Using Bedrock or Vertex
Integrate with AWS Bedrock or GCP Vertex AI for enterprise LLM deployment.
AWS Bedrock Setup
bedrock:
region: "us-east-1"
credentials:
type: "service_account"
role_arn: "arn:aws:iam::123456789:role/agentic-bedrock"
model_id: "anthropic.claude-4-opus"
endpoint_config:
max_retries: 3
timeout: 300
IAM Configuration
{
"Version": "2012-10-17",
"Statement": [{
"Effect": "Allow",
"Action": [
"bedrock:InvokeModel",
"bedrock:InvokeModelWithResponseStream"
],
"Resource": "arn:aws:bedrock:*:*:model/*"
}]
}
GCP Vertex AI Setup
vertex:
project_id: "my-gcp-project"
location: "us-central1"
credentials:
type: "service_account"
key_file: "/path/to/service-account.json"
model: "gemini-1.5-pro"
endpoint_config:
max_retries: 3
timeout: 300
Service Account Permissions
aiplatform.endpoints.predict
aiplatform.models.get
Benefits of Managed Services
Security: VPC endpoints, IAM integration
Compliance: SOC2, HIPAA, PCI options
Scalability: Auto-scaling capabilities
Monitoring: Native cloud observability
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