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Bitcoin’s Death Cross

Neil Stevenson

Let’s start off the New Year with a fun code example! This example shows how Jet is used to spot the dramatically-named Death Cross for the price of Bitcoin, which is an indication to sell, Sell, SELL!. The idea here is that we could automatically analyze stock market prices and use this information to guide […]

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Hazelcast with Istio Service Mesh

Mesut Celik

Istio is said to be the next thing if you follow the Kubernetes path, and service meshes are mentioned whenever you go to a cloud-native meetup or conference like KubeCon. However, you do not always leverage something for the sake of popularity. The Hazelcast-Istio support discussion was started by a user after a GitHub issue […]

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Hazelcast Resilient to Kubernetes Zone Failures

Rafal Leszko

Data is valuable. Or I should write, some data is valuable. You may think that if the data is important to you, then you must store it in the persistent volume, like a database or filesystem. This sentence is obviously true. However, there are many use cases in which you don’t want to sacrifice the […]

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Stream Deduplication with Hazelcast Jet

Jaromir Hamala

Hazelcast Jet 3.2 introduces stateful map, filter, and flatmap operations, which are very strong primitives. In this blog, I am going to show you how to use stateful filter for detecting and removing duplicate elements in a stream. Why Deduplication? Deduplication is often used to achieve idempotency or effectively-once delivery semantics in messaging systems. Imagine […]

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Hazelcast Delivers Ultra-Fast Cloud Application Performance in IBM Cloud Pak for Applications

Kelly Herrell

We are excited to announce that Hazelcast in-memory technologies are now available for sale from IBM with the IBM Cloud Pak™ for Applications. The Hazelcast in-memory computing platform is an ultra-fast processing architecture for mission-critical applications where microseconds matter. The world’s most data-centric companies complement their systems of record, such as databases, with in-memory solutions […]

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Right-Sizing Your On-Demand Infrastructure for Payment Processing in Any Cloud

Dan Ortega
by Dan Ortega | October 17, 2019

In an ideal world, consumer-facing online businesses would deliver a consistent, efficient, and secure payment processing experience to their customers. Although there are lots of variables in running an e-commerce site, completing the sale is pretty much at the top of the list. When consumers go online to make purchases during a busy period such […]

How to Secure Your Hazelcast Cloud Deployments

Enes Akar
by Enes Akar | October 08, 2019

Securing your data is much more critical than ever before, as security breaches and cyber attacks continue to escalate. Security is a must, but generally, it requires tradeoffs in performance and user-friendliness. With Hazelcast Cloud, we provide you with several ways to secure your deployments without losing the performance and simplicity of Hazelcast.  Hazelcast Cloud […]

High-Speed Transaction Processing with No Compromise on Fraud Detection

Dan Ortega
by Dan Ortega | October 01, 2019

Transaction processing in today’s global payments networks is what essentially powers the global economy. The framework for transaction processing has expanded and morphed considerably over the past few years as consumers have started using their mobile devices to execute payments. Meanwhile, non-traditional deep-pocketed players like Google and Apple have entered the system with competitive alternatives, […]

Hazelcast Jet Connectors Release Announcement

Emin Demirci
by Emin Demirci | September 18, 2019

Since the first release of Hazelcast Jet Extension Modules in July, we’ve been focused on enhancing the set of extension modules that we have to make the integration easy between Hazelcast Jet and third-party data providers.  Today, we are happy to announce the release of the following modules: MongoDB Connector MongoDB is a general-purpose, document-based, […]

Open Banking and the Application of In-Memory Technologies

Dan Ortega
by Dan Ortega | September 12, 2019

The Open Banking initiative, also referred to as PSD2 (Payment Services Directive), is a textbook example of streaming technology applied to modern banking requirements. In this model, banks (primarily in Europe) are required to make their back-end systems for customer accounts and payment services available to other members of the financial payment ecosystem. While this […]

Where Is My Cache? Architectural Patterns for Caching Microservices

Rafal Leszko
by Rafal Leszko | September 10, 2019

I’m sure you use caching somewhere in your system. This can be either to improve performance, reduce backend load, or to decrease downtime. Everybody uses caching. Caching is everywhere. However, in which part of your system should it be placed? If you look at the following diagram representing a simple microservice architecture, where would you […]

Redis Load Handling vs Data Integrity: Tradeoffs in Distributed Data Store Design

Greg Luck
by Greg Luck | September 04, 2019

Introduction We all know that selecting the right technology for your business-critical systems is hard. You first have to decide what characteristics are most important to you, and then you need to identify the technologies that fit that profile. The problem is that you typically only get a superficial view of how technologies work, and […]

Running Apache Beam on Hazelcast Jet

Neil Stevenson
by Neil Stevenson | September 03, 2019

In June 2019, we announced the inclusion of Hazelcast Jet as a runner for Apache Beam. Now it’s time for an example showing how it’s done. As a bonus, it’s not “Word Count.” IoT Data The data we will use is a series of 2,000 GPS points and time offsets: # Latitude, Longitude, Time-Offset 45.417,8.179,1629 45.417,8.178,1630 […]

Auto-Scaling Clusters with Hazelcast Cloud

Enes Akar
by Enes Akar | August 08, 2019

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 […]

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