The business challenges organizations face today are enormous: increased efficiency, lower costs, supply chain resilience, revenue growth, talent retention, and digital fragmentation. A modern enterprise needs an adaptable operating model to support its business goals. This requires a range of data, analytical, and AI capabilities to reach the desired business outcomes—from simple to cutting edge.
Percepio Tracealyzer is available for many popular real-time operating systems (RTOS), including FreeRTOS, Zephyr, and Azure RTOS ThreadX, and also for Linux. But what if you want to use it for another RTOS, one that Percepio doesn’t provide an integration for? Then you’ve been out of luck—until now.
A zero-day vulnerability (CVE-2023-5129) in the WebP image library is being actively exploited, putting major browsers and scores of additional apps at risk.
PromCon, the annual Prometheus community conference, is around the corner, and this year I’ll have exciting news to share from the Prometheus Java community: The highly anticipated 1.0.0 version of the Prometheus Java client library is here! At Grafana Labs, we’re big proponents of Prometheus. And as a maintainer of the Prometheus Java client library, I highly appreciate the support, as it helps us to drive innovation in the Prometheus community.
The shift from traditional monitoring to observability is widespread, and necessary. It's the way we make sense of increasingly complex and distributed systems. But when we capture all this data at scale... what do we do with it all? If this data itself had inherent value, we’d all be rich. But in the real world data does not provide us value until we can act on what it tells us.
Traditional data center networking can’t meet the needs of today’s AI workload communication. We need a different networking paradigm to meet these new challenges. In this blog post, learn about the technical changes happening in data center networking from the silicon to the hardware to the cables in between.
Data growth has significantly out-pacing budgets; the products we use, have to do more. This is where optimization comes into play. Generally, optimization is associated with reduction which may be intimidating…what if something important is reduced? How can you identify what should be reduced? Reduction isn’t about removing context, but about removing repetitive data, meaningless fields, or even flattening JSON.
