move fast and s/break/make things - rafael schloming, datawire.io
TRANSCRIPT
Microservices: move fast and break make things
(topologies of business logic)Rafael Schloming
CTO
datawire.io
Three components of Microservices
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Technology
ProcessPeople
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Process
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Microservices: Service Oriented Development
What this means
Why it works
How to do it
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Architecture vs Development
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Engineering is Guess & Check
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Cost of Guess/Check
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Cost of Guess/Check
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Mod
ern
Deve
lopm
ent
Punc
h Ca
rds
Moore’s Law
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Cost of Guess/Check
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Serv
ice
O. D
evel
opm
ent
Serv
ice
O. A
rchi
tect
ure
Cloud
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Software vs SaaS
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VS
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Microservices is Service Oriented Development
The output of the process:
● Continuously improving Software as a Service
The process:
● Guess (incremental improvements)● Check (both functionality and health)
The tools:
● Deployment - make small guesses● Observability - measure the impact on health● Resilience - ensure negative health impacts are not catastrophic
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People
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Microservices: Architecture for Distributing Accountability
What this means
Why it works
How to do it
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Cheap Guess/Check merges roles
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Aggregate Health: Christmas Tree Lights
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A B C D EX
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Two Perspectives
C’s problem: Is it worth it? D’s problem: Did I break C?
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C DX
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Two Solutions
Operational Responsibility System Visibility & Resilience
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datawire.io
Microservices is Service Oriented Development
The output of the process:
● Continuously improving Software as a Service
The process:
● Guess (incremental improvements)● Check (functionality, individual health, overall toxicity)
The tools:
● Deployment - make small guesses● Observability - measure the impact on individual health & overall toxicity● Resilience - ensure negative impact is not catastrophic and doesn’t cascade
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Technology
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Microservices Technology: SoD Scaffolding
Requirements
Design
Implementation
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Early (Small/Shallow Topologies)
Deployment
● Fast pipeline (minimum time from git -> cloud)● Self service provisioning
Observability
● Service level metrics (throughput, latency, availability)
Resilience
● Incremental rollout
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Later (Large/Deep Topologies)
Deployment
● Fast pipeline (minimum time from git -> cloud)● Self service provisioning
Observability
● Service level metrics & logging (throughput, latency, availability)● Trace level visibility (profiling, logging, stack traces)
Resilience
● Incremental rollout● Timeouts, Deadlines, Retries, Budgets, Circuit Breakers, Rate Limiting
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Microservices Scaffolding Design
Resource Orchestration:
● PaaS● Cluster Managers (kubernetes and friends)
Traffic Management
● L7 Sidecar● SDK
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Example Implementation Options
Resource Orchestration
● Kubernetes, Mesos, AWS ECS, ...
Traffic Management (L7 Sidecar)
● Envoy, SmartStack, L8d, ...
Traffic Management (SDK)
● gRPC, finagle, ...
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For more information...
Resources:
● https://www.datawire.io/guide● https://www.microservices.com● https://eng.lyft.com/announcing-envoy-c-l7-proxy-and-communication-bus-925
20b6c8191● https://engineeringblog.yelp.com
Contact:
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