Operations | Monitoring | ITSM | DevOps | Cloud

MLOps is the short term for machine learning operations and it represents a set of practices that aim to simplify workflow processes and automate machine learning and deep learning deployments. It accomplishes the deployment and maintenance of models reliably and efficiently for production, at a large scale. MLOps is slowly evolving into an independent approach to the machine learning lifecycle that includes all steps – from data gathering to governance and monitoring.

K3s and Rancher Kubernetes Engine (RKE2) are two Kubernetes distributions from the SUSE Rancher container platform. Either project can be used to run a production-ready cluster; however, they target different use cases and consequently possess unique characteristics. This article will explain the similarities and differences between the projects. You’ll learn when it makes sense to use RKE2 instead of K3s and vice versa.

In the software industry, monitoring and observability come hand in hand and are referenced simultaneously, but both are not the same thing. Having the right tools for these capabilities is vital to keep your systems, data, and security perimeter safe. With cloud solutions topping up in the integration space, great tools have been available in the market, and choosing the right one would be challenging.

Application engineers play a crucial role in bridging customer needs and the efforts of application development teams. Applications are becoming more complex—businesses are seeking to deliver more services while the software engineering components underlying those them are expanding and interacting in new ways. This combination of factors is driving the need for application engineers who can understand both the business and the technical aspects of applications.

Organizing a software release is a cross-team effort and a large undertaking. Leveraging the power of Mattermost Playbooks can help your team stay on deadline and keep confusion at bay. In this post, we’ll learn how to quickly integrate Mattermost into your GitLab release pipeline to help streamline your release processes. At the end of the blog post, there’s a link to a release management demo that you can try out in the browser to see these ideas in action.

MongoDB has evolved into the database solution of choice for developers looking to build efficient, scalable applications in the cloud. But, as when using any cloud-based infrastructure, using MongoDB introduces an additional layer of complexity to customers’ IT spend. This week, we announced support for MongoDB on the CloudZero Platform.