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2017 Microservices Practitioner Virtual Summit - Opening Keynote: Trends in Microservices - Richard Li

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Page 1: 2017 Microservices Practitioner Virtual Summit - Opening Keynote: Trends in Microservices - Richard Li
Page 2: 2017 Microservices Practitioner Virtual Summit - Opening Keynote: Trends in Microservices - Richard Li

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Thanks for joining us.

Page 3: 2017 Microservices Practitioner Virtual Summit - Opening Keynote: Trends in Microservices - Richard Li

What best describes your role?

Other 15%

DevOps Engineer 12%

Platform Engineer 15%

Engineering Management 25%

Developer 33%

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https://gitter.im/datawire/summit

#msvsummit

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Monday, July 24

1 PM - 1:30 PM EDT Opening Keynote: Trends in Microservices Richard Li, Datawire

1:30 PM - 2:30 PM EDT Microservices at Squarespace Kevin Lynch & Doug Jones, Squarespace

Tuesday, July 25

10 AM - 11 AM EDT How to Avoid Creating a GitHub Junkyard Lauri Apple, Zalando

1 PM - 2 PM EDT Ancestry’s Journey towards Microservices, Containerization, and Kubernetes Paul MacKay, Ancestry

Wednesday, July 26

1 PM - 2 PM EDT Move fast, make things: how developers can successfully adopt microservices Rafael Schloming, Datawire

Thursday, July 27

1 PM - 2 PM EDT The Mechanics of Deploying Envoy at Lyft Matt Klein, Lyft

Page 6: 2017 Microservices Practitioner Virtual Summit - Opening Keynote: Trends in Microservices - Richard Li
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Microservices

Single Release Cycle of Monolithic Apps

Multiple, Independent Release Cycles

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Five trends in microservices adoption

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reliability, availability, scalability

Trend 1: The evolving role of operations.

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reliability, availability, scalability

developer productivity

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• dev environment

• app resilience • CD pipeline • app monitoring • canary

deployment • …

Platform Engineers: common tools & infrastructure for the rest of the dev team.

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TODAY! 1:30pm EDT

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Trend 2: It’s a polyglot world (and really, it always has been).

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It’s very hard to build an effective microservices architecture with a single language stack.

Each service might be written in a single language, but the library versions used are different

• If you try to make them the same, you end up with a distributed monolith

Different languages are good at different things, e.g., Python for data analysis is a common use case

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Trend 3: The Service Mesh

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Service Mesh

Service

Service

Service

Service

Service

Service

Resilience

Observability

Security

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A service mesh lets services communicate with each other.

Hystrix, Ribbon, Eureka (Library approach)

AirBnb SmartStack (Proxy approach)

Envoy / Istio (Proxy)

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A service mesh lets services communicate with each other.

Envoy / Istio

Thursday, 1pm EDT

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I'm running a service mesh in production 3%

I'm actively evaluating service meshes 8%

I've read about them 32% Not at all

57%

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Trend 4: Open source infrastructure

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8%

8%

7%

19%58%

We are not using Kubernetes

We have a dev/test cluster for evaluation

We have a dev/test cluster under active use

We are running a few production services on Kubernetes

We’re mostly running our production on Kubernetes

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Trend 5: Bottoms up adoption

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“We’re going agile” “We’re adopting J2EE” “We’re adopting the cloud”

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“We’re going agile” “We’re adopting J2EE” “We’re adopting the cloud”

“This is taking forever, I’m just going to start with an empty repo.”

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“This is taking forever, I’m just going to start with an empty repo.”

Wednesday, 1pm EDT

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Thank you! And introducing Squarespace.