Operations | Monitoring | ITSM | DevOps | Cloud

We recently moved our infrastructure fully into Google Cloud. Most things went very smoothly, but there was one issue we came across last week that just wouldn’t stop cropping up. What follows is a tale of rabbit holes, red herrings, table flips and (eventually) a very satisfying smoking gun. Grab a cuppa, and strap in. Our journey starts, fittingly, with an incident getting declared... 💥🚨

Ever since its release in September 2014, Kubernetes has been equally powerful and meme-able in the engineering world. For all the magic of its container orchestration and compute resource management, it’s also mysterious and, to many, confounding — especially when it comes time to pay for it. As we’ve written before, migrating to Kubernetes often means losing cost visibility.

Kubernetes has become the de facto standard for container orchestration, offering powerful features for managing and scaling containerized applications. In this guide, we will explore the various aspects of Kubernetes scaling and explain how to effectively scale your applications using Kubernetes. From understanding the scaling concepts to practical implementation techniques, this guide aims to equip you with the knowledge to leverage Kubernetes scaling capabilities efficiently.

Containers have gained significant popularity due to their ability to isolate applications from the diverse computing environments they operate in. They offer developers a streamlined approach, enabling them to concentrate on the core application logic and its associated dependencies, all encapsulated within a unified unit.

Artificial intelligence (AI) won’t fade anytime soon, and since Generative AI (genAI) joined the party in Nov. 2022, innovative business strategies will only get louder. The not-so-fun part of AI and genAI’s growth shows up when businesses resist change and the adoption of emerging technologies. But the truth is – business leaders must step up.

Azure Functions offers a serverless solution that streamlines the development process, minimizes infrastructure overhead, and results in cost savings. The beauty of this approach is that you no longer need to grapple with server deployment and maintenance; the cloud infrastructure automatically furnishes the essential resources to support your applications.

As technology advances and business environments become increasingly competitive, your DevOps team has to continuously improve your product. The challenge is to free up their time so that they can release new product features and improve existing ones. Automating repetitive tasks is one way to accomplish this. Manual approaches also tend to generate or miss errors, slow time to market, and fail to test and monitor system health quickly enough.

Microsoft Azure provides a completely managed event routing service called Azure Event Grid. It allows you to respond to events received from various Azure services and external applications and forward them to different Azure services and endpoints. Azure Event Grid provides a unified way to manage events in Azure with event-driven programming. With Event Grids, you can create event-driven applications in a serverless environment, cutting down costs and performance lags.

London, United Kingdom, 26 September 2023. Canonical announced today that Charmed MLFlow, Canonical’s distribution of the popular machine learning platform, is now generally available. Charmed MLFlow is part of Canonical’s growing MLOps portfolio. Ideal for model registry and experiment tracking, Charmed MLFlow is integrated with other AI and big data tools such as Apache Spark and Kubeflow. The solution runs on any infrastructure, from workstations to public and private clouds.