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!
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As cloud technologies evolve, applications require less human intervention and maintenance. “Serverless” is a term that implies that users should have nothing to do with servers. The most exciting claim of serverless functions is that they scale automatically as the user base and load grows. Moreover, when there is no user activity, there will be […]
Recently, an interesting paper was published by UC Berkeley with their review of serverless computing and quite reasonable predictions: “…Just as the 2009 paper identified challenges for the cloud and predicted they would be addressed and that cloud use would accelerate, we predict these issues are solvable and that serverless computing will grow to dominate […]
We are excited to announce the new repository for extension modules of Hazelcast Jet. This repository will be home for the Hazelcast Jet extension modules, including connectors (including both sources and sinks), custom aggregations, and context factories. All of these modules will help make the integration easier for 3rd-party products in your pipelines. The main […]
Stream processing refers to real-time management of data entering a banking system (or any information system, actually) at high speed and volume, usually from a broad range of sources. The “management” aspect means data is wholly or partially processed and contextualized before entering an in-memory (operational) system, where pre-processing can significantly accelerate response times. Before […]
After releasing Hazelcast Jet 3.0 in May, we are happy to announce its first update, Hazelcast Jet 3.1. Hazelcast Jet is now an Apache Beam Runner Apache Beam is a framework for building distributed batch and stream processing applications over a unified API. The API itself is decoupled from the underlying execution implementation, making it […]
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Unbounded, unordered, global-scale datasets are increasingly common in day-to-day business – IoT sensor network data streams, mobile usage statistics, large scale monitoring, the list is endless. Numerous applications seek the ability to quickly react to dynamic streaming data, as it is either a mandatory requirement or a competitive advantage. API Churn As a consequence, lots […]
Hazelcast IMDG is tightly integrated into the Kubernetes ecosystem thanks to the Hazelcast Kubernetes plugin. In previous blog posts, we shared how to use auto-discovery for the embedded Hazelcast and steps for scaling it up and down using native kubectl commands. In this post, we’ll focus on another useful feature, Rolling Upgrade. You can apply […]
The megatrends that have been driving the adoption of Hazelcast by the world’s largest organizations are now strikingly clear: Enterprises are awash in data and must leverage it for business advantage New applications must process stored and streaming data Application latency is the new downtime. The money is in the microseconds To meet these needs […]
At Hazelcast we take reliability very seriously. With the new CP Subsystem module, Hazelcast has become the first and only IMDG that offers a linearizable distributed implementation of the Java concurrency primitives backed by the Raft consensus algorithm. In addition to well-grounded designs and proven algorithms, reliability also requires a substantial amount of testing. We […]
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