CreateStreamGroupInputBuilder

Struct CreateStreamGroupInputBuilder 

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#[non_exhaustive]
pub struct CreateStreamGroupInputBuilder { /* private fields */ }
Expand description

A builder for CreateStreamGroupInput.

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impl CreateStreamGroupInputBuilder

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pub fn description(self, input: impl Into<String>) -> Self

A descriptive label for the stream group.

This field is required.
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pub fn set_description(self, input: Option<String>) -> Self

A descriptive label for the stream group.

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pub fn get_description(&self) -> &Option<String>

A descriptive label for the stream group.

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pub fn stream_class(self, input: StreamClass) -> Self

The target stream quality for sessions that are hosted in this stream group. Set a stream class that is appropriate to the type of content that you're streaming. Stream class determines the type of computing resources Amazon GameLift Streams uses and impacts the cost of streaming. The following options are available:

A stream class can be one of the following:

  • gen5n_win2022 (NVIDIA, ultra) Supports applications with extremely high 3D scene complexity. Runs applications on Microsoft Windows Server 2022 Base and supports DirectX 12. Compatible with Unreal Engine versions up through 5.4, 32 and 64-bit applications, and anti-cheat technology. Uses NVIDIA A10G Tensor GPU.

    • Reference resolution: 1080p

    • Reference frame rate: 60 fps

    • Workload specifications: 8 vCPUs, 32 GB RAM, 24 GB VRAM

    • Tenancy: Supports 1 concurrent stream session

  • gen5n_high (NVIDIA, high) Supports applications with moderate to high 3D scene complexity. Uses NVIDIA A10G Tensor GPU.

    • Reference resolution: 1080p

    • Reference frame rate: 60 fps

    • Workload specifications: 4 vCPUs, 16 GB RAM, 12 GB VRAM

    • Tenancy: Supports up to 2 concurrent stream sessions

  • gen5n_ultra (NVIDIA, ultra) Supports applications with extremely high 3D scene complexity. Uses dedicated NVIDIA A10G Tensor GPU.

    • Reference resolution: 1080p

    • Reference frame rate: 60 fps

    • Workload specifications: 8 vCPUs, 32 GB RAM, 24 GB VRAM

    • Tenancy: Supports 1 concurrent stream session

  • gen4n_win2022 (NVIDIA, ultra) Supports applications with extremely high 3D scene complexity. Runs applications on Microsoft Windows Server 2022 Base and supports DirectX 12. Compatible with Unreal Engine versions up through 5.4, 32 and 64-bit applications, and anti-cheat technology. Uses NVIDIA T4 Tensor GPU.

    • Reference resolution: 1080p

    • Reference frame rate: 60 fps

    • Workload specifications: 8 vCPUs, 32 GB RAM, 16 GB VRAM

    • Tenancy: Supports 1 concurrent stream session

  • gen4n_high (NVIDIA, high) Supports applications with moderate to high 3D scene complexity. Uses NVIDIA T4 Tensor GPU.

    • Reference resolution: 1080p

    • Reference frame rate: 60 fps

    • Workload specifications: 4 vCPUs, 16 GB RAM, 8 GB VRAM

    • Tenancy: Supports up to 2 concurrent stream sessions

  • gen4n_ultra (NVIDIA, ultra) Supports applications with high 3D scene complexity. Uses dedicated NVIDIA T4 Tensor GPU.

    • Reference resolution: 1080p

    • Reference frame rate: 60 fps

    • Workload specifications: 8 vCPUs, 32 GB RAM, 16 GB VRAM

    • Tenancy: Supports 1 concurrent stream session

This field is required.
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pub fn set_stream_class(self, input: Option<StreamClass>) -> Self

The target stream quality for sessions that are hosted in this stream group. Set a stream class that is appropriate to the type of content that you're streaming. Stream class determines the type of computing resources Amazon GameLift Streams uses and impacts the cost of streaming. The following options are available:

A stream class can be one of the following:

  • gen5n_win2022 (NVIDIA, ultra) Supports applications with extremely high 3D scene complexity. Runs applications on Microsoft Windows Server 2022 Base and supports DirectX 12. Compatible with Unreal Engine versions up through 5.4, 32 and 64-bit applications, and anti-cheat technology. Uses NVIDIA A10G Tensor GPU.

    • Reference resolution: 1080p

    • Reference frame rate: 60 fps

    • Workload specifications: 8 vCPUs, 32 GB RAM, 24 GB VRAM

    • Tenancy: Supports 1 concurrent stream session

  • gen5n_high (NVIDIA, high) Supports applications with moderate to high 3D scene complexity. Uses NVIDIA A10G Tensor GPU.

    • Reference resolution: 1080p

    • Reference frame rate: 60 fps

    • Workload specifications: 4 vCPUs, 16 GB RAM, 12 GB VRAM

    • Tenancy: Supports up to 2 concurrent stream sessions

  • gen5n_ultra (NVIDIA, ultra) Supports applications with extremely high 3D scene complexity. Uses dedicated NVIDIA A10G Tensor GPU.

    • Reference resolution: 1080p

    • Reference frame rate: 60 fps

    • Workload specifications: 8 vCPUs, 32 GB RAM, 24 GB VRAM

    • Tenancy: Supports 1 concurrent stream session

  • gen4n_win2022 (NVIDIA, ultra) Supports applications with extremely high 3D scene complexity. Runs applications on Microsoft Windows Server 2022 Base and supports DirectX 12. Compatible with Unreal Engine versions up through 5.4, 32 and 64-bit applications, and anti-cheat technology. Uses NVIDIA T4 Tensor GPU.

    • Reference resolution: 1080p

    • Reference frame rate: 60 fps

    • Workload specifications: 8 vCPUs, 32 GB RAM, 16 GB VRAM

    • Tenancy: Supports 1 concurrent stream session

  • gen4n_high (NVIDIA, high) Supports applications with moderate to high 3D scene complexity. Uses NVIDIA T4 Tensor GPU.

    • Reference resolution: 1080p

    • Reference frame rate: 60 fps

    • Workload specifications: 4 vCPUs, 16 GB RAM, 8 GB VRAM

    • Tenancy: Supports up to 2 concurrent stream sessions

  • gen4n_ultra (NVIDIA, ultra) Supports applications with high 3D scene complexity. Uses dedicated NVIDIA T4 Tensor GPU.

    • Reference resolution: 1080p

    • Reference frame rate: 60 fps

    • Workload specifications: 8 vCPUs, 32 GB RAM, 16 GB VRAM

    • Tenancy: Supports 1 concurrent stream session

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pub fn get_stream_class(&self) -> &Option<StreamClass>

The target stream quality for sessions that are hosted in this stream group. Set a stream class that is appropriate to the type of content that you're streaming. Stream class determines the type of computing resources Amazon GameLift Streams uses and impacts the cost of streaming. The following options are available:

A stream class can be one of the following:

  • gen5n_win2022 (NVIDIA, ultra) Supports applications with extremely high 3D scene complexity. Runs applications on Microsoft Windows Server 2022 Base and supports DirectX 12. Compatible with Unreal Engine versions up through 5.4, 32 and 64-bit applications, and anti-cheat technology. Uses NVIDIA A10G Tensor GPU.

    • Reference resolution: 1080p

    • Reference frame rate: 60 fps

    • Workload specifications: 8 vCPUs, 32 GB RAM, 24 GB VRAM

    • Tenancy: Supports 1 concurrent stream session

  • gen5n_high (NVIDIA, high) Supports applications with moderate to high 3D scene complexity. Uses NVIDIA A10G Tensor GPU.

    • Reference resolution: 1080p

    • Reference frame rate: 60 fps

    • Workload specifications: 4 vCPUs, 16 GB RAM, 12 GB VRAM

    • Tenancy: Supports up to 2 concurrent stream sessions

  • gen5n_ultra (NVIDIA, ultra) Supports applications with extremely high 3D scene complexity. Uses dedicated NVIDIA A10G Tensor GPU.

    • Reference resolution: 1080p

    • Reference frame rate: 60 fps

    • Workload specifications: 8 vCPUs, 32 GB RAM, 24 GB VRAM

    • Tenancy: Supports 1 concurrent stream session

  • gen4n_win2022 (NVIDIA, ultra) Supports applications with extremely high 3D scene complexity. Runs applications on Microsoft Windows Server 2022 Base and supports DirectX 12. Compatible with Unreal Engine versions up through 5.4, 32 and 64-bit applications, and anti-cheat technology. Uses NVIDIA T4 Tensor GPU.

    • Reference resolution: 1080p

    • Reference frame rate: 60 fps

    • Workload specifications: 8 vCPUs, 32 GB RAM, 16 GB VRAM

    • Tenancy: Supports 1 concurrent stream session

  • gen4n_high (NVIDIA, high) Supports applications with moderate to high 3D scene complexity. Uses NVIDIA T4 Tensor GPU.

    • Reference resolution: 1080p

    • Reference frame rate: 60 fps

    • Workload specifications: 4 vCPUs, 16 GB RAM, 8 GB VRAM

    • Tenancy: Supports up to 2 concurrent stream sessions

  • gen4n_ultra (NVIDIA, ultra) Supports applications with high 3D scene complexity. Uses dedicated NVIDIA T4 Tensor GPU.

    • Reference resolution: 1080p

    • Reference frame rate: 60 fps

    • Workload specifications: 8 vCPUs, 32 GB RAM, 16 GB VRAM

    • Tenancy: Supports 1 concurrent stream session

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pub fn default_application_identifier(self, input: impl Into<String>) -> Self

The unique identifier of the Amazon GameLift Streams application that you want to set as the default application in a stream group. The application that you specify must be in READY status. The default application is pre-cached on always-on compute resources, reducing stream startup times. Other applications are automatically cached as needed.

If you do not link an application when you create a stream group, you will need to link one later, before you can start streaming, using AssociateApplications.

This value is an Amazon Resource Name (ARN) or ID that uniquely identifies the application resource. Example ARN: arn:aws:gameliftstreams:us-west-2:111122223333:application/a-9ZY8X7Wv6. Example ID: a-9ZY8X7Wv6.

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pub fn set_default_application_identifier(self, input: Option<String>) -> Self

The unique identifier of the Amazon GameLift Streams application that you want to set as the default application in a stream group. The application that you specify must be in READY status. The default application is pre-cached on always-on compute resources, reducing stream startup times. Other applications are automatically cached as needed.

If you do not link an application when you create a stream group, you will need to link one later, before you can start streaming, using AssociateApplications.

This value is an Amazon Resource Name (ARN) or ID that uniquely identifies the application resource. Example ARN: arn:aws:gameliftstreams:us-west-2:111122223333:application/a-9ZY8X7Wv6. Example ID: a-9ZY8X7Wv6.

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pub fn get_default_application_identifier(&self) -> &Option<String>

The unique identifier of the Amazon GameLift Streams application that you want to set as the default application in a stream group. The application that you specify must be in READY status. The default application is pre-cached on always-on compute resources, reducing stream startup times. Other applications are automatically cached as needed.

If you do not link an application when you create a stream group, you will need to link one later, before you can start streaming, using AssociateApplications.

This value is an Amazon Resource Name (ARN) or ID that uniquely identifies the application resource. Example ARN: arn:aws:gameliftstreams:us-west-2:111122223333:application/a-9ZY8X7Wv6. Example ID: a-9ZY8X7Wv6.

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pub fn location_configurations(self, input: LocationConfiguration) -> Self

Appends an item to location_configurations.

To override the contents of this collection use set_location_configurations.

A set of one or more locations and the streaming capacity for each location.

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pub fn set_location_configurations( self, input: Option<Vec<LocationConfiguration>>, ) -> Self

A set of one or more locations and the streaming capacity for each location.

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pub fn get_location_configurations(&self) -> &Option<Vec<LocationConfiguration>>

A set of one or more locations and the streaming capacity for each location.

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pub fn tags(self, k: impl Into<String>, v: impl Into<String>) -> Self

Adds a key-value pair to tags.

To override the contents of this collection use set_tags.

A list of labels to assign to the new stream group resource. Tags are developer-defined key-value pairs. Tagging Amazon Web Services resources is useful for resource management, access management and cost allocation. See Tagging Amazon Web Services Resources in the Amazon Web Services General Reference. You can use TagResource to add tags, UntagResource to remove tags, and ListTagsForResource to view tags on existing resources.

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pub fn set_tags(self, input: Option<HashMap<String, String>>) -> Self

A list of labels to assign to the new stream group resource. Tags are developer-defined key-value pairs. Tagging Amazon Web Services resources is useful for resource management, access management and cost allocation. See Tagging Amazon Web Services Resources in the Amazon Web Services General Reference. You can use TagResource to add tags, UntagResource to remove tags, and ListTagsForResource to view tags on existing resources.

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pub fn get_tags(&self) -> &Option<HashMap<String, String>>

A list of labels to assign to the new stream group resource. Tags are developer-defined key-value pairs. Tagging Amazon Web Services resources is useful for resource management, access management and cost allocation. See Tagging Amazon Web Services Resources in the Amazon Web Services General Reference. You can use TagResource to add tags, UntagResource to remove tags, and ListTagsForResource to view tags on existing resources.

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pub fn client_token(self, input: impl Into<String>) -> Self

A unique identifier that represents a client request. The request is idempotent, which ensures that an API request completes only once. When users send a request, Amazon GameLift Streams automatically populates this field.

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pub fn set_client_token(self, input: Option<String>) -> Self

A unique identifier that represents a client request. The request is idempotent, which ensures that an API request completes only once. When users send a request, Amazon GameLift Streams automatically populates this field.

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pub fn get_client_token(&self) -> &Option<String>

A unique identifier that represents a client request. The request is idempotent, which ensures that an API request completes only once. When users send a request, Amazon GameLift Streams automatically populates this field.

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pub fn build(self) -> Result<CreateStreamGroupInput, BuildError>

Consumes the builder and constructs a CreateStreamGroupInput.

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impl CreateStreamGroupInputBuilder

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pub async fn send_with( self, client: &Client, ) -> Result<CreateStreamGroupOutput, SdkError<CreateStreamGroupError, HttpResponse>>

Sends a request with this input using the given client.

Trait Implementations§

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impl Clone for CreateStreamGroupInputBuilder

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fn clone(&self) -> CreateStreamGroupInputBuilder

Returns a duplicate of the value. Read more
1.0.0 · Source§

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source. Read more
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impl Debug for CreateStreamGroupInputBuilder

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fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter. Read more
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impl Default for CreateStreamGroupInputBuilder

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fn default() -> CreateStreamGroupInputBuilder

Returns the “default value” for a type. Read more
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impl PartialEq for CreateStreamGroupInputBuilder

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fn eq(&self, other: &CreateStreamGroupInputBuilder) -> bool

Tests for self and other values to be equal, and is used by ==.
1.0.0 · Source§

fn ne(&self, other: &Rhs) -> bool

Tests for !=. The default implementation is almost always sufficient, and should not be overridden without very good reason.
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impl StructuralPartialEq for CreateStreamGroupInputBuilder

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Returns self with the quirk() set to [Quirk :: Resetting].

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fn whenever(&self, value: Condition) -> Painted<&T>

Conditionally enable styling based on whether the Condition value applies. Replaces any previous condition.

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Enable styling painted only when both stdout and stderr are TTYs:

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type Error = Infallible

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impl<T, U> TryInto<U> for T
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type Error = <U as TryFrom<T>>::Error

The type returned in the event of a conversion error.
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