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Orchestration Patterns for
Microservices with Messaging by
RabbitMQ
Greg Chase, Pivotal Software
Dan Baskette, Pivotal Software
Agenda
2
1.  Communication Requirements for Microservices
2.  Use cases where RabbitMQ shines
3.  How to use RabbitMQ for Pivotal Cloud Foundry
4.  Demo
3
Communication Requirements for
Microservices
Why Systems are Evolving to Microservices
Architectures
Characteristics of a
Microservices system:
●  Independent executable
component
●  Does one thing well
●  Often Event & message
driven
●  Fault tolerant
●  Evolutionary
Differentiating Requirements for Communicating
Between Microservices
●  Timing: Synchronous, asynchronous, batched, delayed, offline
●  Interactions: Notification, acknowledged, request-response, workflow
●  Scale: 1000’s messages per second / 10,000’s / 100,000’s
●  Cardinality: 1 to 1 or 1 to many?
Great for request-response, but can break microservices style
Synchronous Communication Starts Out Simple
Benefits
●  Simple and familiar
●  Easy to test
●  Firewall friendly
●  Simpler architecture
Drawbacks
●  Server must always send a
response
●  Both sender and receiver must
be available
●  Not scalable by itself
Trip
Management
Passenger
(mobile)
POST/trips Get/passengers/<passengerID>
REST Passenger
Management
202 OK201 Created
REST
More complex to setup but can simplify services, provide scale & resilience
Asynchronous Communications Patterns
Event Log / Topic Firehose Message queues
Two common patterns for handling messaging in MSA:
Producer
Hadoop Apps DBs
8
Patterns for RabbitMQ
Open source message broker for communication between decoupled applications
What is RabbitMQ?
Asychronous
Messaging
●  Multiple
protocols
●  Queues
●  Exchanges
Developer
Experience
●  Containers
●  Configuration
management
●  Cross-language
●  All major
languages
Distributed
Deployment
●  Highly
available
●  High scale
●  Multi-zone
Enterprise & Cloud
Ready
●  Authentication
●  Encryption
●  Cloud-friendly
Tools & Plugins
●  Continuous
integration
●  Metrics
●  Enterprise
integration
Management &
Monitoring
●  HTTP-API
●  Command line
●  UI tool
Exchanges route messages to queues to await delivery
RabbitMQ Concepts
P
C
Exch
C
Producer Exchange:
●  Fanout
●  Direct
●  Topic
●  Header
“Foo.bar”
Binding
“*.bar”
“Foo.#”
Queues Consumers
“Meta” match “value”
Easy, flexible messaging supporting many message types and routes
Example Patterns for RabbitMQ and Use Cases
Work queues
C
C
General Pub/Sub
C
C
P Exch
Routing
C
C
P Exch
“*.bar”
“Foo.#”
“Meta” match “value”
1
How to use RabbitMQ for Pivotal
Cloud Foundry
Provide RabbitMQ as a service for your developers
RabbitMQ for Pivotal Cloud Foundry
●  Two kinds of deployments
○  Pre-provisioned HA multitenant
RabbitMQ cluster
○  Dedicated single node RabbitMQ
instances
●  Developers gain self-service
access to dedicated or vhost
●  Monitoring available via RabbitMQ
tools
●  RabbitMQ for PCF metrics
exposed to PCF Firehouse
●  Automate deployment,
management and monitoring of
RabbitMQ
HA RabbitMQ multi tenant cluster or dedicated single nodes
Deploy Two Types for RabbitMQ Services in PCF
●  Pre-provision RabbitMQ as highly
available cluster
●  Utilize RabbitMQ HAProxies for load
balancing
●  Deploy to multiple availability zones
●  Simple provisioning through CF CLI
●  On demand provisioning of dedicated
RabbitMQ single nodes
●  Select maximum service instances to
control consumption of IaaS resources
●  Developers have direct access to
RabbitMQ instances
App
Elastic
Runtime
Message Brokers in Microservices Architecture
An opinionated packaging of RabbitMQ for Cloud Native development
Targeted Use Cases for RabbitMQ for PCF
Inter application messaging Backing service for:
Spring Cloud Services
Spring Cloud Data Flow
Quarterly release cadence
Future enhancements of RabbitMQ for PCF
Based on RabbitMQ 3.6.x
Multitenant clusters
Dedicated single node
1.8 1.9 1.10 1.11
Based on RabbitMQ 3.7.x
Dedicated cluster
Ongoing improvements to developer experience and operator automation
This timeline reflects current forecast of product enhancements and may change without notice. These
are not to be construed as committed dates or versions for delivery.
1
FunCollector
Demo
FunCollector - Demo App
●  Spring Boot microservices based
●  Cloud Native and Deployed on Pivotal Cloud Foundry
●  Services
‒  RabbitMQ for Publish/Subscribe messaging between components
‒  Pivotal Google Compute Service Broker - Machine Learning API
‒  PostgreSQL Storage
●  Each component is independently scalable
●  Built to address my “Vice”
Web UI
Web UI
Web UI
ImageRecog
Vision APIImageRecog
Vision APIImageRecog
Vision API
PopIdentifier
PopIdentifier
PopIdentifier
Photo Accepted and
Published to VisionReady
Queue as Object with
Bytestream
Photo is consumed
from queue and
forwarded to
Google Vision API
for Text
Recognition
Object is Enhanced with
Metadata and Published to
VisionResults Queue
Metadata is consumed from
queue and evaluated. Then it’s
compared vs. Master List and
item is Identified
Photo is taken by user and
uploaded
TheCollector
Identified item
is published to
Identified
Queue
Queue is consumed and
Database Updated
FunCollector
Agenda
2
1.  Communication Requirements for Microservices
2.  Use cases where RabbitMQ shines
3.  How to use RabbitMQ for Pivotal Cloud Foundry
4.  Demo
Orchestration Patterns for Microservices with Messaging by RabbitMQ

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Orchestration Patterns for Microservices with Messaging by RabbitMQ

  • 1. Orchestration Patterns for Microservices with Messaging by RabbitMQ Greg Chase, Pivotal Software Dan Baskette, Pivotal Software
  • 2. Agenda 2 1.  Communication Requirements for Microservices 2.  Use cases where RabbitMQ shines 3.  How to use RabbitMQ for Pivotal Cloud Foundry 4.  Demo
  • 4. Why Systems are Evolving to Microservices Architectures Characteristics of a Microservices system: ●  Independent executable component ●  Does one thing well ●  Often Event & message driven ●  Fault tolerant ●  Evolutionary
  • 5. Differentiating Requirements for Communicating Between Microservices ●  Timing: Synchronous, asynchronous, batched, delayed, offline ●  Interactions: Notification, acknowledged, request-response, workflow ●  Scale: 1000’s messages per second / 10,000’s / 100,000’s ●  Cardinality: 1 to 1 or 1 to many?
  • 6. Great for request-response, but can break microservices style Synchronous Communication Starts Out Simple Benefits ●  Simple and familiar ●  Easy to test ●  Firewall friendly ●  Simpler architecture Drawbacks ●  Server must always send a response ●  Both sender and receiver must be available ●  Not scalable by itself Trip Management Passenger (mobile) POST/trips Get/passengers/<passengerID> REST Passenger Management 202 OK201 Created REST
  • 7. More complex to setup but can simplify services, provide scale & resilience Asynchronous Communications Patterns Event Log / Topic Firehose Message queues Two common patterns for handling messaging in MSA: Producer Hadoop Apps DBs
  • 9. Open source message broker for communication between decoupled applications What is RabbitMQ? Asychronous Messaging ●  Multiple protocols ●  Queues ●  Exchanges Developer Experience ●  Containers ●  Configuration management ●  Cross-language ●  All major languages Distributed Deployment ●  Highly available ●  High scale ●  Multi-zone Enterprise & Cloud Ready ●  Authentication ●  Encryption ●  Cloud-friendly Tools & Plugins ●  Continuous integration ●  Metrics ●  Enterprise integration Management & Monitoring ●  HTTP-API ●  Command line ●  UI tool
  • 10. Exchanges route messages to queues to await delivery RabbitMQ Concepts P C Exch C Producer Exchange: ●  Fanout ●  Direct ●  Topic ●  Header “Foo.bar” Binding “*.bar” “Foo.#” Queues Consumers “Meta” match “value”
  • 11. Easy, flexible messaging supporting many message types and routes Example Patterns for RabbitMQ and Use Cases Work queues C C General Pub/Sub C C P Exch Routing C C P Exch “*.bar” “Foo.#” “Meta” match “value”
  • 12. 1 How to use RabbitMQ for Pivotal Cloud Foundry
  • 13. Provide RabbitMQ as a service for your developers RabbitMQ for Pivotal Cloud Foundry ●  Two kinds of deployments ○  Pre-provisioned HA multitenant RabbitMQ cluster ○  Dedicated single node RabbitMQ instances ●  Developers gain self-service access to dedicated or vhost ●  Monitoring available via RabbitMQ tools ●  RabbitMQ for PCF metrics exposed to PCF Firehouse ●  Automate deployment, management and monitoring of RabbitMQ
  • 14. HA RabbitMQ multi tenant cluster or dedicated single nodes Deploy Two Types for RabbitMQ Services in PCF ●  Pre-provision RabbitMQ as highly available cluster ●  Utilize RabbitMQ HAProxies for load balancing ●  Deploy to multiple availability zones ●  Simple provisioning through CF CLI ●  On demand provisioning of dedicated RabbitMQ single nodes ●  Select maximum service instances to control consumption of IaaS resources ●  Developers have direct access to RabbitMQ instances App Elastic Runtime
  • 15. Message Brokers in Microservices Architecture
  • 16. An opinionated packaging of RabbitMQ for Cloud Native development Targeted Use Cases for RabbitMQ for PCF Inter application messaging Backing service for: Spring Cloud Services Spring Cloud Data Flow
  • 17. Quarterly release cadence Future enhancements of RabbitMQ for PCF Based on RabbitMQ 3.6.x Multitenant clusters Dedicated single node 1.8 1.9 1.10 1.11 Based on RabbitMQ 3.7.x Dedicated cluster Ongoing improvements to developer experience and operator automation This timeline reflects current forecast of product enhancements and may change without notice. These are not to be construed as committed dates or versions for delivery.
  • 19. FunCollector - Demo App ●  Spring Boot microservices based ●  Cloud Native and Deployed on Pivotal Cloud Foundry ●  Services ‒  RabbitMQ for Publish/Subscribe messaging between components ‒  Pivotal Google Compute Service Broker - Machine Learning API ‒  PostgreSQL Storage ●  Each component is independently scalable ●  Built to address my “Vice”
  • 20. Web UI Web UI Web UI ImageRecog Vision APIImageRecog Vision APIImageRecog Vision API PopIdentifier PopIdentifier PopIdentifier Photo Accepted and Published to VisionReady Queue as Object with Bytestream Photo is consumed from queue and forwarded to Google Vision API for Text Recognition Object is Enhanced with Metadata and Published to VisionResults Queue Metadata is consumed from queue and evaluated. Then it’s compared vs. Master List and item is Identified Photo is taken by user and uploaded TheCollector Identified item is published to Identified Queue Queue is consumed and Database Updated FunCollector
  • 21. Agenda 2 1.  Communication Requirements for Microservices 2.  Use cases where RabbitMQ shines 3.  How to use RabbitMQ for Pivotal Cloud Foundry 4.  Demo