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

Why eBPF is Poised to Revolutionize Kubernetes [Without Anyone Noticing]

Have you heard about eBPF? It’s the technology that’s set to transform the Kubernetes landscape. In this article, we’ll explore what eBPF is and why it’s poised to become the next big thing in Kubernetes. But here’s the catch – despite its game-changing potential, it seems that few people are truly aware of its impact. Let’s delve into the details and discover why you should care.

What Is A Time-Series Metric?

Today, businesses and organizations rely heavily on metrics and analytics to make informed decisions. Metrics are important whether you’re a developer, a marketer, or the head of a company. One type of metric that is widely used is a time-series metric. Time-series metrics provide insights into how data changes over time. With time-series data, businesses can track trends, detect anomalies, and make predictions.

The case for engineering automation

When you survey developers on how to improve engineering practices and their daily job experience, their answers invariably include getting rid of little annoying things - what's called toil. Toil is manual and repetitive tasks that waste your time. Toil is arguably worse than crisis, because a crisis is temporary and firefighting can feel rewarding when it's over. Toil is more like a death march - an insidious force that eventually leads to burnout.

Kubeflow vs MLFlow

Learn the main differences between the MLOps tools of choice: Kubeflow and MLFlow Started by Google a couple of years ago, Kubeflow is an end-to-end MLOps platform for AI at scale. Canonical has its own distribution, Charmed Kubeflow, which addresses the entire machine-learning lifecycle. Charmed Kubeflow is a suite of tools, such as Notebooks for training, Pipeline for automation, Katib for hyperparameter tuning or KServe for model serving and more. Charmed Kubeflow benefits from a wide range of integrations with other tools such as MLFlow, Spark, Grafana or Prometheus.