Digital transformation continues to be a key focus for many organizations, and this usually means the automation of processes and data. At its core, automation is meant to simplify and streamline business operations. However, if not implemented correctly, it can introduce complexity, risk and fragmentation. The proliferation of automation tools, combined with the rapid growth […]
0 CommentsNew Relic this week added support for the Model Context Protocol (MCP) to its observability platform to surface insights into artificial intelligence (AI) agents and applications. Originally developed by Anthropic, MCP is rapidly becoming a de facto application programming interface (API) for enabling interoperability between AI agents and other sources of data. New Relic has […]
0 CommentsGearset has extended the scope of the observability of Salesforce applications it provides to include software developed using low-code Flex and object-oriented Apex programming tools. Source: DevOps.com
0 CommentsSupporting today’s DevOps — where AI is involved — requires developers to switch from seeing observability as a solely technical aspect to thinking of it as a way to explain what happens in the system Source: DevOps.com
0 CommentsTo encourage effective AI use among developers and smooth the path to adoption, enterprises must define clear use cases for AI agents. Source: DevOps.com
0 CommentsAlthough having options gives developers more ways to solve specific project requirements, an excessive number of choices can be overwhelming, leading to indecision, procrastination, suboptimal selections or even complete inaction. Source: DevOps.com
0 CommentsJFrog and NVIDIA today announced they have expanded the integrations between their software development platforms to now include the Enterprise AI Factory, a set of frameworks and blueprints for building artificial intelligence (AI) applications. As a result, software artifacts created using the NVIDIA Enterprise AI Factory can be housed in the JFrog Software Supply Chain […]
0 CommentsThe AI skills gap is widening, and today’s developers are expected to keep up. AI, used in conjunction with a powerful enterprise-grade low-code platform, holds significant potential to help bridge this gap when harnessed accessibly for smarter, faster development. Source: DevOps.com
0 CommentsAn in-depth look at AI-native testing and the capability it has of pushing things through the DevOps pipeline, faster. Source: DevOps.com
0 CommentsDatadog at its DASH 2025 conference today previewed a raft of artificial intelligence (AI) agents that automate tasks ranging from assessing infrastructure alerts that normally require the expertise of a site reliability engineer (SRE), to fixing code and triaging cybersecurity issues using the company’s security information event management (SIEM) platform. In addition, Datadog is also […]
0 Comments