Mobile users are unforgiving, and discovering an issue in the wild might result in users abandoning the app for good. Therefore, mobile apps and websites must be rock solid before launching to meet market demands. In this article, we explore the top 10 mobile testing challenges that app developers and testers face, as well as recommended strategies and best practices for addressing them effectively.

For many Gen AI-based applications, usage-based billing is crucial. It is especially important if you are using third-party models that charge you for tokens used. You want to ensure that your cost of tokens used is covered by your customers, in addition to charging for your own value add. In this tutorial, we will build a quick Chat Bot API using OpenAI’s ChatGPT, and then use Moesif and Stripe to meter the number of tokens used and report the usage to Stripe to be charged.

Enterprise IT leaders across industries are tasked with preparing their organizations for the technologies of the future – which is no simple task. With the use of AI exploding, Cloudera, in partnership with Researchscape, surveyed 600 IT leaders who work at companies with over 1,000 employees in the U.S., EMEA and APAC regions.

We're pleased to announce the general availability of Kong Insomnia 9.3.3. This release ships with numerous improvements, particularly around performance. We strongly recommend updating to this latest version to get the best user experience in your daily workflow with Insomnia.

BigQuery recently gained support for the latest Gemini models, as well as safety enhancements and grounding support.

The world of Data Integration continues to evolve at a rapid pace, and Qlik has evolved along with it at equal pace, starting with acquisitions of Podium, Attunity, and now Talend, Qlik’s Data Integration and Quality solutions are a formidable force to have in your toolkit when you are looking to modernise data engineering in your organisation.

Given its intricate and cross-system nature, effectively managing master data necessitates a robust technological infrastructure. The process begins with data collection, utilizing Extract, Transform, Load (ETL) and Extract, Load, Transform (ELT) processes for normalization and integration.

Businesses are seeking ways to collect all the data from their digital sources and draw out patterns that can reinterpret human participation with automation. A vanguard in this attempt is the emergence of large language models (LLMs) powered by artificial intelligence (AI).

APIs are the backbone of the modern enterprise. However, troubleshooting API errors and resolving issues quickly can be challenging given their role in application operational continuity and customer experience. Time-sensitive resolution demands monitoring and deep analytical insights into API performance and usage. Combining both these capabilities in one tool accelerates real-time resolution and empowers stakeholders to surface business-critical API performance metrics through a self-service motion.

From smart homes to wearable devices to connected cars, the Internet of Things (IoT) is bringing about a new era of hyper-connectivity. Experts expect investments in the IoT ecosystem to rise above $1 trillion in 2026 — with no signs of slowing down. Application programming interfaces (APIs) are the backbone of IoT, ensuring scalability and security across billions of connected devices.