alien-core 3.3.60

# Which machines the instance catalog lists. `scripts/instance-catalog/generate.py` reads this
# file and the clouds' machine APIs and writes `src/instance_catalog/catalog.rs`. vCPU, memory,
# local disk and GPU numbers come from the API; the rest comes from this file (labels, GPU
# types the API doesn't name, `overrides`) or from the disk constants in generate.py.
#
# Each `[[<platform>.series]]` entry is one series of a category:
#   series         The series name machines are grouped by.
#   category       The `InstanceFamily` it belongs to.
#   label          The name people see for the series.
#   pattern        A regex for the series' machine names, where `{n}` stands for a number and
#                  `{size}` for an AWS size (`medium`, `large`, `2xlarge`, ...). Defaults to
#                  `{series}.{size}` on AWS and `{series}-{n}` on GCP; Azure always sets it.
#   from, to       The smallest and the largest machine to include, by vCPU then memory.
#                  `to` defaults to the largest one. Bare-metal machines never match.
#   sizes          Explicit machine names, in place of `pattern`, `from` and `to`.
#   machine        The provider machine type the `sizes` run on, when the catalog name adds an
#                  accelerator to it (`n1-standard-4-t4` runs on `n1-standard-4`).
#   attached_gpu   The accelerator such a row adds, by the provider's accelerator name.
#   gpu_type       The GPU type for a series whose API names no GPU model (Azure).
#   auto_select_to The largest machine automatic selection may pick; it may pick none of the
#                  series without it. Automatic selection picks from a fixed set of machines, so
#                  adding a series or a size never changes what an existing stack gets.
#   nested_virt    Whether the series exposes nested virtualization, with the provider's page.
#   overrides      Per machine name, values that replace the API's: `memory_gib`,
#                  `ephemeral_storage_gib` and `nested_virt`. Only machines automatic selection
#                  may pick can have them: they keep the values existing pools are sized and
#                  validated with.
#
# Series order is the order a series appears in within its category, and the tie-break between
# two machines of equal size in automatic selection.

[aws]
regions = ["us-east-1", "us-west-2"]

[[aws.series]]
series = "t4g"
category = "Burstable"
label = "Burstable · Graviton2"
from = "t4g.micro"
to = "t4g.2xlarge"
auto_select_to = "t4g.xlarge"

[[aws.series]]
series = "t3"
category = "Burstable"
label = "Burstable · Intel"
from = "t3.xlarge"
to = "t3.2xlarge"
auto_select_to = "t3.xlarge"

[[aws.series]]
series = "m7g"
category = "GeneralPurpose"
label = "General purpose · Graviton3"
from = "m7g.medium"
auto_select_to = "m7g.4xlarge"

[[aws.series]]
series = "m8g"
category = "GeneralPurpose"
label = "General purpose · Graviton4"
from = "m8g.medium"

[[aws.series]]
series = "m7i"
category = "GeneralPurpose"
label = "General purpose · Intel · 7th gen"
from = "m7i.large"
auto_select_to = "m7i.4xlarge"
# The API reports nested virtualization for m7i. The series keeps the flag it had before the
# catalog was generated, so automatic picks and existing validation stay the same.

# https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/amazon-ec2-nested-virtualization.html
[[aws.series]]
series = "m8i"
category = "GeneralPurpose"
label = "General purpose · Intel · 8th gen"
from = "m8i.large"
to = "m8i.96xlarge"
auto_select_to = "m8i.4xlarge"
nested_virt = true

[[aws.series]]
series = "m8i-flex"
category = "GeneralPurpose"
label = "General purpose · Intel · 8th gen · Flex"
from = "m8i-flex.large"
to = "m8i-flex.16xlarge"
nested_virt = true

[[aws.series]]
series = "m8a"
category = "GeneralPurpose"
label = "General purpose · AMD · 8th gen"
from = "m8a.medium"

[[aws.series]]
series = "c7g"
category = "ComputeOptimized"
label = "Compute optimized · Graviton3"
from = "c7g.medium"
auto_select_to = "c7g.4xlarge"

[[aws.series]]
series = "c8g"
category = "ComputeOptimized"
label = "Compute optimized · Graviton4"
from = "c8g.medium"
auto_select_to = "c8g.4xlarge"

[[aws.series]]
series = "c8i"
category = "ComputeOptimized"
label = "Compute optimized · Intel · 8th gen"
from = "c8i.large"
to = "c8i.96xlarge"
auto_select_to = "c8i.4xlarge"
nested_virt = true

[[aws.series]]
series = "c8i-flex"
category = "ComputeOptimized"
label = "Compute optimized · Intel · 8th gen · Flex"
from = "c8i-flex.large"
to = "c8i-flex.16xlarge"
nested_virt = true

[[aws.series]]
series = "c8a"
category = "ComputeOptimized"
label = "Compute optimized · AMD · 8th gen"
from = "c8a.medium"

[[aws.series]]
series = "r7g"
category = "MemoryOptimized"
label = "Memory optimized · Graviton3"
from = "r7g.medium"
auto_select_to = "r7g.4xlarge"

[[aws.series]]
series = "r8g"
category = "MemoryOptimized"
label = "Memory optimized · Graviton4"
from = "r8g.medium"

[[aws.series]]
series = "r6a"
category = "MemoryOptimized"
label = "Memory optimized · AMD · 6th gen"
from = "r6a.large"
auto_select_to = "r6a.4xlarge"

[[aws.series]]
series = "r7i"
category = "MemoryOptimized"
label = "Memory optimized · Intel · 7th gen"
from = "r7i.large"
auto_select_to = "r7i.4xlarge"
# The API reports nested virtualization for r7i; it stays unflagged like m7i.

[[aws.series]]
series = "r8i"
category = "MemoryOptimized"
label = "Memory optimized · Intel · 8th gen"
from = "r8i.large"
to = "r8i.96xlarge"
nested_virt = true

[[aws.series]]
series = "r8i-flex"
category = "MemoryOptimized"
label = "Memory optimized · Intel · 8th gen · Flex"
from = "r8i-flex.large"
to = "r8i-flex.16xlarge"
nested_virt = true

[[aws.series]]
series = "r8a"
category = "MemoryOptimized"
label = "Memory optimized · AMD · 8th gen"
from = "r8a.medium"

[[aws.series]]
series = "i4i"
category = "StorageOptimized"
label = "Storage optimized · Intel · 4th gen"
from = "i4i.xlarge"
auto_select_to = "i4i.8xlarge"
# AWS reports local disk in decimal GB (937 GB is 872 GiB). These sizes are automatic picks,
# so they keep the disk existing pools are sized and validated with.
overrides = { "i4i.xlarge" = { ephemeral_storage_gib = 937 }, "i4i.2xlarge" = { ephemeral_storage_gib = 1875 }, "i4i.4xlarge" = { ephemeral_storage_gib = 3750 }, "i4i.8xlarge" = { ephemeral_storage_gib = 7500 } }

[[aws.series]]
series = "i7i"
category = "StorageOptimized"
label = "Storage optimized · Intel · 7th gen"
from = "i7i.large"
nested_virt = true

[[aws.series]]
series = "i8g"
category = "StorageOptimized"
label = "Storage optimized · Graviton4"
from = "i8g.large"

[[aws.series]]
series = "g5"
category = "GpuCompute"
label = "GPU · NVIDIA A10G"
sizes = ["g5.xlarge", "g5.2xlarge"]
auto_select_to = "g5.2xlarge"
# AWS reports local disk in decimal GB. These sizes keep the disk existing pools are sized with.
overrides = { "g5.xlarge" = { ephemeral_storage_gib = 250 }, "g5.2xlarge" = { ephemeral_storage_gib = 450 } }

[[aws.series]]
series = "p4d"
category = "GpuCompute"
label = "GPU · NVIDIA A100"
sizes = ["p4d.24xlarge"]
auto_select_to = "p4d.24xlarge"
# AWS reports local disk in decimal GB. This size keeps the disk existing pools are sized with.
overrides = { "p4d.24xlarge" = { ephemeral_storage_gib = 8000 } }

[[aws.series]]
series = "p5"
category = "GpuCompute"
label = "GPU · NVIDIA H100"
sizes = ["p5.48xlarge"]
auto_select_to = "p5.48xlarge"
# The API reports 8 x 3800 GB of NVMe.
overrides = { "p5.48xlarge" = { ephemeral_storage_gib = 8000 } }

# Nested virtualization on GCP is any Intel series except E2 and the M (memory-optimized) series:
# https://docs.cloud.google.com/compute/docs/instances/nested-virtualization/overview
[gcp]
zones = ["us-central1-a", "us-central1-b", "us-central1-c", "us-central1-f"]
# Arm series (N4A, C4A) are left out: the Google Cloud host image is x86 only.

[[gcp.series]]
series = "e2"
category = "Burstable"
label = "Burstable · shared core"
sizes = ["e2-micro", "e2-small", "e2-medium"]
auto_select_to = "e2-medium"

[[gcp.series]]
series = "n2-standard"
category = "GeneralPurpose"
label = "General purpose · Intel · N2"
from = "n2-standard-2"
auto_select_to = "n2-standard-16"
nested_virt = true

[[gcp.series]]
series = "n4-standard"
category = "GeneralPurpose"
label = "General purpose · Intel · N4"
from = "n4-standard-2"
nested_virt = true

[[gcp.series]]
series = "c3-standard"
category = "ComputeOptimized"
label = "Compute optimized · Intel · C3"
from = "c3-standard-4"
auto_select_to = "c3-standard-8"
nested_virt = true
# The API reports twice this memory and Google allows nested virtualization on C3; these
# values match what existing pools on these sizes are sized and validated with.
[gcp.series.overrides."c3-standard-4"]
memory_gib = 8
nested_virt = false
[gcp.series.overrides."c3-standard-8"]
memory_gib = 16
nested_virt = false

[[gcp.series]]
series = "c4-standard"
category = "ComputeOptimized"
label = "Compute optimized · Intel · C4"
from = "c4-standard-2"
nested_virt = true

[[gcp.series]]
series = "c4-highcpu"
category = "ComputeOptimized"
label = "Compute optimized · Intel · C4 high CPU"
from = "c4-highcpu-2"
nested_virt = true

[[gcp.series]]
series = "n4-highcpu"
category = "ComputeOptimized"
label = "Compute optimized · Intel · N4 high CPU"
from = "n4-highcpu-2"
nested_virt = true

[[gcp.series]]
series = "n2-highmem"
category = "MemoryOptimized"
label = "Memory optimized · Intel · N2 high memory"
from = "n2-highmem-2"
auto_select_to = "n2-highmem-32"
nested_virt = true
# Google allows nested virtualization on N2; these sizes stay off, matching what existing
# pools on them are validated with.
[gcp.series.overrides."n2-highmem-2"]
nested_virt = false
[gcp.series.overrides."n2-highmem-4"]
nested_virt = false
[gcp.series.overrides."n2-highmem-8"]
nested_virt = false
[gcp.series.overrides."n2-highmem-16"]
nested_virt = false
[gcp.series.overrides."n2-highmem-32"]
nested_virt = false

[[gcp.series]]
series = "n4-highmem"
category = "MemoryOptimized"
label = "Memory optimized · Intel · N4 high memory"
from = "n4-highmem-2"
nested_virt = true

[[gcp.series]]
series = "c4-highmem"
category = "MemoryOptimized"
label = "Memory optimized · Intel · C4 high memory"
from = "c4-highmem-2"
nested_virt = true

[[gcp.series]]
series = "c3d-standard"
category = "StorageOptimized"
label = "Storage optimized · AMD · C3D"
sizes = ["c3d-standard-8", "c3d-standard-16", "c3d-standard-30"]
auto_select_to = "c3d-standard-30"
# These sizes have no local SSD (only the `-lssd` types do). The GCP controller sizes their
# persistent boot disk from this number.
[gcp.series.overrides."c3d-standard-8"]
ephemeral_storage_gib = 480
[gcp.series.overrides."c3d-standard-16"]
ephemeral_storage_gib = 960
[gcp.series.overrides."c3d-standard-30"]
ephemeral_storage_gib = 1920

# An N1 machine with one attached T4; GCP lists the GPU as an accelerator type, not a machine.
[[gcp.series]]
series = "n1-t4"
category = "GpuCompute"
label = "GPU · NVIDIA T4"
sizes = ["n1-standard-4-t4"]
machine = "n1-standard-4"
attached_gpu = "nvidia-tesla-t4"
auto_select_to = "n1-standard-4-t4"

[[gcp.series]]
series = "a2-highgpu"
category = "GpuCompute"
label = "GPU · NVIDIA A100"
sizes = ["a2-highgpu-1g", "a2-highgpu-8g"]
auto_select_to = "a2-highgpu-8g"
# The API reports 680 GiB. The size keeps the memory existing pools are sized and validated
# with.
overrides = { "a2-highgpu-8g" = { memory_gib = 1360 } }

[[gcp.series]]
series = "a3-highgpu"
category = "GpuCompute"
label = "GPU · NVIDIA H100"
sizes = ["a3-highgpu-8g"]
auto_select_to = "a3-highgpu-8g"
# The API reports 16 bundled local SSDs.
overrides = { "a3-highgpu-8g" = { ephemeral_storage_gib = 100 } }

[azure]
regions = ["eastus", "westus2"]

[[azure.series]]
series = "Bs"
category = "Burstable"
label = "Burstable · B"
sizes = ["Standard_B1s", "Standard_B2s", "Standard_B2ms", "Standard_B4ms"]
auto_select_to = "Standard_B4ms"

# https://learn.microsoft.com/en-us/azure/virtual-machines/sizes/general-purpose/dsv4-series says
# nested virtualization is supported. The series keeps the flag it had before the catalog was
# generated, so automatic picks and existing validation stay the same.
[[azure.series]]
series = "Dsv4"
category = "GeneralPurpose"
label = "General purpose · Intel · Dsv4"
sizes = ["Standard_D2s_v4"]
auto_select_to = "Standard_D2s_v4"

# https://learn.microsoft.com/en-us/azure/virtual-machines/sizes/general-purpose/dsv5-series
[[azure.series]]
series = "Dsv5"
category = "GeneralPurpose"
label = "General purpose · Intel · Dsv5"
pattern = "Standard_D{n}s_v5"
from = "Standard_D2s_v5"
auto_select_to = "Standard_D16s_v5"
nested_virt = true

# https://learn.microsoft.com/en-us/azure/virtual-machines/sizes/general-purpose/dsv6-series
[[azure.series]]
series = "Dsv6"
category = "GeneralPurpose"
label = "General purpose · Intel · Dsv6"
pattern = "Standard_D{n}s_v6"
from = "Standard_D2s_v6"
nested_virt = true

# https://learn.microsoft.com/en-us/azure/virtual-machines/sizes/general-purpose/dasv6-series
[[azure.series]]
series = "Dasv6"
category = "GeneralPurpose"
label = "General purpose · AMD · Dasv6"
pattern = "Standard_D{n}as_v6"
from = "Standard_D2as_v6"
nested_virt = true

# https://learn.microsoft.com/en-us/azure/virtual-machines/sizes/compute-optimized/fsv2-series
[[azure.series]]
series = "Fsv2"
category = "ComputeOptimized"
label = "Compute optimized · Intel · Fsv2"
pattern = "Standard_F{n}s_v2"
from = "Standard_F2s_v2"
auto_select_to = "Standard_F16s_v2"
nested_virt = true

# https://learn.microsoft.com/en-us/azure/virtual-machines/sizes/memory-optimized/esv5-series
[[azure.series]]
series = "Esv5"
category = "MemoryOptimized"
label = "Memory optimized · Intel · Esv5"
pattern = "Standard_E{n}s_v5"
from = "Standard_E2s_v5"
auto_select_to = "Standard_E16s_v5"
nested_virt = true

# https://learn.microsoft.com/en-us/azure/virtual-machines/sizes/memory-optimized/esv6-series
[[azure.series]]
series = "Esv6"
category = "MemoryOptimized"
label = "Memory optimized · Intel · Esv6"
pattern = "Standard_E{n}s_v6"
from = "Standard_E2s_v6"
nested_virt = true

# https://learn.microsoft.com/en-us/azure/virtual-machines/sizes/storage-optimized/lsv3-series says
# nested virtualization is supported. The series keeps the flag it had before the catalog was
# generated, so automatic picks and existing validation stay the same.
[[azure.series]]
series = "Lsv3"
category = "StorageOptimized"
label = "Storage optimized · Intel · Lsv3"
pattern = "Standard_L{n}s_v3"
from = "Standard_L8s_v3"
auto_select_to = "Standard_L32s_v3"
[azure.series.overrides."Standard_L8s_v3"]
ephemeral_storage_gib = 1788
[azure.series.overrides."Standard_L16s_v3"]
ephemeral_storage_gib = 3576
[azure.series.overrides."Standard_L32s_v3"]
ephemeral_storage_gib = 7154

# Azure reports a GPU count but not its model, so the GPU type is named here.
[[azure.series]]
series = "NCasT4_v3"
category = "GpuCompute"
label = "GPU · NVIDIA T4"
sizes = ["Standard_NC4as_T4_v3"]
gpu_type = "nvidia-t4"
auto_select_to = "Standard_NC4as_T4_v3"

[[azure.series]]
series = "NCads_A100_v4"
category = "GpuCompute"
label = "GPU · NVIDIA A100"
sizes = ["Standard_NC24ads_A100_v4", "Standard_NC96ads_A100_v4"]
gpu_type = "nvidia-a100"
auto_select_to = "Standard_NC96ads_A100_v4"
# The API reports NVMe of 894 and 3576 GiB; these values add the temp disk.
[azure.series.overrides."Standard_NC24ads_A100_v4"]
ephemeral_storage_gib = 958
[azure.series.overrides."Standard_NC96ads_A100_v4"]
ephemeral_storage_gib = 3916

[[azure.series]]
series = "NDisr_H100_v5"
category = "GpuCompute"
label = "GPU · NVIDIA H100"
sizes = ["Standard_ND96isr_H100_v5"]
gpu_type = "nvidia-h100"
auto_select_to = "Standard_ND96isr_H100_v5"
# The API reports 28610 GiB of NVMe, more than an Azure OS disk can hold.
overrides = { "Standard_ND96isr_H100_v5" = { ephemeral_storage_gib = 1000 } }