Distributed Tracing: Understand how your systems work together

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Distributed Tracing Understand how your components work together

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About me José Carlos Chávez ● Software Engineer at Typeform focused on the aggregate of responses services. ● Zipkin core team and open source contributor for Observability projects.

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Distributed Systems

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Distributed systems A collection of independent components appears to its users as a single coherent system. Characteristics: ● Concurrency ● No global clock ● Independent failures

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Water heater Gas supplier Cold water storage tank Shutoff valve First floor branch Tank valve 爆$❄#☭ Distributed systems

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Auth service Images service Videos service DB2 DB3 DB4 TCP error (2003) 500 Internal Error 500 Internal Error GET /media/e5k2 API Proxy Distributed systems: Understanding failures DB1 Media API

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Water heater Gas supplier Cold water storage tank Shutoff valve First floor branch Tank valve 爆$❄#☭ I AM HERE! First floor distributor is clogged! Distributed systems: Understanding failures

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We do have that, it is called logs!

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API Proxy Auth service Media API Images service Videos service DB2 DB3 DB4 TCP error (2003) 500 Internal Error 500 Internal Error GET /media/e5k2 Logs & Concurrency DB1

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[24/Oct/2017 13:50:07 +0000] “GET /media HTTP/1.1” 200 … **0/13548” [24/Oct/2017 13:50:07 +0000] “GET /media HTTP/1.1” 200 … **0/23948” [24/Oct/2017 13:50:08 +0000] “GET /media HTTP/1.1” 200 … **0/12396” [24/Oct/2017 13:50:07 +0000] “GET /videos HTTP/1.1” 200 … **0/23748” [24/Oct/2017 13:50:07 +0000] “GET /images HTTP/1.1” 200 … **0/23248” [24/Oct/2017 13:50:07 +0000] “GET /auth HTTP/1.1” 200 … **0/26548” [24/Oct/2017 13:50:07 +0000] “POST /media HTTP/1.1” 200 … **0/13148” [24/Oct/2017 13:50:07 +0000] “GET /media HTTP/1.1” 200 … **0/2588” [24/Oct/2017 13:50:07 +0000] “GET /auth HTTP/1.1” 500 … **0/3248” [24/Oct/2017 13:50:07 +0000] “POST /media HTTP/1.1” 200 … **0/23548” [24/Oct/2017 13:50:07 +0000] “GET /images HTTP/1.1” 200 … **0/22598” [24/Oct/2017 13:50:07 +0000] “GET /videos HTTP/1.1” 200 … **0/13948” ... ? ? Logs & Concurrency

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Water heater Gas supplier Cold water storage tank Shutoff valve First floor branch Tank valve 爆$❄#☭ I AM HERE! First floor distributor is clogged! Distributed systems: Understanding failures

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Distributed Tracing to unclog your pipes

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API Proxy Media API Auth Videos Images Time 500 error Distributed tracing [1508410442] no cache for resource, retrieving from DBc TraceID d52d38b69b0fb15efa

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Distributed Tracing: What answers I get? ● What services did a request pass through? ● What occurred in each service for a given request? ● Where did the error happen? ● Where are the bottlenecks? ● What is the critical path for a request? ● Who should I page?

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Distributed Tracing & friends Credits: Peter Bourgon

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Benefits of Distributed Tracing ● (almost) Immediate feedback ● System insight, clarifies non trivial interactions ● Visibility to critical paths and dependencies ● Understand latencies ● Request scoped, not request’s lifecycle scoped.

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Trace’s Anatomy ● A trace shows an execution path through a distributed system ● A span in the trace represents a logical unit of work (with a start and end) ● A context includes information that should be propagated across services ● Tags and logs (optional) add complementary information to spans. /things auth.Auth Time GET /videos mysql.Get T R A C E

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Elements of distributed tracing Credits: Nic Munroe Leg 1: inbound propagation Leg 2: outbound propagation Leg 3: in-process propagation Distributed Tracing

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Leg 1: Inbound propagation When your service process a request or consume a message. API Proxy Media API GET /media TraceID: fAf3oXL6DS SpanID: dZ0xHIBa1A ...

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Leg 2: Outbound propagation When your service makes an outbound call to another service Media API Video service GET /videos TraceID: fAf3oXL6DS ParentID: dZ0xHIBa1A SpanID: y74fr5udj http/get

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mysql.Query redis.Get Leg 3: In process propagation When performing an operation inside the service Media API Cache service Images service GET /images

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API Proxy Media API Auth Videos Images Time 500 error Distributed tracing [1508410442] no cache for resource, retrieving from DBc TraceID d52d38b69b0fb15efa

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Any overhead? For users: ● Observability tools are meant to be unintrusive ● Sampling reduces overhead ● (Don’t) trace every single operation For developers: ● Not all libraries are ready to plug instruments ● Instrumentation can be delegated to common frameworks

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Introducing Apache Zipkin

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Apache Zipkin Based on BigBrotherBird (B3) and inspired on Google Dapper (2010). It was open sourced by Twitter (2012) and joined Apache Incubator on September 2018. ● Mature tracing model emerged from users’ needs. ● Used by large companies like Netflix, SoundCloud and Yelp but also not too big ones. ● Strong community: ○ @zipkinproject ○ gitter.im/openzipkin

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Service (instrumented) Transport Collect spans Collector API UI Storage DB Visualize Retrieve data Store spans http/kafka/grpc Receive spans Deserialize and schedule for storage Cassandra/MySQL/ElasticSearch Zipkin: architecture