Curious about Gatling load testing for Kubernetes? Learn how it compares to Speedscale when it comes to functionality, setup, CI/CD integration & more.

Microsoft Excel, a cornerstone in the realm of data management, is extensively utilized across various industries for its robust capabilities in data analysis, storage, and intricate calculation functionalities. However, when it comes to importing Excel files into other Software as a Service (SaaS) applications, users often encounter a range of import errors that can hinder productivity and data accuracy.

You might have heard the rumors circulating in the tech world—PHP, the venerable programming language, isn’t as secure as its modern counterparts. With roots tracing back nearly three decades, PHP soared to popularity during the early days of the web, when security practices were still finding their footing.

In this blog post we are going to discuss using JMeter localised to a language other than English. We are not discussing computer languages that are supported. We will look at currently supported languages and how to change your local instance to use these languages. We will also look at how you can submit a language translation if you would like to and have the ability to.

With the increasing importance of real-time data in modern businesses, companies are leveraging distributed streaming platforms to process and analyze data streams in real time. Many companies are also transitioning to the cloud, which is often a gradual process that takes several years and involves incremental stages. During this transition, many companies adopt hybrid cloud architectures, either temporarily or permanently.

Apache Iceberg has recently grown in popularity because it adds data warehouse-like capabilities to your data lake making it easier to analyze all your data—structured and unstructured. It offers several benefits such as schema evolution, hidden partitioning, time travel, and more that improve the productivity of data engineers and data analysts. However, you need to regularly maintain Iceberg tables to keep them in a healthy state so that read queries can perform faster.

In a world full of microservices and distributed systems, building robust and reliable APIs is of paramount concern. One key concept that plays a vital role in achieving reliability is idempotency. In this article, we'll delve into the world of idempotency, exploring what it is, why it's important, and how it can be implemented to solve the persistent problem of duplicate processing in APIs. Along the way, we'll see how to build an idempotent API in Node.js with Redis.