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ADOPTERS.md

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# Adopters
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This list represents the collection of organizations that are using PipeCD within their environments. If you are currently utilizing PipeCD and not yet on this list, we strongly encourage you to add your organization here as well!
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This list represents the collection of organizations that are using PipeCD within their environments. If you are currently using PipeCD and not yet on this list, we strongly encourage you to add your organization here as well!
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The objective of this list is to serve as a comprehensive and authoritative resource for the entire PipeCD adopter community, while also inspiring those who are embarking on their PipeCD journey.
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docs/rfcs/0002-lambda-deployment.md

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# Summary
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This RFC proposes adding a new service deployment from PipeCD: AWS Lambda deployment. Similar to the current [Google clould run deployment](https://pipecd.dev/docs/feature-status/#cloudrun-deployment).
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This RFC proposes adding a new service deployment from PipeCD: AWS Lambda deployment. Similar to the current [Google cloud run deployment](https://pipecd.dev/docs/feature-status/#cloudrun-deployment).
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# Motivation
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1. Configure piped to be able to clone the source of Lambda function ( on the same repo which deployment be handled by piped or via remote git repo ).
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2. Compress the source code and deploy with [SAM](https://docs.aws.amazon.com/serverless-application-model/latest/developerguide/serverless-sam-cli-command-reference.html) or using [aws-sdk](https://github.com/aws/aws-lambda-go) ( piped handle the deployment ).
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The deployment configuration sample as bellow:
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The deployment configuration sample as below:
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In case of source code for Lambda function is on the same repo handled by Piped
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```yaml

docs/rfcs/0007-deployment-chain.md

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## More examples regards known use-cases
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The above configuration contains sample for a completely flexsible deployment chain (multiple applications with difference kinds deployed across environment). For clarity, here are some examples for each known use-cases listed in [above section](#motivation)
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The above configuration contains a sample for a completely flexible deployment chain (multiple applications with different kinds deployed across environments). For clarity, here are some examples for each known use-cases listed in [above section](#motivation)
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### Use-case <1>: chain of deployments contains multiple applications cross kinds
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![image](assets/deployment-chain-kind.png)

docs/rfcs/0014-multi-cluster-deployment-for-k8s.md

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Currently, we need to prepare the kubeconfig file manually.
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But it would be nice to prepare it automatically.
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It might realize it by using cloud vender feature, for example using Workload Identity on GKE, or IRSA on EKS.
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It means piped get kubeconfig when it starts by using them.
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It might be possible by using cloud vendor features, for example Workload Identity on GKE or IRSA on EKS. This would allow piped to obtain the kubeconfig at startup.
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# Alternatives
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## Idea: Execute Stages in parallel within a pipeline
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![image](assets/0014-pipeline-paralell-stage.png)
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![image](assets/0014-pipeline-parallel-stage.png)
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### UX
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docs/rfcs/0017-deployment-trace.md

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}
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```
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The idea is to use `commit_hash` to the reference keys to link between a deployment trace with all deployments triggred by the same change in application repo (commit_hash referrenced commit). Once we could built the deploymen trace object that contains commit_hash and add `commit_hash` value to deployment model objects, we can query for deployment trace and show it to the UI.
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The idea is to use `commit_hash` to the reference keys to link between a deployment trace with all deployments triggered by the same change in application repo (commit_hash referenced commit). Once we build the deployment trace object that contains commit_hash and add `commit_hash` value to deployment model objects, we can query for deployment trace and show it to the UI.
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The deployment model will add one field like this
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