Operations | Monitoring | ITSM | DevOps | Cloud

If you're like most companies running large-scale, data- intensive workloads in the cloud, you’ve realized that you have significant quantities of waste in your environment. Smart organizations implement a host of FinOps and other activities to address this waste and the cost it incurs: … and the list goes on. These are infrastructure-level optimizations.

In the dynamic landscape of cloud operations, Network Operations Centers (NOCs) are crucial in ensuring service reliability and performance. However, managing the diverse workloads of NOC teams can be challenging. At MoovingON, we are dedicated to providing solutions that enhance operational efficiency and cultivate a positive work environment for our engineers. To this end, we are excited to introduce a powerful new feature in our moovingon.ai platform: Enhanced Dashboards for Workload Management.

If you're like most companies running large-scale, data-intensive workloads in the cloud, you’ve realized that you have significant quantities of waste in your environment. Smart organizations implement a host of FinOps and other activities to address this waste and the cost it incurs: … and the list goes on. These are infrastructure-level optimizations.

We are excited to announce the release of ARM builds in the Pipelines cloud runtime. Our release of Linux based ARM runners in cloud allows you to build and deploy software for ARM-based systems with all the benefits of our fully managed CI/CD platform. To use the new cloud ARM runners in your pipeline, make the following modifications to your bitbucket-pipelines.yml file.

Many companies migrate to the cloud and overlook costs in favor of innovation, speed, and flexibility. They assume that the cloud is inherently more cost-effective than on-premises infrastructure. However, the organizations soon realize that the same characteristics that make the cloud such an enticing and flexible resource can also lead to unexpectedly higher usage bills than expected. The challenge is to find the right balance between optimal system performance, engineering velocity, and cost.

The rapidly growing interest in AI has raised a corresponding demand for specialized cloud compute that is built to run training and inference workloads in a cost-efficient and performant manner. Google Cloud Tensor Processing Units (TPUs) have become a popular accelerated compute solution for AI/ML workloads.

Finding trained financial planning and analysis (FP&A) professionals isn’t too much trouble for most companies. The tricky part is finding a candidate with the right technical and soft skills for your organization’s needs. The following interview questions will help you find a qualified FP&A professional for your company. Listen to their responses to gauge their reasoning, expertise, situational awareness, ambition, and individual attitude toward various aspects of the FP&A profession.