Systems | Development | Analytics | API | Testing

On October 29, 2024,* Node.js v22 officially transitioned into *Long Term Support (LTS) with the codename 'Jod'. For developers and organizations relying on the stability of Node.js for production environments, this transition marks a key milestone for Node.js 22.x, ensuring it will receive critical updates and security support for years to come. Let’s take a closer look at what this means, along with a refresher on the Node.js release lifecycle .

The need for smartphones and the mobile app development company is growing rapidly because of the boom in the digitalization of the market world. Therefore, several businesses and organizations are taking this as a huge opportunity to bring their business into the online world. Now, literally, every entrepreneur and company is capitalizing on mobile applications, whether they're focused on their specific industry or providing on-demand services.

Is AI taking up human jobs? Can AI replace human intelligence? Will Artificial Intelligence replace humans in a few years? Well, these questions are in the news and spreading like wildfire on the internet leaving no one behind. This rapid advancement of AI has sparked intense debates about the potential implications for the future of work and the role of humans in a world increasingly driven by intelligent machines.

Ensuring that a growing codebase follows best practices and does not deviate from the standards is essential for any project. However, this can typically only be enforced manually by code reviews and other similar processes. As with any other manual task, this can be time-consuming, tedious, and error-prone. That's where architecture testing comes in. Architecture testing allows you to automatically enforce code standards such as naming conventions, method usage, directory structure, and more.

Are you ready to step into the digital world where the possibilities are boundless and the pace is exhilarating? The world is indeed embracing the digital revolution with open arms, and the gateway to this extraordinary universe lies in the palms of our hands. Yes, you guessed it right! Smartphones and mobile devices have become an integral part of our lives. As a result, this has led to the significant popularity of app development among businesses.

Push notifications play an important role in user engagement and retention in your mobile app, keeping users up to date and creating a sense of urgency that leads to purchases. And in Android, we get the added benefit of Firebase Cloud Messaging (FCM) notification service, which acts as a middleman between the app server and the user’s Android device. It helps the delivery of push notifications, even if the app is not active or the user is using a different app on their device.

It’s here! The Kong Gateway Operator release we teased at API Summit is now available for you all to use. KGO 1.4 allows you to configure Kong Konnect using CRDs, attach your DataPlane resources to Konnect with minimal configuration, and even manage the deployment of custom plugins using Kubernetes CRDs. Keep reading to find out more.

Understanding how your APIs handle and process data drives better decision-making. Different kinds of data flow through APIs and the services that consume them. But the actual information lives inside the HTTP request and response bodies. If you can effectively leverage that data with the contextual API metrics like status codes and routes, you can better understand how your customers consume your services.

The rise of AI has transformed how businesses operate, creating a surge in demand for AI-driven APIs, particularly those that leverage Large Language Models (LLMs). These APIs are at the heart of many modern applications, driving automation, customer interaction, and sophisticated data analysis. However, with this increased use comes a need for organizations to effectively monitor and manage the costs and consumption of these APIs.

Kafka is a highly popular realtime data streaming platform, renowned for handling massive volumes of data with minimal latency. Typical use cases include handling user activity tracking, log aggregation and IoT telemetry. Kafka’s architecture, based on distributed partitions, allows it to scale horizontally across multiple brokers. But although Kafka excels at high data throughput, scaling it to manage thousands of client connections can be costly and complex.