Better application deployments in kubernetes

[yairyairyair]

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1. Is this request related to a challenge you're experiencing?

yes

2. Describe the feature you'd like to see

would like a better app deployment when i am running dify in kubernetes.
i want the app to be deployed separately in a different kubernetes deployment.
this can be done via CRD or via knative or via whatever.

i mean that when i am publishing an app dify.ai will create a new kubernetes deployment with service and ingress and i can access it via the same URL and embed it but it will be a separate entity that even if i remove dify.ai (helm uninstall) the app will still run and can also scale and all of the kubernetes advantages.

3. How will this feature improve your workflow or experience?

it will greatly improve scalability and resiliience of dify.ai apps.

4. Additional context or comments

No response

5. Can you help us with this feature?

• I am interested in contributing to this feature.

[dosubot]

Hey there, @yairyairyair! 👋 I'm Dosu, a friendly bot here to lend a hand with bugs, answer your questions, and help you get started with contributing while we wait for a human maintainer to join us. I'm diving into your issue about enhancing application deployments in Kubernetes with Dify and will get back to you with a comprehensive response shortly. Hang tight!

[yairyairyair]

I think this will also GREATLY improve the cloud experience too if my dify.ai app in the cloud will have higher availability and auto-scaling capabilities (might even be cheaper if can scale to zero 0)

[dosubot]

To enhance Dify's deployment process within Kubernetes and deploy each app as a separate Kubernetes deployment, you can follow a structured approach to improve scalability, resilience, and the cloud experience. This involves creating a Kubernetes deployment for each application, defining services and ingress for external accessibility, implementing auto-scaling, and ensuring the setup remains functional even if Dify is removed.

1. Define Kubernetes Deployment for Each Application: Create a Kubernetes deployment YAML file for each application, specifying the container image, resources, and any necessary environment variables.

2. Create a Service for Each Deployment: Define a Kubernetes service for each deployment to make the application accessible within the Kubernetes cluster.

3. Define Ingress for External Accessibility: To access each application via a URL, define an ingress resource. This step requires an Ingress controller in your Kubernetes cluster.

4. Implement Auto-Scaling: Use Horizontal Pod Autoscalers (HPA) for each deployment to automatically adjust the number of pods based on observed CPU utilization or other metrics.

5. Scaling to Zero for Cost Efficiency: Integrate with a serverless framework like KEDA for event-driven autoscaling that supports scaling deployments to/from zero based on event sources or metrics.

6. Ensure Independence from Dify: Store all necessary configurations, secrets, and environment variables within Kubernetes resources (like Secrets and ConfigMaps) to maintain functionality without Dify.

These steps are a general guide and may require adjustments based on your specific environment and use case. If you have further questions or need assistance, feel free to ask.

Sources

• en/user-guide/launching-dify-apps/developing-with-apis/README.md
• en/getting-started/install-self-hosted/docker-compose.md

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[crazywoola]

Please refer this link #2931 about use helm to deploy dify.ai