ●(2) Platform back end – Supports data aggregation, analysis – Drives process flow from probes to the UI – Analysis includes ●SkyWalking natives traces and metrics, 3rd party, ●Including Istio and Envoy telemetry, Zipkin trace format – Can customize aggregation and analysis – Using Observability Analysis Language for ●Native metrics ●Meter System for extension metrics

5. SkyWalking Architecture ●(3) Storage – Houses SkyWalking data – Through an open/pluggable interface – Choose an existing implementation such as ●ElasticSearch, H2, ●MySQL cluster managed by Sharding-Sphere – Implement your own

6. SkyWalking Architecture ●(4) User Interface (UI) – Highly customizable – Web based interface – End users can ●Visualize data ●Manage data

7. SkyWalking Users

8. SkyWalking Probe Protocols ● Probe protocols, how agents send/receive – Collected metrics data and traces – The formats of each entity ● Cross Process Propagation Headers Protocol (and ) ● Cross Process Correlation Headers Protocol –Are in wire data format – Agent/SDK usually uses HTTP/MQ/HTTP2 headers – To carry the data with RPC request – Remote agent will receive this in a request handler – And bind the context with this specific request

9. SkyWalking Probe Protocols ● Trace Data Protocol – Is out of wire data – Agent/SDK uses this to send traces – And metrics to Skywalking – Or other compatible backend

10. SkyWalking Query Protocol ● The backend provides query capability ● To SkyWalking UI and others ● Query capabilities depends on analysis metrics ● These queries are based on GraphQL – A query language for the API – A server-side runtime for executing queries – By using a type system you define for your data – Isn't tied to any specific database – Or storage engine – Backed by your existing code and data

11. SkyWalking Language Agents ● Micro service meshes supported – Istio – Envoy ● Multiple language agents supported – Java – .Net Core – PHP – NodeJS – Golang – LUA agents

12. Available Books ● See “Big Data Made Easy” Apress Jan 2015 – See “Mastering Apache Spark” ● Packt Oct 2015 – See “Complete Guide to Open Source Big Data Stack ● “Apress Jan 2018” – ● Find the author on Amazon www.amazon.com/Michael-Frampton/e/B00NIQDOOM/ – Connect on LinkedIn ● www.linkedin.com/in/mike-frampton-38563020 –

13. Connect ● Feel free to connect on LinkedIn –www.linkedin.com/in/mike-frampton-38563020 ● See my open source blog at open-source-systems.blogspot.com/ – ● I am always interested in – New technology – Opportunities – Technology based issues – Big data integration