Operations | Monitoring | ITSM | DevOps | Cloud

The Canonical Data Fabric team is pleased to announce the first beta release of Charmed Spark, our solution for Apache Spark. Apache Spark is a free, open source software framework for developing distributed, parallel processing jobs. It’s popular with data engineers and data scientists alike when building data pipelines for both batch and continuous data processing at scale.

When people ask about the negative points preventing higher electric Vehicles (EV) sales, two points are raised systematically: range anxiety and the availability of charging stations. Range anxiety refers to the fear of running out of battery while driving. Of course, with more range or more charging stations, range anxiety decreases. Unfortunately, most countries lack EV charging infrastructure that meets consumer expectations.

Complying with US government security standards such as FIPS, FedRAMP, and DISA-STIG is essential for federal agencies and any business that deploys systems and services for U.S. government use. However, maintaining a compliant IT ecosystem is a major undertaking, as each regulation brings a host of specialised requirements. And dealing with the never-ending stream of security vulnerabilities that require patching only adds to this task.

In Ernest Hemingway’s novel “The Sun Also Rises,” there is a memorable exchange between the author and the main character, Mike. When asked how he went bankrupt, Mike responds with a concise yet profound answer: “Two ways. Gradually, then suddenly.” Innovation happens much in the same way. Gradually, then suddenly. Ideas simmer and evolve, gaining traction until they reach a tipping point.

In today’s digital landscape, organisations of all sizes have expanded their presence in the cloud. But with this expansion comes a significant increase in the attack surface, making security a top concern. In this blog, we will dive into the exciting world of cloud cyber security, and explore a stronger approach to securing your workloads with the help of Ubuntu.

Canonical, the company behind Ubuntu, is thrilled to announce its membership of the Eclipse Adoptium Working Group. As an esteemed project under the Eclipse Foundation, the Adoptium Working Group brings together renowned OpenJDK builders and distributors such as Alibaba, Azul, Huawei, IBM, Microsoft, Red Hat, Rivos, and, most recently, Google.

Data scientists and machine learning engineers are often looking for tools that could ease their work. Kubeflow and MLFlow are two of the most popular open-source tools in the machine learning operations (MLOps) space. They are often considered when kickstarting a new AI/ML initiative, so comparisons between them are not surprising. This blog covers a very controversial topic, answering a question that many people from the industry have: Kubeflow vs MLFlow: Which one is better?

Low-ops means minimising the effort for operating applications by automating as many tasks as possible. However, given the maximum automation, how can an SRE or DevOps engineer stay in control? Doesn’t automating tasks and being in control sound like a paradox?