In the present digital period, Artificial Intelligence (AI) is impacting the future of various aspects of Quality Assurance (QA). This evolution has resulted in strategies for ensuring quality is effectively integrated into development processes.

As organizations continue to migrate to the cloud and search for ways to reduce costs, Perforce has released Helix Core 2023.2 – giving users the ability to connect their archive depots to S3-backed (or S3-compatible) cloud object storage. S3 storage support offers users a durable and convenient solution that grows automatically and indefinitely. In the following article I explain S3 storage, diving into the benefits of using S3 storage, and how to get started using S3 Storage within Helix Core.

AI was the hot topic of 2023 and will continue to reign in 2024: ChatGPT first launched at the end of 2022 and became a massive hit in just a few months. Google released Bard shortly after, and then, new AI tools just kept popping up, prompting marketers to learn how to leverage them to become more efficient and productive.

At Ghost Inspector, we pride ourselves on creating tools that simplify the testing process, making it possible for anyone to build a test without coding skills. With our wide-ranging usability options, even our seasoned users sometimes wonder if they’ve fully tapped into Ghost Inspector’s capabilities. So we’ve put together this guide to detail Ghost Inspector’s more nuanced and advanced features.

This blog post describes support for materialized views for the Iceberg table format in Cloudera Data Warehouse. Apache Iceberg is a high-performance open table format for petabyte-scale analytic datasets. It has been designed and developed as an open community standard to ensure compatibility across languages and implementations.

We asked executives across Tricentis for their thoughts on topics that have the testing industry buzzing: artificial intelligence (AI), mobile testing, and increasing reliance on low-code/no-code testing solutions. Read on for Tricentis insiders’ take on these hot topics and how they impact the future of the industry.

Data engineers, data scientists and other data professional leaders have been racing to implement gen AI into their engineering efforts. But a successful deployment of LLMs has to go beyond prototyping, which is where LLMOps comes into play. LLMOps is MLOps for LLMs. It’s about ensuring rapid, streamlined, automated and ethical deployment of LLMs to production. This blog post delves into the concepts of LLMOps and MLOps, explaining how and when to use each one.

Apache Kafka® cluster administrators often need to solve problems like how to onboard new teams, manage resources like topics or connectors, and maintain permission control over these resources. In this post, we will demonstrate how to use Confluent for Kubernetes (CfK) to enable GitOps with a CI/CD pipeline and delegate resource creation to groups of people without distributing admin permission passwords to other people in the organization.

Investment in AI for manufacturing is expected to grow by 57% by 2026. That’s hardly surprising — with AI’s ability to augment worker productivity, improve efficiency and drive innovation, its potential in manufacturing is vast. AI’s predictive capabilities can help manufacturing leaders anticipate market trends and make data-driven decisions, creating financial opportunities for suppliers as well as customers.