Systems | Development | Analytics | API | Testing

Microservices architecture has emerged as a popular approach for developing software applications in recent years. Instead of building monolithic applications, microservices architecture involves breaking down an application into smaller, independent services that can be developed, deployed, and scaled independently. This approach offers a number of benefits, including increased flexibility, better scalability, and improved fault tolerance.

If your business deals in large volumes of data, chances are that you are at least somewhat familiar with PostgreSQL, or you may use it actively in your data management strategy. PostgreSQL is a powerful relational database system, and it is completely open source. As of 2019, PostgreSQL was the second-most-common database solution for professionals. Thirty-four percent of more than 75,000 Respondents reported that it was their first choice.

In the competitive landscape of iOS app development, ensuring the quality and functionality of your application is crucial. That’s where automated testing tools come in, enabling developers to streamline their testing processes and deliver robust, bug-free applications. In this comprehensive overview, we dive into the world of automated testing tools for iOS, exploring the top contenders that can revolutionize your testing efforts.

The Apigee API Gateway is a tool that enables the management, analysis, and security of APIs. This API gateway enables organizations to optimize their digital ecosystems and deploy user-friendly products. It is particularly valuable for developers, IT professionals, and SaaS businesses interested in enhancing their API infrastructure, streamlining development workflows, and ensuring secure and seamless connectivity.

Natural language processing and large language models to help BigQuery process dataframes.

The rise of generative AI and the massive popularity of OpenAI’s ChatGPT has led to widespread recognition that software applications are about to fundamentally change. Generative AI offers the potential to both deliver breakthrough new application capabilities and transform the way people interact with software.

Automated testing has emerged as a prominent practice that leverages machines (compute power, scripts, machine learning, genAI) to validate the quality of a software application. With the promise of increased efficiency, broadened test coverage, and accelerated software delivery, automated testing has become a cornerstone initiative for modern software engineering teams.

Visionaries from Capgemini, Databricks and Fivetran lay out the data quality imperative for implementing enterprise AI applications.

When WebSockets were first announced in 2011, they had some teething problems. As a result of these teething problems, only the most daring and experimental developers would rely solely on WebSockets for realtime communication. For most of us, it became a necessity to implement a fallback protocol in case the WebSocket connection can’t be established.