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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
SkyWalking Architecture
SkyWalking Architecture
● The architecture has four parts
● (1) Probes
– Collect data and reformat it
– For SkyWalking requirements
– Different probes support different sources
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
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
SkyWalking Architecture
● (4) User Interface (UI)
– Highly customizable
– Web based interface
– End users can
● Visualize data
● Manage data
SkyWalking Users
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
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
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
SkyWalking Language Agents
● Micro service meshes supported
– Istio
– Envoy
● Multiple language agents supported
– Java
– .Net Core
– PHP
– NodeJS
– Golang
– LUA agents
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
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

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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
  • 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
  • 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