ComputeFleetVmCategory Struct

Definition

Namespace:

Azure.ResourceManager.ComputeFleet.Models

Assembly:

Azure.ResourceManager.ComputeFleet.dll

Package:

Azure.ResourceManager.ComputeFleet v1.0.0

Source:

ComputeFleetVmCategory.cs

VMCategories defined for Azure VMs. See: https://learn.microsoft.com/en-us/azure/virtual-machines/sizes/overview?tabs=breakdownseries%2Cgeneralsizelist%2Ccomputesizelist%2Cmemorysizelist%2Cstoragesizelist%2Cgpusizelist%2Cfpgasizelist%2Chpcsizelist#general-purpose

public readonly struct ComputeFleetVmCategory : IEquatable<Azure.ResourceManager.ComputeFleet.Models.ComputeFleetVmCategory>

type ComputeFleetVmCategory = struct

Public Structure ComputeFleetVmCategory
Implements IEquatable(Of ComputeFleetVmCategory)

Inheritance

ValueType

ComputeFleetVmCategory

Implements

IEquatable<ComputeFleetVmCategory>

Constructors

ComputeFleetVmCategory(String)

Initializes a new instance of ComputeFleetVmCategory.

Properties

ComputeOptimized	Compute optimized VM sizes have a high CPU-to-memory ratio. These sizes are good for medium traffic web servers, network appliances, batch processes, and application servers.
FpgaAccelerated	FPGA optimized VM sizes are specialized virtual machines available with single or multiple FPGA. These sizes are designed for compute-intensive workloads. This article provides information about the number and type of FPGA, vCPUs, data disks, and NICs. Storage throughput and network bandwidth are also included for each size in this grouping.
GeneralPurpose	General purpose VM sizes provide balanced CPU-to-memory ratio. Ideal for testing and development, small to medium databases, and low to medium traffic web servers.
GpuAccelerated	GPU optimized VM sizes are specialized virtual machines available with single, multiple, or fractional GPUs. These sizes are designed for compute-intensive, graphics-intensive, and visualization workloads.
HighPerformanceCompute	Azure High Performance Compute VMs are optimized for various HPC workloads such as computational fluid dynamics, finite element analysis, frontend and backend EDA, rendering, molecular dynamics, computational geo science, weather simulation, and financial risk analysis.
MemoryOptimized	Memory optimized VM sizes offer a high memory-to-CPU ratio that is great for relational database servers, medium to large caches, and in-memory analytics.
StorageOptimized	Storage optimized virtual machine (VM) sizes offer high disk throughput and IO, and are ideal for Big Data, SQL, NoSQL databases, data warehousing, and large transactional databases. Examples include Cassandra, MongoDB, Cloudera, and Redis.

Methods

Equals(ComputeFleetVmCategory)	Indicates whether the current object is equal to another object of the same type.
ToString()	Returns the fully qualified type name of this instance.

Operators

Equality(ComputeFleetVmCategory, ComputeFleetVmCategory)	Determines if two ComputeFleetVmCategory values are the same.
Implicit(String to ComputeFleetVmCategory)	Converts a String to a ComputeFleetVmCategory.
Inequality(ComputeFleetVmCategory, ComputeFleetVmCategory)	Determines if two ComputeFleetVmCategory values are not the same.