The COVID-19 pandemic and the resulting economic uncertainty forced businesses to rethink how they approach growth. This especially rang true in the financial services industry, where financial trends have the most direct impact. Curiosity, collaboration, and adaptability all became key to surviving this new climate.

Regression testing is an important practice in software development. It tests to ensure your application remains stable and reliable even as changes and updates are introduced. Each new change introduces a risk of breaking existing functionalities, potentially causing shipping delays or launch postponements. Evaluating your application against a full suite of tests helps find and fix unexpected software bugs or errors.

Think about the monotonous task of extracting data from sources like spreadsheets and emails and typing it into various systems. Repetitive tasks and manual workflows lurking inside business processes slow down teams, introduce human error, and erode employee engagement. Slow, ineffective processes can also kill an organization’s time to market and customer satisfaction.

Data is one of the most valuable commodities an organization has. Every company stores and manages a substantial amount of information. But how do you gain revenue from it? Here, we discuss three ways you can monetize data with an embedded analytics investment.

We're thrilled to announce the general availability of Kong Gateway Open Source (OSS) 3.7. This latest version features cutting-edge AI Gateway updates with new streaming plugins, as well as performance and security improvements. Let’s dive into the enhancements and explore the tangible benefits that these features bring to your organization.

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).

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.

As a contract software developer, I am exposed to oodles of Ruby code. Some code is readable, some obfuscated. Some code eschews whitespace, as if carriage returns were a scarce natural resource, while other code resembles a living room fashioned by Vincent Van Duysen. Code, like the people who author it, varies. Yet, it's ideal to minimize variation. Time and effort are best spent on novel problems.

Quality Assurance (QA) teams must run extensive tests to ensure that a website or application performs as intended before release. However, rather than manually running these tests, which can hinder productivity, modern teams are using QA automation. By automating QA testing workflows, teams can rapidly execute these tests using standardized processes, frameworks, and software. Developers can quickly fix any errors and deliver high-quality code so that product teams can speed up release times.