How to solve the data discoverability problem with Data Portal and Flink
Learn how the Data Portal and Apache Flink in Confluent Cloud can help developers and data practitioners find the data they need to quickly create new data products.
Systems | Development | Analytics | API | Testing
Modern Software Development For Today's Systems & Applications
Solving the Dual-Write Problem: Effective Strategies for Atomic Updates Across Systems
The dual-write problem occurs when two external systems must be updated in an atomic fashion. A classic example is updating an application’s database while pushing an event into a messaging system like Apache Kafka. If the database update succeeds but the write to Kafka fails, the system ends up in an inconsistent state. However, the dual-write problem isn’t unique to event-driven systems or Kafka. It occurs in many situations involving different technologies and architectures.
Retrieval Augmented Generation (RAG) with Data Streaming
How do you prevent hallucinations from large language models (LLMs) in GenAI applications? LLMs need real-time, contextualized, and trustworthy data to generate the most reliable outputs. Kai Waehner, Global Field CTO at Confluent, explains how RAG and a data streaming platform with Apache Kafka and Flink make that possible.
Data Streaming Awards 2024: Nominations Are Now Open
The Data Streaming Awards is back for its third year! Designed to bring the data streaming community together, this one-of-a-kind industry award event recognizes organizations that are harnessing the power of this revolutionary technology to drive business and customer experience transformation. If you know a company (even your own team) that is using data streaming technology to transform their business and provide amazing value to their customers and communities, the time is now to submit a nomination.
Best Practices for Confluent Terraform Provider
Managing Confluent Cloud infrastructure efficiently poses challenges due to the complexities involved in deploying and maintaining various components like environments, clusters, topics, and authorizations. Without proper tooling and practices, teams struggle with manual configuration errors, lack of consistency, and potential security risks. The Confluent Terraform.
Confluent Welcomes Data to the Thunderdome
The Defense Information Systems Agency (DISA) launched an ambitious program with a name as intimidating as the effort to re-imagine the security architecture of the Department of Defense (DoD). Thunderdome is DISA’s zero trust network access and application security architecture.
How to Set Up a Fully Managed Alerting Pipeline Using Confluent Cloud Audit Logs
In large organizations, Confluent Cloud is often simultaneously accessed by many different users along with business-critical applications, potentially across different lines of business. With so many individual pieces working together, the risk of an individual outage, error, or incident affecting other services increases. An incident could be constituted by a user clicking a wrong button, an application’s misconfiguration, or just a bug—you name it.
Serverless Decoded: Reinventing Kafka Scaling with Elastic CKUs
Apache Kafka has become the de facto standard for data streaming, used by organizations everywhere to anchor event-driven architectures and power mission-critical real-time applications. However, this rise has also sparked discussions on improving Kafka operations and cost-efficiency—streaming data is naturally prone to bursts and often unpredictable, resulting in inevitable variations in workloads and demand on your Kafka cluster(s).
Modernize Payments Architecture for ISO 20022 Compliance
The payments industry is evolving rapidly, fueled by technological advancements, changing consumer behaviors, and a growing appetite for real-time transactions. As this transformation unfolds, new standards have been introduced to ensure the payments ecosystem's safety, security, and efficiency.
Event-Driven Microservices in Banking and Fraud Detection | Designing Event-Driven Microservices
How do we know whether Event-Driven Microservices are the right solution? This is the question that Tributary Bank faced when they looked at modernizing their old fraud-detection system. They were faced with many challenges, including scalability, reliability, and security. Some members of their team felt that switching to an event-driven microservice architecture would be the magic bullet that would solve all of their problems. But is there any such thing as a magic bullet? Let's take a look at the types of decisions Tributary Bank had to make as they started down this path.