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Data Streaming

Current '23 Keynote: Streaming into the Future - The Evolution & Impact of Data Streaming Platforms

Jay Kreps (Confluent Co-Founder and CEO), Shaun Clowes (Confluent CPO), and data streaming leaders from organizations like NASA, Warner Brothers, and Notion explore the past, present, and future of data streaming. They will address two key questions: how can organizations integrate data across their applications to deliver better experiences, and how can they embed data and analytics into every part of the business to drive better decision-making?

Confluent unveils Apache Flink® on Confluent Cloud, making it easier to build real-time applications with stream processing on a unified platform

Confluent launches the industry's only serverless, cloud-native Flink service to simplify building high-quality, reusable data streams. Confluent expands Stream Governance capabilities with Data Portal, so teams can easily find all the real-time data streams in an organisation. New Confluent Cloud Enterprise offering lowers the cost of private networking and storage for Apache Kafka.

Introducing Confluent Cloud for Apache Flink

In the first three parts of our Inside Flink blog series, we discussed the benefits of stream processing, explored why developers are choosing Apache Flink® for a variety of stream processing use cases, and took a deep dive into Flink's SQL API. In this post, we'll focus on how we’ve re-architected Flink as a cloud-native service on Confluent Cloud. However, before we get into the specifics, there is exciting news to share.

Deliver Intelligent, Secure, and Cost-Effective Data Pipelines

The Q3 Confluent Cloud Launch comes to you from Current 2023, where data streaming industry experts have come together to share insights into the future of data streaming and new areas of innovation. This year, we’re introducing Confluent Cloud’s fully managed service for Apache Flink®, improvements to Kora Engine, how AI and streaming work together, and much more.

Boost Data Streaming Performance, Uptime, and Scalability | Data Streaming Systems

Operate the data streaming platform efficiently by focusing on prevention, monitoring, and mitigation for maximum uptime. Handle potential data loss risks like software bugs, operator errors, and misconfigurations proactively. Leverage GitOps for real-time alerts and remediation. Adjust capacity to meet demand and monitor costs with Confluent Cloud's pay-as-you-go model. Prepare for growth with documentation and minimal governance.

Use GitOps as an efficient CI/CD pipeline for Data Streaming | Data Streaming Systems

Early automation saves time and money. GitOps improves CI/CD pipeline, enhancing operations & traceability. Learn to use GitOps for data streaming platforms & streaming applications with Apache Kafka and Confluent Cloud.

Robust Disaster Recovery with Kafka and Confluent Cloud | Data Streaming Systems

Explore the resilience of Kafka, understand the implications of datacenter disruptions, and mitigate data loss impacts. Learn to scale with Confluent Cloud, cluster and schema linking, and how to use an active/passive disaster recovery pattern for business continuity.

Challenges Using Apache Kafka | Data Streaming Systems

Streaming platforms need key capabilities for smooth operations: data ingestion, development experience, management, security, performance, and maintenance. Self-managed platforms like Apache Kafka can meet these needs, but can be costly and require intensive maintenance. On the other hand, Confluent Cloud offers fully-managed services with features like scalable performance, auto-balancing, tiered storage, and enhanced security and resiliency. It provides systematic updates and maintenance, freeing users from infrastructure concerns. Confluent Cloud streamlines creation of a global, well-governed data streaming platform.