Problem: Kafka is a powerful distributed data architecture, but it is incredibly complex to keep clusters running at peak capacity and ensure data availability. Developers and other key resources often get pulled off their projects to deal with scalability or availability issues. Provisioning Confluent allows you to fully offload or drastically reduce Kafka management and keep your key resources focused on projects that drive revenue.
Problem: Kafka does not have good signalling mechanisms in place to help you find and troubleshoot issues within its ecosystem. It's tough to identify and solve problems that lead to lag, downtime, or data loss which can cause parts of your business to grind to a halt. Confluent Cloud and Platform offer the visibility, durability, and reliability organizations need to ensure event availability.
Problem: Apache Kafka is a complex system that requires a lot of tuning to run at peak performance and expertise to ensure its components are healthy. Supporting Kafka in house can be a massive expense and resource drain and drag out resolution times. Confluent provides committer-led support from the team with more Kafka expertise than anyone that’s powered by our in-depth visibility into real-time health and performance data from our customers.
Offload Kafka operations to a fully-managed cloud-native service with a 99.95% uptime SLA, including automated bug fixes, cluster optimization, and in-place upgrades.
Get alerts for potential issues on self-hosted deployments based on our expert tested algorithms to identify and resolve them before they happen
Get a fully-managed support experience for self-managed Kafka by automatically providing visibility into cluster health and performance data.
Protect against single zone failures with multi-AZ synchronous replication across three zones
Upgrades with zero downtime to ensure you are always on the latest stable version of Kafka
Kafka bugs proactively fixed on-demand without waiting for the next Kafka release.
99.95% uptime SLA to ensure your environment remains up and running
Continuous, real-time analysis of metadata that alerts you to potential problems before they arise
Centralize multi-cluster management and monitoring, adhering to established event streaming SLAs
Automate rolling upgrades without impacting availability and failure recovery to minimize downtime.
Automate partition rebalances to minimize lag or downtime and ensure peak performance.
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