Hazelcast Cloud is an enterprise-grade in-memory computing platform deployed and managed by the Hazelcast CloudOps team. The service
is powered by Hazelcast IMDG Enterprise HD and leverages widely adopted technologies, such as Docker and Kubernetes, to provide dynamic orchestration and containerization. Hazelcast Cloud supports applications developed in some of the most common languages, including Java, Node.js, Python. Go, and .NET.
Hazelcast Cloud delivers enterprise-grade Hazelcast software in the cloud, deployed as a fully managed service. Leveraging over a decade of experience and best practices, Hazelcast Cloud delivers a high-throughput, low-latency service that scales to your needs while remaining simple to deploy. If you’re considering moving to the Cloud, or are looking for an easy ramp on deploying in-memory technology, this white paper on migrating in-memory to the cloud is an informative and helpful resource.
Setting up servers and configuring software can get in the way of the problems you are trying to solve. With Hazelcast Cloud we take all of those pain points away.
Watch this webinar to learn how you can instantly fire up and then work with Hazelcast Cloud from anywhere in the world. With our auto-generated client stubs for Java, Go, Node.js, Python and .NET, we can have you connected and coding in less than a minute!
Get a 30-day free trial.
Get started today with the
industry’s leading in-memory computing platform.
The in-memory speed you count on, with the convenience and scalability of cloud.
Through conceptual overviews, demos, and hands-on practice, you will learn to create stream processing pipelines using Java and Hazelcast Jet. This class is for advanced Java programmers who want to take their first steps in understanding and working with stream processing as well as for those who are already experienced in building the data processing applications and want to learn more about working with streaming data.
By the end of the course, you will have built and run distributed streaming pipelines to transform, enhance, and aggregate streaming data. You will also be able to discuss various stream processing options in terms of solving real-world, business-related problems.
The course includes the following lessons:
Note that stream processing pipelines are built using Java lambdas. If you are not familiar with this type of coding, you may not be able to complete many of the hands-on exercises without referring to the sample solutions.