Apache Kafka is an open-source distributed event-streaming platform that lets applications publish, store, and subscribe to continuous streams of records organized into topics. Producers write records to a topic; consumers read them independently and at their own pace, decoupling systems that generate data from systems that process it.
Key takeaways
- Kafka is an open-source, distributed event-streaming and messaging platform.
- Producers publish to topics; consumers subscribe and read at their own pace.
- Records persist for a retention window, so consumers can replay past events.
- Versa uses Kafka as the backbone for VMS, Analytics log export, and Director events.
- Kafka clusters scale by adding brokers and partitions, not by replacing hardware.
On this page: Why it mattersHow it worksTypesKafka & VersaFAQ
Why is Kafka important?
Modern systems generate continuous streams of data – clickstreams, sensor readings, log lines, user-identity events – faster than a database can absorb in single writes. Kafka matters because it decouples the systems producing this data from the systems consuming it: a producer writes a record once, and any number of independent consumers can read the same stream at their own pace or replay it long after it landed. That removes the point-to-point integration sprawl traditional messaging queues create, where every new consumer needs a dedicated connection back to every producer.
For organizations instrumenting real-time pipelines – security telemetry, IoT fleets, or event-driven microservices – Kafka’s durability and ordering guarantees make it a default backbone for event-driven architecture, scaling horizontally by adding brokers and partitions rather than replacing hardware.
What is Kafka?
Kafka organizes data into topics: named streams of records that producers append to and consumers read from. Each topic is split into partitions, distributed across a cluster of servers called brokers; partitioning is what lets Kafka scale throughput and gives ordering guarantees within – but not across – a partition. Consumer groups subscribe and read independently, each tracking its own read position (an offset), so multiple applications can consume the same stream without interfering with each other.
Brokers replicate each partition across multiple nodes so a single broker failure doesn’t lose data, and retention is time- or size-based rather than delete-on-read, so a new consumer can replay history instead of seeing only new messages. Connections can run over TLS, and clients typically authenticate to brokers using SASL – username/password, SCRAM, or OAuth tokens – rather than relying on network trust alone.
Types of Kafka deployments
Kafka deployments generally fall into three patterns. Self-managed clusters run entirely on infrastructure the operator controls – brokers installed on-premises or in a private cloud, with the operator responsible for capacity planning, patching, and failover. Managed cloud services, such as Confluent Cloud or Amazon MSK, offload broker operations to a provider, exposing the same producer and consumer APIs without the operational burden. Multi-cluster, geo-replicated deployments link two or more Kafka clusters – often in different sites or regions – using a replication tool such as MirrorMaker, which mirrors topics from a source cluster to a destination cluster for disaster recovery or multi-data-center designs.
The choice affects operational overhead more than application design: producers and consumers use the same client APIs regardless of the pattern underneath.
Kafka & Versa
Versa uses Kafka as the messaging backbone for Versa Messaging Service (VMS), the component that distributes real-time data – user-identity events, threat feeds, device risk scores, and endpoint information – between Versa headend components and SASE gateways. SASE for SIM can publish subscriber events over Kafka as an alternative to RADIUS, and the SCIM, UEBA, and XIP-EIP microservices each configure a Kafka broker topic, address, port, and SASL or certificate-based authentication.
VMS clusters can also enable Kafka MirrorMaker to replicate data between VMS nodes for redundancy, a step Versa requires before integrating EDR platforms such as CrowdStrike, Microsoft Defender, and SentinelOne. Versa Analytics can stream logs to an external Kafka cluster as a remote log collector, configuring topics and TLS/SASL authentication on the log collector exporter. Separately, Versa Director publishes object-change and event notifications over Kafka for downstream systems.
Frequently asked questions
What is a Kafka topic?
A topic is a named, append-only stream of records that producers write to and consumers read from. Kafka splits each topic into partitions so it can distribute storage and read/write load across multiple brokers, while preserving order within a single partition.
What is the difference between Kafka and a traditional message queue?
A traditional queue typically deletes a message once a consumer reads it. Kafka retains records for a configurable period regardless of whether they’ve been read, so independent consumer groups can read – and replay – the same stream without affecting each other.
Does Kafka require ZooKeeper?
Older Kafka versions relied on a separate Apache ZooKeeper ensemble for cluster metadata and leader election. Since Kafka’s KRaft mode became production-ready, brokers handle that coordination internally, removing the ZooKeeper dependency.
How does Kafka guarantee message ordering?
Kafka guarantees order only within a single partition: records written to the same partition are read back in the order they were produced. Across partitions there’s no ordering guarantee, so strict global ordering requires routing related records to the same partition key.
How does Versa secure Kafka connections to VMS?
Versa secures Kafka connections to VMS with TLS-encrypted transport and certificate-based or SASL authentication – VMS broker configurations support SCRAM and OAuth-bearer SASL mechanisms alongside CA, client-certificate, and private-key uploads, the same controls Analytics log exports use.
More on Kafka
If you want to learn more, these are sources we trust.
| Apache Kafka: Documentation |
|---|
| The Apache Kafka project’s official documentation: architecture, topics, producers and consumers, and operations. |
Related terms
If you’re reading about Kafka, these are worth looking at next.
| Versa Messaging Service | Privacy-Enhanced Mail | Subject Alternative Name |
|---|---|---|
| The Kubernetes-based headend service that uses Kafka as its message-streaming backbone to distribute identity, threat, and risk-score data across Versa components. | The certificate and key encoding format Kafka’s TLS-secured remote collectors require for CA, client, and private-key files. | The certificate extension that TLS validation checks when Kafka clients authenticate brokers over an encrypted connection. |