The following blog was written together with Petar Torre, Solutions Architect at Intel. This blog describes how Cloudify automates the deployment and monitoring of Machine Learning systems, by orchestrating an Intel-optimized TensorFlow workload running inference with a pre-trained ResNet-50 model from the Intel Model Zoo. In a nutshell, a container running a Jupyter Notebook with the Intel optimized TensorFlow model is scheduled as a Kubernetes pod on K3S on AWS EC2.

Nowadays, when most people think about the term “machine learning,” they think of advanced, refined applications such as Chat-GPT, the chatbot-based deep learning text generator, or AlphaGo, the computer program that’s currently the “world's best player” of the board game Go.

Migrating your workloads to the cloud can bring some undeniable benefits to your organisation. For example, you can leverage cloud automation to significantly improve your time to market. You can also benefit from the ever increasing number of cloud regions to place your workloads close to your clients. This improves the response time of your services and, as a result, your customers’ satisfaction.

CloudSpend: Cloud cost management With the rising popularity of a hybrid cloud strategy, businesses need to keep their spending in check. To provide high availability for its data, more organizations have started to adopt a multi-cloud strategy, and they have choices for cloud platforms. AWS and Azure accounted for the lion’s share of the market in 2022. With their expertise in providing IaaS, this has also often resulted in disparate deployments with respect to cost estimation and control.

Data is the lifeline of modern businesses, and losing it can have serious consequences. That’s why backup and recovery strategies are crucial for any organization. Azure Storage is one of the most reliable and secure cloud storage solutions available, making it an excellent option for storing backups. In this article, we will explore the benefits and challenges of using Azure Storage as a backup location and provide you with a step-by-step guide to set up and manage your backups.

Monitoring is not a goal, but a path. Depending on the maturity of your project, it can be labeled in one of these six steps of the cloud monitoring journey. You will find best practices for all of them and examine what companies get from each one. From classic virtual machines to large Kubernetes clusters or even serverless architectures, companies have adopted the cloud as a mainstream way to provide their online services.