Igniters, Let's discuss approaches for a global announcement/promotion of the release. I would suggest focusing on a blog post and a community webinar.
The blog post will introduce significant improvements (service grid, thin clients, new metrics system, ML, etc.) sharing references to documentation pages with more details. It will be published on blogs.apache.org in a format similar to this one - https://blogs.apache.org/ignite/entry/apache-ignite-2-7-deep. I can work on it unless anybody else is willing to share the news on behalf of the community. Next, the blog post will be featuring a community webinar that is breaking down a subset of the improvements in more detail. Please see an abstract below with suggested topics for a detailed overview. @Alexey Zinoviev <zaleslaw....@gmail.com>, would you be able to present the ML part? @Nikolay Izhikov <nizhi...@apache.org> or @Andrey Gura <ag...@gridgain.com> would you like to take over the metrics section? I'll work the attendees through the items listed in "Sustainable production under high load". We should target the webinar for the April timeframe. *Topmost changes in Apache Ignite 2.8 for production maintenance and machine learning* *Apache Ignite community rolled out more than 1900 changes in Ignite 2.8 that enhanced almost all the components of the platform. The release notes go with hundreds of lines trying to catalog the improvements. Join this webinar led by Ignite community members demonstrating and dissecting new capabilities related to production maintenance, monitoring, and machine learning that you do not want to lose sight of:* - *Sustainable production under high load: Ignite persistence compaction and consistent crash recovery, baseline topology auto-adjustment, no interruption of operations for some cluster topology change events.* - *Next-generation system for monitoring and code tracing: design and usage, exporters configuration (JMX, SQL, OpenCensus) * - *Ignite Machine Learning major upgrade: a revised approach for models training/evaluation, models importing from Spark ML, XGBoost and much more * - Denis
