Systems | Development | Analytics | API | Testing

For a time, desktop applications were declared dead. They became too costly to develop and deploy compared to web apps, which allowed businesses to easily onboard new users, release updates instantly and introduce recurring pricing models rather than one-off purchases.

Software teams today face intense pressure to deliver updates rapidly without compromising quality.

Have you ever thought of finding a bug in your software before it becomes a problem that costs too much to fix? That is what Shift Left Testing means—testing is done at the beginning of the development process. In the traditional approach, testing happens at the end of the development phase; defects found reduce development efficiency and lead to delays, high costs, and the risk of frustrated users.

Unit testing is a software testing method in which individual components or units of code are tested in isolation to confirm they function as intended.

In the evolving landscape of software testing, Behavior-Driven Development (BDD) has emerged as a powerful methodology for improving collaboration between technical and non-technical team members. However, the implementation of BDD tools like Gherkin and Cucumber often falls short of their intended purpose. Let's explore how to effectively use these tools and avoid common pitfalls.

Modern organizations generate and collect vast amounts of log data each day from an ever-increasing number of sources that includes IT infrastructure, networking devices, applications, cloud services, security tools, and more. This data is essential for powering use cases from security operations and threat hunting to application performance monitoring, but tapping into the full potential of log data can be challenging for organizations without the right tools and capabilities.

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.

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.