alt Hacker News> one downside I've observed with some serverless in the past is that it can introduce up-front latency delays as the system spins up support to handle your spike
[cofounder of blacksmith here]
This is exactly one of the symptoms of running CI on traditional hyperscalers we're setting out to solve. The fundamental requirement for CI is that each job requires its own fresh VM (which is unlike traditional serverless workloads like lambdas). To provision an EC2 instance for a CI job:
- you're contending against general on-demand production workloads (which have a particular demand curve based on, say, the time of day). This can typically imply high variance in instance provisioning times.
- since AWS/GCP/Azure deploy capacity out as spot instances with a guaranteed pre-emption warning, you're also waiting for the pre-emption windows to expire before a VM can be handed to you!
Replies
Excellent! I did some work in the past on prediction of behavior given past data, and I can tell you two things we learned:
- there are low-frequency and high frequency effects (so you can make predictions based on last week, for example, but those predictions fall flat if the company rushes launches at the EOQ or takes the last couple weeks in December off).
- you can try to capture those low-frequency effects, but in practice we consistently found that comprehension by end-users beat out a high-fidelity model, and users were just not going to learn an idea like "you can generate any wave by summing two other waves." The user feedback they got was that they consistently preferred the predictive model being a very dumb "The next four weeks look like the past four weeks" and an explicit slider to flag "Christmas is coming: we anticipate our load to be 10% of normal" (which can simultaneously tune the prediction for Christmas and drop Christmas as an outlier when making future predictions). When they set the slider wrong they'd get the wrong predictions, but they were wrong predictions that were "their fault" and they understood; they preferred wrong predictions they could understand to less-wrong predictions they had to think about Fourier analysis to understand.
> The fundamental requirement for CI is that each job requires its own fresh VM (which is unlike traditional serverless workloads like lambdas). To provision an EC2 instance for a CI job
Is this different to lambdas or ECS services due to the need to setup a VM / container and nested virtualisation / Docker-in-Docker is not supported?