How we're using 'chaos engineering' to make cloud computing less vulnerable to cyber attacks Fascinating look at how deliberately introducing faults into cloud tech and then measuring the results helps identify and address potential vulnerabilities & weaknesses in a system's design, architecture, and operational practices.

From new AI-focused roles to enhanced efficiency and work-life balance, AI's impact on the #FutureOfWork is widespread and consequential for both executives and employees.

With nearly 3 in 4 companies going over their estimated cloud budgets, #cloudoverspend is a serious problem that undermines the cloud's many transformative benefits. Here's what you can do to keep costs in check:

Believe it or not, data to train #AImodels increasingly comes from other AI models in the form of synthetic data, which translates to cost reductions, but also poses some risk. Important analysis:

To scale growth, maximize efficiency and drive innovation, it's essential to unify the increasingly disparate data spread across on-prem, private and public cloud environments. Your guide to advancing the crucial objective:

Challenging the conventional wisdom that #AImodels must be powered by massive volumes of data, smaller, more efficient models that enable fast predictions and require less computational power are gaining traction.

💡Without a #cloudnative backup architecture, data resilience is practically unattainable. Important analysis:

From improving operations & customer experiences to driving revenue growth, AI is playing a pivotal role in transforming #telecom. Analysis ⬇️

AI can predict workload patterns and dynamically allocate resources such as CPU, memory, and storage to prevent resource abuse, ensuring optimal performance and reducing costs. More on using AI to optimize #CloudOps ⬇️