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Spotinfo
CLI for exploring Spot instance pricing across AWS, GCP and Azure. Inspect Spot instance types, savings, price, and AWS interruption frequency — offline, from embedded data.
Install
brew install alexei-led/tap/spotinfoInstall command taken from the project's README or registry entry. Always review code before running it.
README excerpt
Read full README on GitHub →spotinfo
Pick a Spot machine on AWS, GCP or Azure from one command line. No credentials. Every price
ships inside the binary, so --offline answers in about a tenth of a second.
The problem
Spot capacity is far cheaper than On-Demand — between 40% and 85% off in the snapshots that ship with this tool. Finding the right machine does not scale by hand:
- Each cloud publishes prices in a different place, in a different shape, on a different schedule. AWS has a JSON feed and an interruption Advisor. GCP has server-rendered HTML pages. Azure has a REST API and a separate documentation site for vCPU and memory.
- The consoles rank by price. They do not rank by "cheapest machine with at least 4 vCPU and 16 GiB that my workload can survive losing".
- A price page has no memory of yesterday, so a script that reads one is a scraper you now own.
The result is that most teams pick one instance family, hard-code it, and stop looking.
What spotinfo does
One command ranks real machines against a real requirement, and says where the number came from.
$ spotinfo recommend --cloud azure --architecture arm64 --min-vcpu 4 --min-memory-gib 16
RANK CLOUD REGION MACHINE ARCHITECTURE vCPU MEMORY GiB USD/HOUR SAVINGS RISK WHY
1 azure centralindia Standard_D4ps_v6 arm64 4 16.0 0.017076 81% unavailable ARCHITECTURE_MATCH,COST_POLICY,KNOWN_POSITIVE_PRICE,RESOURCE_MINIMUMS_MET
2 azure centralindia Standard_D4ps_v5 arm64 4 16.0 0.018665 81% unavailable ARCHITECTURE_MATCH,COST_POLICY,KNOWN_POSITIVE_PRICE,RESOURCE_MINIMUMS_MET
3 azure centralindia Standard_D4pds_v5 arm64 4 16.0 0.022361 81% unavailable ARCHITECTURE_MATCH,COST_POLICY,KNOWN_POSITIVE_PRICE,RESOURCE_MINIMUMS_MET
Four properties make that output worth trusting:
It works with no credentials. Price snapshots ship inside the binary, and a weekly job
refreshes them through a reviewed pull request. AWS and Azure additionally read live feeds
when they can reach them — AWS on every run, Azure when you name one or two regions — and
fall back to the snapshot when they cannot. --offline skips every price and risk request;
only --with-score still reaches a cloud, because no snapshot carries a placement figure.
It says what it does not know. GCP and Azure publish no redistributable interruption
data, so every candidate reports RISK: unavailable. It is never a zero and never a low
bucket. A cloud that measures nothing must not outrank a cloud that measures honestly. On
GCP, --live-risk fetches a per-project preemption rate for the ranked page — Google
measures it differently from AWS, so it is shown and never filtered on.
It refuses questions it cannot answer, and says why. --workload web caps interruption
frequency at an AWS Spot Advisor bucket boundary. Ask for it on a cloud that measures
something else and the command stops before it reads a price, naming the vendor limit rather
than a feature nobody built:
$ spotinfo recommend --cloud gcp --workload web --architecture x86_64 --min-vcpu 4 --min-memory-gib 16
spotinfo: gcp: unsupported capability: risk: the web workload caps interruption frequency at 5%, an AWS Spot Advisor bucket boundary, and gcp publishes no figure measured that way; workload cost applies no ceiling and answers on every cloud
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