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@berndruecker
Monitoring and Orchestration
of Your Microservices
Landscape with
Kafka and Zeebe
Berlin, Germany
mail@berndruecker.io
@berndruecker
Bernd Ruecker
Co-founder and
Chief Technologist of
Camunda
@berndruecker
Simplified example:
dash button
Photo by 0xF2, available under Creative Commons BY-ND 2.0
license. https://www.flickr.com/photos/0xf2/29873149904/
@berndruecker
Three steps…
@berndruecker
(Micro-)services
Checkout
Payment
Inventory
Shipment
@berndruecker
Autonomous (micro-)services
Checkout
Payment
Inventory
Shipment
Dedicated Application Processes
Dedicated infrastructure
Dedicated Development Teams
@berndruecker
Data, data, data, …
Source: Microservices orchestration survey,
July 2018, 354 responses
@berndruecker
92 %
@berndruecker
Example
Checkout
Payment
Inventory
Shipment
The button blinks if we can
ship within 24 hours
@berndruecker
Request/response: temporal coupling
Checkout
Payment
Inventory
Shipment
Request
Response
The button blinks if we can
ship within 24 hours
@berndruecker
Temporal decoupling with events and read models
Checkout
Payment
Inventory
Shipment
Good
Stored
Read
Model
Good
Fetched
The button blinks if we can
ship within 24 hours
*Events are facts about what happened (in the past)
@berndruecker
Order
Placed
Payment
Received
Goods
Fetched
Notification
Checkout
Payment
Inventory
Shipment
Event-driven architecture
@berndruecker
Peer-to-peer event chains
Checkout
Payment
Inventory
Shipment
Order
placed
Payment
received
Goods
shipped
Goods
fetched
@berndruecker
Peer-to-peer event chains
Checkout
Payment
Inventory
Shipment
Order
placed
Payment
received
Goods
shipped
Goods
fetched
@berndruecker
The danger is that it's very easy to make
nicely decoupled systems with event
notification, without realizing that you're
losing sight of that larger-scale flow, and
thus set yourself up for trouble in future
years.
https://martinfowler.com/articles/201701-event-driven.html
@berndruecker
The danger is that it's very easy to make
nicely decoupled systems with event
notification, without realizing that you're
losing sight of that larger-scale flow, and
thus set yourself up for trouble in future
years.
https://martinfowler.com/articles/201701-event-driven.html
@berndruecker
The danger is that it's very easy to make
nicely decoupled systems with event
notification, without realizing that you're
losing sight of that larger-scale flow, and
thus set yourself up for trouble in future
years.
https://martinfowler.com/articles/201701-event-driven.html
@berndruecker
Monitoring Workflows Across Microservices
https://www.infoq.com/articles/monitor-workflow-collaborating-microservices
@berndruecker
Typical approachesDistributed Tracing
Data Lake / Event Monitoring
Process Mining
Process Tracking
@berndruecker
Tracking
Checkout Inventory
Payment Shipment
Kafka
Zeebe
@berndruecker
Tracking + BI
Checkout Inventory
Payment Shipment
Kafka
Zeebe
Camunda
Optimize
Other reporting
/ BIO solutions
@berndruecker
Tracking + BI
Checkout Inventory
Payment Shipment
Kafka
Zeebe
Camunda
Optimize
Other reporting
/ BIO solutions
@berndruecker
Tracking + BI
Checkout Inventory
Payment Shipment
Kafka
Zeebe
Camunda
Optimize
Other reporting
/ BIO solutions
This is totally non-invasive
But also limited in power
@berndruecker
Live hacking
https://github.com/berndruecker/flowing-retail/
Zeebe.io
Zeebe Architecture
Operate
We do two workflow engines
Camunda ZeebePersistent
State
Persistent
change
RDMS
Demo architecture
Checkout Inventory
Payment Shipment
Kafka
Zeebe
Spring
Boot
Services
Spring Cloud Streams
Kafka Connect
Operate
@berndruecker
But you can start acting upon certain events
@berndruecker
Vodafone, Liongate & WDW
Presented at CamundaCOn Berlin 2018
@berndruecker
What we currently build with some customers…
Camunda
Optimize
Elastic
17
Registration
requested
Credit
checked
Address
checked
Customer
registered
@berndruecker
Stefan Tilkov: Microservice Patterns & Antipatterns - MicroXchg 2018
@berndruecker
Peer-to-peer event chains
Checkout
Payment
Inventory
Shipment
Order
placed
Payment
received
Goods
shipped
Goods
fetched
Fetch the goods
before the
payment
@berndruecker
Peer-to-peer event chains
Checkout
Payment
Inventory
Shipment
Fetch the goods
before the
payment
Goods
fetched
Order
placed
Payment
received
Goods
shipped
@berndruecker
What we wanted
Photo by Lijian Zhang, available under Creative Commons SA 2.0 License and Pedobear19 / CC BY-SA 4.0
@berndruecker
„Challenges?“
Source:
Microservices orchestration survey,
July 2018, 354 responses
https://camunda.com/microservices-orchestration-survey-results-2018/
@berndruecker
Order
Extract the end-to-end responsibility
Checkout
Payment
Inventory
Shipment
*Commands have an intent about
what needs to happen in the future
Payment
received
Order
placed
Retrieve
payment
@berndruecker
Order
It is about where to decide about the coupling!
Checkout
Payment
Inventory
Shipment
Order
placed
Retrieve
payment
Order decides
. to listen to the event
. to issue the command
@berndruecker
Order
It is about where to decide about the coupling!
Checkout
Payment
Inventory
Shipment
Order
placed
Retrieve
payment
It can still be messaging!
@berndruecker
Order
Checkout
Payment
Inventory
Shipment
Stateful orchestration
This orchestration
requires state
@berndruecker
Order
Checkout
Payment
Inventory
Shipment
@berndruecker
Now it is easy to change the flow
@berndruecker
Live hacking
https://github.com/berndruecker/flowing-retail/
Demo architecture
Checkout Inventory
Payment Shipment
Kafka
Zeebe
Spring
Boot
Services
Spring Cloud Streams
Order
Alternative:
Kafka Connect
@berndruecker
BPMN
Business Process
Model and Notation
ISO Standard
@berndruecker
BPMN supports integration use cases
Aggregator
Re-Sequencer
Combined with timeouts:
Zeebe supports Message TTL
@berndruecker
BPMN supports integration use cases
Compensation
@berndruecker
Biz Dev Ops
@berndruecker
Hybrid architectures
Order
Credit
Card
Customer
Credit
Payment
Pub/Sub
e.g. Kafka
Pub/Sub
Work Distribution
e.g. External Task
Request/Response
e.g. REST
@berndruecker
Order
Checkout
Payment
Inventory
Shipment
Every service owns its workflow!
@berndruecker
Finding the right balance
61
Observe Microservice Paradigms
● Loose Coupling
● Autonomy
● Event Collaboration
Ensure Flow Manageability
• End-To-End Visibility
• Meet Business Process SLA
• Support Continuous Process
Improvement
@berndruecker
@berndruecker
Kafka
Zeebe
Produce
Record
Consume
Records
Event-
Stream
@berndruecker
Kafka
Zeebe
low latency,
high-throughput
low frequency,
latency doesn‘t matter
What people think workflow
automation can do
What we currently teach
workflow automation
to be able to do
What workflow automation
can already do today
Workflow Automation at scale
How?
@berndruecker
@berndruecker
Recap
• In event-driven-systems it is easy to loose sight of the flow
• Visibility is essential to survive
• You need to balance orchestration and chorography
• Distributed systems need stateful orchestration
• Workflow automation is an essential building block
• BPMN is very powerful and provides BizDevOps
• Zeebe rocks :-)
@berndruecker
Thank you!
@berndruecker
mail@berndruecker.io
@berndruecker
https://berndruecker.io
https://medium.com/berndruecker
https://github.com/berndruecker
https://www.infoq.com/articles/events-
workflow-automation
Contact:
Slides:
Blog:
Code:
https://www.infoworld.com/article/3254777/
application-development/
3-common-pitfalls-of-microservices-
integrationand-how-to-avoid-them.html
https://thenewstack.io/5-workflow-automation-
use-cases-you-might-not-have-considered/

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