One of the most common pain points we hear is around managing the flow and placement of data between datacenters. Almost every Apache Kafka user eventually ends up with clusters in multiple datacenters, whether their own datacenters or different regions in public clouds. There are many reasons you might need data to reside in Kafka clusters spread across multiple datacenters.
These different use cases lead to a number of different deployment patterns for Kafka, but they all share a common requirement: data needs to be copied from one Kafka cluster to another (and sometimes in both directions).
Although Apache Kafka ships with a tool called MirrorMaker that allows you to copy data between two Kafka clusters, it is pretty barebones. We regularly see users encounter gaps that make it more difficult to execute a multi-datacenter plan than it should be. For example, MirrorMaker will copy each message from the source cluster to destination cluster, but doesn’t keep anything else about the two clusters in sync: topics can end up with different numbers of partitions, different replication factors, and different topic-level settings. Trying to manually keep all these settings in sync is error prone and can lead downstream applications, or even replication itself, to fail if the systems fall out of sync. It also has a complex configuration spread across multiple files, requires keeping those configs in sync across instances, and is yet another service to deploy and monitor. We have consistently seen the need for an easier, more complete solution to working with Kafka across multiple datacenters.
Today, I’m happy to introduce Multi-Datacenter Replication, a new capability within Plateforme Confluent that makes it easy to replicate your data between Kafka clusters across multiple datacenters. Multi-Datacenter Replication fully automates this process, whether you’re aggregating data for analytics, need a backup, or are migrating from on prem to the cloud.
Confluent Platform now comes with these important features out of the box:
With these features you get hassle-free replication of data, at scale, without writing a single line of code.
At its core, Multi-Datacenter Replication is implemented via a Kafka source connector that reads input from one Kafka cluster and passes that data to the API to be produced to the destination cluster. This means Multi-Datacenter Replication is enabled by all the benefits you’ve come to expect from the Kafka Connect API: the ability to scale elastically, fault tolerance, and a shared, easy to monitor infrastructure for data integration. This also means you can monitor Multi-Datacenter Replication in Confluent Control Center with the same ease as you would monitor any other connector.
As an example of how you can immediately start leveraging Multi-Datacenter Replication, let’s look at an aggregation use case. Suppose you have an application running in multiple data centers. In each DC you have a Kafka cluster that your application reports data about user actions to. You can process the resulting data within each datacenter independently, but to get a global view of what your users are doing you would need to combine the data sets. For some simple types of analysis you might be able to combine the results from each datacenter, but in many cases, you’ll need to get all the data in one place and then run your analysis.
The image shows how you would implement this pattern with Multi-Datacenter Replication:
Here you can see how simple setting up Multi-Datacenter Replication from Confluent Control Center is:
The connector should start creating topics in the destination cluster immediately and then start replicating messages. If you create new topics or modify settings on existing topics, you should see those reflected shortly in the destination cluster without any manual intervention.
As you can see, after some initial setup, Multi-Datacenter Replication can be mostly hands-off while ensuring your data is correctly replicated. If you want to see how easy it is for yourself, download Confluent Platform to try it out and check out the documentation for more details, configuration options, and examples. While Multi-Datacenter Replication is easy to implement, planning for a Multi-datacenter architecture can be more complex and involve many decisions, trade-offs and possible pitfalls. For this reason, we created the Multi-datacenter services engagement for you to consult with an expert and plan out your Multi-datacenter deployment.