This talk will explain key principles, costs, and benefits of microservices and show via a series of live demos and working examples how to extend a Python application to quickly and easily benefit from migrating to a microservices architecture.

1. An Illustrated Guide to
Microservices
Rafael Schloming
Co-Founder & Chief Architect

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This is a Python talk… really...
1. Datawire is a python shop
2. We like python so much, we use it to write code in other languages (yes, we have
a compiler written in python)
3. Python & Microservices complement each other really well
4. We will write an actual microservice in python, just hold out for it
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What’s a Microservice?

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Common Microservice Definitions
It’s a service that is...
● Small
● Self contained
● Narrow in scope
● Bounded context
● Independent
● Loosely coupled
Correct, but incomplete...
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Common Microservice Definitions (as applied to Legos)
A piece of plastic that is…
● Small
● Self contained
● Narrow in scope
● Bounded context
● Independent
● Loosely coupled
What’s missing…?
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Combine to build AWESOME!
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What do you get when you combine Microservices?
Topologies!
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Death Star Topology

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Wait, why do I want a death star?
Maybe you don’t, but your CXO does
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Organizational Scale
AgilityVelocity

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Topologies
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Topologies have always been a thing
● Topologies aren’t new, they have always been the bread and butter of distributed
systems design
● In fact we’ve all been stuck living in the same topology for a while now
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Topologies are powerful
Information flows through topologies like water through a pipe or current on a wire
Probably the most important factor in the performance of a distributed system
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Topologies are the purview of the Elite
Architects define the topology
Developers get to plug in business logic in a few predefined places
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Microservices bring topology to Developers
Developers define the topology
Business logic is distributed rather than being centralized
The topology changes and grows much more quickly
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Topologies can solve a lot of problems
Integration
Operational Scale
Reliability
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Operational Scale (Linear Topology)
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Ingest Source of Truth Transform Present
Template for many data driven businesses…

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Operational Scale (Linear Topology)
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Ingest Source of Truth Transform Present
Template for many data driven businesses…
Network Disk Disk + CPU Network + CPU

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Scale Components Independently
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Ingest Source of Truth Transform Present
Template for many data driven businesses…
Network Disk Disk + CPU Network + CPU

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Integration (Fan Out Topology)
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Reliability
Software Bug
Centralized Business
Logic can be a Single
Point of Failure
Operational Failure

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Reliability
Software Bug
Decentralize Business Logic to
Isolate Failures

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Organizational Scale
Software Bug
Decentralized Business Logic Means
● Multiple Teams
● Smaller Codebases
● Ramp up Developers Faster

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Can topologies give me a death star?
They help, but not quite… you need to build topologies quickly!
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Organizational Scale
AgilityVelocity

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Microservices vs SOA
(Service Oriented Architecture)
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Common Explanations
Both are topologies of services
● Fine grained SOA
● Integration pattern vs application components
● Organizational factors...
We need a better definition…
● These explanations ignore the process that yields the topology
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Architecture and Development are different processes
Both can yield topologies of services, but SOA won’t build your death star. For that you
need agile topologies
Microservices: Service Oriented Development
Architecture:
● Lots of up front thinking
● Slow iteration cycle
● Months/years until you get feedback
Development:
● Experimental
● Rapid iteration cycle
● Minutes/hours until you get feedback
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You need a new Mindset and new Tooling
So, how do I build Agile Topologies?
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Mindset
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What’s the new Mindset?
The role of architecture changes
● An architect’s job is to enable developers, not confine them
● Architecture teams -> developer infrastructure, developer happiness, …
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Up Front Thinking Experimentation

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Tooling
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What tools enable experimentation & rapid iteration?
You need three things when you decentralize your business logic:
1. A way to make your topology resilient to software bugs
○ Where does my catchall go?
○ Minimize impact of bugs reaching production
○ Graceful degradation instead of catastrophic failure
2. A robust tool for deployment pipelines that enables both service and system level
testing
○ Where do your integration tests go?
3. Good visibility into the state of the running system
○ Where does my printf go?
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How do you build these tools?
It’s all about how you manage your topology
● Transition from DNS -> Discovery
● Central load balancers -> Smart Endpoints
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Routing table is (relatively) static
Routing policy is global
Traditional Topology Management
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Client
DNS
Load Balancer
Serverresolve
traffic

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Routing table is updated in realtime
Routing policy is local
Microservices Topology Management
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Client
Discovery
Server
heartbeats
routes
Smart
Endpoint

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Demo
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Summary
Useful definitions:
● Microservice: A node in an Agile Service Topology
● Microservices: Service Oriented Development
How to build a death star (trifecta of velocity, agility, and organizational scale):
● Mindset: architecture -> experimentation
● Tooling: Discovery + Smart Endpoints
With these tools you can get started in half an hour instead of spending six months
rearchitecting
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To learn more
Contact me:
● rhs@datawire.io
Jobs
● https://www.datawire.io/careers/
Try
● https://github.com/datawire/mdk
● https://www.datawire.io
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