Operations | Monitoring | ITSM | DevOps | Cloud

July 2023

Hacking our Way Towards ML-first Jupyter Notebooks - Civo Navigate NA 2023

In this Navigate 2023 talk, Matt Dupree discusses various challenges in data work and machine learning and proposes potential solutions. He highlights the importance of static analysis to address the problem of refactoring in data notebooks. Dupree emphasizes the need for automated testing workflows using IPython's hooks and profiles to minimize errors and missed opportunities. Furthermore, he suggests the development of Jupyter Bridge plugins to alleviate the repetitive typing of code and simplify the interaction between Python and JavaScript.

Netdata & Ansible example: ML demo room

We are always trying to lower the barrier to entry when it comes to monitoring and observability and one place we have consistently witnessed some pain from users is around adopting and approaching configuration management tools and practices as your infrastructure grows and becomes more complex. To that end, we have begun recently publishing our own little example ansible project used to maintain and manage the servers used in our public Machine Learning Demo room.

8 Important Things You Should Know About The Tech Used In The Food Industry

Are you curious about the technology that powers the food industry? From farm to fork, the use of cutting-edge tech has revolutionized how we produce, process, and consume our favorite meals. Whether you're a food enthusiast, a health-conscious individual, or simply intrigued by the latest innovations, understanding the role of technology in the food industry is vital. In this blog post, we'll explore eight important things you should know about the tech used in the food industry.

How Technological Advancements Transform Hiring Processes and Decisions

Technology has forever changed the landscape of businesses, especially in terms of HR practices. From hiring to onboarding and beyond, technological advancements have drastically altered the way companies develop their teams and make decisions. Automated technologies can help streamline processes, improve accuracy around evaluating job candidates, simplify communication and collaboration between colleagues globally-the list goes on! To better understand how technology influences human resources today and into the future, let's take a closer look at how far it has come already in transforming different stages within the typical hiring process.

ML Observability: what, why, how

Note: This post is co-authored by Simon Aronsson, Senior Engineering Manager for Canonical Observability Stack. AI/ML is moving beyond the experimentation phase. This involves a shift in the way of operating because productising AI involves many sophisticated processes. Machine learning operations (MLOps) is a new practice that ensures ML workflow automation in a scalable and efficient manner. But how do you make MLOps observable?