Webinar – Creating an Elixir machine learning module for a monitoring and maintenance platform.
What to expect in this webinar?
WombatOAM is the only tool designed to empower teams with complete visibility and customisable alerts built specifically for BEAM-based systems (covering everything from Erlang & Elixir to Cowboy and RabbitMQ). We’ve recently worked on a number of exciting updates, including a new User-Interface and a machine learning module that will create alerts of any abnormal performance based on your standard system performance. This webinar will take you through all of the new features of WombatOAM, including how we built the machine learning module, its performance, and what we learned about creating an ML project in Elixir.
What you’ll learn:
What is WombatOAM
How WombatOAM empowers developers
How WombatOAM works
What our new Machine Learning Module does
How we built our Machine Learning Module in Elixir
Mohamed Ali Khechine (Dali) has worked at Erlang Solutions since 2018 within the WombatOAM team. He is interested in everything metrics and alerting for the BEAM virtual Machine.
Tamas Lengyel: Is a member of the Erlang Solutions team who has recently graduated with a Master’s degree in Computer science, his last thesis was titled “Software failure prediction by analysing runtime metrics”. The results of this work has been included in WombatOAM.