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‎VERSION‎

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1.11.712
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1.11.713

‎generated/src/aws-cpp-sdk-gameliftstreams/include/aws/gameliftstreams/GameLiftStreamsClient.h‎

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@@ -203,20 +203,21 @@ class AWS_GAMELIFTSTREAMS_API GameLiftStreamsClient : public Aws::Client::AWSJso
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* configuration of the compute resources that Amazon GameLift Streams will use
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* when streaming, such as the CPU, GPU, and memory. </p> <p> Stream capacity
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* represents the number of concurrent streams that can be active at a time. You
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* set stream capacity per location, per stream group. There are two types of
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* capacity, always-on and on-demand: </p> <ul> <li> <p> <b>Always-on</b>: The
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* streaming capacity that is allocated and ready to handle stream requests without
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* delay. You pay for this capacity whether it's in use or not. Best for quickest
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* time from streaming request to streaming session. Default is 1 (2 for high
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* stream classes) when creating a stream group or adding a location. </p> </li>
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* <li> <p> <b>On-demand</b>: The streaming capacity that Amazon GameLift Streams
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* can allocate in response to stream requests, and then de-allocate when the
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* session has terminated. This offers a cost control measure at the expense of a
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* greater startup time (typically under 5 minutes). Default is 0 when creating a
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* stream group or adding a location. </p> </li> </ul> <p>Values for capacity must
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* be whole number multiples of the tenancy value of the stream group's stream
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* class.</p> <p> To adjust the capacity of any <code>ACTIVE</code> stream group,
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* call <a
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* set stream capacity per location, per stream group. The following capacity
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* settings are available: </p> <ul> <li> <p> <b>Always-on capacity</b>: This
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* setting, if non-zero, indicates minimum streaming capacity which is allocated to
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* you and is never released back to the service. You pay for this base level of
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* capacity at all times, whether used or idle. </p> </li> <li> <p> <b>Maximum
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* capacity</b>: This indicates the maximum capacity that the service can allocate
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* for you. Newly created streams may take a few minutes to start. Capacity is
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* released back to the service when idle. You pay for capacity that is allocated
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* to you until it is released. </p> </li> <li> <p> <b>Target-idle capacity</b>:
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* This indicates idle capacity which the service pre-allocates and holds for you
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* in anticipation of future activity. This helps to insulate your users from
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* capacity-allocation delays. You pay for capacity which is held in this
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* intentional idle state. </p> </li> </ul> <p>Values for capacity must be whole
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* number multiples of the tenancy value of the stream group's stream class.</p>
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* <p> To adjust the capacity of any <code>ACTIVE</code> stream group, call <a
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* href="https://docs.aws.amazon.com/gameliftstreams/latest/apireference/API_UpdateStreamGroup.html">UpdateStreamGroup</a>.
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* </p> <p> If the <code>CreateStreamGroup</code> request is successful, Amazon
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* GameLift Streams assigns a unique ID to the stream group resource and sets the
@@ -982,22 +983,24 @@ class AWS_GAMELIFTSTREAMS_API GameLiftStreamsClient : public Aws::Client::AWSJso
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* capacity of a stream group per location. If you want to change the stream class,
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* create a new stream group. </p> <p> Stream capacity represents the number of
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* concurrent streams that can be active at a time. You set stream capacity per
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* location, per stream group. There are two types of capacity, always-on and
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* on-demand: </p> <ul> <li> <p> <b>Always-on</b>: The streaming capacity that is
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* allocated and ready to handle stream requests without delay. You pay for this
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* capacity whether it's in use or not. Best for quickest time from streaming
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* request to streaming session. Default is 1 (2 for high stream classes) when
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* creating a stream group or adding a location. </p> </li> <li> <p>
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* <b>On-demand</b>: The streaming capacity that Amazon GameLift Streams can
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* allocate in response to stream requests, and then de-allocate when the session
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* has terminated. This offers a cost control measure at the expense of a greater
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* startup time (typically under 5 minutes). Default is 0 when creating a stream
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* group or adding a location. </p> </li> </ul> <p>Values for capacity must be
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* whole number multiples of the tenancy value of the stream group's stream
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* class.</p> <p>To update a stream group, specify the stream group's Amazon
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* Resource Name (ARN) and provide the new values. If the request is successful,
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* Amazon GameLift Streams returns the complete updated metadata for the stream
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* group. Expired stream groups cannot be updated.</p><p><h3>See Also:</h3> <a
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* location, per stream group. The following capacity settings are available: </p>
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* <ul> <li> <p> <b>Always-on capacity</b>: This setting, if non-zero, indicates
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* minimum streaming capacity which is allocated to you and is never released back
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* to the service. You pay for this base level of capacity at all times, whether
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* used or idle. </p> </li> <li> <p> <b>Maximum capacity</b>: This indicates the
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* maximum capacity that the service can allocate for you. Newly created streams
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* may take a few minutes to start. Capacity is released back to the service when
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* idle. You pay for capacity that is allocated to you until it is released. </p>
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* </li> <li> <p> <b>Target-idle capacity</b>: This indicates idle capacity which
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* the service pre-allocates and holds for you in anticipation of future activity.
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* This helps to insulate your users from capacity-allocation delays. You pay for
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* capacity which is held in this intentional idle state. </p> </li> </ul>
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* <p>Values for capacity must be whole number multiples of the tenancy value of
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* the stream group's stream class.</p> <p>To update a stream group, specify the
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* stream group's Amazon Resource Name (ARN) and provide the new values. If the
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* request is successful, Amazon GameLift Streams returns the complete updated
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* metadata for the stream group. Expired stream groups cannot be
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* updated.</p><p><h3>See Also:</h3> <a
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* href="http://docs.aws.amazon.com/goto/WebAPI/gameliftstreams-2018-05-10/UpdateStreamGroup">AWS
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* API Reference</a></p>
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*/

‎generated/src/aws-cpp-sdk-gameliftstreams/include/aws/gameliftstreams/model/CreateStreamGroupRequest.h‎

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@@ -58,43 +58,88 @@ class CreateStreamGroupRequest : public GameLiftStreamsRequest {
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* streaming. Stream class determines the type of computing resources Amazon
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* GameLift Streams uses and impacts the cost of streaming. The following options
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* are available: </p> <p>A stream class can be one of the following:</p> <ul> <li>
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* <p> <b> <code>gen5n_win2022</code> (NVIDIA, ultra)</b> Supports applications
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* with extremely high 3D scene complexity. Runs applications on Microsoft Windows
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* Server 2022 Base and supports DirectX 12. Compatible with Unreal Engine versions
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* up through 5.4, 32 and 64-bit applications, and anti-cheat technology. Uses
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* NVIDIA A10G Tensor GPU.</p> <ul> <li> <p>Reference resolution: 1080p</p> </li>
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* <li> <p>Reference frame rate: 60 fps</p> </li> <li> <p>Workload specifications:
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* 8 vCPUs, 32 GB RAM, 24 GB VRAM</p> </li> <li> <p>Tenancy: Supports 1 concurrent
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* stream session</p> </li> </ul> </li> <li> <p> <b> <code>gen5n_high</code>
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* (NVIDIA, high)</b> Supports applications with moderate to high 3D scene
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* complexity. Uses NVIDIA A10G Tensor GPU.</p> <ul> <li> <p>Reference resolution:
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* 1080p</p> </li> <li> <p>Reference frame rate: 60 fps</p> </li> <li> <p>Workload
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* specifications: 4 vCPUs, 16 GB RAM, 12 GB VRAM</p> </li> <li> <p>Tenancy:
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* Supports up to 2 concurrent stream sessions</p> </li> </ul> </li> <li> <p> <b>
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* <code>gen5n_ultra</code> (NVIDIA, ultra)</b> Supports applications with
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* extremely high 3D scene complexity. Uses dedicated NVIDIA A10G Tensor GPU.</p>
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* <p> <b> <code>gen6n_pro_win2022</code> (NVIDIA, pro)</b> Supports applications
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* with extremely high 3D scene complexity which require maximum resources. Runs
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* applications on Microsoft Windows Server 2022 Base and supports DirectX 12.
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* Compatible with Unreal Engine versions up through 5.6, 32 and 64-bit
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* applications, and anti-cheat technology. Uses NVIDIA L4 Tensor Core GPU.</p>
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* <ul> <li> <p>Reference resolution: 1080p</p> </li> <li> <p>Reference frame rate:
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* 60 fps</p> </li> <li> <p>Workload specifications: 8 vCPUs, 32 GB RAM, 24 GB
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* 60 fps</p> </li> <li> <p>Workload specifications: 16 vCPUs, 64 GB RAM, 24 GB
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* VRAM</p> </li> <li> <p>Tenancy: Supports 1 concurrent stream session</p> </li>
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* </ul> </li> <li> <p> <b> <code>gen4n_win2022</code> (NVIDIA, ultra)</b> Supports
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* applications with extremely high 3D scene complexity. Runs applications on
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* Microsoft Windows Server 2022 Base and supports DirectX 12. Compatible with
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* Unreal Engine versions up through 5.4, 32 and 64-bit applications, and
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* anti-cheat technology. Uses NVIDIA T4 Tensor GPU.</p> <ul> <li> <p>Reference
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* </ul> </li> <li> <p> <b> <code>gen6n_pro</code> (NVIDIA, pro)</b> Supports
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* applications with extremely high 3D scene complexity which require maximum
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* resources. Uses dedicated NVIDIA L4 Tensor Core GPU.</p> <ul> <li> <p>Reference
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* resolution: 1080p</p> </li> <li> <p>Reference frame rate: 60 fps</p> </li> <li>
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* <p>Workload specifications: 8 vCPUs, 32 GB RAM, 16 GB VRAM</p> </li> <li>
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* <p>Workload specifications: 16 vCPUs, 64 GB RAM, 24 GB VRAM</p> </li> <li>
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* <p>Tenancy: Supports 1 concurrent stream session</p> </li> </ul> </li> <li> <p>
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* <b> <code>gen4n_high</code> (NVIDIA, high)</b> Supports applications with
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* moderate to high 3D scene complexity. Uses NVIDIA T4 Tensor GPU.</p> <ul> <li>
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* <b> <code>gen6n_ultra_win2022</code> (NVIDIA, ultra)</b> Supports applications
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* with high 3D scene complexity. Runs applications on Microsoft Windows Server
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* 2022 Base and supports DirectX 12. Compatible with Unreal Engine versions up
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* through 5.6, 32 and 64-bit applications, and anti-cheat technology. Uses NVIDIA
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* L4 Tensor Core GPU.</p> <ul> <li> <p>Reference resolution: 1080p</p> </li> <li>
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* <p>Reference frame rate: 60 fps</p> </li> <li> <p>Workload specifications: 8
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* vCPUs, 32 GB RAM, 24 GB VRAM</p> </li> <li> <p>Tenancy: Supports 1 concurrent
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* stream session</p> </li> </ul> </li> <li> <p> <b> <code>gen6n_ultra</code>
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* (NVIDIA, ultra)</b> Supports applications with high 3D scene complexity. Uses
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* dedicated NVIDIA L4 Tensor Core GPU.</p> <ul> <li> <p>Reference resolution:
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* 1080p</p> </li> <li> <p>Reference frame rate: 60 fps</p> </li> <li> <p>Workload
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* specifications: 8 vCPUs, 32 GB RAM, 24 GB VRAM</p> </li> <li> <p>Tenancy:
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* Supports 1 concurrent stream session</p> </li> </ul> </li> <li> <p> <b>
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* <code>gen6n_high</code> (NVIDIA, high)</b> Supports applications with moderate
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* to high 3D scene complexity. Uses NVIDIA L4 Tensor Core GPU.</p> <ul> <li>
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* <p>Reference resolution: 1080p</p> </li> <li> <p>Reference frame rate: 60
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* fps</p> </li> <li> <p>Workload specifications: 4 vCPUs, 16 GB RAM, 8 GB VRAM</p>
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* </li> <li> <p>Tenancy: Supports up to 2 concurrent stream sessions</p> </li>
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* </ul> </li> <li> <p> <b> <code>gen4n_ultra</code> (NVIDIA, ultra)</b> Supports
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* applications with high 3D scene complexity. Uses dedicated NVIDIA T4 Tensor
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* fps</p> </li> <li> <p>Workload specifications: 4 vCPUs, 16 GB RAM, 12 GB
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* VRAM</p> </li> <li> <p>Tenancy: Supports up to 2 concurrent stream sessions</p>
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* </li> </ul> </li> <li> <p> <b> <code>gen6n_medium</code> (NVIDIA, medium)</b>
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* Supports applications with moderate 3D scene complexity. Uses NVIDIA L4 Tensor
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* Core GPU.</p> <ul> <li> <p>Reference resolution: 1080p</p> </li> <li>
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* <p>Reference frame rate: 60 fps</p> </li> <li> <p>Workload specifications: 2
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* vCPUs, 8 GB RAM, 6 GB VRAM</p> </li> <li> <p>Tenancy: Supports up to 4
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* concurrent stream sessions</p> </li> </ul> </li> <li> <p> <b>
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* <code>gen6n_small</code> (NVIDIA, small)</b> Supports applications with
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* lightweight 3D scene complexity and low CPU usage. Uses NVIDIA L4 Tensor Core
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* GPU.</p> <ul> <li> <p>Reference resolution: 1080p</p> </li> <li> <p>Reference
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* frame rate: 60 fps</p> </li> <li> <p>Workload specifications: 1 vCPUs, 4 GB RAM,
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* 2 GB VRAM</p> </li> <li> <p>Tenancy: Supports up to 12 concurrent stream
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* sessions</p> </li> </ul> </li> <li> <p> <b> <code>gen5n_win2022</code> (NVIDIA,
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* ultra)</b> Supports applications with extremely high 3D scene complexity. Runs
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* applications on Microsoft Windows Server 2022 Base and supports DirectX 12.
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* Compatible with Unreal Engine versions up through 5.6, 32 and 64-bit
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* applications, and anti-cheat technology. Uses NVIDIA A10G Tensor Core GPU.</p>
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* <ul> <li> <p>Reference resolution: 1080p</p> </li> <li> <p>Reference frame rate:
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* 60 fps</p> </li> <li> <p>Workload specifications: 8 vCPUs, 32 GB RAM, 24 GB
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* VRAM</p> </li> <li> <p>Tenancy: Supports 1 concurrent stream session</p> </li>
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* </ul> </li> <li> <p> <b> <code>gen5n_high</code> (NVIDIA, high)</b> Supports
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* applications with moderate to high 3D scene complexity. Uses NVIDIA A10G Tensor
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* Core GPU.</p> <ul> <li> <p>Reference resolution: 1080p</p> </li> <li>
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* <p>Reference frame rate: 60 fps</p> </li> <li> <p>Workload specifications: 4
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* vCPUs, 16 GB RAM, 12 GB VRAM</p> </li> <li> <p>Tenancy: Supports up to 2
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* concurrent stream sessions</p> </li> </ul> </li> <li> <p> <b>
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* <code>gen5n_ultra</code> (NVIDIA, ultra)</b> Supports applications with
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* extremely high 3D scene complexity. Uses dedicated NVIDIA A10G Tensor Core
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* GPU.</p> <ul> <li> <p>Reference resolution: 1080p</p> </li> <li> <p>Reference
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* frame rate: 60 fps</p> </li> <li> <p>Workload specifications: 8 vCPUs, 32 GB
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* RAM, 16 GB VRAM</p> </li> <li> <p>Tenancy: Supports 1 concurrent stream
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* session</p> </li> </ul> </li> </ul>
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* RAM, 24 GB VRAM</p> </li> <li> <p>Tenancy: Supports 1 concurrent stream
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* session</p> </li> </ul> </li> <li> <p> <b> <code>gen4n_win2022</code> (NVIDIA,
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* ultra)</b> Supports applications with extremely high 3D scene complexity. Runs
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* applications on Microsoft Windows Server 2022 Base and supports DirectX 12.
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* Compatible with Unreal Engine versions up through 5.6, 32 and 64-bit
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* applications, and anti-cheat technology. Uses NVIDIA T4 Tensor Core GPU.</p>
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* <ul> <li> <p>Reference resolution: 1080p</p> </li> <li> <p>Reference frame rate:
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* 60 fps</p> </li> <li> <p>Workload specifications: 8 vCPUs, 32 GB RAM, 16 GB
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* VRAM</p> </li> <li> <p>Tenancy: Supports 1 concurrent stream session</p> </li>
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* </ul> </li> <li> <p> <b> <code>gen4n_high</code> (NVIDIA, high)</b> Supports
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* applications with moderate to high 3D scene complexity. Uses NVIDIA T4 Tensor
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* Core GPU.</p> <ul> <li> <p>Reference resolution: 1080p</p> </li> <li>
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* <p>Reference frame rate: 60 fps</p> </li> <li> <p>Workload specifications: 4
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* vCPUs, 16 GB RAM, 8 GB VRAM</p> </li> <li> <p>Tenancy: Supports up to 2
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* concurrent stream sessions</p> </li> </ul> </li> <li> <p> <b>
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* <code>gen4n_ultra</code> (NVIDIA, ultra)</b> Supports applications with high 3D
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* scene complexity. Uses dedicated NVIDIA T4 Tensor Core GPU.</p> <ul> <li>
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* <p>Reference resolution: 1080p</p> </li> <li> <p>Reference frame rate: 60
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* fps</p> </li> <li> <p>Workload specifications: 8 vCPUs, 32 GB RAM, 16 GB
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* VRAM</p> </li> <li> <p>Tenancy: Supports 1 concurrent stream session</p> </li>
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* </ul> </li> </ul>
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*/
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inline StreamClass GetStreamClass() const { return m_streamClass; }
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inline bool StreamClassHasBeenSet() const { return m_streamClassHasBeenSet; }

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