Enable opt-in for high frequency GPU metrics

[yanhaoluo666]

Note

This PR is dependent on PR370 and PR371, will update go.mod file and rebase once they are merged.

Description of the issue

Currently, GPU metrics are collected at a one-minute interval, which works well for most machine learning (ML) training jobs. However, for ML inference, where execution times can be as short as 2-3 seconds, this interval is insufficient.

Description of changes

This PR provides customer gpu metrics collection interval customization by introducing a new configuration field. Changes are listed below:

1. Introduce a new field - accelerated_compute_gpu_metrics_collection_interval to let customer denote metrics collection interval, default value is 60.
2. If customer sets it to a value less than 60, belows changes will take effect:
   2.1 the batch period will turn from 5s to 60s for batch processor;
   2.2 groupbyattrs processor will be added to awscontainerinsights pipeline to compact metrics from the same resource;
   2.3 gpu sampling frequency would use configured value in awscontainerinsights receiver(PR 370);
   2.4 all gpu metrics will be compressed and converted to cloudwatch histogram type in emf exporter(PR 371);

We have also tried out to provide keys for groupbyattrs processor to only compact gpu metrics, but there is hardly improvement for cpu and memory.

License

By submitting this pull request, I confirm that you can use, modify, copy, and redistribute this contribution, under the terms of your choice.

Tests

1. deploy this PR along with PR 370 and PR 371 to personal eks cluster
2. Spinned up a ML job then checked cloudwatch logs and metrics, confirmed
   2.1 gpu metrics were sampled every second, i.e. there were 60 datapoints in each PutLogEvent call;
   2.2 gpu metrics were in cloudwatch histogram format.

• logs sample

{
    "CloudWatchMetrics": [
        {
            "Namespace": "ContainerInsights",
            "Dimensions": [
                [
                    "ClusterName"
                ],
                [
                    "ClusterName",
                    "ContainerName",
                    "Namespace",
                    "PodName"
                ],
                [
                    "ClusterName",
                    "ContainerName",
                    "FullPodName",
                    "Namespace",
                    "PodName"
                ],
                [
                    "ClusterName",
                    "ContainerName",
                    "FullPodName",
                    "GpuDevice",
                    "Namespace",
                    "PodName"
                ]
            ],
            "Metrics": [
                {
                    "Name": "container_gpu_temperature",
                    "Unit": "None",
                    "StorageResolution": 60
                },
                {
                    "Name": "container_gpu_power_draw",
                    "Unit": "None",
                    "StorageResolution": 60
                },
                {
                    "Name": "container_gpu_utilization",
                    "Unit": "Percent",
                    "StorageResolution": 60
                },
                {
                    "Name": "container_gpu_memory_utilization",
                    "Unit": "Percent",
                    "StorageResolution": 60
                },
                {
                    "Name": "container_gpu_memory_used",
                    "Unit": "Bytes",
                    "StorageResolution": 60
                },
                {
                    "Name": "container_gpu_memory_total",
                    "Unit": "Bytes",
                    "StorageResolution": 60
                }
            ]
        }
    ],
    "ClusterName": "cpipeline",
    "ContainerName": "main",
    "FullPodName": "gpu-burn-577f5d7468-4j54s",
    "GpuDevice": "nvidia0",
    "InstanceId": "i-0f01fff8faa360227",
    "InstanceType": "g4dn.xlarge",
    "Namespace": "kube-system",
    "NodeName": "ip-192-168-6-219.ec2.internal",
    "PodName": "gpu-burn",
    "Sources": [
        "dcgm",
        "pod",
        "calculated"
    ],
    "Timestamp": "1760375344178",
    "Type": "ContainerGPU",
    "UUID": "GPU-60efa417-4d26-c4ba-9e62-66249559952d",
    "Version": "0",
    "kubernetes": {
        "container_name": "main",
        "containerd": {
            "container_id": "5bfc51b6805d8bdc96e34f262394ae2702cc5d55ad186c660acbef414aa86223"
        },
        "host": "ip-192-168-6-219.ec2.internal",
        "labels": {
            "app": "gpu-burn",
            "pod-template-hash": "577f5d7468"
        },
        "pod_name": "gpu-burn-577f5d7468-4j54s",
        "pod_owners": [
            {
                "owner_kind": "Deployment",
                "owner_name": "gpu-burn"
            }
        ]
    },
    "container_gpu_memory_total": {
        "Values": [
            16006027360
        ],
        "Counts": [
            60
        ],
        "Max": 16006027360,
        "Min": 16006027360,
        "Count": 60,
        "Sum": 982473768960
    },
    "container_gpu_memory_used": {
        "Values": [
            0,
            176060768,
            245366784,
            14254342144,
            253755392,
            111149056,
            207608048,
            251658240
        ],
        "Counts": [
            8,
            1,
            1,
            46,
            1,
            1,
            1,
            1
        ],
        "Max": 14254342144,
        "Min": 0,
        "Count": 60,
        "Sum": 656945446912
    },
    "container_gpu_memory_utilization": {
        "Values": [
            1.185,
            0.9862,
            90.0607,
            1.609,
            0.6948,
            1.3572000000000002,
            1.5559999999999998,
            0
        ],
        "Counts": [
            1,
            1,
            46,
            1,
            1,
            1,
            1,
            8
        ],
        "Max": 90.0607,
        "Min": 0,
        "Count": 60,
        "Sum": 4150.226400000004
    },
    "container_gpu_power_draw": {
        "Values": [
            32.662,
            70.563,
            69.099,
            32.760,
            69.49,
            33.549,
            69.978,
            69.197,
            33.844,
            63.907,
            65.919,
            70.368,
            70.27,
            38.921,
            69.435,
            68.360,
            69.88,
            70.173,
            68.318,
            70.119,
            67.872,
            70.466,
            65.626,
            67.97,
            69.826,
            32.859,
            33.352,
            70.660,
            70.075,
            33.253,
            69.294,
            69.587,
            68.904,
            38.429,
            82.459,
            69.685,
            69.392,
            68.849,
            69.782,
            68.458
        ],
        "Counts": [
            2,
            2,
            1,
            1,
            1,
            1,
            4,
            1,
            1,
            1,
            1,
            1,
            3,
            1,
            1,
            1,
            3,
            1,
            1,
            1,
            1,
            1,
            1,
            1,
            1,
            4,
            1,
            3,
            2,
            2,
            1,
            1,
            1,
            1,
            1,
            4,
            1,
            1,
            2,
            1
        ],
        "Max": 82.459,
        "Min": 32.662,
        "Count": 60,
        "Sum": 3748.8209999999995
    },
    "container_gpu_temperature": {
        "Values": [
            42,
            43,
            44
        ],
        "Counts": [
            12,
            32,
            16
        ],
        "Max": 44,
        "Min": 42,
        "Count": 60,
        "Sum": 2628
    },
    "container_gpu_utilization": {
        "Values": [
            96,
            6,
            8,
            14,
            58,
            0,
            64,
            9,
            89,
            7,
            100
        ],
        "Counts": [
            1,
            1,
            1,
            1,
            1,
            6,
            1,
            1,
            1,
            2,
            44
        ],
        "Max": 100,
        "Min": 0,
        "Count": 60,
        "Sum": 4858
    }
}

• metrics graph

Requirements

Before commiting your code, please do the following steps.

1. Run make fmt and make fmt-sh. - done
2. Run make lint. - done

---

Integration Tests

To run integration tests against this PR, add the ready for testing label.

[yanhaoluo666]

Updated from Udp to UDP since make lint failed: https://github.com/aws/amazon-cloudwatch-agent/actions/runs/18476654488/job/52642571583

[spanaik]

There are more metrics here that needs to be added.

[yanhaoluo666]

added with reference to https://github.com/aws/amazon-cloudwatch-agent/blob/main/translator/translate/otel/exporter/awsemf/kubernetes.go#L505

[spanaik]

Nice

[spanaik]

[nit] micro-optimization: Swap the EnhancedCI check before the AcceleratedCompute Check.

[movence]

I'm uncelar what this really does. can you elaborate why?

[yanhaoluo666]

Currently the batch period of batchprocessor is 5s and it would be changed to 60s if high freq gpu metrics is enabled. That's all about it, common.LogsKey and common. MetricsKey denotes 5s and 60s respectively.