Hazelcast Presents at Tech Field Day 23

Introducing In-Memory Computing with Hazelcast

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CEO Kelly Herrell provides a quick overview of Hazelcast, its history and the future of the leading in-memory computing platform. He begins with some background on the market and Hazelcast’s success to date, providing in-memory compute solutions on a global scale and growing rapidly. Industry trends like Kubernetes, micro services, hybrid cloud, edge computing, and machine learning are driving adoption of in-memory computing to empower applications to act instantaneously on data. It is used in payment processing, fraud detection, e-commerce, and edge computing, offering real-time processing and low latency for applications. Hazelcast is a boundary less modern digital compute and data layer for fast data and compute.

Personnel: Kelly Herrell

Demonstrating Vehicle Telemetry Solutions with Hazelcast

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Sr. Solutions Architect, Terry Walters, will present a vehicle telemetry demo that shows how real-time in-memory technologies from Hazelcast can be used to ensure safe driving at manufacturing plants and beyond. After discussing the challenges of vehicle navigation, Walters presents a telemetry solution using mobile devices, a web application, and real-time event ingestion, dynamic rule execution, and inferred events on the hazel cast platform. The example includes Netty, Hazelcast JET and IMDG, and Jetty to ingest and query data. Walters then discusses this solution in depth with the Tech Field Day delegates.

Personnel: Terry Walters

Hazelcast In-Memory Data Grid Overview and Use Cases

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Sr. Director of Technical Solutions, Dale Kim, will dive into Hazelcast’s in-memory data grid and event stream processing engine. He will also highlight some interesting and innovative use cases built by Hazelcast customers. After presenting the differences between the open source and enterprise editions of Hazelcast’s solution, Kim presents an architectural discussion of distributed computing using Hazelcast, including a look at data flows (streams and ad hoc requests), and where Hazelcast fits into enterprise application architecture. Hazelcast can ingest data from a variety of sources, including Kafka, MQ, IoT, enterprise applications, files, sockets, and database events, and output actionable content to these. Hazelcast acts as a system of record for distributed data in a cloud-first, memory-first, fast, reliable, and simplified way, providing low latency with resilience.

Personnel: Dale Kim

How Hazelcast Jet Can Monitor Financial Trades

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Field CTO, Neil Stevenson, will showcase how Hazelcast Jet, a real-time streaming engine, can be used by banks and investors to monitor trades. The financial industry must monitor trades in real time, but traditional solutions delay analysis for batch processing. Hazelcast Jet can process streams of data in real time for near-real-time visibility with a simplified processing pipeline.

Personnel: Neil Stevenson

Edge, Mainframe, FS Cloud, and ML with Hazelcast, IBM, and Intel

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Dale Kim, Sr. Director of Technical Solutions, will walk through Hazelcast’s partnership with IBM and Intel and how we’re working together on a number of use cases tied to edge computing, mainframe optimization, IBM Cloud and more. Kim presents cloud-native deployment of Hazelcast in IBM Cloud with Red Hat OpenShift and edge computing with IBM’s Edge Ecosystem. He also presents mainframe integration with hybrid cloud built on IBM Red Hat OpenShift. Next Kim turns to fast compute and memory with Intel Optane PMem and Xeon Scalable CPUs. Finally, Kim presents use cases for Hazelcast, including caching, fast restart with Optane, on-demand analytics, continuous query with drill down, and a payment processing reference architecture.

Personnel: Dale Kim