Operations | Monitoring | ITSM | DevOps | Cloud

In part one of this series, I introduced you to Kubeflow, a machine learning platform for teams that need to build machine learning pipelines. In this section, we will learn how to take an existing machine learning project and turn it into a Kubeflow machine learning pipeline, which in turn can be deployed onto Kubernetes. As you are going through this exercise, think about how you can convert your existing machine learning projects into a Kubeflow one.

There are many challenges that engineering teams face when attempting to incorporate a multi-cloud approach into their infrastructure goals. Kubernetes does a good job of addressing some of these issues, but managing the communication of clusters that span multiple cloud providers in multiple regions can become a daunting task for teams. Often this requires complex VPNs and special firewall rules to multi-cloud cluster communication.

The blessing and curse of cloud computing is flexibility. Now more than ever, companies leveraging the cloud are being revered for their ability to scale up usage of critical applications remotely for employees working from home, while in the same breath lambasted as IT costs sky-rocket. And in the midst of soaring usage, capacity, and cost come budget-cuts to fend off any other necessary evils during this challenging time.

Hello and welcome to another issue of This Month in Qovery! Qovery helps developer to deploy their applications in the Cloud in just a few seconds. This is a monthly summary of its progress and community.

When it started to really get traction as a concept, almost 10 years ago, DevOps was primarily used to push rapid changes to web environments with minimal impact for the users. That might still be true today but DevOps as a concept evolved. A lot. We now rely on DevOps models to move at high velocity, adapting and developing at speeds that are light years away from anything we’ve seen before. It’s the way we deliver, test, monitor, and release functionalities.

Across the world, many network operators, fiber network wholesalers, municipalities, and local authorities are in a race to put fiber in the ground. New techniques and specialized tools have reduced the time it takes to deploy optical fiber and increased the amount of fiber held in a single duct, this makes the dream of providing fiber to every premise a cost-effective reality.

The pandemic has heightened IT leaders’ need for efficiency in managing what we’re seeing more and more as a hybrid cloud world. We recently polled IT leaders across the US and EMEA on their current challenges, changes, and goals around hybrid cloud deployments, infrastructure visibility, use of AI/ML, and more.