Confluent Cloud takes Apache Kafka to a whole new level. Learn how serverless infrastructure is built and apply these learnings to your own projects.
As companies shift workloads to the cloud, they also shift their expectations about what it means to be cloud-native and invest in solutions that align better with them. This page describes what those user expectations are and how Apache Kafka's capabilities have been extended for Confluent Cloud.
In the following series, we focus on how to design and implement the key properties of cloud-native services. If you prefer, you may also read the technical paper version of the content.
Explore some of the key requirements of cloud-native data systems and how they align with the concept of “company-wide scale” that served as a North Star for Apache Kafka development from its earliest days.
Read more: Design Considerations for Cloud-Native Data Systems
Listen to podcast: Using Apache Kafka as Cloud-Native Data System ft. Gwen Shapira
Confluent Cloud provides self-serve provisioning with no complex cluster sizing. You can scale up and down automatically between 0-100 MBps, while paying only for what you use. Elasticity in Confluent Cloud is enabled by using Kafka between the control plane and the data plane, and Self Balancing Clusters and Infinite Storage.
Providing optimal performance to thousands of concurrent users requires a level of discipline and process adherence that goes way beyond traditional application development. Learn how such performance guarantees are built into Confluent Cloud and how you can bring these learnings and processes to your own cloud native applications.
Multi-tenant services are delivered as a high-level abstraction, allowing Confluent Cloud to achieve economies of scale. Learn how you get isolation from other users via security features, user namespacing, and performance.
Confluent Cloud audits specific operations that are more sensitive to corruption and or have more inherent risk. The storage durability audit service can detect data anomalies in real time, while scaling to high throughput and large volumes of data. This ensures that all your data moving through Confluent Cloud is durable and safe.