Entries tagged [machine]

Ignite 2.8 Released: Less Stress in Production and Advances in Machine Learning

March 11, 2020 by Denis Magda. Share in Facebook, Twitter

With thousands of changes contributed to Apache Ignite 2.8 that enhanced almost all the components of the platform, it’s possible to overlook some of the improvements that can convince you to upgrade to this version sooner than later. While a quick check of the release notes will help to discover anticipated bug fixes, this article aims to guide through enhancements every Ignite developer should be aware of.

New Subsystem for Production Monitoring and Tracing

Several months of constant work on IEP-35: Monitoring & Profiling has resulted in the creation of a robust and elastic subsystem for production monitoring and diagnostic (aka. profiling). This was influenced by the needs of many developers who deployed Ignite in critical environments and were asking for a foundation that can be integrated with many external monitoring tools and be expanded easily.

The new subsystem consists of several registries that group individual metrics related to a specific Ignite component. For instance, you will find registries for cache, compute, or service grid APIs. Since the registries are designed to be generic, specific exporters can observe the state of Ignite via a myriad of tools supporting various protocols. By default, Ignite 2.8 introduces exporters for monitoring interfaces such as log files, JMX and SQL views, and contemporary ones such as OpenCensus.

Apache Ignite 2.4 ings Advanced Machine Learning and Spark DataFrames Capabilities

March 15, 2018 by Denis Magda. Share in Facebook, Twitter

Usually, Ignite community rolls out a new version once in 3 months, but we had to make an exception for Apache Ignite 2.4 that consumed five months in total. We could easily blame Thanksgiving, Christmas and New Year holidays for the delay and would be forgiven, but, in fact, we were forging the release you can't simply pass by.

Let's dive in and search for a big fish.

Machine Learning General Availability

Eight months ago, at the time of Apache Ignite 2.0, we put out the first APIs that formed the foundation of the Ignite's machine learning component of today. Since that time, Ignite machine learning experts and enthusiasts have been moving the liary to the general availability condition meticulously. And Ignite 2.4 became a milestone that let us consider the ML Grid to be production ready.

Apache Ignite 2.0: Redesigned Off-heap Memory, DDL and Machine Learning

May 5, 2017 by Denis Magda. Share in Facebook, Twitter

We released the long-awaited Apache Ignite version 2.0 on May 5. The community spent almost a year incorporating tremendous changes to the legacy Apache Ignite 1.x architecture. And all of that effort paid off. Our collective blood, sweat (and perhaps even a few tears) opened up new and exciting opportunities for the Apache Ignite project.

Have I piqued your interest about this new release yet? Let's walk through some of the main new features that have appeared under the hood of Apache Ignite 2.0.