HN user
Thanks, peer review is what I'm after
The GB/sec calc is there My assumption was that even with k8s there'll be an API gateway, GTM etc
Comparing AWS Lamda = 147,167.87 USD to K8s with autoscaling:
DS32a_v4 at spot pricing = 66 * 0.5704 * 24 * 365 = 329782.46 USD With 2 FTEs @ 100k total is 529782.46 USD Caveat application can tolerate autoscaling delays
Summary: AWS Lambda is 3.5x cheaper than a Kubernetes solution
AWS Lambda $0.20 per 1M requests $0.0000166667 for every GB-second SLA 99.95%
Lets assume - 2000 calls/sec - each call is 1 sec duration - 0.128 GB/sec/call - db, storage iops will be the same if deployed as K8s - 5x9s SLA (imples a three region deployment)
requests per year = 2000 * 3600 * 24 * 365 = 63072000000 request costs = 0.2 * 63072000000 / 1000000 = 12,614 USD
GB/sec per year = 0.128 * 2000 * 3600 * 24 * 365 = 8073216000 GB/sec costs = 8073216000 * 0.0000166667 = 134,553.87
Total cost = 12614 + 134553.87 = 147,167.87 USD
The equivalent K8s would be - three clusters - 2000 cores (more likely 10% more = 2200) - 256GB memory
Three clusters will require 3000 cores to cater for region loss - 3000 cores on 32 core machines => 94 machines - round up to 99 machines to give vm level redundancy => 33 machines per cluster
Azure D32a_v4 (32 core, 128 GiB, 800 GiB storage) = $1.84/hour PAYG; $0.5704/hour Spot
DS32a_v4 at spot pricing = 99 * 0.5704 * 24 * 365 = 494673.696 USD
Plus FTE support (e.g. n FTEs @ 100k USD)
With 2 FTEs total is 694,673 USD
Summary: AWS Lambda is 4.7x cheaper than a Kubernetes solution