Andromeda: performance, isolation, and velocity at scale in cloud network virtualization
Andromeda: performance, isolation, and velocity at scale in cloud network virtualization Dalton et al., NSDI’18
Yesterday we took a look at the Microsoft Azure networking stack, today it’s the turn of the Google Cloud Platform. (It’s a very handy coincidence to have two such experience and system design report papers appearing side by side so that we can compare). Andromeda has similar design goals to AccelNet: performance close to hardware, serviceability, and the flexibility and velocity of a software-based architecture. The Google team solve those challenges in a very different way though, being prepared to make use of host cores (which you’ll recall the Azure team wanted to avoid).
We opted for a high-performance software-based architecture instead of a hardware-only solution like SR-IOV because software enables flexible, high-velocity feature deployment… Andromeda consumes a few percent of the CPU and memory on-host. One physical CPU core is reserved for the Andromeda dataplane… In the future, we plan to increase the dataplane CPU reservation to two physical cores on newer hosts with faster physical NICs and more CPU cores in order to improve VM network throughput.
High-level design
Both the control plane and data plane use a hierarchical structure. The control Continue reading
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