@Marvin How do I configure AWS Cloudwatch settings in my deployments?

To configure AWS Cloudwatch settings in your deployments, you can follow the guidelines and validation checks provided by the Prefect AWS integration. Here's a summary of key points extracted from the Prefect AWS documentation: 1. Configure Cloudwatch Logs: - To stream output, CloudWatch logs must be configured. - The

configure_cloudwatch_logs

setting should align with

stream_output

. - If

configure_cloudwatch_logs

is not explicitly provided, it defaults to the value of

stream_output

.

python
    @root_validator(pre=True)
    def set_default_configure_cloudwatch_logs(cls, values: dict) -> dict:
        """
        Streaming output generally requires CloudWatch logs to be configured.
        To avoid entangled arguments in the simple case, `configure_cloudwatch_logs`
        defaults to matching the value of `stream_output`.
        """
        configure_cloudwatch_logs = values.get("configure_cloudwatch_logs")
        if configure_cloudwatch_logs is None:
            values["configure_cloudwatch_logs"] = values.get("stream_output")
        return values

2. Execution Role ARN Requirement: - When configuring CloudWatch logs, you must provide an

execution_role_arn

. - If the ARN is not provided directly or via task definition, an error will be raised.

python
    @root_validator
    def configure_cloudwatch_logs_requires_execution_role_arn(cls, values: dict) -> dict:
        """
        Enforces that an execution role arn is provided (or could be provided by a
        runtime task definition) when configuring logging.
        """
        if (
            values.get("configure_cloudwatch_logs")
            and not values.get("execution_role_arn")
            and not values.get("task_definition_arn")
            and not (values.get("task_definition") or {}).get("executionRoleArn")
        ):
            raise ValueError(
                "An `execution_role_arn` must be provided to use "
                "`configure_cloudwatch_logs` or `stream_logs`."
            )
        return values

For a thorough implementation, you should review the full documentation for the Prefect AWS integration. Here are the relevant links: - ECS Task Configuration - ECS Worker Configuration Should you encounter issues such as random flow run failures or specific error messages, checking Prefect's GitHub issues might also be informative. Here's an instance of a related issue: GitHub Issue #8080. I hope this helps. If you'd like more details or examples, feel free to ask!

@Marvin do you have an example of a AWS cloudwatch configuration?

It seems the code example provided doesn't specifically cover AWS Cloudwatch configuration. However, here is an illustrative example based on the general guidelines for AWS Cloudwatch settings in Prefect deployments:

python
from prefect import flow
from prefect_aws.ecs import ECSTask, ECSAgent, create_ecs_task_definition

@flow(log_prints=True)
def my_workflow():
    # Define ECS task with Cloudwatch log configuration
    task_definition = create_ecs_task_definition(
        family="my-task-family",
        container_name="my-container",
        image="my-docker-image",
        configure_cloudwatch_logs=True,  # Ensure Cloudwatch logs are configured
        execution_role_arn="arn:aws:iam::123456789012:role/ecsTaskExecutionRole"  # Replace with your execution role ARN
    )

    # Create an ECS task
    ecs_task = ECSTask(
        task_definition_arn=task_definition["taskDefinitionArn"],
        cluster="my-cluster",
        launch_type="FARGATE"
    )

    # Run the ECS task
    ecs_task.run()

    print("Running workflow with ECS task and Cloudwatch logging.")

if __name__ == "__main__":
    my_workflow()

### Explanation: 1. ECS Task Definition: - Configure the ECS task definition, ensuring Cloudwatch logs are set up with

configure_cloudwatch_logs=True

. - Provide the required

execution_role_arn

. 2. ECS Task: - Create and run an ECS task using the task definition with Cloudwatch logging enabled. You can find more details and examples in the Prefect AWS documentation and ECS Worker documentation. If you need more details or assistance, feel free to ask!

@Marvin can you share an example from a prefect.yaml file?

Here is an example of how to configure AWS Cloudwatch settings within a

prefect.yaml

file for a deployment:

yaml
# prefect.yaml

version: 2

deployments:
  - name: my-ecs-deployment
    flow_name: my_workflow
    infra_overrides:
      configure_cloudwatch_logs: true
      execution_role_arn: "arn:aws:iam::123456789012:role/ecsTaskExecutionRole"  # Replace with your execution role ARN
      cloudwatch_logs_options:
        awslogs-group: "my-log-group"
        awslogs-stream-prefix: "my-log-stream"
        awslogs-region: "us-west-2" # Replace with your region
    infrastructure:
      type: prefect_aws.ecs.ECS
      env:
        PREFECT_LOGGING_LEVEL: INFO

### Explanation: 1. Version: - This indicates the version of the Prefect deployment specification. 2. Deployments: - Includes a list of deployments (in this case, just one named

my-ecs-deployment

). 3. Flow Name: - The flow associated with this deployment is

my_workflow

. 4. Infrastructure Overrides: - `configure_cloudwatch_logs`: Set to

true

to ensure Cloudwatch logs are configured. - `execution_role_arn`: Provide the ARN of the IAM role with appropriate permissions. - `cloudwatch_logs_options`: Include additional Cloudwatch configuration options such as log group, prefix, and region. 5. Infrastructure: - Specifies the infrastructure type being used (

prefect_aws.ecs.ECS

). - Sets up environment variables, with

PREFECT_LOGGING_LEVEL

set to

INFO

. ### Links: - AWS Cloudwatch Logs Configuration Documentation ### References: - Prefect AWS ECS Documentation - Prefect AWS ECS Worker Documentation Feel free to modify the configuration based on your specific needs. If you have additional questions or need further assistance, let me know!

@Marvin what is the

infra_overrides

tag in prefect.yaml file?

The

infra_overrides

tag in a

prefect.yaml

file is used to provide specific overrides or customizations for the infrastructure on which the deployment will run. It allows you to specify infrastructure-related settings that can change how the underlying infrastructure behaves without altering the core definition of the infrastructure block. Here is a description and an example to illustrate: ### Description: - Purpose: The

infra_overrides

tag is used to apply specific settings that modify or extend the infrastructure configuration. This provides the flexibility to fine-tune behaviors such as environment variables, resource allocations, and additional parameters for different deployment scenarios. - Usage: It is generally used to configure settings like CPU, memory, environment variables, and other infrastructure-specific parameters. ### Example in `prefect.yaml`:

yaml
# prefect.yaml

version: 2

deployments:
  - name: my-ecs-deployment
    flow_name: my_workflow
    infra_overrides:
      configure_cloudwatch_logs: true
      execution_role_arn: "arn:aws:iam::123456789012:role/ecsTaskExecutionRole"  # Replace with your execution role ARN
      cloudwatch_logs_options:
        awslogs-group: "my-log-group"
        awslogs-stream-prefix: "my-log-stream"
        awslogs-region: "us-west-2" # Replace with your region
    infrastructure:
      type: prefect_aws.ecs.ECS
      env:
        PREFECT_LOGGING_LEVEL: INFO

### Key Elements: - configure_cloudwatch_logs: Enables Cloudwatch logs for the ECS task. - execution_role_arn: The ARN of the IAM role with necessary permissions. - cloudwatch_logs_options: Additional Cloudwatch configuration options. - env: Specifies environment variables (like

PREFECT_LOGGING_LEVEL

set to

INFO

). ### More Details: Referring to the Prefect documentation, here is an excerpt explaining how

infra_overrides

works with KubernetesJob infrastructure:

markdown
overrides and customizations
When creating deployments using KubernetesJob infrastructure, the infra_overrides parameter expects a dictionary. For a KubernetesJob, the customizations parameter expects a list. Containers expect a list of objects, even if there is only one. For any patches applying to the container, the path value should be a list, for example: /spec/templates/spec/containers/0/resources
A Kubernetes-Job infrastructure block defined in Python:

customizations = [
{
  "op": "add",
  "path": "/spec/template/spec/containers/0/resources",
  "value": {
    "requests": {
      "cpu": "2000m",
      "memory": "4gi"
    },
    "limits": {
      "cpu": "4000m",
      "memory": "8Gi",
      "<http://nvidia.com/gpu|nvidia.com/gpu>": "1"
    }
  }
}
]
k8s_job = KubernetesJob(
  namespace=namespace,
  image=image_name,
  image_pull_policy=KubernetesImagePullPolicy.ALWAYS,
  finished_job_ttl=300,
  job_watch_timeout_seconds=600,
  pod_watch_timeout_seconds=600,
  service_account_name="prefect-server",
  customizations=customizations,
)
k8s_job.save("devk8s")

A Deployment with infra-overrides defined in Python:
infra_overrides={
  "customizations": [
    {
      "op": "add",
      "path": "/spec/template/spec/containers/0/resources",
      "value": {
        "requests": {
          "cpu": "2000m",
          "memory": "4gi"
        }
      }
    }
  ]
}

For more detailed information, you can refer to the sources: - Prefect AWS ECS Documentation - Prefect Kubernetes Customizations This will give you a deeper understanding of how to leverage

infra_overrides

effectively in your Prefect deployments.

infra_overrides

has been superseded by

job_variables

- marvin was just using some old lingo there

Ahh that makes, I was wondering why I couldn’t find that tag anywhere

oh also yeah

KubernetesJob

falls into the same bin, deprecated but still in our docs gotta bias marvin away from these things at some point soon here are some likely relevant resources: • docs on job variable overrides • some working examples of these things