Kubernetes 1.29 released with 11 new stable features, many more in alpha/beta
The Kubernetes release team has announced the release of Kubernetes 1.29, which includes nearly 50 improvements. The theme of this release is Mandala, which the release team explains “reflects our community’s interconnectedness—a vibrant tapestry woven by enthusiasts and experts alike. Each contributor is a crucial part, adding their unique energy, much like the diverse patterns … continue reading
GPUs Are Fast, I/O is Your Bottleneck
Unless you’ve been living off the grid, the hype around Generative AI has been impossible to ignore. A critical component fueling this AI revolution is the underlying computing power, GPUs. The lightning-fast GPUs enable speedy model training. But a hidden bottleneck can severely limit their potential – I/O. If data can’t make its way to … continue reading
Creating network visibility everywhere … and beyond!
NASA’s new James Webb telescope is remarkable. In the coming years, it will discover the edge of the observable universe, allowing astronomers to search for the very earliest stars and galaxies, formed more than 13 billion years ago. The telescope’s visibility surpasses that of its Hubble predecessor 100-fold, providing insights into the nearby universe too, determining … continue reading
Five common questions about observability
Observability has emerged as a key capability that successful organizations need in order to deliver improved digital services to customers, employees and partners. It is especially relevant for today’s IT Ops environments where flexibility has given way to complexity for highly distributed and hybrid environments. ITOps Times recently asked Sudip Datta, head of AIOps & … continue reading
Smart data: Accelerating the journey from data to insights
Today’s AIOps and observability solutions are applying increasing levels of intelligence to IT Ops data with the goal of generating actionable insights. However, sophisticated AI and ML can sometimes be no match for ‘bad data.’ It’s the age-old problem of garbage in/garbage out. Data can’t simply be taken at face value because it can lead … continue reading
How to get from where you are to AIOps
AIOps grew out of performance monitoring. Before AIOps, organizations relied on specialists staring at dashboards in Network Operations Centers to see any system anomalies. Then, they’d page someone to alert them to the problem, who would then do an analysis of the alert and try to find the root cause. And that person might have … continue reading
Rancher Labs supports multi-cluster Kubernetes applications
Rancher Labs today announced support in its open-source management platform for multi-cluster global Kubernetes applications, which the company believes will be a big reason for that platform’s uptake going forward. “The number of production clusters is showing that multi-cluster with Kubernetes is becoming a reality,” said Sheng Liang, co-founder and CEO of Rancher Labs. “Everything … continue reading
IT operations monitoring can help prevent business services failures
As IT organizations move towards digitizing services and operations, there is an ever-increasing dependence on the IT infrastructure that supports these needs. It follows that any degradation of performance of the infrastructure directly affects the manner in which business is conducted and, therefore, the bottom line. A quick Google search reveals several recent examples. And … continue reading
premium For a successful AIOps integration, avoid these four common problems
The explosion in operational data and machine-learning compute capacity is finally enabling AIOps — Artificial Intelligence for Operations. But like many other technologies, AIOps fits within a larger organizational and systems context, and enterprises need to ensure that they are ready for the shift. Successfully implementing an AIOps solution requires an awareness of the potential … continue reading
How automation has changed APM
Changes in software development that have led to accelerated delivery cadences are stressing other parts of the application life cycle. This is especially true in organizations adopting microservices architecture, where teams are working autonomously to deliver their software, which by definition relies on communication with other services to form a more complete application. And one … continue reading
