Kafka in the Cloud: Why it’s 10x better with Confluent | Find out more
Software applications are the secret sauce of success for modern businesses today. But legacy applications in the past, despite having a logical modular design, were built as a large monolith with a single code base, sharing access to a single database and deployed as a single unit. While this approach worked a decade ago, this kind of tightly coupled architecture has many drawbacks in today’s environment where agile development to accelerate continuous innovation is critical to competitive success.
These challenges with monolithic applications resulted in organizations adopting a microservices architecture but as is so often the case, new technologies that solve problems in one area introduce new problems in others. And these problems with REST APIs and Message Queues, used for inter-service communication are not dissimilar to the challenges from monoliths.
These challenges include slow release/update cycles for new features, a lack of reliability and scale, as well as high operational costs and mounting technical debt.
Confluent, built on top of Apache Kafka, enables a new class of event-driven microservices, by completely decoupling services from one another and serves as the data backbone for your event-streaming applications. As a result, organizations can rapidly build and deploy state-of-the-art cloud-native applications with greater flexibility, at scale, and be more responsive to customer demands. Deploy on-prem, in the cloud, or both with a variety of deployment frameworks.
Eliminate the operational hassles for cluster management, so your developers can spend more time building applications. Remove dependencies between systems with a completely decoupled architecture and standardized schemas. Build and scale stateful services and real-time stream processing applications, faster using familiar SQL syntax.
Facilitate easy data access so each team has access to the right data at the right time for their specific needs. Eliminate slowdown and outages due to slow consumers. Meet regulatory needs by saving trusted, high-quality data for as long as your business needs.
Incrementally modernize from monoliths to microservices to reduce the operational costs of running legacy applications. Migrate your supporting data infrastructure at your own pace to a modern event-driven architecture. All with no downtime or business disruption.
Eliminate the operational hassles for cluster management with a fully managed cloud-native service that can elastically scale between 0-100MBps. Work in the language of your choice including Java, C, Node.js, Ruby, Go, .NET, or Python.
Eliminate inter-service bottlenecks and dependencies so developers can seamlessly connect to any data system while maintaining schema compatibility, version control, and quality assurance.
Regardless of whether your services need local state or not, a streaming platform using ksqlDB provisions for both, with an ability to create materialized views using event sourcing and simple SQL based syntax.
Build a system of record for systems and applications while eliminating slowdown due to slow or offline consumers. Build multi-datacenter, multi-region and hybrid cloud deployments for high availability and disaster recovery scenarios.
Discover, understand, and trust your event streams with Stream Catalog, Stream Quality and Stream Lineage, while offloading the management to Confluent.
Instantly connect to any legacy system with a rich ecosystem of 120+ fully managed connectors including CDC, JMS, and JDBC connectors. Incrementally migrate data from monoliths to microservices to modernize legacy applications with no business disruption.
Go from idea to proof-of-concept with a toolkit of code samples for the most popular use cases
“Using Confluent-designed microservices has allowed us to cut our go-to-market time in half. Confluent plays a pivotal role in delivering messages between microservices-based applications and connecting all our services as a core foundation.”
Hudson Lee, Platform Engineering Leader, eBay Korea
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