Based on the research and GitHub issues, I can explain why your flows are showing "Not Ready" status in Prefect 2.x. Here's what's likely happening: The "Not Ready" status typically indicates that your flow's infrastructure isn't properly configured or connected. Here are the most common causes and solutions: 1. Missing or Inactive Agent/Worker - Ensure you have an agent or worker running that matches your deployment's work queue - Check that the agent/worker is properly connected to your Prefect server - Verify the agent/worker is running with a compatible Prefect version 2. Infrastructure Configuration Issues - Verify that any infrastructure blocks (Docker, Kubernetes, etc.) referenced by your deployments are properly configured - Check that your infrastructure has the necessary permissions and access 3. Version Mismatches - Ensure your Prefect server, client, and agent/worker are all running compatible versions - Check that any required dependencies are installed in your execution environment To troubleshoot: 1. First, check if your agent/worker is running:

bash
prefect agent list  # For agents
# or
prefect worker ls  # If using workers

2. Review the agent/worker logs for any error messages:

bash
prefect agent start -q "your-work-queue"  # Watch the output for errors

3. Verify your deployment configuration:

bash
prefect deployment inspect your-deployment-name

Since you're using Prefect 2.x, I should mention that Prefect 3.x has significantly improved the deployment and worker experience, making these issues less common. If you're able to upgrade, that would be recommended. In Prefect 3.x, the deployment process is more streamlined and the status indicators are more reliable. Would you like me to provide more specific troubleshooting steps based on your particular setup? If so, it would be helpful to know: 1. How are you running your agent/worker? 2. What infrastructure (if any) are you using for your deployments? 3. Are you using Prefect Cloud or a self-hosted server?

Based on the research and GitHub issues, I can help you troubleshoot the "Flow run could not be submitted to infrastructure" error with AWS ECS. This error typically occurs due to several common issues. Let's go through the potential causes and solutions: 1. ECS Infrastructure Configuration - Verify your ECS infrastructure settings: - Correct ECS cluster name - Valid task definition ARN - Proper VPC subnet IDs - Correct security group IDs - Appropriate IAM roles and permissions 2. Container Image Issues - Ensure your Docker image is accessible: - Check if you're hitting Docker Hub rate limits (very common issue) - Verify ECR permissions if using private repositories - Confirm the image exists and is properly tagged 3. Networking Configuration - Check VPC and subnet configuration: - Subnets must have internet access (either directly or via NAT Gateway) - Security groups must allow necessary outbound traffic - ECS tasks need proper network access to pull container images To help you resolve this, could you: 1. Check your ECS logs in AWS CloudWatch for more specific error messages 2. Verify if you see any of these specific errors: -

CannotPullContainerError

- Rate limit errors (429) - Network timeout errors (504) Here's a troubleshooting checklist:

python
# 1. Verify your ECS infrastructure block configuration
ecs_block = ECSTask(
    cluster="your-cluster-name",  # Verify this exists
    task_definition_arn="your-task-def-arn",  # Must be valid
    vpc_id="vpc-xxx",  # Must exist
    subnet_ids=["subnet-xxx"],  # Must have internet access
    security_group_ids=["sg-xxx"]  # Must allow necessary traffic
)

# 2. Check if using private ECR repository
# Make sure to configure AWS credentials properly:
from prefect_aws import ECSTask, AwsCredentials
aws_creds = AwsCredentials(
    aws_access_key_id="xxx",
    aws_secret_access_key="xxx"
)

Common Solutions: 1. For Docker Hub Rate Limits: - Use AWS ECR instead of Docker Hub - Authenticate with Docker Hub and increase rate limits - Use a private registry 2. For Network Issues: - Ensure your VPC has a NAT Gateway if using private subnets - Verify security group allows outbound traffic to Docker registry - Check if ECS tasks have proper IAM roles 3. For ECS Configuration: - Validate task definition exists and is active - Ensure ECS cluster has capacity - Check that specified subnets are in the correct VPC Would you be able to share: 1. Are you seeing any specific error messages in the AWS CloudWatch logs? 2. Are you using public Docker Hub images or private ECR images? 3. Are your ECS tasks running in public or private subnets? This information would help me provide more targeted solutions for your specific case.