Refer to the Exhibit Practice Questions

{
  "TrainingJobName": "my-training-job-1",
  "TrainingJobStatus": "Failed",
  "FailureReason": "AlgorithmError: OutOfMemoryError: CUDA out of memory. Tried to allocate 4.00 GiB (GPU 0; 8.00 GiB total capacity; 3.95 GiB already allocated; 2.50 GiB free; 4.00 GiB reserved in total by PyTorch)"
}

{
  "Version": "2012-10-17",
  "Statement": [
    {
      "Effect": "Allow",
      "Action": "s3:GetObject",
      "Resource": "arn:aws:s3:::my-training-data/*"
    }
  ]
}

[CloudTrail Log Entry]
{
    "eventSource": "sagemaker.amazonaws.com",
    "eventName": "CreateTrainingJob",
    "userIdentity": {
        "arn": "arn:aws:iam::123456789012:user/john.doe"
    },
    "requestParameters": {
        "trainingJobName": "my-training-job",
        "hyperParameters": {
            "batch_size": "32",
            "epochs": "10"
        },
        "inputDataConfig": [
            {
                "channelName": "training",
                "dataSource": {
                    "s3DataSource": {
                        "s3Uri": "s3://my-bucket/train/data.csv"
                    }
                }
            }
        ]
    },
    "responseElements": null,
    "sourceIPAddress": "203.0.113.5",
    "userAgent": "console.amazonaws.com"
}

{
  "EndpointConfigName": "my-fm-endpoint-config",
  "ProductionVariants": [
    {
      "VariantName": "variant1",
      "ModelName": "my-fm-model",
      "InitialInstanceCount": 1,
      "InstanceType": "ml.g5.xlarge",
      "InitialVariantWeight": 1.0
    }
  ]
}

Resources:
  BedrockAgent:
    Type: AWS::Bedrock::Agent
    Properties:
      AgentName: MyAgent
      FoundationModel: anthropic.claude-v2
      Instruction: "You are a helpful assistant."
      KnowledgeBases:
        - KnowledgeBaseId: !Ref MyKnowledgeBase
      PromptOverrideConfiguration: null
  MyKnowledgeBase:
    Type: AWS::Bedrock::KnowledgeBase
    Properties:
      Name: MyKB
      RoleArn: !GetAtt KBRole.Arn
      KnowledgeBaseConfiguration:
        Type: VECTOR
        VectorKnowledgeBaseConfiguration:
          EmbeddingModelArn: !Sub arn:aws:bedrock:${AWS::Region}::foundation-model/amazon.titan-embed-text-v1
      StorageConfiguration:
        Type: OPENSEARCH_SERVERLESS
        OpensearchServerlessConfiguration:
          CollectionArn: !GetAtt MyCollection.Arn
          VectorIndexName: my-index
  MyCollection:
    Type: AWS::OpenSearchServerless::Collection
    Properties:
      Name: my-collection
      Type: VECTORSEARCH

Refer to the exhibit.
{
  "completion": "The capital of France is Paris. The capital of Germany is Berlin. The capital of",
  "stop_reason": "max_tokens",
  "usage": {
    "input_tokens": 10,
    "output_tokens": 30
  }
}

Refer to the exhibit.
{
  "message": "You do not have access to the requested model. Please request access via the AWS Management Console."
}

Refer to the exhibit.

```yaml
Resources:
  MyNotebookInstance:
    Type: AWS::SageMaker::NotebookInstance
    Properties:
      InstanceType: ml.t2.medium
      VolumeSizeInGB: 5
      DirectInternetAccess: Enabled
```

Excerpt from an AWS CloudFormation template.

Refer to the exhibit.

```json
{
  "TrainingJobStatus": "Failed",
  "FailureReason": "ClientError: ValidationException: The instance type ml.p3.2xlarge is not supported in the requested region (us-east-1)."
}
```

This is the output of `aws sagemaker describe-training-job --training-job-name my-training-job`.

{
  "Version": "2012-10-17",
  "Statement": [
    {
      "Effect": "Allow",
      "Action": "sagemaker:InvokeEndpoint",
      "Resource": "arn:aws:sagemaker:us-east-1:123456789012:endpoint/my-model-endpoint",
      "Condition": {
        "StringEquals": {
          "aws:SourceVpce": "vpce-12345678"
        }
      }
    }
  ]
}

Refer to the exhibit.

SageMaker Training Job Configuration:
{
  "AlgorithmSpecification": {
    "TrainingImage": "763104351884.dkr.ecr.us-west-2.amazonaws.com/huggingface-pytorch-training:1.13.1-transformers4.26.0-gpu-py39-cu117-ubuntu20.04",
    "TrainingInputMode": "File"
  },
  "HyperParameters": {
    "epochs": "3",
    "per_device_train_batch_size": "8",
    "learning_rate": "2e-5",
    "max_seq_length": "512"
  },
  "InputDataConfig": [
    {
      "ChannelName": "train",
      "DataSource": {
        "S3DataSource": {
          "S3DataType": "S3Prefix",
          "S3Uri": "s3://my-bucket/train/"
        }
      },
      "ContentType": "text/csv"
    }
  ],
  "OutputDataConfig": {
    "S3OutputPath": "s3://my-bucket/output/"
  },
  "ResourceConfig": {
    "InstanceType": "ml.p3.2xlarge",
    "InstanceCount": 1,
    "VolumeSizeInGB": 50
  },
  "RoleArn": "arn:aws:iam::123456789012:role/SageMakerRole",
  "StoppingCondition": {
    "MaxRuntimeInSeconds": 86400
  }
}

Refer to the exhibit.

CloudWatch Log message:
{
  "timestamp": "2025-02-12T10:15:30.000Z",
  "message": "ThrottlingException: Rate exceeded for modelId anthropic.claude-v2. RequestId: abc123",
  "logGroup": "/aws/bedrock/modelinvocations",
  "logStream": "modelinvocations/us-west-2/123456789012"
}

Refer to the exhibit.

{
  "modelId": "anthropic.claude-v2",
  "contentType": "application/json",
  "accept": "application/json",
  "body": {
    "prompt": "Human: Summarize the following text in 50 words. Text: AWS is a cloud platform. Response:",
    "max_tokens_to_sample": 200,
    "temperature": 1.0,
    "stop_sequences": ["\n\nHuman:"]
  }
}

AWS CloudFormation template snippet:
Resources:
  BedrockKnowledgeBase:
    Type: AWS::Bedrock::KnowledgeBase
    Properties:
      Name: support-kb
      RoleArn: arn:aws:iam::123456789012:role/BedrockKnowledgeBaseRole
      KnowledgeBaseConfiguration:
        Type: VECTOR
        VectorKnowledgeBaseConfiguration:
          EmbeddingModelArn: arn:aws:bedrock:us-east-1::foundation-model/amazon.titan-embed-text-v1
      StorageConfiguration:
        Type: OPENSEARCH_SERVERLESS
        OpensearchServerlessConfiguration:
          CollectionArn: arn:aws:aoss:us-east-1:123456789012:collection/abc123
          FieldMapping:
            MetadataField: metadata
            TextField: text
  DataSource:
    Type: AWS::Bedrock::DataSource
    Properties:
      KnowledgeBaseId: !Ref BedrockKnowledgeBase
      Name: s3-source
      DataSourceConfiguration:
        Type: S3
        S3Configuration:
          BucketArn: arn:aws:s3:::my-docs-bucket
      VectorIngestionConfiguration:
        ChunkingConfiguration:
          ChunkingStrategy: FIXED_SIZE