Category: Hazelcast

Feed: Blog – Hazelcast. Author: Burak Celebi. This is the first blog post for Hazelcast IMDG’s Blue/Green Deployments feature, which is the most recent member of the Enterprise edition.  “Blue/Green deployment” refers to a software technique used to reduce or even eliminate system downtime and the associated business risk by deploying two mirrored production environments referred to as “Blue” and “Green”.  In Hazelcast IMDG 3.12, we released a new Hazelcast Enterprise feature for Blue/Green deployments. It provides a client failover mechanism that allows for client connections to be rerouted to a different cluster without requiring a client network configuration update ... Read More

Feed: Blog – Hazelcast. Author: Vladimir Schreiner. Tech conferences and meetups have been canceled or postponed across the world. To make the situation a little bit more pleasing for everybody who misses them, Hazelcast has started a series of virtual tech meetups. Please join us on Thursdays, starting April 2nd. Always at 3:30pm CET/ 7:30am PDT / 10:30am EDT / 2:30pm GMT. The list of topics: Streaming in the world of legacy applications (Vladimir Schreiner) Date: Thursday, April 2, 2020 Join: https://hazelcast.com/resources/tech-talk-streaming-in-the-world-of-legacy-applications/ A practical introduction to CDC (Change Data Capture). Architecture, trade-offs, tooling, and demos. There are common themes when ... Read More

Feed: Blog – Hazelcast. Author: Seb Benmbarek. Today, we’re happy to announce the general availability of Hazelcast Cloud Enterprise on AWS. This much-anticipated release will make it even easier for solution architects and developers with a need for extra-low latency to leverage the power of Hazelcast IMDG within their cloud technology stack. What is Hazelcast Cloud Enterprise? Even though we already offer many options to run Hazelcast enterprise software in the cloud, we’ve seen a growing interest from our customers and prospects for a fully managed service. Hazelcast Cloud Enterprise enables you to easily develop and deploy low-latency applications in ... Read More

Feed: Blog – Hazelcast. Author: Mike Yawn. Hazelcast Cloud Enterprise is the new cloud-native managed service that allows you to quickly set up a cluster of Hazelcast IMDG nodes in a public cloud (Amazon Web Services today, with Google GCP and Microsoft Azure coming later this year), and have that cluster fully managed for you by Hazelcast. Setting up the cluster requires just a few steps, and we will take you through everything you need to do to get your first cloud-based cluster up and running.   For this blog, we’ll deploy our Hazelcast Cloud Enterprise cluster on Amazon AWS, ... Read More

Feed: Blog – Hazelcast. Author: Villiam Ďurina. Hazelcast Jet is a distributed stream processing engine that supports exactly-once semantics even in the presence of cluster member failures. This is achieved by snapshotting the internal state of the processors at regular intervals into reliable storage and then, in case of a failure, using the latest snapshot to restore the state and continue. However, the exactly-once guarantee didn’t work with most of the connectors. Only replayable sources, such as Apache Kafka or IMap Journal were supported. And no sink supported this level of guarantee. Why was that? The original snapshot API had ... Read More

Feed: Blog – Hazelcast. Author: Nicolas Frankel. Hazelcast Jet allows you to distribute stream processing over several cluster nodes. While it comes with several out-of-the-box sources to read from (Hazelcast IMap, JMS, JDBC, etc.), and sinks to write to, there’s no Java 8 streams source. In this post, we are going to create an adapter to bridge this gap. A Look at the SourceBuilder API The com.hazelcast.jet.pipeline.Sources class contains the available sources mentioned above. That should be your first stop because nobody wants to reinvent the wheel. To create a custom source, the entry point is the SourceBuilder class. It ... Read More

Feed: Blog – Hazelcast. Author: Kelly Herrell. Given the unprecedented scale of COVID-19, we would like to take a moment to share how Hazelcast is navigating the situation to maintain our commitment to you and your customers while protecting the health and safety of our team members. Our responsibility. With more than 130 employees across 21 countries, we’re a highly distributed workforce that enables us to be flexible during times like now. Regardless, the health and safety of our customers and employees are of the utmost importance and we’re asking that all employees avoid travel and group meetings unless it ... Read More

Feed: Blog – Hazelcast. Author: Neil Stevenson. Today is PI DAY! Obviously, Pi has rather more than 2 decimal places. To have some fun, let’s use Jet to drive multiple Python workers to calculate Pi with increasing accuracy. Pi is the ratio of a circle’s radius to its circumference. It’s 3.14. It’s 3.1416. It’s 3.14159266 or whatever. It has apparently an infinite number of decimal places. But how to calculate it? There are various ways, but here we’re going to use the “Monte Carlo method.” Random points on a square that contains a circlePicture a circle that exactly fits inside a ... Read More

Feed: Blog – Hazelcast. Author: Vladimir Schreiner. Machine learning projects can be split into two phases: Training Inference During the training phase, data science teams have to obtain, analyze and understand available data and generalize it into a mathematical model. The model uses the features of the sample data to reason about data it has never seen. Although it can be completely custom code, it is usually based on proven machine learning algorithms, such as Naïve Bayes, K Means, Linear Regression, Deep Learning, Random Forests or Decision Trees. The act of building the model from the sample (training) data is ... Read More

Feed: Blog – Hazelcast. Author: Can Gencer. We’re happy to introduce Hazelcast Jet 4.0 and its new features. This release was a significant effort and featured 230 PRs merged which makes it one of our biggest releases in terms of new features. Distributed Transactions Jet previously had first-class support for fault tolerance through implementation of the Chandy-Lamport distributed snapshotting algorithm, which requires participation from the whole pipeline, including sources and sinks. Previously, the at-least-once and exactly-once processing guarantees were only limited to replayable sources such as Kafka. Jet 4.0 comes with a full two-phase commit (2PC) implementation, which makes it ... Read More