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Jin Chi He

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Enhance Any Sequencer to support watching run (#583)

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Enhance Any Sequencer to support watching run approved lgtm size/L

Which issue is resolved by this Pull Request: Resolves #

Description of your changes: Currently the Any Sequencer support watching taskrun and conditions, do not support watching run, the PR is going to support that.

Environment tested:

  • Python Version (use python --version):
  • Tekton Version (use tkn version):
  • Kubernetes Version (use kubectl version):
  • OS (e.g. from /etc/os-release):

Checklist:

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jinchihe

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pull request commentkubeflow/kfp-tekton

Enhance Any Sequencer to support watching run

/lgtm Thanks Jinchi.

jinchihe

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pull request commentkubeflow/kfp-tekton

Enhance Any Sequencer to support watching run

[APPROVALNOTIFIER] This PR is APPROVED

This pull-request has been approved by: <a href="https://github.com/kubeflow/kfp-tekton/pull/583#issuecomment-834129218" title="Approved">fenglixa</a>, <a href="https://github.com/kubeflow/kfp-tekton/pull/583#" title="Author self-approved">jinchihe</a>

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pull request commentkubeflow/kfp-tekton

Enhance Any Sequencer to support watching run

/approve

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pull request commentkubeflow/kfp-tekton

Enhance Any Sequencer to support watching run

@vincent-pli: changing LGTM is restricted to collaborators

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/lgtm

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pull request commentkubeflow/kfp-tekton

Enhance Any Sequencer to support watching run

/lgtm

jinchihe

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pull request commentkubeflow/kfp-tekton

Enhance Any Sequencer to support watching run

@vincent-pli @fenglixa Would you please help to review? Great thanks!

jinchihe

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pull request commentkubeflow/kfp-tekton

Enhance Any Sequencer to support watching run

[APPROVALNOTIFIER] This PR is NOT APPROVED

This pull-request has been approved by: <a href="https://github.com/kubeflow/kfp-tekton/pull/583#" title="Author self-approved">jinchihe</a> To complete the pull request process, please assign ckadner after the PR has been reviewed. You can assign the PR to them by writing /assign @ckadner in a comment when ready.

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jinchihe

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PR opened kubeflow/kfp-tekton

Enhance Any Sequencer to support watching run

Which issue is resolved by this Pull Request: Resolves #

Description of your changes: Currently the Any Sequencer support watching taskrun and conditions, do not support watching run, the PR is going to support that.

Environment tested:

  • Python Version (use python --version):
  • Tekton Version (use tkn version):
  • Kubernetes Version (use kubectl version):
  • OS (e.g. from /etc/os-release):

Checklist:

  • [ ] The title for your pull request (PR) should follow our title convention. Learn more about the pull request title convention used in this repository. <!-- PR titles examples:

    • fix(frontend): fixes empty page. Fixes #1234 Use fix to indicate that this PR fixes a bug.
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    • chore: set up changelog generation tools Use chore to indicate that this PR makes some changes that users don't need to know.
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Tommy Li

commit sha 4c09f46de60d6bc6048eebf6d64dc18a30583a73

Fix /logs api and add tests (#582)

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Fix /logs api and add tests approved lgtm size/S

Which issue is resolved by this Pull Request: Resolves #578

Description of your changes: This PR address the API log issue with standard Tekton tasks. For standard Tekton tasks on KFP, we name the main container as "main" following the Argo convention. However, the Tekton controller will always inject the step- prefix to all the user steps when translating them into containers because it may inject initial containers and sidecars under certain settings.

As for custom task, there's no concept of steps anymore because the workload is not always backed by a new single pod. Thus, currently it will return an error message to let any client know the log api for custom task is not valid rather than of panic. e.g. for CEL custom task, there's no dedicated pod backing for this task because the workload is done in the controller. curl 'http://<endpoint>/apis/v1beta1/runs/<run_id>/nodes/<custom_task_id>/log'

{"error_message":"InternalServerError: error in opening log stream: pods \"conditional-cel\" not found","error_details":"InternalServerError: error in opening log stream: pods \"conditional-cel\" not found"}

Note: The correct way to use this API should be curl 'http://<endpoint>/apis/v1beta1/runs/<run_id>/nodes/<task_podname>/log', custom_task_id can't be the pod name in this case.

For open source UI, we are not calling the log api for custom tasks already, so no need to update the open source UI.

Environment tested:

  • Python Version (use python --version):
  • Tekton Version (use tkn version): 0.21
  • Kubernetes Version (use kubectl version): 1.18
  • OS (e.g. from /etc/os-release):

Checklist:

  • [ ] The title for your pull request (PR) should follow our title convention. Learn more about the pull request title convention used in this repository. <!-- PR titles examples:

    • fix(frontend): fixes empty page. Fixes #1234 Use fix to indicate that this PR fixes a bug.
    • feat(backend): configurable service account. Fixes #1234, fixes #1235 Use feat to indicate that this PR adds a new feature.
    • chore: set up changelog generation tools Use chore to indicate that this PR makes some changes that users don't need to know.
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+21 -3

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Tomcli

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issue closedkubeflow/kfp-tekton

Log API didn't cover the edge case with custom tasks that don't produce logs

/kind bug

What steps did you take and what happened: With the introduction of Tekton custom task, some custom task doesn't need to create new pods to run workloads. This means there's no logs for the custom task since it only get back the controller status. The current log API didn't cover this edge case and panic because log API was introduced before Tekton diverge its pipelinerun spec with custom task.

We need to check whether the Tekton task is a Tekton custom task without pods/logs before retrieving/streaming the log file. If the custom task doesn't have any pod/log, return empty string or warning message as the logs to maintain backward compatibility.

Panic we are seeing

panic: runtime error: invalid memory address or nil pointer dereference
[signal SIGSEGV: segmentation violation code=0x1 addr=0x0 pc=0x1d68c24]
goroutine 1 [running]:
github.com/tektoncd/cli/pkg/helper/log.(*Reader).readAvailablePipelineLogs(0xc0000c2960, 0xc000224000, 0x2d, 0x0, 0x0, 0x0)
	/workspace/src/github.com/tektoncd/cli/pkg/helper/log/pipeline_reader.go:90 +0xc4
github.com/tektoncd/cli/pkg/helper/log.(*Reader).readPipelineLog(0xc0000c2960, 0x24, 0x21cfec8, 0x7ffeefbffc6e, 0xc000101340)
	/workspace/src/github.com/tektoncd/cli/pkg/helper/log/pipeline_reader.go:41 +0x13d
github.com/tektoncd/cli/pkg/helper/log.(*Reader).Read(0xc0000c2960, 0x8, 0xc0001c52c0, 0xc0000c2960, 0x0)
	/workspace/src/github.com/tektoncd/cli/pkg/helper/log/reader.go:77 +0xb8
github.com/tektoncd/cli/pkg/cmd/pipelinerun.Run(0xc0001c52c0, 0xc0002f0040, 0x0)
	/workspace/src/github.com/tektoncd/cli/pkg/cmd/pipelinerun/logs.go:105 +0x81
github.com/tektoncd/cli/pkg/cmd/pipelinerun.logCommand.func1(0xc000311340, 0xc000326e40, 0x1, 0x3, 0x0, 0x0)
	/workspace/src/github.com/tektoncd/cli/pkg/cmd/pipelinerun/logs.go:78 +0x1ba
github.com/spf13/cobra.(*Command).execute(0xc000311340, 0xc0002f1b80, 0x3, 0x4, 0xc000311340, 0xc0002f1b80)
	/workspace/pkg/mod/github.com/chmouel/cobra@v0.0.0-20200107083527-379e7a80af0c/command.go:834 +0x460
github.com/spf13/cobra.(*Command).ExecuteC(0xc0002e62c0, 0xc0002f0040, 0xc0002e62c0, 0xc000098058)
	/workspace/pkg/mod/github.com/chmouel/cobra@v0.0.0-20200107083527-379e7a80af0c/command.go:922 +0x2fb
github.com/spf13/cobra.(*Command).Execute(...)
	/workspace/pkg/mod/github.com/chmouel/cobra@v0.0.0-20200107083527-379e7a80af0c/command.go:872
main.main()
	/workspace/src/github.com/tektoncd/cli/cmd/tkn/main.go:29 +0x4b

What did you expect to happen:

Additional information: [Miscellaneous information that will assist in solving the issue.]

Environment:

  • Python Version (use python --version):
  • SDK Version:
  • Tekton Version (use tkn version):
  • Kubernetes Version (use kubectl version):
  • OS (e.g. from /etc/os-release):

closed time in 2 days

Tomcli

pull request commentkubeflow/kfp-tekton

Fix /logs api and add tests

/lgtm

Tomcli

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pull request commentkubeflow/kfp-tekton

Fix /logs api and add tests

/cc @drewbutlerbb4 @yhwang

Tomcli

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pull request commentkubeflow/kfp-tekton

Fix /logs api and add tests

[APPROVALNOTIFIER] This PR is APPROVED

This pull-request has been approved by: <a href="https://github.com/kubeflow/kfp-tekton/pull/582#" title="Author self-approved">Tomcli</a>

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Tomcli

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PR opened kubeflow/kfp-tekton

Fix /logs api and add tests

Which issue is resolved by this Pull Request: Resolves #578

Description of your changes: This PR address the API log issue with standard Tekton tasks. For standard Tekton tasks on KFP, we name the main container as "main" following the Argo convention. However, the Tekton controller will inject the step- prefix to all the user steps because it may inject initial containers and sidecars under certain settings.

As for custom task, there's no concept of steps anymore because the workload is not always backed by a new single pod. Thus, currently it will return an error message to let any client know the log api for custom task is not valid rather than of panic. e.g. for CEL custom task, there's no dedicated pod backing for this task because the workload is done in the controller.

{"error_message":"InternalServerError: error in opening log stream: pods \"conditional-cel\" not found","error_details":"InternalServerError: error in opening log stream: pods \"conditional-cel\" not found"}

For open source UI, we are not calling the log api for custom tasks already, so no need to update the open source UI.

Environment tested:

  • Python Version (use python --version):
  • Tekton Version (use tkn version): 0.21
  • Kubernetes Version (use kubectl version): 1.18
  • OS (e.g. from /etc/os-release):

Checklist:

  • [ ] The title for your pull request (PR) should follow our title convention. Learn more about the pull request title convention used in this repository. <!-- PR titles examples:

    • fix(frontend): fixes empty page. Fixes #1234 Use fix to indicate that this PR fixes a bug.
    • feat(backend): configurable service account. Fixes #1234, fixes #1235 Use feat to indicate that this PR adds a new feature.
    • chore: set up changelog generation tools Use chore to indicate that this PR makes some changes that users don't need to know.
    • test: fix CI failure. Part of #1234 Use part of to indicate that a PR is working on an issue, but shouldn't close the issue when merged. -->
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+21 -3

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Tommy Li

commit sha c1b4d8480922bb433369cd7368e4e1c90cde0e84

Add instructions on upgrade kfp-tekton multi-users and fix new multi-users permission (#581) * add instrctions on upgrade kfp-tekton and fix multi-users permission * Apply suggestions from code review Co-authored-by: Andrew Butler <Andrew.Butler@ibm.com> * Fix markdown links after suggestions Co-authored-by: Andrew Butler <Andrew.Butler@ibm.com>

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Add instructions on upgrade kfp-tekton multi-users and fix new multi-users permission approved lgtm size/S

Which issue is resolved by this Pull Request: Resolves #580

Description of your changes:

Environment tested:

  • Python Version (use python --version):
  • Tekton Version (use tkn version): 0.21
  • Kubernetes Version (use kubectl version): 1.18
  • OS (e.g. from /etc/os-release):

Checklist:

  • [ ] The title for your pull request (PR) should follow our title convention. Learn more about the pull request title convention used in this repository. <!-- PR titles examples:

    • fix(frontend): fixes empty page. Fixes #1234 Use fix to indicate that this PR fixes a bug.
    • feat(backend): configurable service account. Fixes #1234, fixes #1235 Use feat to indicate that this PR adds a new feature.
    • chore: set up changelog generation tools Use chore to indicate that this PR makes some changes that users don't need to know.
    • test: fix CI failure. Part of #1234 Use part of to indicate that a PR is working on an issue, but shouldn't close the issue when merged. -->
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+29 -0

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Tomcli

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issue closedkubeflow/kfp-tekton

Cache server only effect in certain namespace for now, should has ability to watch all namespaces

/kind feature

Description: [A clear and concise description of what your proposal. What problem does it solve?] For now, cache server will only effect on one certain namespace(namespace: kubeflow), it should has ability to watch all namespaces.

To enable such ability, there are two steps required:

  1. cache server has variables namespace_to_watch to define the namespace it effected: https://github.com/kubeflow/kfp-tekton/blob/de00ccadef3214e85c252a75906455d4fe3ee94e/manifests/kustomize/base/cache/cache-deployment.yaml#L63 set --namespace_to_watch=

  2. Change https://github.com/kubeflow/kfp-tekton/blob/master/manifests/kustomize/base/cache/cache-role.yaml to clusterrole and change https://github.com/kubeflow/kfp-tekton/blob/master/manifests/kustomize/base/cache/cache-rolebinding.yaml to clusterrolebinding

So we need either add these step to https://github.com/kubeflow/kfp-tekton/tree/master/backend/src/cache or enable option in kustomize

@Tomcli what do you think?

Additional information: [Miscellaneous information that will assist in solving the issue.]

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vincent-pli

Pull request review commentkubeflow/kfp-tekton

Add instructions on upgrade kfp-tekton multi-users and fix new multi-users permission

 To install the standalone Kubeflow Pipelines with Tekton, run the following step 3. Visit [KFP Tekton Admin Guide](/guides/kfp-admin-guide.md) for how to configure kfp-tekton with different settings.  +## Upgrade Multi-Users KFP-Tekton on Kubeflow
## Upgrade to Multi-User KFP-Tekton on Kubeflow
Tomcli

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Pull request review commentkubeflow/kfp-tekton

Add instructions on upgrade kfp-tekton multi-users and fix new multi-users permission

 To install the standalone Kubeflow Pipelines with Tekton, run the following step 3. Visit [KFP Tekton Admin Guide](/guides/kfp-admin-guide.md) for how to configure kfp-tekton with different settings.  +## Upgrade Multi-Users KFP-Tekton on Kubeflow++1. If you haven't installed Kubeflow 1.3+, Follow the [Kubeflow install instructions](https://www.kubeflow.org/docs/ibm/deploy/install-kubeflow-on-iks/#kubeflow-installation) to install Kubeflow with multi-users.
1. If you haven't installed Kubeflow 1.3+, Follow the [Kubeflow install instructions](https://www.kubeflow.org/docs/ibm/deploy/install-kubeflow-on-iks/#kubeflow-installation) to install Kubeflow with multi-user capabilities.
Tomcli

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Pull request review commentkubeflow/kfp-tekton

Add instructions on upgrade kfp-tekton multi-users and fix new multi-users permission

 To install the standalone Kubeflow Pipelines with Tekton, run the following step 3. Visit [KFP Tekton Admin Guide](/guides/kfp-admin-guide.md) for how to configure kfp-tekton with different settings.  +## Upgrade Multi-Users KFP-Tekton on Kubeflow++1. If you haven't installed Kubeflow 1.3+, Follow the [Kubeflow install instructions](https://www.kubeflow.org/docs/ibm/deploy/install-kubeflow-on-iks/#kubeflow-installation) to install Kubeflow with multi-users.++2. To upgrade the Multi-Users version of KFP-Tekton, custom task controllers, and core Tekton controller, please run
2. To upgrade to the Multi-User version of KFP-Tekton, custom task controllers, and core Tekton controller, please run
Tomcli

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Pull request review commentkubeflow/kfp-tekton

Add instructions on upgrade kfp-tekton multi-users and fix new multi-users permission

   * [Other Cloud Providers or On-Prem Kubernetes Deployment](#other-cloud-providers-or-on-prem-kubernetes-deployment) - [Standalone Kubeflow Pipelines with Tekton Backend Deployment](#standalone-kubeflow-pipelines-with-tekton-backend-deployment) - [Kubeflow installation including Kubeflow Pipelines with Tekton Backend](#kubeflow-installation-including-kubeflow-pipelines-with-tekton-backend)+- [Upgrade Multi-Users KFP-Tekton on Kubeflow](#upgrade-multi-users-kfp-tekton-on-kubeflow)
- [Upgrade to Multi-User KFP-Tekton on Kubeflow](#upgrade-multi-users-kfp-tekton-on-kubeflow)
Tomcli

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pull request commentkubeflow/kfp-tekton

Sanitize Tekton result parameters when passing to custom task inputs

Thanks @Tommy

Tomcli

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Tommy Li

commit sha 633848134d52ae3fa52038b11d2f9461837f0007

Sanitize Tekton result parameters when passing to custom task inputs (#579)

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Sanitize Tekton result parameters when passing to custom task inputs approved lgtm size/M

Which issue is resolved by this Pull Request: Resolves #577

Description of your changes: When passing the Tekton result parameters with underscore keys to custom tasks, the Tekton variables are not properly sanitized. Thus, this PR fix the sanitization for custom task inputs.

Environment tested:

  • Python Version (use python --version):
  • Tekton Version (use tkn version):
  • Kubernetes Version (use kubectl version):
  • OS (e.g. from /etc/os-release):

Checklist:

  • [ ] The title for your pull request (PR) should follow our title convention. Learn more about the pull request title convention used in this repository. <!-- PR titles examples:

    • fix(frontend): fixes empty page. Fixes #1234 Use fix to indicate that this PR fixes a bug.
    • feat(backend): configurable service account. Fixes #1234, fixes #1235 Use feat to indicate that this PR adds a new feature.
    • chore: set up changelog generation tools Use chore to indicate that this PR makes some changes that users don't need to know.
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Tomcli

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