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The latest News and Information on DevOps, CI/CD, Automation and related technologies.

Priority-Based Escalation Policies: Because Not All Notifications Burn the Same

Let's face it – not all notifications are created equal. That paper cut of a CSS bug probably doesn't need the same response as your production database doing its best impression of a black hole. Today, we're thrilled to announce Priority-Based Escalation Policies, a powerful new way to ensure your team's response matches the notification severity.

Proactive Monitoring: How Engineers Use CloudWatch to Save Customers Money

At MetricFire, we love talking with engineers about their tech stacks, SRE challenges, and how they approach infrastructure monitoring. Recently, we had a great chat with Yoimer Roman from a Latin American cloud consulting company, that helps clients make smarter business decisions by leveraging AWS CloudWatch monitoring. Yoimer wears many hats: mentoring his team on all things AWS, designing custom cloud environments, and bridging the gap between technical challenges and non-technical stakeholders.

Accelerating AI with open source machine learning infrastructure

The landscape of artificial intelligence is rapidly evolving, demanding robust and scalable infrastructure. To meet these challenges, we’ve developed a comprehensive reference architecture (RA) that leverages the power of open-source tools and cutting-edge hardware.

Using CircleCI to test and deploy Python serverless functions on Microsoft Azure

Serverless computing simplifies app development by abstracting away server management. Azure Functions provides a robust platform for event-driven, on-demand code execution. In this tutorial, we’ll create and deploy a Python-based Azure Function—one that parses incoming JSON—using CircleCI. For a more granular and enable programmatic access to Azure resources, we’ll use service principal for secure authentication and the Azure CLI orb to streamline our CI/CD pipeline.

Unlocking Edge AI: a collaborative reference architecture with NVIDIA

The world of edge AI is rapidly transforming how devices and data centers work together. Imagine healthcare tools powered by AI, or self-driving vehicles making real-time decisions. These advancements rely on bringing AI directly to edge devices. However, building a robust architecture for diverse edge environments presents significant hurdles. This blog introduces our new reference architecture, designed to simplify edge AI deployment.

Building optimized LLM chatbots with Canonical and NVIDIA

The landscape of generative AI is rapidly evolving, and building robust, scalable large language model (LLM) applications is becoming a critical need for many organizations. Canonical, in collaboration with NVIDIA, is excited to introduce a reference architecture designed to streamline and optimize the creation of powerful LLM chatbots. This solution leverages the latest NVIDIA AI technology, offering a production-ready AI pipeline built on Kubernetes.

Tech Debt as Innovation? How Netflix Turns It Into Opportunity

At Civo Navigate San Francisco 2025, Lisa Smith, from Netflix shares a fresh perspective on how tech debt can drive innovation instead of slowing teams down. Learn how to staff legacy systems, handle tricky deprecations, and evaluate the “tech debtiness” of your infrastructure to unlock growth and efficiency. Discover how to turn tech debt into a strategic advantage for your engineering team.

Cloud migration security: Risks, strategies, and best practices

Whether you’re migrating from on-premises to the cloud, between cloud providers, or to more advanced cloud architectures, each path shares common security challenges that must be addressed head-on. With the right approach, you can actually enhance your security posture during migration. In this article, we'll dig into practical approaches to cloud migration security, covering everything from initial planning to post-migration maintenance.

#038 - Kubernetes Supercharging Particle Physics with Ricardo Rocha (CERN)

Ricardo from CERN, who leads the platform infrastructure teams, discusses CERN's significant role in particle physics research with the Large Hadron Collider. The conversation covers how CERN manages the massive amounts of data generated from experiments using a worldwide computing grid. Ricardo shares CERN's journey with adopting Kubernetes for various applications, including critical systems controlling detectors and accelerators. He also touches upon CERN's involvement with the CNCF and the Kubernetes community.