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Messaging: The fine line between awesome and awful
LAILA BOUGRIA
And how to stay on the right side of it…
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No content
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When I was young…
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The monolith
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Symptoms
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Let’s use messaging!
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Messaging benefits
Easier
decoupling
Increased
resilience
Better
performance
Granular
scalability
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Challenges
Out of order
Hard to troubleshoot
Duplicates
System is slower
UI is inconsistent
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Distributed, big ball of mud
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System is slower
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Request-response
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Even slower…
Producer
Request queue
Response queue
Consumer
Producer Consumer
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Sync vs async request-response
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One-way Request-response
Messaging communication patterns
Publish-subscribe
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Decoupling
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Place order process
1
Store order Charge credit
card
2
Package order
3
Ship the order
4
Bill order
5
Adjust stock
6
Verify customer
status
8
Order more
stock?
7
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Place order process
Store order Charge credit
card
Package order Ship the order Bill order Adjust stock Verify customer
status
Order more
stock?
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Finding logical boundaries
Talk this through with the business
Event storming
Uncover false assumptions
By asking many, many questions!
Rinse and repeat to keep untangling things
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We end up somewhere here…
Customer
places order
Store order
Charge
order
Package
order
Backorder
order items
Package
order
Ship order Bill order
Order more
stock?
Verify
customer
status
In
stock?
Stock
arrived?
Refund
order
Yes
No
No
Yes
Sales
Payments
Packaging
Invoicing
Shipping
Stock
Marketing
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Communicate between boundaries
One way communication
Request-reply
Publish-Subscribe
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The passive-aggressive publisher
Publish-subscribe is not a good fit when:
You expect something specific to be done
You need a response with data to continue
You need control over who receives the event
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Recap
Decouple components by finding logical boundaries
Decouple data by understanding which data depends on
each other and which data changes together
Choose the right communication pattern to communicate
across components
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UI is inconsistent
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Glitches
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Adjust the language
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Ensure message delivery
Show action details
Local storage
Used in several social media applications
Illusion of progress
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Defining SLAs
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Future messages
Delayed delivery
Supported in Azure Service Bus, Rabbit MQ, Amazon SQS
Calculate the SLA expiration, use it as the delivery time
Verify whether the SLA was violated
Take appropriate action
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Recap
Adjust language in the UI
Create the illusion of progress
Define Service Level Agreements
Enforce Service Level Agreements with delayed messages
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Things occur out of order
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Do we need ordering?
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Order workflow
Customer
places order
Store order
Charge
order
Package
order
Backorder
order items
Package
order
Ship order Bill order
Order more
stock?
Verify
customer
status
In
stock?
Stock
arrived?
Refund
order
Yes
No
No
Yes
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Send out messages in the right order
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Causes of ordering issues
Latency
Processing time
Concurrency
Load increase
Retries
Service availability
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Let’s make it ordered
Store order Charge credit
card
Package order Ship the order Bill order Adjust stock Verify customer
status
Order more
stock?
Sales Payments Shipments Invoices Stock
Customer
status
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Central component drives the business process
Knows and stores the state of the process
Decides which step is next and when
Recreates order
Orchestration
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Orchestration
Order Orchestrator
Message broker
Sales Payments Shipping Invoicing Stock
Customer
status
Packaging
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Orchestration
Order Orchestrator
Message broker
Sales Payments Shipping Invoicing Stock
Customer
status
Packaging
Stock Orchestrator
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Orchestration pros & cons
Order Orchestrator
Message broker
Sales Payments Shipping Invoicing
Packaging
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Expect out-of-order messages
Test out-of-order cases
Use orchestration to model workflows
Guard the coupling within a single workflow
Choreography is an alternative for orchestration
Recap
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It’s impossible to troubleshoot failures
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Message processing failed, but what’s the root cause?
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We did not expect duplicates
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And then there were more
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Idempotency
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Message deduplication
Detect whether a message was processed before
If so, discard the message
Deterministic Message ID
Deduplication windows
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No distributed transactions
Different types of infrastructure within a single system
Transactional guarantees are not cross-infrastructure
Outbox pattern: consistency across database and broker
Atomicity problem
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Failure management pattern
Ensure data consistency, step-by-step
Sequence of local transactions
Roll back / compensate if one of the operations fail
Saga distributed transactions pattern
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Saga distributed transaction pattern
Saga
Service A
Service B
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Make the change idempotent
Use the saga pattern for distributed transactions
Prefer communication over queues instead of REST APIs
Ensure REST APIs are idempotent
Investigate compensating requests
Recap
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Messaging buys you options to solve scalability, reliability,
coupling and performance problems
Commit to decoupling your logic and data
Think how out-of-order processing affects your workflows
Invest in observability
Make idempotency a key pattern in your design
Conclusion