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To win in today’s global economy, organizations must deliver exceptional customer experiences and data-driven, backend operations. This requires the ability to react, respond, and adapt to a continuous, ever-changing flow of data from across an organization in real time. This has driven the rapid rise of Kafka as a key enabler to helping companies cut across silos and process the flow of business events as they happen. However, given the high level of technical complexity, need for constant monitoring, and time-consuming custom tooling, self-managing Kafka is difficult and often takes large teams of specialized professionals. These challenges can result in costly project delays and inefficient resource investments, holding organizations back as they compete to innovate and win in a digital-first world.

Confluent for Kubernetes – Bringing Benefits From the Leading Data in Motion Cloud Platform to On-Premises Environments

With the launch of Confluent for Kubernetes, Confluent brings together the cloud-native advantages learned from Confluent Cloud with the control and customization from self-managing their private infrastructure in on-premises environments. So whether an organization is transitioning to the cloud or needs to keep workloads on premises, they can take full advantage of Confluent for Kubernetes’ cloud-native capabilities, including a declarative API to deploy and operate Confluent. The platform also makes moving applications to the public cloud easier by seamlessly migrating workloads to wherever your business needs them with the ability to connect and share data with Confluent Cloud. By reimagining what is possible for private infrastructure with the capabilities of modern cloud computing, it is easier than ever for organizations to build and manage a private cloud Kafka service for moving data across a business.

• Enhanced reliability – As a cloud-native system, Confluent for Kubernetes intelligently detects if a process fails and will automatically restart processes or reschedule as necessary. Automated rack awareness spreads replicas of a partition across different racks, improving the availability of your brokers and limiting the risk of data loss. With automated reliability, organizations can minimize the risk of business disruption, reduce downtime costs, and limit data loss.

• Automated elasticity – Meet changing business demands with the ability to scale up using API-driven operations. The platform will automatically generate configurations, schedule and run new broker processes, and ensure data is balanced across brokers so that clusters can be efficiently utilized. With the ability to spin up and down Confluent clusters, organizations can control infrastructure costs while quickly scaling to meet their business needs.

• Simplified infrastructure management – A core concept of the cloud-native paradigm is the ability to focus on higher value activities that create business value rather than performing complex sequences of low-level infrastructure-related operations. Confluent for Kubernetes extends the Kubernetes API, enabling organizations to define the desired high-level state of clusters rather than manage all the low-level details. This infrastructure-as-code approach reduces operational burden and achieves a faster time to value, while enhancing security with standards that can be easily and consistently deployed across an organization.