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.
