To say modern enterprises are built on the cloud is an understatement. According to Gartner, enterprise spending on cloud applications surged to 57.7% in 2022, and investments into public cloud services hit a respectable 41%. These numbers are only predicted to grow further in 2025 as enterprises accelerate cloud rollouts and move into a cloud microservices architecture to realize greater agility, productivity, and competitiveness.

Azure Blob Storage is a cloud-based storage service provided by Microsoft Azure that allows users to store vast amounts of unstructured data like documents, images, videos, and more. Monitoring Azure Blob Storage is crucial for ensuring optimal performance, data security, and efficient cost management.

The pressure to release application features faster to meet the demands of customers presents a number of challenges, including unforeseen deployment delays, custom feature sets, and complex rollbacks when errors occur. To overcome these challenges, developers can use Flagsmith, an open source feature flagging and remote configuration service that allows developers to easily roll out and test new features for a specific subset of users.

As more and more businesses adopt microservices and leverage cloud infrastructures, keeping track of services and resources becomes increasingly important. Comprehensive monitoring is needed to ensure optimal performance, avoid downtime and ensure all have a great user experience. But leaving monitoring to the cloud provider may not give you the insights you need.

Stateful workloads require consistent access to specific network and disk artifacts. Yet with little tolerance for interruptions, it’s no surprise that these workloads can be costly to run. As a result, organizations face a challenging trade-off between consistency and cost-efficiency as their cloud estates scale and cost concerns grow. However, running stateful workloads doesn’t necessitate overprovisioned, expensive, and unpredictable compute costs.

ChatGPT has been the talk of the town for more than four months now. As the first ever artificial intelligence (AI) -powered chatbot, it has quickly gained immense popularity, helping students, engineers and even executives generate content, write and debug code and run market analyses. But could ChatGPT be used for anything other than natural language processing (NPL)? Could it, for example, assist businesses with strategic decision-making? I decided to try it out.

Microsoft Azure, one of the leading cloud computing platforms, provides various services that enable businesses to run and manage applications efficiently. Among these services are virtual machines (VMs), which offer scalable computing resources to accommodate the diverse requirements of modern applications. In this article, we will delve into the different Azure VM types available and guide you on how to select the most suitable option for your specific needs.

Welcome to the second part of this series of blog posts on How to throw custom exceptions inside Logic Apps. In this series of five blogs, I will cover throwing custom exceptions in Logic Apps. I will cover the following topics: In this second approach, we are going to do a small fine-tuning of the previous approach by adding the capability to define custom error messages for each condition and, of course, get that information inside the Catch Scope.