Reactive microservices

Reactive MicroServices

Leveraging Reactive principlesin a technology agnostic way

Lorenzo NicoraSenior Consultant @ OpenCredo

@nicusX

https://opencredo.com/author/lorenzo

“Reactive” is…

Reactive

Semantically overloaded term

adj. “Readily responsive to stimulus” [Merrian-Webster dictionary]

From Latin “reagere”: act in return

Lorenzo Nicora Reactive μServices

Reactive as…

Reactive asReactive Manifesto


Reactive Manifesto


ü Responsive à Low latency

ü Resilient à Stay responsive on failure

ü Elastic à Scale as needed

ü Message-Driven à Asynchronous messages

as only communication between components

Simplifying


✗ No Blocking operation

✗ No Synchronization à No Contention

✗ No Resource hogging

Reactive Manifesto promotes

Decoupling and isolation in…üTime à Concurrent processing

üSpace à Components location decoupling


Reactive as..

Akka Spring Boot

a set of Architectural

Patterns and Principles

Not necessarilyrelated to

a specific technology

a set of technologies


A set of architectural patterns and principlesapplicable to MicroServices

ü Non-blocking processingü Message-based communicationü Asynchronous delegationü Resilience: Isolation & Replication; Backpressureü Elasticityü Location transparency

Reactive as Architectural Patterns


a MicroService is..

• Communicate with others over the network

• Part of a distributed system

• Independently deployed

• Independently scalable

MicroServices


Macro levelat μService boundariesBetween Services; external resources

Across the MicroService Stack

Micro levelwithin the μServiceBetween internal components


Do not block threads

Never block a threaddoing nothing and

waiting for an Input or a Response

Threads are limited resources(Thread starving)

(React to Input / Response)Lorenzo Nicora Reactive μServices

Non-blocking à Faster


Non-blocking Communication

Macro (at service boundaries)

✗ Limit Request/Response pattern

üOne-way messaging (fire and forget)

üPrefer messaging protocols rather than HTTP

Non-blocking


Non-blocking Communication and IO

Micro (within the Service)

✗ Limit blocking/direct method calls

üFutures, Promises, Callbacks

ü Internal messaging (e.g. Actor model)

üNon-blocking IO and drivers

Non-blocking


Non-blocking + Blocking = Blocking

✗ Many resources only provide blocking API• Prefer technologies with non-blocking API

✗ Do not block on a Future…• To extract the result• To handle exceptions

❗Know where your thread come from• Thread pools

Non-blocking pitfalls


Delegation

* External components

Delegate a task asynchronouslyto other components*

Macro (at Service boundaries)

o Delegate tasks to other μServices

o Send Request as a Message

o When required, Response come back as a Message


Delegation

* Internal component

Delegate a task asynchronouslyto other components*

Micro (within the Service)

o Execute sub-tasks in separate threads• Futures/Promises, Callbacks…

o Run multiple tasks in parallel


Parallel Delegation


Resilience: Stay responsive in face of failure

Resilience

Design expecting failure

Failure happens!

Fail-Safe


• Failure (e.g. connection failure, timeout…)• Unexpected event• Not recoverable• No meaningful response to your client

• Error (e.g. user input error)• Expected condition• A specific response to the client (your protocol)

Failure ≠ Error


Resilience: Isolation + Replication

Resilience à Isolation + Replication

Macro

o Deployment Isolation

o Bulkheads• Prevent cascading failures

• Neither to peer services, nor upstream/downstream


Resilience à Isolation + Replication

o Replication • Legacy (always valid) HA approach

• Multiple peer services

• Data Replication

Resilience: Isolation + Replication


Fail silent; Fail fastthen Recover, when possible

o Prevent cascading failureso Isolate failing collaborators

• Downstream μServices• External services• Resources (DB…)

Resilience: Circuit Breakers


Expect Failure…

Resilience: Handle failure

… Handle FailureLorenzo Nicora Reactive μServices

Handle Errors and Failures

separately

Consistently report Errors to your client

Error is part of your “protocol” (business logic)

Gracefully degrade on Failure

Avoid ”All or nothing” logic à Partial Responses

Handling Failure


Explicitly set and handle timeoutson every asynchronous interaction

Never rely on default settings and handlingfor timeouts

Timeouts - Failures

When collaboration is asynchronous (messaging)a Failure becomes a Time-out


Prevent fast publishers from overrunning slow consumers

✗ Drop messages (acceptable?)✗ Cause catastrophic cascade failures

Back-pressure


Buffers overflow!and will not save you

Back-pressure

à BackpressureConsumer…ü Give feedback to publisherü Drive the pace


Ability to scale when required

Macro

ü Scale services and resources• Add/Remove VM, Container, Cluster nodes

❗ Scaling data (application state)• Only Partitioning, Sharding

Elasticity

Scaling: an infrastructure concern,but application must be designed for it


Your collaborator may be anywhereLocal or Remote

Architecture may evolveLocal à Remote

“There ain’t no such thing as a transparent synchronous remotisation”

Async Messaging work the same local and remote

Location Transparency


You need to find your collaborator

o Service Discovery• Dynamic service registration• Heartbeat, Gossip, Health Check (is a service dead?)• DNS

o Load Balancers

Location Transparency


Conclusions


ü Reactive as a set ofArchitectural Patterns and PrinciplesØ low latency/high throughputØ scale linearly Ø resiliencyØ …

ü When not using a ”Reactive” technologyapply discipline,but still enforce Reactive Principles

ü Keep in mind when designing both…Macro: μService architectureMicro: internal software design

Conclusions


Reactive Manifesto: http://www.reactivemanifesto.org/à Glossary http://www.reactivemanifesto.org/glossary

References


Q&A

Thanks.Lorenzo Nicora Reactive μServices

Reactive microservices

Software

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