Operations | Monitoring | ITSM | DevOps | Cloud

If you’re using containers to deploy your software, it is important to be aware of potential vulnerabilities within your container images. These may be introduced through dependencies in your built image, or perhaps through dependencies within the base image(s) used to build your image.

In Part 1 of this blog series, I proposed that closed-loop orchestration (CLO) is a data management problem. Data extends beyond your medical history, social media, and other PII in the digital world. Configurations, inventories, and monitoring systems are based on managing, interpreting, and actioning data. CLO is a workflow about manipulating the data around the target environments. Even the policies and constraints need to be expressed as data.

Vehicles are becoming more and more like mobile data centres. On average, a modern vehicle contains over 60 sensors that monitor various aspects of the vehicle, generating an immense amount of data that is processed on the go. This transformation is creating an unprecedented set of challenges for OEMs. Edge computing is a new paradigm that is changing how data is processed in these types of environments.

Today marks a significant milestone for Qovery and a highly anticipated evolution of our product, especially among Platform Engineers and DevOps professionals. We're thrilled to announce the "Bring Your Own Kubernetes" (BYOK) offer in beta access, a transformative step in our journey towards more flexible and adaptive infrastructure management. Please keep reading to understand why we extend our offer.

The 2023 CloudZero Makeover (Rebrand) Role-Based Access Control: New Editor Role Usage Data In Analytics View Your Data By GCP Tags CostFormation® Proportional Allocation Improvements Small Bites If you’ve visited CloudZero lately, you’ve probably seen a few changes. New logo, new app, new website, new look and feel — okay, more than a few changes. What provoked the rebrand?

Last year, we released Reliability Management, a combination of pre-built reliability tests and scoring to give you a consistent way to define, test, and measure progress toward reliability standards across your organization. Today, we fulfill the next stage of that promise with the release of Custom Reliability Test Suites, Custom Scoring, and Dashboards.

With automation and CI/CD practices, the entire AI workflow can be run and monitored efficiently, often by a single expert. Still, running AI/ML on GPU instances has its challenges. This tutorial shows you how to meet those challenges using the control and flexibility of CircleCI runners combined with Scaleway, a powerful cloud ecosystem for building, training, and deploying applications at scale.

In a traditional DevOps implementation, you automate the build, test, release, and deploy process by setting up a CI/CD workflow that runs whenever a change is committed to a code repository. This approach is also useful in MLOps: If you make changes to your machine learning logic in your code, it can trigger your workflow. But what about changes that happen outside of your code repository?