The latest News and Information on DevOps, CI/CD, Automation and related technologies.
Some of the highest priorities for engineers - from NOC Engineers, DevOps & Site Reliability Engineers - are the automation and optimization of their production environments. Many companies today face tough challenges with their Network Operations Centers (NOCs) or production environments. These challenges fall into the hands of engineering teams.
On-premises vs cloud MDM deployment With the rise of SaaS application management, mobile device management (MDM) services have gained popularity among IT professionals. Modern computing environments rely on the efficient use and provisioning of resources. But which one is right for your business: on-premise or cloud MDM deployment? While this may seem like a simple question, there are many factors that come into play when deciding which method to go with. This article discusses the differences between on-premises vs. cloud MDM deployment. It will also present examples, use cases, and pros and cons of these two deployment options.
If you pick a random SaaS company out of a jar and go to their website, chance are they integrate with another tool. Typically, the end goal of integrations is to meet users in the middle by working with other tools they’re already using on a day-to-day. Put another way, integrations are a strategic business decision. But the question remains: why don’t companies just build a tool with similar functionality in order to make the product stickier?
When people hear ‘containers,’ they don’t immediately think about an IT solution that helps businesses create and distribute applications seamlessly. However, the container concept has been around for a long time, helping companies in various industries globally. Containers continue to change the landscape of app development and deployment. This guide below will help you understand containerization and the best orchestration tools to manage containers.
While AI seems to be the topic of the moment, especially in the tech industry, the need to make it happen in a reliable way is becoming more obvious. MLOps, as a practice, finds itself in a place where it needs to keep growing and remain relevant in view of the latest trends. Solutions like ChatGPT or MidJourney dominated internet chatter last year, but the main question is…What do we foresee in the MLOps space this year and where is the community of MLOps practitioners focusing their energy?
