It's essential to test web applications to ensure reliability, functionality, and a good user experience. That's why robust testing frameworks have become so important for web developers. Among the plethora of available tools, Cypress and Playwright have emerged as two of the most popular choices for automating end-to-end testing. In this Cypress versus Playwright comparison guide, we'll explore the strengths and weaknesses of the two tools, their features, and their differences. Cypress or Playwright?

For data engineers, the Generative AI (Gen AI) era is a transformative shift in how we approach data architecture and analytics. Professionals at the forefront of this shift will be gathering in San Francisco, at the Data+AI Summit June 10-13. Attendees will be exploring tools that integrate with Databricks Intelligent Data Platform that decrease data management costs and improve data's impact on business outcomes.

Apache Kafka has become the de facto standard for data streaming, used by organizations everywhere to anchor event-driven architectures and power mission-critical real-time applications. However, this rise has also sparked discussions on improving Kafka operations and cost-efficiency—streaming data is naturally prone to bursts and often unpredictable, resulting in inevitable variations in workloads and demand on your Kafka cluster(s).

An application programming interface (API) defines a set of rules and protocols that allow different software entities to communicate with one another. Open or public APIs offer free access to everyone with little or no restrictions. These public APIs allow developers to build innovative solutions and extend existing ones covering a variety of use cases. In this article, we cover some of the best open APIs from different categories.

Enterprises are encountering an ever-increasing number of threats to their digital assets. Attack Surface Management (ASM) has emerged as a crucial practice to mitigate these risks and enhance overall cybersecurity. By understanding and effectively managing the attack surface, enterprises can proactively identify and address vulnerabilities, reducing the likelihood of successful attacks.

The payments industry is evolving rapidly, fueled by technological advancements, changing consumer behaviors, and a growing appetite for real-time transactions. As this transformation unfolds, new standards have been introduced to ensure the payments ecosystem's safety, security, and efficiency.

Despite the transformative potential of AI, many financial planning and analysis (FP&A) teams are hesitating, waiting for this emerging technology to mature before investing. According to a recent Gartner report, a staggering 61% of finance organizations haven’t yet adopted AI. Finance has always been considered risk averse, so it is perhaps unsurprising to see that AI adoption in finance significantly lags other departments.

Amazon OpenSearch is a popular fully managed analytics engine that makes it easier for customers to do interactive log analytics, real-time application monitoring, and semantic and keyword searches. It can also be used as a vector engine that helps organizations build and augment GenAI applications without managing infrastructure (we’ll talk about this in future blogs). Additionally, the service provides a reliable, scalable infrastructure designed to handle massive data volumes.

LLM evaluation is the process of assessing the performance and capabilities of LLMs. This helps determine how well the model understands and generates language, ensuring that it meets the specific needs of applications. There are multiple ways to perform LLM evaluation, each with different advantages. In this blog post, we explain the role of LLM evaluation in AI lifecycles and the different types of LLM evaluation methods. In the end, we show a demo of a chatbot that was developed with crowdsourcing.

A look at how to augment LLM results with retrieval augemented generation (RAG) and vector search, directly from BigQuery.