Companies need a data-processing solution that increases the speed of business agility, not one that is complicated by too many technology requirements. This requires a system that delivers continuous/real-time data-processing capabilities for the new business reality.
Stream processing is a hot topic right now, especially for any organization looking to provide insights faster. But what does it mean for users of Java applications, microservices, and in-memory computing?
In this webinar, we will cover the evolution of stream processing and in-memory related to big data technologies and why it is the logical next step for in-memory processing projects.
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!
Update streaming jobs in Hazelcast Jet without data loss or interruptions.
Job Upgrade makes use of Jet state snapshots to address a variety of requirements, including modifications in business logic, bug fixes, and configuration changes.
Easy to Implement
Job upgrades can be triggered via a Java API or from a command line.
State snapshots of current jobs are taken and saved.
New classes or changes are distributed to the Jet nodes.
New versions are started, and data is read from the saved snapshot.
No Disruption to Customers
Everything listed above happens in milliseconds, with essentially no latency.
Allows A/B Testing on New Features
Multiple versions of a Jet Job can run concurrently, writing results to separated sinks.
After the testing period, pick the better version, and shut down the other.
Introduce relevant filtering or transforming steps to streaming data-centric applications.
Change business rules or add new operators as the business logic driving your streaming applications evolves.
Change IP addresses for sources or sinks without disrupting streaming services.
In this video tutorial, Hazelcast cloud software engineer Rafal Leszko walks you through the steps to get Hazelcast running in embedded mode in a Kubernetes cluster.
Get up and running with the Hazelcast IMDG C# / .NET Client quickly with this easy to use reference card.
Get up and running with the Hazelcast IMDG Python Client quickly with this easy to use reference card.
Whether you're interested in learning the basics of in-memory systems, or you're looking for advanced, real-world production examples and best practices, we've got you covered.