@ancient-wolf-19325 What does turning

flyteconnector

to

enabled

in

values.yaml

actually do?

flyteconnector:
  enabled: false

Setting

flyteconnector.enabled: true

in

values.yaml

enables the deployment of the Flyte Connector service as part of your Flyte installation. This service is responsible for handling connector-based tasks (such as Databricks, Snowflake, Airflow, etc.) by running a dedicated connector service pod in your Kubernetes cluster, allowing Flyte to offload and manage external or specialized workloads via gRPC requests to the connector service. If set to

false

, the connector service and its related resources will not be deployed, and connector-based tasks will not be available in your Flyte deployment. This flag is referenced in the Helm chart to conditionally create the connector's Kubernetes resources (Deployment, Service, ServiceAccount, etc.) and to include connector-specific configuration in the Flyte system (flyte-binary/values.yaml, flyteconnector/values.yaml, propeller/configmap.yaml). Would you like more detail on how this affects task execution or Helm deployment? Sources: - flyte-binary/values.yaml - flyteconnector/values.yaml - propeller/configmap.yaml 👍 0 button 👎 0 button 💡 Hint: Mention @runllm in the thread for followups.

@ancient-wolf-19325 I have had it as false, how will the existing task execution change if at all?

It could be possible that if you previously had

flyteconnector.enabled: false

, your Flyte deployment did not run the connector service, so only standard task types (like container, sidecar, k8s-array) and plugin-based tasks were available. Enabling the connector will not affect existing standard or plugin-based task executions; they should continue to work as before, since the connector is only required for connector-based task types. Though I'm not entirely certain, it might be that enabling the connector simply adds support for new connector-based tasks (e.g., Databricks, Airflow, Snowflake), but does not change the execution of tasks that do not use the connector. Existing workflows and tasks that do not specify a connector-based type will remain unaffected (flyte-binary/values.yaml, flyte-core/README.md). Would you like more detail on which task types use the connector or how to migrate tasks? Sources: - flyte-binary/values.yaml - flyte-core/README.md 👍 0 button 👎 0 button 💡 Hint: Mention @runllm in the thread for followups.

@ancient-wolf-19325 Do I need to change the default configurations for

flyteconnector

after turning it

true

or will default settings suffice?

The default settings for

flyteconnector

will deploy a single replica with standard resource requests/limits and expose the connector service on port 8000 using the default image and configuration. For many use cases, these defaults are sufficient to get started, especially in development or testing environments (flyteconnector/values.yaml). However, for production or when using specific connectors (e.g., Databricks, OpenAI, Snowflake), you may need to adjust configurations such as secrets, resource limits, or enabled connectors to match your environment and security requirements (flyte-binary/values.yaml). Would you like more detail on which settings to customize for production or for a specific connector? Sources: - flyteconnector/values.yaml - flyte-binary/values.yaml 👍 0 button 👎 0 button 💡 Hint: Mention @runllm in the thread for followups.

@ancient-wolf-19325 Yes I'd like to hear what to consider when rolling the flyteconnector to production for example with OpenAI connector

For production use of

flyteconnector

with the OpenAI connector, you should consider: (1) securely providing your OpenAI API key as a Kubernetes secret and patching it into the

flyteconnector

deployment, (2) configuring resource requests/limits to match expected workload, (3) enabling the OpenAI connector in your Flyte configuration, and (4) ensuring network and RBAC permissions are set appropriately. The default settings are not secure or robust enough for production, especially regarding secret management and resource scaling (OpenAI Batch connector setup). You must also update your Flyte deployment's Helm values to enable the connector, set the correct task type mapping, and restart the deployment after patching secrets. Review logging, monitoring, and timeout settings for production reliability. For example, set the OpenAI API key as a base64-encoded secret, patch it into the

flyteconnector

secret, and restart the deployment as shown in the official guide. Would you like a step-by-step breakdown or a sample configuration? Sources: - OpenAI Batch connector setup 👍 0 button 👎 0 button 💡 Hint: Mention @runllm in the thread for followups.