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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industry’s leading in-memory computing platform.
The in-memory speed you count on, with the convenience and scalability of cloud.
Hazelcast Management Center enables monitoring and management of nodes running Hazelcast IMDG or Jet. This includes monitoring the overall state of clusters, as well as detailed analysis and browsing of data structures in real time, updating map configurations, and taking thread dumps from nodes.
During development, Management Center provides deep insights. In production, it can be directly used by IT operations or integrated with enterprise monitoring tools using REST and JMX. It can also provide dedicated controls for WAN Replication for monitoring replication.
The home page of the Management Center provides a dashboard-style overview. For each node, it displays at-a-glance statistics to quickly gauge the status and health of each member, as well as the cluster as a whole.
Insights into the usage and status of distributed data structures is provided by the Caches, Maps, Queues, Topics, MultiMaps, and Executors pages, which provide a drill-down view into the operational statistics of individual data structures.
Centralized monitoring and management of each cluster member is available on the member’s page. Each member’s CPU and memory utilization, runtime properties, partition count and configuration is available at a glance.
Hazelcast nodes expose a JMX management interface with statistics on distributed data structures and the state of node internals. The Management Center provides JMX and REST APIs to view and control cluster aspects from a single endpoint. The Enterprise Management Center provides JMX and REST APIs to view and control cluster aspects from a single endpoint.
This case study profiles a major US media company's use of in-memory technology to enable high-volume Machine Learning and Artificial Intelligence applications used to build out 360-degree customer profiles, in real-time, that are used to create chatbots to handle customer support inquiries.
In this White Paper, Hazelcast provides business-level examples of how 5G and In-Memory can work together for Edge Use cases.
When microseconds can mean the difference between success and failure, caching solutions deliver blinding speed with scalable and flexible management of data. In this white paper, we cover specific of caching solutions, where and why an enterprise would be interested, its application across multiple industries and its impact on data management, including Artificial Intelligence and Machine Learning use cases.
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.