Systems | Development | Analytics | API | Testing

As organizations build more APIs, manual processes and frequent handoffs in the API development workflow can lead to a slower time to market, higher development costs, and poor-quality APIs. They can also result in APIs being poorly documented, causing poor API adoption and lower revenues. APIOps aims to address these issues by automating the entire API lifecycle, leveraging DevOps and GitOps principles. But what is DevOps, and what is GitOps?

The concept of insurance predates the printing press and the steam engine. So it's likely no surprise that the industry — as obviously adaptable as it is — often faces challenges related to the modernization of legacy systems. In the age of AI and APIs (application programming interfaces), streamlining operations and modernizing are paramount to success.

In the ever-evolving world of sports and entertainment, fan engagement has emerged as a critical factor in driving retention and long-term success. At the Ably Realtime Fan Engagement Summit in New York City, industry experts shared valuable insights into the relationship between fan engagement and retention, emphasizing the importance of creating compelling digital experiences and fostering genuine connections.

APIs are the bread and butter of the internet. The ability to interact with our applications programmatically enables interoperability and makes our lives as developers easier. Unfortunately, web applications are vulnerable to malicious actors that seek to misuse them or degrade their performance, which is why rate limiting is an important part of any API.

Google regularly updates its developer policies to make sure Google Play is a safe and trustworthy platform for everyone. While this is unquestionably necessary and essential to protect users and their data, keeping up with the latest changes to ensure applications remain safe and compliant can feel a little overwhelming for developers.

There are many ways AI can improve government case management processes. Examples include: AI capabilities often depend on a large language model (LLM), an advanced AI system that can understand, analyze, interpret, and generate human language. It uses deep learning techniques to predict and produce coherent text based on input prompts. A large language model trained on government agency data is capable of tasks like text extraction, translation, summarization, and conversational responses.

The life sciences industry is rapidly embracing artificial intelligence (AI) to automate complex processes, enhance efficiency, and improve outcomes. From drug development to patient care, AI-driven automation is transforming the landscape. Here are some of the top artificial intelligence use cases for process automation in the pharmaceutical industry.

Ably was proud to celebrate our 8th birthday this year, and we’ve enjoyed reflecting on some of our achievements since launching in 2016. When we launched, we believed that realtime interactions would underpin our everyday digital experiences, rather than just augment them. And so we set out on a mission to build the definitive realtime experience platform.

React Native is an open-source framework that Meta (then Facebook) designed to build native applications for Android, iOS, and other platforms. The framework is built so anyone familiar with React can easily build cross-platform applications without learning a completely different framework or language. However, there are differences in the functionality of the two, including: There are many more differences, but we’ll get into those later in the post.

AWS Lambda is a serverless compute service that enables you to run code without the need to provision or manage servers. This makes it an ideal choice for developers aiming to build scalable and efficient applications with minimal infrastructure overhead.