As we move from monolithic applications to microservices, the ability to colocate workloads offers a tremendous opportunity to realize greater development velocity, robustness, and resource utilization. But workload colocation can also introduce performance variability and affect service levels. Google describes the problem as the “tail at scale”—the amplification of negative results observed at the tail of the latency curve when many systems are involved.
With its latest tooling capabilities, Intel has an experiments framework to calculate the trade-offs between low latency and higher density. Niklas Nielsen discusses the challenges and complexities of workload colocation, why solving these challenges matters to your business no matter the size, and how Intel intends to help smarter resource allocations with its latest tooling capabilities and Kubernetes.
This session is sponsored by Intel.
Niklas Nielsen is a distributed systems architect in Intel’s Software Defined Infrastructure group. During his time at Intel, he has driven projects focusing on enabling Intel technologies in open source cluster schedulers, such as Apache Mesos and Kubernetes. Previously, Niklas worked as a Apache Mesos committer with cluster scheduling at Mesosphere and on language runtimes and dynamic compilers at Adobe.
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