Systems | Development | Analytics | API | Testing

As businesses strive to make data-driven decisions, the need for efficient and timely data integration practices becomes increasingly evident. Enter Change Data Capture (CDC), a technique that has revolutionized the way organizations handle data synchronization and integration.

Data is key to building resilience and achieving operational excellence—but first, your data must be intelligible. Luckily, modern BI solutions have intuitive interfaces that allow business users to build interactive data visualizations and contextual data stories. With this knowledge at their fingertips, your entire organization is empowered to make data-driven decisions.

Today, efficient and scalable testing solutions are crucial. As applications grow in complexity and the frequency of releases increases, the need for a more robust, automated, and integrated testing framework becomes critical. To meet these challenges, we created Katalon TestCloud, a cloud-hosted solution that delivers on-demand, flexible, and secure multi-browser/platform and mobile testing environments.

In token-based architecture, tokens represent the client’s entitlement to access protected resources. Access tokens (or bearer tokens as they're commonly known) are issued by authorization servers after successful user authentication. The tokens are passed as credentials in the request to the target APIs which inform the API that the bearer of the token is authorized to access the API and perform certain actions.

Realtime data is rapidly becoming a standard in many consumer applications. From responsive chat applications to low latency financial applications, nobody wants to refresh their browser for new data. With lots of data bouncing around Kafka behind a firewall, it begs the question of how you can serve this information to your users without sacrificing on latency. Ably provides a seamless way to serve this data to your end users devices, globally, through a direct integration with Confluent Cloud.

To update a document in MongoDB, I used to fetch it, update the values, and save back the entry. I would question the need for an update method. Looking back, it's evident that performance optimizations were hardly a concern when working on a personal project. Working with a larger dataset is a whole different story, though. This is where no-code tools can't help. In this article, I'll share some of my learnings when it comes to working in MongoDB with millions of documents.

In parts one and two of this series, we only dealt with the pure CRUD aspects of using SQLite as a production database. In this post, we will explore the world of queue mechanisms, using SQLite as the pub/sub adapter for ActiveJob. Let's make use of LiteJob to handle incoming webhooks in our Rails application.

UI testing in mobile app development is a challenging task due to multiple factors such as flaky tests, saving screenshots, printing useful logs and readability of test codes. We will be talking about a new UI testing framework Kaspresso for Android apps and how it is different from other frameworks when it comes down to solving these challenges.

In today’s fast-paced world, businesses face the challenge of managing the ever-expanding volume of data at their disposal, an issue that often hinders their ability to derive the critical and accurate insights they need to thrive and stay competitive. Driven by the monumental rise of generative AI, cloud services, remote work, and IoT devices, most organizations expect their data to double by 2025.

The term 'data pipeline' is everywhere in data engineering and analytics, yet its complexity is often understated. As businesses gain large volumes of data, understanding, processing, and leveraging this data has never been more critical. A data pipeline is the architectural backbone that makes data usable, actionable, and valuable. It's the engineering marvel that transforms raw data into insights, driving decisions and strategies that shape the future of enterprises.