monitoring microservices @ sf microservice meeting

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Monitoring Microservices [email protected] @tom_wilkie

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Page 2: Monitoring Microservices @ SF Microservice meeting
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VisualisationMonitoring Tracing

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Monitoring

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Traditional 3-tier architectureIncoming traffic

Load balancers

Application servers

Database & replica

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Microservice architecture

Public APIWeb UI

NoSQL serversDatabase

Message Broker

Services

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Microservices should be treated like cattle not pets

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USE Method* - for every resource, check: • utilization, • saturation, and • errors

RED Method - for every service, check request: • rate, • error (rate), and • duration (distributions)

* http://www.brendangregg.com/usemethod.html

An alternative view

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Monitoring

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Visualisation

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Weave Scope

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Connection Tracking

# cat /proc/net/tcp

# conntrack -E -p tcp

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Demo time

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Visualisation

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VisualisationMonitoring Tracing

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@weaveworks github.com/weaveworks

Questions?http://weave.works/product/scope

[email protected] @tom_wilkie

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Tracing

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Distributed Tracing

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Not a new topic

• Lots of literature • Existing open source

projects • e.g. Zipkin, originally from

Twitter

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• Challenge: detecting causality between incoming and outgoing requests

• Existing solutions require propagation of some unique ID (dapper, zipkin)

• This requires application-specific modifications

some service

incomingrequest

outgoingrequests

?

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Can this be done without application modifications?

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Demo time

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Tracing