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Spot Pricing Notes

These are just my notes, check out https://cloudoptimizer.io/ for a real implimentation

Usage

Find CPU by trait:

# Get the CPU with the fastest single-threaded performance
yq '.processors.intel |sort_by(.cpumarkSingleThread)' instances.yaml |yq '.[-1]'

Output:

cpu_name: Xeon E-2378G
slug: 2378G
release_date: 2021
cpu_cores: 8
cpu_threads: 16
baseClock: 2800
turboClock: 5100
tdp: 80w
memory: DDR4
cpumarkSingleThread: 3477
cpumarkMultiThread: 22755

Just get the name:

yq '.processors.intel |sort_by(.cpumarkSingleThread)' instances.yaml |yq '.[-1].cpu_name'
> Xeon E-2378G

Find instance by CPU:

# get all instances using that CPU modle
> yq '.vendors.*.*.[] | select(.cpu == "Xeon E-2378G")' instances.yaml

Output:

instance_name: m3.small.x86
cpu: Xeon E-2378G
numCpus: 1
instance_vCores: 16
ram: 64GB
diskSize:
  - 480GB
numDisks: 2
price: 0.11

AWS

Getting AWS prices is actuall pretty straight-forward, each metadata filed is queryable in an intuitive way.

Resources:

Preferred Instances:

echo "Name,vCores,Memory,Drives,Price" > table.csv
INSTANCE_TYPE_LIST=("m6i.large" "m6i.2xlarge" "m6i.4xlarge")

for i in "${INSTANCE_TYPE_LIST[@]}"
do
  INSTANCE_TYPE="m6i.large"
  ZONE="eu-central-1a"
  INSTANCES="m6i.large"
  START=$(date +%Y-%m-%dT00:00:00)
  END=$(date +%Y-%m-%dT%H:%M:%S)

  VCORES=$(aws ec2 describe-instance-types \
  --instance-types $INSTANCE_TYPE |grep "VCPUINFO" |awk '{print $4}')

  MEMORY=$(aws ec2 describe-instance-types \
  --instance-types $INSTANCE_TYPE |grep "MEMORYINFO" |awk '{print $2}')

  DISK=$(aws ec2 describe-instance-types \
  --instance-types $INSTANCE_TYPE |grep "SUPPORTEDROOTDEVICETYPES" |awk '{print $2}')

  PRICE=$(aws ec2 describe-spot-price-history \
  --availability-zone $ZONE \
  --instance-types $INSTANCES \
  --product-description "Linux/UNIX" \
  --start-time $START \
  --end-time $END |awk '{print $5}')

 echo "$INSTANCE_TYPE,$VCORES,$MEMORY,$DISK,$PRICE" >> table.csv
done

rich table.csv

How to Get prices:

ZONE="eu-central-1a"
INSTANCES="m6i.large"
START=$(date +%Y-%m-%dT00:00:00)
END=$(date +%Y-%m-%dT%H:%M:%S)

aws ec2 describe-spot-price-history \
--availability-zone $ZONE \
--instance-types $INSTANCES \
--product-description "Linux/UNIX" \
--start-time $START \
--end-time $END \
--output table

Azure

Azure is also pretty straight-forward but you will need to do some filtering on the query results to get the data you need. There are however some large potential issues you need to plan around.

  • westeurope = Netherlands
  • northeurope = Ireland
  1. Gen1 vs Gen2 VMs.
  • Azure has 2 hypervsirs they use. Gen1 which is based on legacy BIOS, and Gen2 which is based on UEFI. Many VM families only support one or the other, though some support both. You will need to check which is required by the VM family you want to use. See HERE
  1. Availability

  • Not every Azure datacenter has every type of machine. You will need to check if the machine you want is availbe in the datacenter you will be using.

    az vm list-skus --location "westeurope" \
  --size Standard_N \
  --output table
  1. Quotas
  • Azure uses resource quotas just liek all the other major clouds. These may be too low for you to create certain types of virtual machines, GPUs, Spot instances, or Low-Priority VMs. You can request quota changes via the portal HERE.

More Resources:

GPU VM Types

VM Name CPU Name vCores RAM GPU Name GPUs vRAM Monthly Spot
Standard_NC6 Xeon E5-2690 v3 6 56 Tesla K80 1 12 80.75
Standard_NC6s_v2 Xeon E5-2690 v4 6 112 Tesla P100 1 16 185.73
Standard_NC6s_v3 Xeon E5-2690 v4 6 112 Tesla V100 1 12 1,251.83
Standard_NC4as_T4_v3 AMD EPYC 7V12(Rome) 4 28 Tesla T4 1 16 229.25
Standard_ND6s Xeon E5-2690 v4 6 112 Tesla P40 1 24 286.82
Standard_NV6 Xeon E5-2690 v3 6 56 Tesla M60 1/2 8 94.53
Standard_NV12 Xeon E5-2690 v3 6 56 Tesla M60 1 16 189.05
Standard_NV12s_v3 Xeon E5-2690 v4 12 112 Tesla M60 0.5 8 98.75
Standard_NV24s_v3 Xeon E5-2690 v4 12 112 Tesla M60 1 16 197.36
Standard_NV4as_v4 AMD EPYC 7V12(Rome) 4 14 Radeon MI25 1/8 2 20.15
Standard_NV32as_v4 AMD EPYC 7V12(Rome) 32 112 Radeon MI25 1 16 161.35
Standard_NV6ads_A10_v5 AMD EPYC 74F3V(Milan) 6 55 Nvidia A10 1/6 4 163.43
Standard_NV36ads_A10_v5 AMD EPYC 74F3V(Milan) 36 440 Nvidia A10 1 24 1152.32

Get current prices witha gross one-liner:

export ARM_SKU="Standard_NV36ads_A10_v5"
export LOCATION="'EU West'"
export METER_NAME=$(echo "'$ARM_SKU Spot'"| sed 's/Standard_//g' |sed 's/_/ /g')
export ARM_SKU_NAME=$(echo "'$ARM_SKU'")

docker run --platform linux/amd64 \
-e API_URL="https://prices.azure.com/api/retail/prices" \
-e LOCATION="$LOCATION"  \
-e SERVICE_NAME="'Virtual Machines'" \
-e SERVICE_FAMILY="'Compute'" \
-e METER_NAME="$METER_NAME" \
-e ARM_SKU_NAME="$ARM_SKU_NAME" \
-e ARM_SKU="$ARM_SKU" \
-e ARM_CLIENT_ID=$(bw get item admin-robot |jq -r '.fields[] |select(.name=="clientId") |.value') \
-e ARM_CLIENT_SECRET=$(bw get item admin-robot |jq -r '.fields[] |select(.name=="clientSecret") |.value') \
-e ARM_TENANT_ID=$(bw get item admin-robot |jq -r '.fields[] |select(.name=="tenantId") |.value') \
mcr.microsoft.com/azure-cli:2.9.1 sh -c 'az login --service-principal \
--username "$ARM_CLIENT_ID" \
--password "$ARM_CLIENT_SECRET" \
--tenant "$ARM_TENANT_ID" 2>&1 > /dev/null && \
echo "az rest --method get --uri \"${API_URL}?\\\$filter=\
location eq $LOCATION and \
serviceName eq $SERVICE_NAME and \
serviceFamily eq $SERVICE_FAMILY and \
armSkuName eq $ARM_SKU_NAME and \
meterName eq $METER_NAME"\" \
--query \"[Items][0][*].{name:productName, sku:armSkuName, location:location, hourly_price:retailPrice, hourly_price:retailPrice, currency:currencyCode, type:type}\" \
-o json |sh' |jq

Equinix Spot Metal

Equinix isnt a cloud-provider so much as a colocation service with a good set of APIs. They dont have a fancy cli so you just query an API endpoint and get back a json file that basically already in the format we want anyway.

Resources

How to Get Prices with a gross one-liner

TOKEN=$(bw get notes equinix-api-token) && \
URL="https://api.equinix.com/metal/v1/market/spot/prices/metros" && \
METRO="am" && \
PRICES=$(curl -X GET -H "X-Auth-Token: $TOKEN" $URL -d "metro=$METRO" | \
python3 -c "import sys, json; print(json.load(sys.stdin)['spot_market_prices']['am'])"| sed "s/'/\"/g") && \
echo $PRICES |jq

Google Cloud Platform (out of date, api now on v2beta)

  • europe-west1 = Belgium
  • europe-west4 = Netherlands

Google is the worst when it comes to transparancy around what exact CPU you will get when you request a VM from them. UNless you want the NEWEST (A2 - Cascade lake), you could get ANY cpu from a mix of old to really old CPUs. The fact that the only GPU capable SKU's are the N1 (random cpu) or A2 (cascade lake) means I can't really give an accurate CPU model or date.

GCP is also frustrating because we have to put in a LOT of boilerplate to get the data we want. Since GCP doesnt use machine families the same way others do, we have to get the individual prices of the CPU type, RAM amount, and GPU type that we will use in the VM. Once we have all these data-points we can create a final price.

How to get Prices

  1. have an existing project (an organzation alone isnt enough)
  2. Enable the Cloud Billing API: https://console.cloud.google.com/flows/enableapi?apiid=cloudbilling.googleapis.com
  3. Create an API key: https://cloud.google.com/docs/authentication/api-keys

Create an API key using the gcloud CLI

gcloud alpha services api-keys create --display-name=SOME_NAME

Get price per CPU core

# JQ explanation
# 1. set the REGION arg to an array represented as a string - required to check multiple regions
# 2. filter results for items in the desired regions. uses 'index' because we need to find an item in a nested array
# 3. filter for items priced by the hour 'h'. This removes reserved instances from results
# 4. filter based on the `resourceGroups` filed which is poorly named. It's closer to `family` or `machine type` from other cloud providers.
# 5. filter usage types for Preemptable only, you could also filter for OnDemand type instances.
# 6. Check if the description contains the GPU type we want. This data is oddly not in its own filed anywhere.

curl https://cloudbilling.googleapis.com/v1/services/6F81-5844-456A/skus?key=$(bw get notes "GCP API key") > skus_compute_engine.json

export FAMILY="N1Standard" # or `CPU`
export REGION='"europe-west1", "europe-west4", "europe-central2"'
export CORES="16"
export CPU_TIER="N1" # or A2 

DATA=$(cat skus_compute_engine.json \
  | jq -r --arg REGION "$REGION" '.skus[] 
  | select((.serviceRegions | index( '"$REGION"' )) 
  and select(.pricingInfo[0].pricingExpression.usageUnit=="h") 
  and .category.resourceGroup==env.FAMILY 
  and .category.usageType=="Preemptible" 
  and select(.description | contains( env.CPU_TIER )))')

export NANOS=$(echo $DATA |jq '.pricingInfo[0].pricingExpression.tieredRates[0].unitPrice.nanos')
CONVERTED_RATE=$(bc <<< "scale=5; $NANOS/1000000000")
CPU_PRICE=$( bc <<< "scale=5; $CONVERTED_RATE * $CORES" )
echo "CPU Price: $CPU_PRICE"

Get RAM price:

export FAMILY="N1Standard" # or `RAM`
export REGION='"europe-west1", "europe-west4"'
export RAM_AMOUNT="64"
export CPU_TIER="N1"

DATA=$(cat skus_compute_engine.json \
  | jq -r --arg REGION "$REGION" '.skus[] 
  | select((.serviceRegions | index( '"$REGION"' )) 
  and select(.pricingInfo[0].pricingExpression.usageUnit=="GiBy.h") 
  and .category.resourceGroup==env.FAMILY 
  and .category.usageType=="Preemptible" 
  and select(.description | contains( env.CPU_TIER )))')

export NANOS=$(echo $DATA |jq '.pricingInfo[0].pricingExpression.tieredRates[0].unitPrice.nanos')
CONVERTED_RATE=$(bc <<< "scale=5; $NANOS/1000000000")
RAM_PRICE=$( bc <<< "scale=5; $CONVERTED_RATE * $RAM_AMOUNT" )
echo "RAM Price: $RAM_PRICE"

Get price per GPU

# JQ explanation
# 1. set the REGION arg to an array represented as a string - required to check multiple regions
# 2. filter results for items in the desired regions. uses 'index' because we need to find an item in a nested array
# 3. filter for items priced by the hour 'h'. This removes reserved instances from results
# 4. filter based on the `resourceGroupz filed which is poorly named. It's closer to 'family' or 'machine type' from other cloud providers.
# 5. filter usage types for Preemptable only, you could also filter for OnDemand type instances.
# 6. Check if the description contains the GPU type we want. This data is oddly not in its own filed anywhere.

GPU Types: T4, P4, A100, P100

export FAMILY="GPU"
export GPU_TYPE="T4"
export GPUS=1
export REGION='"europe-west1", "europe-west4"'

DATA=$(cat skus_compute_engine.json \
  | jq -r --arg REGION "$REGION" '.skus[] 
  | select((.serviceRegions | index( '"$REGION"' )) 
  and select(.pricingInfo[0].pricingExpression.usageUnit=="h") 
  and .category.resourceGroup==env.FAMILY 
  and .category.usageType=="Preemptible" 
  and select(.description | contains( env.GPU_TYPE )))')


export NANOS=$(echo $DATA |jq '.pricingInfo[0].pricingExpression.tieredRates[0].unitPrice.nanos')

CONVERTED_RATE=$(bc <<< "scale=5; $NANOS/1000000000")

GPU_PRICE=$( bc <<< "scale=5; $CONVERTED_RATE * $GPUS" )

echo "GPU Price: $GPU_PRICE"

Combine prices

COMBINED_PRICE=$(bc <<< "scale=5; $CPU_PRICE + $RAM_PRICE + $GPU_PRICE")
echo "Combined Price: $COMBINED_PRICE"

Chart Rough Draft

Vendor Name CPU Name CPU Date vCPU MEM DISK Price/hr
GCP c2d-highcpu-2 Zen3 AMD EPYC Milan Q1-2021 2 4 ??? $0.0198
GCP c2d-highcpu-4 Zen3 AMD EPYC Milan Q1-2021 4 8 ??? $0.0396
Azure Standard_D4d_v4 Xeon Platinum 8272CL Q2-2019 4 16 150 $0.04
GCP c2d-standard-4 Zen3 AMD EPYC Milan Q1-2021 4 16 ??? $0.04796
GCP c2-standard-4 3.9 GHz Cascade Lake Xeon Q1-2020 4 16 ??? $0.0557
GCP c2d-highcpu-8 Zen3 AMD EPYC Milan Q1-2021 8 16 ??? $0.0792
Azure Standard_D8d_v4 Xeon Platinum 8272CL Q2-2019 8 32 300 $0.08
Equinix m3.small.x86 Rocket Lake Xeon E-2378G Q3-2021 16 64 960 $0.11
AWS M6i.large Xeon Ice Lake 8375C Q2-2020 2 8 ??? $0.113
AWS M6a.large AMD EPYC 7R13 Zen3 Q1-2021 2 8 ??? $0.113
GCP c2-standard-8 3.9 GHz Cascade Lake Xeon Q1-2020 8 32 ??? $0.1114
AWS M6i.xlarge Xeon Ice Lake 8375C Q2-2020 4 16 ??? $0.2259
AWS M6a.xlarge AMD EPYC 7R13 Zen3 Q1-2021 4 16 ??? $0.2259
Equinix n3.xlarge.x86 Xeon Gold 6314U Ice Lake Q2-2021 64 512 7.6TB $0.45
AWS M6i.2xlarge Xeon Ice Lake 8375C Q2-2020 8 32 ??? $0.4518
AWS M6a.2xlarge AMD EPYC 7R13 Zen3 Q1-2021 8 32 ??? $0.4518
Equinix a3.xlarge.x86 2 x Xeon Gold 6338 Q2-2021 128 1TB 480GB $0.75

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notes about querying spot pricing

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bash aws azure gcp spot-instances equinix spot-pricing

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