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!
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.
Hazelcast Enterprise features help simplify the DevOps function for companies that need secure, always-on, low-latency, in-memory processing features. Understanding the feature set of the Enterprise and Enterprise HD editions of the Hazelcast In-Memory Computing Platform will help you run at peak efficiency and performance. Features covered in this paper include: Rolling Upgrades Blue-Green Deployment Automatic […]
Hazelcast Jet (part of the Hazelcast In-Memory Computing Platform) is a high performance, scalable, and fault tolerant stream processing engine built for the highest throughput and lowest latency streaming environments. Job submission in Jet is done either using the Hazelcast Client directly from an application, or via the Hazelcast Command Line Interface (CLI). This guide […]
Are you ready to take your algorithms to the next steps and get them working on real-world data in real-time? We will walk through an architecture for taking a machine learning model into deployment for inference within an open source platform designed for extremely high throughput and low latency.
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.