The higher education industry is experiencing significant transformation. Colleges and universities have embedded digital tools across their academic environments to provide exceptional experiences for students, faculty, and staff. As technology becomes more integral to education, maintaining efficient, secure IT operations while ensuring 24/7 availability presents new challenges for institutions to manage.

Managing IT infrastructure has traditionally been a complex, manual process prone to inefficiencies and human errors. IaC directly addresses these challenges by automating the setup and management of IT infrastructure through code. This approach helps to resolve common infrastructure management problems like lengthy deployment times, configuration drift, and inconsistent configurations.

Kubeflow is an open source MLOps platform that is designed to enable organizations to scale their ML initiatives and automate their workloads. It is a cloud-native solution that helps developers run the entire machine learning lifecycle within a single solution on Kubernetes. It can be used to develop, optimize and deploy models. This blog will walk you through the benefits of using an official distribution of the Kubeflow project.

Adopting a cloud-based, distributed architecture may help your organization scale quickly, but it can also add complexity. Correlating telemetry, security signals, and alerts across services often proves difficult, resulting in slower issue remediation. Additionally, when something goes wrong, figuring out who to contact—for example, the on-call responder or the service owner— may become needlessly time-consuming.

Infrastructure monitoring is necessary for finance companies. Whether running a small fintech startup or managing systems for a global bank, having secure, reliable tools to monitor and manage your infrastructure and applications is fundamental for the success and security of your business. This article covers some common monitoring use cases for financial companies and how you can get the metrics you need with an agent. Try signing up for a free trial today!

The principle of continuous improvement is central to the practice of observability. Naturally, within the data-driven philosophy of DevOps this implies an ongoing cycle of acting, measuring and improving. For many teams, the classic four DORA metrics are seen as a gold standard. As I discussed in a previous article, whilst DORA metrics are a great starting point for assessing your agile capabilities, they are not necessarily definitive.

What if I told you that you're using dashboards wrong? Imagine this: You're on a call with your team, staring at a big, static dashboard full of graphs and numbers. Someone pipes up, "Okay, so what now?" Everyone exchanges glances, unsure of how to move forward. You've got the data, but somehow, you're still stuck. If you’re nodding along, we feel you. The truth is, the way we’ve been using dashboards is outdated. They’re static. They’re rigid.

As someone deeply invested in the evolution of SquaredUp, I’d like to share more about our search capability and how we designed the functionality. SquaredUp can connect to 100+ data sources, thousands of objects, tons of metrics, and and we offer many purpose-built out-of-the-box dashboards and monitors. We've deliberately designed our search experience to be able to handle the complexity of various data environments and make finding relevant information seamless and efficient.

Did you know CFEngine can self-organize hosts into different groups? Say you have a few hosts that you want to reboot once a month. You don’t care when, but you want the hosts to self-organize and pick a date. The select_class attribute for classes type promises might be what you’re looking for. Let’s take a look.