Systems | Development | Analytics | API | Testing

Building distributed systems is a huge undertaking, but the complexity doesn’t end once your application or platform is “production ready.” Keeping these systems online and operational through cloud region outages, a network partition, or just scheduled maintenance is a constant challenge. The bottom line: you don’t want data pipelines for essential business services, customer-facing products, or enterprise data platforms to go dark.

As the adoption of real-time data processing accelerates, the ability to scale stream processing applications to handle high-volume traffic is paramount. Apache Kafka, the de facto standard for distributed event streaming, provides a powerful and scalable library in Kafka Streams for building such applications. Scaling a Kafka Streams application effectively involves a multi-faceted approach that encompasses architectural design, configuration tuning, and diligent monitoring.

While business intelligence dashboards can show you what happened and when, real-time alerts tell you what's happening right now and—when designed right—how to take action before problems escalate. The distinction matters more than you might think. Dashboards help visualize data patterns and trends over time, but real-time alerts can serve automated triggers that detect critical business events and initiate immediate responses.

Whether it’s financial transactions being processed in milliseconds, customer interactions powering personalized experiences, or machine learning models making predictions, the quality of your data directly shapes the quality of business outcomes today. Put simply: bad data equals bad decisions. The costs aren’t just theoretical—they show up as inaccurate dashboards, failed compliance audits, customer churn, and wasted operational resources.

We’re proud to announce that Confluent has been named MongoDB’s 2025 Global Tech Partner of the Year. This award highlights the strength of our partnership and joint go-to-market execution, helping enterprises build the next generation of intelligent, event-driven artificial intelligence (AI) applications.

As artificial intelligence (AI) matures from experimentation into production use cases, the symbiotic relationship between data and AI becomes increasingly clear. To deliver real business impact—smarter automation, better customer experiences, and massive cost takeout—AI use cases are only as powerful as the data they’re running on.

Business intelligence (BI) dashboards contain a wealth of information that companies need to succeed in competitive environments. Marketing and sales departments might rely on pipeline progression dashboards while product managers and engineering teams use them to track product usage and performance KPIs.

Security standards continue to evolve, and organizations need infrastructure that evolves along with them. TLS 1.3 brings stronger encryption to streaming infrastructure for data in transit while ensuring alignment with strict security and compliance requirements. We’re excited to announce that TLS 1.3 is currently available as an opt-in feature on Confluent Cloud Dedicated clusters and all other Confluent Cloud APIs, including Stream Governance, Metrics, and Control Plane.

Building real-time applications in the cloud means making the right infrastructure choices early. And for many engineering teams leveraging Amazon Web Services (AWS), Apache Kafka is a key component of their streaming architectures. While open source Kafka provides a powerful foundation, operating it at scale in production often means navigating challenges when provisioning, scaling, securing, and integrating across environments. That’s where Confluent Cloud comes in.

We are thrilled to announce that Confluent Cloud for Government is now available on the FedRAMP Marketplace with FedRAMP 20x Low authorization, allowing both private and public sector customers to leverage our cloud-native data streaming platform to power their mission-critical applications. This milestone marks the successful completion of Phase One of our FedRAMP 20x Pilot program.