Kubernetes stories
Businesses are turning to observability software to govern AI traffic and secure hybrid systems, as IDC sees the market rising to USD $4.39 billion by 2029.
The rollout aims to help businesses run autonomous AI agents more securely, while easing data, networking and sovereignty constraints.
Customers will soon get faster, cheaper AI training and inference as Google Cloud adds new TPUs, GPU instances and networking.
Enterprise users can now cut response times by up to 25% while adding ransomware detection, single sign-on and migration tools.
The release aims to ease log searching and dashboard management as engineering teams wrestle with rising telemetry volumes and system complexity.
Businesses running AI workloads on Kubernetes are wasting costly graphics processors, with Cast AI finding average GPU utilisation of just 5%.
Enterprises could gain tighter control over AI deployments as the new stack combines governance, security and on-premise data sovereignty.
Analysts can now triage threats and trace outages from inside AI tools, as Elastic’s public preview cuts dashboard switching.
Enterprises under pressure to control AI data and workloads now have an open alternative to single-cloud setups across cloud, on-premises and edge sites.
Enterprises could cut the time needed to bring GPU systems into use, as the integration automates deployment of AI workloads and orchestration.
Companies adopting foundation models are being urged to rethink defences as Protegrity’s new tool aims to shield sensitive data during inferencing.
The move gives OpenSearch a major scientific user with 130 clusters and more than 1.3 petabytes of indexed data to shape its future development.
Rising AI and cloud traffic is pushing demand for tools that can spot threats and performance issues across hybrid networks, IDC says.
The benchmark win could help enterprises compare AI cloud performance more clearly as demand grows for reliable large-scale model training.
The update gives security teams earlier warning on vulnerable container images before they reach production, reducing blind spots across cloud estates.
The software aims to curb AI job failures and GPU waste as enterprises push agentic workloads into production on Nutanix systems.
It could cut migration cycles from days to minutes for firms modernising virtual estates, while keeping data in place for some VM moves.
The move could help enterprises and AI cloud operators manage containers, GPUs and data with one model as demand for edge and agentic AI grows.
Most teams still want human sign-off before Kubernetes cost and performance changes go live, CloudBolt's survey of 321 practitioners found.
AI infrastructure operators can now bill by usage rather than GPU rental as Rafay adds token metering and access controls to its platform.
