Atlassian has introduced Jira Planner, a tool that applies spec-driven development to the requirements planning stage to mitigate AI-related bottlenecks in software testing and dep…
Implementing IT automation effectively requires strategic planning to avoid common pitfalls like wasted resources, inefficient workflows, or poor tool selection. The guide recommen…
Cribl has acquired CardinalOps to expand its capabilities from data routing into SecOps and detection engineering, allowing the company to provide analytics content like mapping sy…
Executives do not need to be technical engineers but must develop enough AI literacy to lead organizational transformations, manage risks, and evaluate strategic investment opportu…
As cyberthreats grow more complex, secure IT infrastructure has evolved from a technical requirement into a strategic necessity for ensuring operational resilience and regulatory c…
As the cost of global cybercrime is projected to reach $13.82 trillion by 2028, organizations are facing an increasingly dangerous "digital jungle" of sophisticated, AI-driven thre…
While traditional Service Level Agreements (SLAs) effectively track technical metrics like uptime, they often fail to capture how IT services impact actual user productivity and sa…
IT automation is shifting from a fragmented collection of disconnected tools toward a unified ecosystem driven by the convergence of Generative AI and traditional technologies like…
Major AI infrastructure vendors, including Qualcomm, OpenAI, and IBM, are developing new hardware and software technologies to address rising energy costs and power constraints in …
Runbook automation provides a strategic solution for IT leaders to address the inefficiencies, human errors, and high costs associated with manual and semiautomated processes. By i…
To manage massive AI infrastructures that exceed human capacity, enterprises are increasingly adopting "AgenticOps" to automate IT operations through autonomous AI agents. However,…
Drawing from HPE Discover 2026, the article outlines how enterprises can optimize their AI economics by focusing on robust networking, efficient "tokenomics" management, and AI-dri…