The document outlines 10 lessons learned from building Confluent Cloud. Some key lessons include that multi-cloud environments can have wildly different implementations; best practices for the cloud change rapidly so constant evolution is needed; running Kafka at scale in the cloud requires decoupling compute and storage; and monitoring the right metrics is important as failures and upgrades will occur frequently at scale in the cloud.

1. 10 Lessons Learned Building
Confluent Cloud
Addison Huddy, Product Manager for Kafka
Dan Rosanova, Product Manager for Cloud

2. #1 Multi-Cloud
On the surface, the cloud are similar.
At the limit, they are wildly different.

3. #2 Constant Cloud Evolution
What is best practice today, won’t be
tomorrow.

4. #3 A New Storage Engine
Running Kafka at scale in the Cloud
requires the decoupling of Compute and
Storage

5. #4 Metrics & Monitoring
Looking at the wrong things

7. #5 K8s is only part of the answer

9. #6 Cloud leads to many, smaller
clusters

10. #7 Pre-cloud thinking & Workload
Isolation
Modern cloud thinking is about density of
workloads and getting rid of waste

11. #8 Upgrades are a constant

12. #9 Failures are to be expected

14. #10 Counting at scale is hard

16. Value Line

17. Copyright 2021, Confluent, Inc. All rights reserved. This document may not be reproduced in any manner without the express written permission of Confluent, Inc. 17
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cnfl.io/blog
Thank you!
@addisonhuddy
@DanRosanova