Systems | Development | Analytics | API | Testing

LLMs are the foundation of gen AI applications. To effectively operationalize and de-risk LLMs and ensure they bring business value, organizations need to consider not just the model itself, but the supporting infrastructure, including GPUs and operational frameworks. By optimizing them to your use case, you can ensure you are using an LLM that is the right fit to your needs.

From humble beginnings, Apache Kafka steadily rose to prominence and now sits as the backbone of data streaming for thousands of organizations worldwide. From its robust API, cloud-native implementations like Confluent Cloud, and synergy with other technologies like Apache Flink, Kafka has grown to cover many use cases across a broad range of industries.

Observability refers to understanding a system’s internal state by examining its external outputs, like logs, metrics, and traces. Borrowed from control theory, it’s the ability to infer what’s happening inside a system without direct access. To visualize observability, consider the human body. We don’t need to open it up to understand its internal state. By measuring external signals like body temperature, heart rate, or blood pressure, we can infer what’s happening inside.

Today we’re going to be talking about Strings in Java. If you write Java often, you know that a String is considered a first-class object, even though it is not one of the eight primitive types. What you may not know is how to handle Strings in production applications best. From handling internationalization and localization to optimizing performance for large-scale applications, understanding how to work with Strings can significantly improve code quality and maintainability.

Businesses nowadays are forced to continuously look for methods to improve their operations due to the unrelenting pace of business. In this environment, hyperautomation emerges as an effective solution that minimizes manual assistance, lowers costly errors, and automates complex procedures. Additionally, it offers businesses a competitive advantage in the marketplace if they can implement automation swiftly and effectively.

When it comes to the quality of software solutions, it is often said that the best testing goes a long way. Just think about the day when you finally launched the perfect software with error-free elaborate systems that have surpassed users’ expectations and, on top of that, provide it in the sea of competitive applications—to have that is to welcome an outstanding testing partner.

Yellowfin’s mission has always been to simplify analytics and make actionable insights easily accessible for everyone. With the release of Yellowfin 9.14, we’re focusing on providing developers with the tools to integrate our advanced analytics into their software seamlessly, expand integration capabilities, and provide a significant step forward in making embedded business intelligence (BI) more accessible and impactful.

In the dynamic world of mobile app development, the speed and simplicity with which you can share builds with testers and stakeholders can be the difference between a successful, on-time, bug-free release – or watching that opportunity fly by. To help your team maximize all of these opportunities, there’s a new feature within Release Management: Build distribution for testing.

Following the deprecation of Realm, we have partnered with MongoDB to ensure that MongoDB customers can continue to deliver the device sync capabilities their customers depend on. The solution: a MongoDB Connector for the Ably LiveSync product. Ably LiveSync enables you to seamlessly fan-out your MongoDB Atlas state to billions of clients in realtime - ensuring reliable, low-latency delivery of your document data.

In this article, I will introduce the steps to release a Flutter app to the App Store using the Codemagic CI/CD. If you have been uploading your app to App Store Connect manually using Xcode and want to simplify that process, I hope you find this article helpful.