Agenda: - Cloud Native vs. SaaS / Serverless Kafka - The Emergence of Kubernetes - Kafka on K8s Deployment Challenges - Confluent Operator as Kafka Operator - Q&A Confluent Operator enables you to: Provisioning, management and operations of Confluent Platform (including ZooKeeper, Apache Kafka, Kafka Connect, KSQL, Schema Registry, REST Proxy, Control Center) Deployment on any Kubernetes Platform (Vanilla K8s, OpenShift, Rancher, Mesosphere, Cloud Foundry, Amazon EKS, Azure AKS, Google GKE, etc.) Automate provisioning of Kafka pods in minutes Monitor SLAs through Confluent Control Center or Prometheus Scale Kafka elastically, handle fail-over & Automate rolling updates Automate security configuration Built on our first hand knowledge of running Confluent at scale Fully supported for production usage 

1. 1
Introduction to Confluent Operator
to establish a Cloud-Native Confluent Platform
and provide a Kafka Operator for Kubernetes
Kai Waehner
Technology Evangelist
contact@kai-waehner.de
LinkedIn
@KaiWaehner
www.confluent.io
www.kai-waehner.de

2. 2
Agenda
● Cloud Native vs. SaaS / Serverless Kafka
● The Emergence of Kubernetes
● Kafka on K8s Deployment Challenges
● Confluent Operator as Kafka Operator
● Q&A
Confluent
Operator

3. 3
Agenda
● Cloud Native vs. SaaS / Serverless Kafka
● The Emergence of Kubernetes
● Kafka on K8s Deployment Challenges
● Confluent Operator as Kafka Operator
● Q&A
Confluent
Operator

4. 4
Business Digitalization Trends are Driving the Need to Process
Events at a whole new Scale, Speed and Efficiency
Mobile Cloud Microservices Internet of Things Machine Learning
The world has changed!

5. 5Best-of-breed Platforms, Partners and Services for Multi-cloud Streams
Private Cloud
Deploy on bare-metal, VMs,
containers or Kubernetes in your
datacenter with Confluent Platform
and Confluent Operator
Public Cloud
Implement self-managed in the public
cloud or adopt a fully managed service
with Confluent Cloud
Hybrid Cloud
Build a persistent bridge between
datacenter and cloud with
Confluent Replicator
Confluent
Replicator
VM
SELF MANAGED FULLY MANAGED

6. 6
Software as a Service (SaaS)
● a software distribution model in
which a third-party provider hosts
applications and makes them
available to customers over the
Internet.
● provides SLAs like uptime
guarantees, throughput, latency, etc.
● Depending on your definition, some
also call this Serverless (BaaS,
Backend as a Service) for
infrastructure components

7. 7
Confluent Cloud
Cloud-Native Confluent Platform Fully-Managed Service
Available on the leading public clouds with mission-critical SLAs.
Serverless Kafka characteristics:
Pay-as-you-go, elastic auto-scaling, abstracting infrastructure (topics not brokers)

8. 8
Confluent Cloud, What does Fully-managed Mean?
Infrastructure
management
(commodity)
Scaling
● Upgrades (latest stable version of Kafka)
● Patching
● Maintenance
● Sizing (retention, latency, throughput, storage, etc.)
● Data balancing for optimal performance
● Performance tuning for real-time and latency requirements
● Fixing Kafka bugs
● Uptime monitoring and proactive remediation of issues
● Recovery support from data corruption
● Scaling the cluster as needed
● Data balancing the cluster as nodes are added
● Support for any Kafka issue with less than 60 minute response time
Infra-as-a-Service
Harness full power of Kafka
Kafka-specific
management
Platform-as-a-Service
Evolve as you
need
Future-proof
Mission-critical reliability
Most Kafka as a Service offerings are partially-managed

9. 9
What is Cloud Native?
Benefits
• Scalable
• Flexible
• Agile
• Elastic
• Automated
• Etc.

10. 10
The Twelve-Factor App
What is Cloud Native?
https://12factor.net/

11. 11
What is Cloud Native?
10 key characteristics (one of many definitions)
● Packaged as lightweight containers
● Developed with best-of-breed languages and frameworks
● Designed as loosely coupled microservices
● Centered around APIs for interaction and collaboration
● Architected with a clean separation of stateless and stateful services
● Isolated from server and operating system dependencies
● Deployed on self-service, elastic, cloud infrastructure
● Managed through agile DevOps processes
● Automated capabilities
● Defined, policy-driven resource allocation
https://thenewstack.io/10-key-attributes-of-cloud-native-applications/

12. 12
Agenda
● Cloud Native vs. SaaS / Serverless Kafka
● The Emergence of Kubernetes
● Kafka on K8s Deployment Challenges
● Confluent Operator as Kafka Operator
● Q&A
Confluent
Operator

13. 13
Cloud-Native Platforms in last 5 years

14. 14
Kubernetes won the battle!

15. 15
Kubernetes innovation not stopping…
● Cloud providers provide Kubernetes as a service
○ AWS, Azure, GCP, …
○ Not all are mature yet J
● Stateful deployments leverage the Kubernetes
Operator pattern
○ For many infrastructure components, like databases, messaging, etc.
○ Community projects, vendors solutions (open source vs. proprietary)
● Service Mesh
○ Envoy, Istio, Linkerd, ...
○ Pull request for Kafka protocol support in Envoy / Istio accepted
recently

16. 16
Evolution of Kafka DevOps
Shell scripts
Ansible/Chef Docker
Kubernetes

17. 17
Agenda
● Cloud Native vs. SaaS / Serverless Kafka
● The Emergence of Kubernetes
● Kafka on K8s Deployment Challenges
● Confluent Operator as Kafka Operator
● Q&A
Confluent
Operator

18. 18
Kafkaesque world of Kafka on Kubernetes

19. 19
Kafka on Kubernetes –
It’s tricky ©
• Translating an existing architecture to Kubernetes
• Failover handling and data balancing
• Communication between ZooKeeper, Kafka Brokers, Clients (Java,
REST, Connect, KSQL), Schema Registry, etc.
• External access from / to outside Kubernetes cluster
• Persistent storage options on prem and in the cloud
• Security configuration
• Rolling upgrades
• Etc.

20. 20
Agenda
● Cloud Native vs. SaaS / Serverless Kafka
● The Emergence of Kubernetes
● Kafka on K8s Deployment Challenges
● Confluent Operator as Kafka Operator
● Q&A
Confluent
Operator

21. ● Global-scale
● Real-time
● Persistent Storage
● Stream Processing
Apache Kafka: The De-facto Standard for Real-Time Event Streaming
Edge
Cloud
Data LakeDatabases
Datacenter
IoT
SaaS AppsMobile
Microservices Machine
Learning
Apache Kafka

22. 22
Real-Time
Inventory
Real-Time
Fraud
Detection
Real-Time
Customer 360
Machine
Learning
Models
Real-Time
Data
Transformation
...
Contextual Event-Driven Applications
Universal Event Pipeline
Data Stores Logs 3rd Party Apps Custom Apps/Microservices
TREAMSSTREAMS
CONNECT CLIENTS

23. 23Confluent establishes Freedom of Choice
● SaaS or Self-Managed or Hybrid
● Confluent’s vision is to introduce cloud native
capabilities to Confluent Platform and enable users who
want a cloud native experience in on-premises and self-
managed cloud environments
● Introducing Confluent Operator

24. 24
Confluent Platform
Operations and Security
Development & Stream Processing
Support,services,training&partners
Apache Kafka
Security plugins | Role-Based Access Control
Control Center | Replicator | Auto Data Balancer | Operator
Connectors
Clients | REST Proxy
MQTT Proxy | Schema Registry
KSQL
Connect Continuous Commit Log Streams
Complete Event
Streaming Platform
Mission-critical
Reliability
Freedom of Choice
Datacenter Public Cloud Confluent Cloud
Self-Managed Software Fully-Managed Service

25. 25
Confluent Operator
● Deployment and management
automation for Confluent
Platform on Kubernetes
● Including Apache Kafka, Zookeeper, Schema
Registry, Connect, Control Center, Replicator, KSQL
● For organizations standardized on
Kubernetes as platform runtime
● Operationalizes years of experience
running Kafka on Kubernetes on the
leading public clouds
Confluent Platform
Confluent Operator
Kubernetes
AWS Azure GCP
RH OpenShift Mesosphere Pivotal
On-Premises Cloud
Docker Images
Automate Deployment of Confluent Platform on Kubernetes on Any Platform at Any Scale

26. 26
Confluent Operator enables you to:
Automate provisioning of
Kafka pods in minutes
Monitor SLAs through Confluent
Control Center or Prometheus
Scale Kafka elastically &
Automate rolling updates
Built on our first hand knowledge
of running Confluent at scale
Cloud-Native Deployment of Kafka and Confluent Platform

27. Confluent’s Kubernetes Journey
05/2017
Confluent Cloud
Early Access
2016
Confluent Cloud
Development
11/2017
Confluent Cloud
GA (AWS)
07/2019
Confluent Operator GA
(Confluent Platform)
2019
Confluent Cloud GA
on AWS, GCP, Azure

28. 28
Confluent Operator:
A custom Kubernetes Controller
API
Server
Scheduler
Controllers &
Custom Controllers
PODS
PVs
ConfigMaps
StatefulSets
Nodes and pods are where
Applications run on Kubernetes
Applications use objects like
StatefulSets, Configmaps, PVs
Custom Controllers create custom
resources that provide unique
application functionality:
● Upgrades, Elasticity, Kafka
Operational Logic
Custom
Resources
Master Node
Worker Nodes

29. 29Helm - The Confluent Operator Package Manager
● Confluent Operator leverages Helm Charts to
deploy, upgrade and uninstall Confluent
Platform custom resources and pods
● Configuration front end for users to specify
how a Confluent Platform Cluster is
deployed:
○ # of replicas for Kafka, Zookeeper
○ Security and Authentication configuration
○ Persistent Storage configuration
● Cluster configuration edits are also
performed using Helm
Operator Helm
Charts - yaml

30. 30
Kubernetes
Cluster K8 NodeK8 NodeK8 Node
Replicator
Pod
C3 Pod SR Pod
K8 Node
Confluent Operator Deployment
Operator
Kafka
Pod
ZK Pod
Persistent Volumes
(AWS EBS, GCE Persistent Disk, Local Persistent Volume, etc.)
External
Access
Load
Balancers
Configurations
ConfigMapsKSQL Pod
REST Proxy
Pod

31. 31
Confluent Operator - Automated Provisioning

32. 32
Confluent Operator - Automated Security
Configuration
SASL PLAIN, SASL_SSL, TLS with
Mutual Authentication
Automate configuration of truststores
and keystores with secret objects
Automate configuration of Kafka and
all Confluent Platform Components

33. 33
Confluent Operator - Scale Horizontally
Automate Scaling:
Spin up new brokers, connect workers
easily
Distribute partitions to new brokers:
Determine balancing plan
Execute balancing plan
Monitor Resources

34. 34
Confluent Operator - Rolling Upgrade of all
components
Automated Rolling Upgrades of all
components - Kafka Brokers,
Zookeeper, Connect, Control Center
Kafka Broker Upgrades:
1. Stop the broker, upgrade Kafka
2. Wait for Partition Leader reassignment
3. Start the upgraded broker
4. Wait for zero under-replicated partitions
5. Upgrade the next broker

35. Agenda
● Cloud Native vs. SaaS / Serverless Kafka
● The Emergence of Kubernetes
● Kafka on K8s Deployment Challenges
● Confluent Operator as Kafka Operator
● Q&A
Confluent
Operator

36. 37
Kai Waehner
Technology Evangelist
contact@kai-waehner.de
@KaiWaehner
www.confluent.io
www.kai-waehner.de
LinkedIn
Questions? Feedback?
Let’s connect!