June 2024 Summaries

Edge computing is gaining popularity as it offers benefits such as reduced latency, improved security and compliance, efficient bandwidth utilization, and better customer experiences. Apache Kafka, a popular data streaming software, is making significant inroads into edge computing scenarios due to its efficiency, durability, and extensibility. The primary factors driving the adoption of edge computing include mitigation of networking limitations, lower latency processes, cost optimization, security and privacy, and scalability. Kafka helps overcome challenges posed by disconnected, intermittent, and constrained networking conditions through local data storage and replication to a cloud-based instance. It also enables real-time processing for near-immediate response in scenarios such as manufacturing, autonomous vehicles, and telecommunications. Edge computing offers cost savings by reducing the need for continuous cloud data transmission and allowing filtering or compression of data before sending it to the cloud. Confluent Platform provides solutions for automation, observability, and monitoring of Kafka clusters at the edge. The platform supports both thick and thin edge scenarios and can be applied to various use cases such as predictive maintenance, smart street applications, and naval onboard systems.

Confluent Platform is an enterprise-grade data streaming platform built by the original creators of Apache Kafka, which addresses common challenges faced when deploying open source Kafka at the edge, including managing complexity, processing capabilities, reliable cloud connectivity, and costs. Confluent provides a holistic set of features that come ready out of the box to accelerate time to value and reduce total cost of ownership (TCO) for data streaming. It offers a broad set of non-Java clients for popular programming languages, pre-built connectors, and stream processing capabilities with support for Apache Flink. Confluent reduces risk and resource investments for Kafka by simplifying operational tasks with enterprise-grade features for DevOps and platform teams, providing security features, governance features, disaster recovery and high availability features, and expert support to ensure business success from initial projects to creating a central nervous system across multiple lines of business.

RAG-enabled GenAI is a powerful approach for improving the accuracy of large language models by leveraging data streaming architectures with Confluent, Flink, and MongoDB. This approach allows data teams to contextualize prompts in real-time with domain-specific company data, making it more likely that the LLM will identify the right pattern in the data and provide a correct response. RAG enables fine-tuning of existing models without requiring significant expertise or resources, but must be implemented in a way that provides accurate and up-to-date information and is governed to scale across applications and teams. An event-driven architecture is beneficial for integrating disparate sources of data from across an enterprise in real-time, promoting reusability and allowing data augmentation for multiple LLM-enabled applications. This approach enables decentralized development teams to work separately to achieve performance and accuracy goals, decreasing time to market and increasing scalability.

Amazon OpenSearch Ingestion now supports Confluent as a source, allowing seamless integration between both platforms. This feature leverages PrivateLink and Elastic Network Interfaces (xENIs) to connect private third-party services like Confluent Cloud Enterprise clusters with private first-party services like an OpenSearch domain. The new Confluent Cloud blueprint in OpenSearch Ingestion enables users to easily utilize private networking in their OpenSearch/Confluent Cloud integration, supporting topics backed by Schema Registry and providing hands-free capacity management. This integration represents a step forward in allowing Confluent Cloud, which features more than 80 fully managed connectors to other systems, to serve as the nexus of ingestion for your OpenSearch implementation.

Confluent is thrilled to be named Microsoft’s 2024 OSS on Azure Global Partner of the Year, reflecting its commitment to delivering open source-based applications and infrastructure solutions on Microsoft Azure. Confluent Cloud offers a fully managed cloud-native Kafka service that integrates into Azure, making data streaming accessible to various companies in different industries. The platform unifies Kafka and Flink into an integrated solution with monitoring, security, and governance, redefining the data streaming experience. By leveraging Confluent’s cloud-native platform, organizations can prioritize application and analytics development over Kafka and data pipeline management, achieving greater data accessibility and fostering continuous ingestion, processing, governance, and sharing of data as a readily available and trustworthy product. The collaboration with Microsoft Azure is built on a shared commitment to drive innovation and technical integrations for joint customers, making it easy for companies to connect their data to Azure’s market-leading services.

Confluent's data streaming platform helps organizations harness vast amounts of data from various sources in real-time, enabling the creation of a holistic view of their infrastructure. By integrating IoT data, cybersecurity can be enhanced through real-time detection and response to malicious activity. Confluent provides a shift-left approach with stream processing, allowing for faster time-to-market and elimination of data quality issues. Stream processing enables correlation of events across multiple logs in real-time, providing a comprehensive view and facilitating informed decision-making. With Confluent, organizations can adopt a fully managed platform that minimizes latency between data generation and analysis, reducing the risk of cyber threats. Additionally, stream data anywhere, offload infrastructure management, and reduce TCO with Confluent's fully managed platform.

The generative AI chatbot is built using Amazon Bedrock and Confluent Cloud, enabling real-time data freshness and supporting the microservices paradigm. The chatbot's architecture consists of two major components: Confluent Cloud and Amazon Bedrock. Confluent Cloud provides a cloud-centered, data streaming platform that enables real-time data streaming capabilities and supports the microservices paradigm, while Amazon Bedrock offers a choice of high-performing foundation models from leading AI companies. The chatbot uses Anthropic's specialized chatbot model hosted on Amazon Bedrock to provide text summarization and data protection capabilities. The architecture dynamically scales in response to varying workloads, making it a flexible and adaptive solution for virtual banking interactions. The generative AI chatbot showcases real-time brilliance, scalability unleashed, and security beyond boundaries, setting a new standard for intelligent banking conversations.

Confluent and Amazon Web Services (AWS) have collaborated to simplify the transition to cloud services and enable real-time data streaming for improved insights and actions. Their solutions, which will be showcased at the AWS Public Sector Summit in Washington, DC on June 26-27, are integrated with over 120 connectors to streamline data migration from legacy systems to AWS. This collaboration helps government agencies accelerate time to value, reduce total cost of ownership, decrease unplanned downtime, and improve productivity by reallocating resources. Confluent's deep integrations with AWS Marketplace and services ensure consistent security, management, and billing for a seamless experience.

Confluent and Amazon Web Services (AWS) have collaborated to simplify cloud migration and management while enabling real-time insights through data streaming. Their solutions are integrated with AWS Marketplace and services, offering over 120 connectors for streaming data from various sources to AWS. This partnership helps government agencies improve customer experience and operational efficiency by breaking down silos, working with legacy systems, and modernizing at their own pace. Confluent and AWS provide a unified management, security, and billing platform, reducing TCO and improving productivity.

In today's fast-paced digital environment, offering real-time services is not just a benefit, but a necessity for businesses to stay agile and competitive. To accelerate the development of data streaming use cases, Build with Confluent is a new partner program that provides specialized software bundles, support from data streaming experts, and access to Confluent's Go-To-Market teams to amplify offerings in the market. This program helps partners monetize real-time solutions built on Confluent's data streaming platform faster and easier than ever, by leveraging pre-built code for common use cases, certification programs to validate solutions, and sales and marketing resources to reach the right audiences. By joining Build with Confluent, partners can help businesses protect themselves against sophisticated attacks such as AI-powered voice deepfakes, and unlock new business outcomes through robust data streaming platforms like Apache Kafka.

Confluent's data streaming platform helps businesses build RAG-enabled GenAI-powered loyalty programs with real-time data processing capabilities using Apache Flink. This enables personalized experiences, automated decision-making, and increased customer retention, ultimately driving revenue growth for organizations. By leveraging Confluent's abstracted away data infrastructure, development teams can focus on building innovative features, while marketing teams gain real-time insights into customer behavior. The platform streamlines data processing, governance, and security, making it an ideal solution for businesses aiming to boost retention and attract new customers in a competitive landscape.

Confluent is a company that offers a unique culture, core values, and support system to its employees, which motivates them to excel in their roles, particularly in customer success engineering. The company encourages diversity, equity, and inclusion through various programs and initiatives. Confluent's products are used by customers across different industries to solve business problems, and the company treats its customers as partners instead of vendors, fostering a fulfilling role for customer success engineers.

The "2024 Data Streaming Report" reveals that data streaming platforms (DSPs) have become a critical foundation for modern businesses, with 79% of IT leaders citing them as pivotal to driving business agility and 63% seeing DSPs extensively or significantly driving AI progress. The report also highlights the growing importance of GenAI technologies in bringing AI applications to market more quickly. With data streaming platforms enabling access to enriched, trustworthy, and contextualized data for scaling real-time AI applications, they are seen as integral to driving data product adoption by many IT leaders. Furthermore, 41% of IT leaders report an ROI of 5x or more on their data streaming investments, with higher levels of maturity leading to even greater returns. DSPs help businesses tackle common data challenges such as siloed data and inconsistent governance practices, enabling real-time, data-driven operations. The Data Streaming Awards recognize organizations that leverage this technology for business transformation.

To build a GenAI model that can utilize real-time data streams with Confluent, Flink, and MongoDB, businesses must adopt a cloud-native foundation and implement centralized data governance. This enables the integration of legacy technology with cloud-native systems, unlocking powerful use cases such as real-time personalization for customers. With Confluent Cloud, companies like Capital One can stream data, productize it, and manage it at scale, making it easier to leverage AI for customer personalization and power real-time fraud detection capabilities. By treating data as a product, businesses can govern their data effectively and share it across the organization as reusable data streams, unlocking value for both the business and its customers.