@Marvin I run a process worker within a docker container in AWS ECS. This worker is thus able to poll an ECS work-pool and run workflows "locally" in its container. This container has all the flow code locally, so it does not need to download flow code before running it. However, right before this process worker executes flow code, I notice a step 'Downloading flow code from storage at <local_path>' which takes 18s to complete. This is a bummer, since I want this process worker to start running flow code as fast as possible. Any idea why this "code download" happens in the first place?

Let's try to solve this little mystery of why your Prefect worker thinks it needs to download flow code even though it's all sitting right there, cozy in the container from the get-go. To tackle this, I need to confirm the Prefect version you're using and delve into the documentation and issues that might hold the key to this quirk in both Prefect 2.x and 3.x. Give me a moment while I consult the appropriate sources for you. From the documentation I found, here's what might be happening with your process worker in AWS ECS: Firstly, in both Prefect 2.x and 3.x, the orchestration involves workers polling work pools for new runs. These workers retrieve scheduled runs and execute them, making decisions based on deployment configurations. In your setup, even though you have the flow code locally in your container, the Prefect worker might still be checking the metadata about the deployment. This could involve a step where it verifies the stored flow code in the configured storage (even though it's not actually downloading it) to ensure consistency. The "Downloading flow code from storage" message can be misleading if the system is merely verifying versus downloading. Here are some considerations and steps you might try to mitigate this: 1. Storage Configuration: Ensure that your deployment configuration explicitly sets the storage location to match the local path or configure the worker to avoid network-dependent checks. 2. Direct Invocation: Check if there's an option to deploy or invoke the workflow more directly when the code is present inside the container through ECS configurations. 3. Polling Configuration: Ensure that the Prefect worker and its ECS configuration are tuned to minimize any overhead related to fetching or caching decisions. You can read more about the AWS ECS guides for Prefect in both Prefect 2.x and 3.x here: - Prefect 2.x ECS Guide - Prefect 3.x ECS Guide It’s a bit like asking a librarian where the books are, only for the librarian to fetch the book from the exact shelf you were staring at. Efficiency can be elusive sometimes. Let me know if you have more questions or need further assistance!

@Marvin When you mention storage configuration, you suggest "configur[ing] the worker to avoid network-dependent checks". How can I achieve this?

To configure your Prefect worker to reduce or avoid network-dependent checks, you can explore a few options based on the Prefect 2.x and 3.x documentation: 1. Local Execution Configuration: If you can specify in your deployment environment that the worker should use the local file system directly without checking remote storage, that would be the most direct approach. This would typically involve setting the storage configuration to local paths explicitly if your infrastructure block supports it. 2. Custom Worker Configuration: Check out the worker configurations. You can define workers that directly support local execution environments. If your worker type supports a local infrastructure setup, it could bypass any unnecessary remote checks. In Prefect 3.x, (as detailed in this guide), you can adjust polling and execution settings to optimize how workers interact with deployments. 3. Direct Work Queue Assignment: Assign workload directly to work queues that intend to run locally. Prefect workers retrieve from work queues and executing runs according to the assignment type (local, cloud, etc.). The configuration might need specific declarations within your deployment definition for Prefect 2.x as mentioned here. Implementing one or more of these measures could help fine-tune your setup to ensure the flows run as soon as possible without redundant checks. Just a reminder that technology sometimes takes roundabout routes – a bit like achieving a straight line by drawing a triangle first. If you have more questions, I'm here to help!

@Marvin Where and how can I configure my worker or deployment specifically to achieve what you mention "If you can specify in your deployment environment that the worker should use the local file system directly without checking remote storage, that would be the most direct approach. This would typically involve setting the storage configuration to local paths explicitly if your infrastructure block supports it."

To configure your Prefect deployment to use the local file system directly and avoid checking remote storage, you can follow these steps based on the documentation for both Prefect 2.x and 3.x: 1. Prefect 2.x - Local Storage Configuration: - Use the default local storage when building your deployment. When you call

prefect deployment build

without specifying a

--storage-block

flag, it defaults to using a

LocalFileSystem

block. This block will use your present working directory as the base path. This means the flow code will be pulled from the local file system where the worker is running. - You can verify and adjust the settings in the

deployment.yaml

file that Prefect creates upon building the deployment. This file contains storage settings and ensuring it points to a local path confirms the avoidance of unnecessary remote checks. 2. Prefect 3.x - Prefect YAML Configuration: - The deployment specifics are usually set in a

prefect.yaml

file which might be in the root of your project. This can detail where and how storage is configured for your deployment. - You can specify local flow code storage through the Process work pool infrastructure. Within the infrastructure config, opting for local storage ensures that the worker will use the filesystem directly without needing remote access. - The configuration is generally placed in the

store-flow-code

section or equivalent in the

prefect.yaml

file. For more detailed examples and instructions, you can explore the documentation links: - Prefect 2.x Storage Options - Prefect 3.x Storing Flow Code With these settings configured, your setup should minimize or eliminate redundant network checks for flow code, ensuring a smoother run. Think of it as allowing your worker to skip the library queue and grab the book directly off your desk! If you need more guidance or hit any bumps, feel free to ask!

@Marvin I use Terraform to specify my deployments. is there a way for me to specify in my deployment terraform resources to use the local file system directly and avoid checking remote storage?

To specify in your Terraform deployment resources that the Prefect worker should use the local file system directly and avoid checking remote storage, it requires configuring the storage blocks properly. Here’s how you can achieve it: 1. Prefect 2.x Using Terraform: - Use the

LocalFileSystem

storage block in your Prefect configuration. This storage type automatically uses your present working directory as its base path during deployment build in Prefect, which should be specified in the Terraform resource configuration you define for deploying Prefect entities. - You can ensure your Prefect deployment initiated via Terraform refers to the

LocalFileSystem

by setting the appropriate storage configuration which aligns with default local storage. 2. Prefect 3.x Configuring for Terraform: - Prefect 3.x allows you to define storage configuration within a

prefect.yaml

file or through the Prefect CLI, specifying local storage explicitly. When generating or updating this file, you should ensure it defines the local storage characteristics compatible with what your Terraform scripts deployed. - Your Terraform scripts would ensure the deployment configuration points to a configuration file that uses local storage, similar to

LocalFileSystem

. This also involves having the worker configurations handle entries from the local filesystem without external pulls. The Prefect deployment documentation gives insights into setting up storage blocks and deployment YAML configurations: - Prefect 2.x Storage Options - Prefect 3.x Storing Flow Code When your Terraform scripts facilitate such Prefect settings, the local execution should minimize unnecessary remote storage checks. It's essential to combine your Terraform setup to accurately reflect and trigger local execution behaviors in your Prefect deployments. If technology had feelings, it’d probably be grateful to avoid unnecessary errands to distant clouds. Let me know if you need further guidance!

@Marvin I still don't understand precisely what happens in the background when the step 'Downloading flow code from storage at <local_path>' is running, and when my code is stored locally on the container. Could you please point to documentation explaining why this step is taking place and how I can control it? In my case I would simply like to disable any copying or syncing, and I want my code to run as soon as possible

In Prefect, the step "Downloading flow code from storage at <local_path>" is part of the execution process where the system ensures the flow code is accessible to the worker executing the flow. Here's a bit more detail on what's happening and options for managing this: 1. Why This Happens: - Verification and Access: Even if the code is stored locally within the container, Prefect might perform verification steps or attempt to synchronize what it perceives as a storage path. This step is often to ensure that code versions are consistent with what's expected by the deployment metadata. - Storage Configuration: Prefect deploys a model where storage blocks are used to manage the flow code's location, promoting consistency across environments. It checks storage paths to validate this consistency. 2. Controlling This Behavior: - Use Local Storage: Ensure your deployments specify using a

LocalFileSystem

storage block. This prevents attempts to fetch or sync with remote sources when unnecessary. In the Prefect configuration, network-dependent steps are omitted if local storage is correctly set. - Deployment Configuration: When creating your deployments, you can customize the

prefect.yaml

file to explicitly point to local directories only, without any fallbacks or additional sync steps from remote sources. 3. Disabling Unnecessary Steps: - Docker Configuration: Embed your code into the Docker image used by the container directly, making sure the image is marked as up-to-date during the deployment step, reducing the need for any downloading steps. - Remove Default Storage Pulls: During the deployment setup (

prefect deploy

), make sure no additional storage pull commands are embedded. To configure these effectively, you should ensure your deployment settings utilize local execution efficiently, specifically opting out of additional storage pulls or syncs. For more specific management and options related to your setup, you can refer to the Prefect documentation on flow code storage: - Prefect 2.x Storage Concepts - Prefect 3.x Storing Flow Code If Prefect still insists on playing librarian for your code, despite all hints, further investigation into specific deployment details or upgrades might be necessary. Let me know if you need more precise guidance!

@Marvin I declare my deployments via Terraform. Is there a way for me to declare a

LocalFileSystem

block and attach it to this deployment?

To declare a

LocalFileSystem

block in Terraform and attach it to a Prefect deployment, you'll need to explicitly define the filesystem block and reference it in your deployment configuration. ### Steps to Declare and Attach a LocalFileSystem Block: 1. Understand Prefect Storage Blocks: - Prefect uses blocks to define storage, including local and remote filesystem options. The

LocalFileSystem

allows interactions with files in the development environment and is defined by specifying paths in your configuration. 2. Using Prefect with Terraform: - While Prefect does not provide a direct Terraform provider, you can automate the process by using scripts or invoking Prefect CLI commands from within Terraform configuration files. This involves managing YAML configuration files that Prefect can use during deployment. 3. Configuration with Prefect CLI in Terraform: - If using Prefect CLI, define your

LocalFileSystem

block within the

prefect.yaml

file. - You can call Prefect commands within Terraform using local-exec provisions to configure each needed setup step once the infrastructure is ready. Here’s a conceptual outline for achieving it:

yaml
# prefect.yaml
flows:
  - name: example_flow
    storage:
      - prefect.filesystems.LocalFileSystem:
          basepath: "/path/to/your/code"

#### Terraform Example to Invoke Prefect CLI:

hcl
resource "null_resource" "deploy_prefect_flow" {
  provisioner "local-exec" {
    command = "prefect deployment build your-flow.py:flow-function-name --name your-flow-name --storage LocalFileSystem(basepath='/path/to/your/code')"
  }
  
  provisioner "local-exec" {
    command = "prefect deployment apply your-flow-deployment.yaml"
  }
}

### Notes: - Implementation: This method leverages Terraform's ability to run shell commands to utilize Prefect’s CLI, which configures your flow deployments. - Modification: Ensure that paths in both Terraform and Prefect configurations correspond to actual directories on the deployment servers/containers for seamless operation. By placing the deployment flow directly within the container and configuring the LocalFileSystem in the Columbus block, you minimize the overhead of retrieving code redundantly while integrating with Terraform. For more detailed guidance, please refer to Prefect's documentation on storage: - Prefect 2.x Filesystem Concepts - Prefect 3.x Storing Flow Code Let me know if you need additional clarification or help!