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Authors: Rui Zang, Cathy Zhang
2022-05-18

tldr - powered by Generative AI

The presentation discusses an enhanced snapshot-based approach to address the challenges of creating new function instances and supporting fast auto-scaling in response to burst traffic. The approach involves breaking the original function code image into essential and non-essential code blocks, regenerating a new set of unique data associated with a specific micro VM instance, and adjusting existing running micro VMs resource boundary to create more function containers.
  • The enhanced snapshot-based approach addresses the challenges of creating new function instances and supporting fast auto-scaling in response to burst traffic.
  • The approach involves breaking the original function code image into essential and non-essential code blocks.
  • A small program is developed to regenerate a new set of unique data associated with a specific micro VM instance.
  • Existing running micro VMs resource boundary is adjusted to create more function containers.
  • The approach reduces code start latency and saves time.
  • The snapshot file needs to be downloaded before starting the container.
  • The essential code blocks are smaller and only a small portion of the data are actually used during the function test run.
  • The snapshot file and essential code blocks combined are much smaller than the original image size.
  • This results in a shorter downloading time and a shorter code start time.