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# Developer docs
This document is aimed at helping maintainers/developers of project understand
the complexity.
We also recommend checking out the
[Teknical Tekton](https://www.youtube.com/channel/UCUEuKDqyRnGFCE7FpainSpQ)
channel for training and tutorials on Tekton!
## How are resources shared between tasks
`PipelineRun` uses PVC to share `PipelineResources` between tasks. PVC volume is
mounted on path `/pvc` by PipelineRun.
- If a resource in a task is declared as output then the `TaskRun` controller
adds a step to copy each output resource to the directory path
`/pvc/task_name/resource_name`.
- If an input resource includes `from` condition then the `TaskRun` controller
adds a step to copy from PVC directory path:
`/pvc/previous_task/resource_name`.
If neither of these conditions are met, the PVC will not be created nor will the
GCS storage / S3 buckets be used.
Another alternative is to use a GCS storage or S3 bucket to share the artifacts.
This can be configured using a ConfigMap with the name `config-artifact-bucket`.
See the
[installation docs](../install.md#how-are-resources-shared-between-tasks) for
configuration details.
Both options provide the same functionality to the pipeline. The choice is based
on the infrastructure used, for example in some Kubernetes platforms, the
creation of a persistent volume could be slower than uploading/downloading files
to a bucket, or if the the cluster is running in multiple zones, the access to
the persistent volume can fail.
## How are inputs handled
Input resources, like source code (git) or artifacts, are dumped at path
`/workspace/task_resource_name`.
- If input resource is declared as below, then resource will be copied to
`/workspace/task_resource_name` directory `from` depended task PVC directory
`/pvc/previous_task/resource_name`.
```yaml
kind: Task
metadata:
name: get-gcs-task
namespace: default
spec:
resources:
inputs:
- name: gcs-workspace
type: storage
```
- Resource definition in task can have custom target directory. If `targetPath`
is mentioned in task input resource as below then resource will be copied to
`/workspace/outputstuff` directory `from` depended task PVC directory
`/pvc/previous_task/resource_name`.
```yaml
kind: Task
metadata:
name: get-gcs-task
namespace: default
spec:
resources:
inputs:
- name: gcs-workspace
type: storage
targetPath: /workspace/outputstuff
```
## How are outputs handled
Output resources, like source code (git) or artifacts (storage resource), are
expected in directory path `/workspace/output/resource_name`.
- If resource has an output "action" like upload to blob storage, then the
container step is added for this action.
- If there is PVC volume present (TaskRun holds owner reference to PipelineRun)
then copy step is added as well.
- If the output resource is declared then the copy step includes resource being
copied to PVC to path `/pvc/task_name/resource_name` from
`/workspace/output/resource_name` like the following example.
```yaml
kind: Task
metadata:
name: get-gcs-task
namespace: default
spec:
resources:
outputs:
- name: gcs-workspace
type: storage
```
- Same as input, if the output resource is declared with `TargetPath` then the
copy step includes resource being copied to PVC to path
`/pvc/task_name/resource_name` from `/workspace/outputstuff` like the
following example.
```yaml
kind: Task
metadata:
name: get-gcs-task
namespace: default
spec:
resources:
outputs:
- name: gcs-workspace
type: storage
targetPath: /workspace/outputstuff
```
## Entrypoint rewriting and step ordering
`Entrypoint` is injected into the `Task` Container(s), wraps the `Task` step to
manage the execution order of the containers. The `entrypoint` binary has the
following arguments:
- `wait_file` - If specified, file to wait for
- `wait_file_content` - If specified, wait until the file has non-zero size
- `post_file` - If specified, file to write upon completion
- `entrypoint` - The command to run in the image being wrapped
As part of the PodSpec created by `TaskRun` the entrypoint for each `Task` step
is changed to the entrypoint binary with the mentioned arguments and a volume
with the binary and file(s) is mounted.
If the image is a private registry, the service account should include an
[ImagePullSecret](https://kubernetes.io/docs/tasks/configure-pod-container/configure-service-account/#add-imagepullsecrets-to-a-service-account)
For more details, see [entrypoint/README.md](../../cmd/entrypoint/README.md).
## Reserved directories
### /workspace
- `/workspace` - This directory is where [resources](#resources) and
[workspaces](#workspaces) are mounted.
### /tekton
The `/tekton/` directory is reserved on containers for internal usage.
Here is an example of a directory layout for a simple Task with 2 script steps:
```
/tekton
|-- bin
`-- entrypoint
|-- creds
|-- downward
| |-- ..2021_09_16_18_31_06.270542700
| | `-- ready
| |-- ..data -> ..2021_09_16_18_31_06.270542700
| `-- ready -> ..data/ready
|-- home
|-- results
|-- run
`-- 0
`-- out
|-- scripts
| |-- script-0-t4jd8
| `-- script-1-4pjwp
|-- steps
| |-- 0 -> /tekton/steps/step-unnamed-0
| |-- 1 -> /tekton/steps/step-foo
| |-- step-foo
| `-- step-unnamed-0
| `-- exitCode
`-- termination
```
| Path | Description |
| ------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| /tekton | Directory used for Tekton specific functionality |
| /tekton/bin | Tekton provided binaries / tools |
| /tekton/creds | Location of Tekton mounted secrets. See [Authentication at Run Time](../auth.md) for more details. |
| /tekton/downward | Location of data mounted via the [Downward API](https://kubernetes.io/docs/tasks/inject-data-application/downward-api-volume-expose-pod-information/#the-downward-api). |
| /tekton/home | (deprecated - see https://github.com/tektoncd/pipeline/issues/2013) Default home directory for user containers. |
| /tekton/results | Where [results](#results) are written to (path available to `Task` authors via [`$(results.name.path)`](../variables.md)) |
| /tekton/run | Runtime variable data. [Used for coordinating step ordering](#entrypoint-rewriting-and-step-ordering). |
| /tekton/scripts | Contains user provided scripts specified in the TaskSpec. |
| /tekton/steps | Where the `step` exitCodes are written to (path available to `Task` authors via [`$(steps.<stepName>.exitCode.path)`](../variables.md#variables-available-in-a-task)) |
| /tekton/termination | where the eventual [termination log message](https://kubernetes.io/docs/tasks/debug-application-cluster/determine-reason-pod-failure/#writing-and-reading-a-termination-message) is written to [Sequencing step containers](#entrypoint-rewriting-and-step-ordering) |
The following directories are covered by the
[Tekton API Compatibility policy](../api_compatibility_policy.md), and can be
relied on for stability:
- `/tekton/results`
- `/tekton/steps`
All other files/directories are internal implementation details of Tekton -
**users should not rely on specific paths or behaviors as it may change in the
future**.
## Handling of injected sidecars
Tekton has to take some special steps to support sidecars that are injected into
TaskRun Pods. Without intervention sidecars will typically run for the entire
lifetime of a Pod but in Tekton's case it's desirable for the sidecars to run
only as long as Steps take to complete. There's also a need for Tekton to
schedule the sidecars to start before a Task's Steps begin, just in case the
Steps rely on a sidecars behavior, for example to join an Istio service mesh. To
handle all of this, Tekton Pipelines implements the following lifecycle for
sidecar containers:
First, the
[Downward API](https://kubernetes.io/docs/tasks/inject-data-application/downward-api-volume-expose-pod-information/#the-downward-api)
is used to project an annotation on the TaskRun's Pod into the `entrypoint`
container as a file. The annotation starts as an empty string, so the file
projected by the downward API has zero length. The entrypointer spins, waiting
for that file to have non-zero size.
The sidecar containers start up. Once they're all in a ready state, the
annotation is populated with string "READY", which in turn populates the
Downward API projected file. The entrypoint binary recognizes that the projected
file has a non-zero size and allows the Task's steps to begin.
On completion of all steps in a Task the TaskRun reconciler stops any sidecar
containers. The `Image` field of any sidecar containers is swapped to the nop
image. Kubernetes observes the change and relaunches the container with updated
container image. The nop container image exits immediately _because it does not
provide the command that the sidecar is configured to run_. The container is
considered `Terminated` by Kubernetes and the TaskRun's Pod stops.
There are known issues with the existing implementation of sidecars:
- When the `nop` image does provide the sidecar's command, the sidecar will
continue to run even after `nop` has been swapped into the sidecar container's
image field. See
[the issue tracking this bug](https://github.com/tektoncd/pipeline/issues/1347)
for the issue tracking this bug. Until this issue is resolved the best way to
avoid it is to avoid overriding the `nop` image when deploying the tekton
controller, or ensuring that the overridden `nop` image contains as few
commands as possible.
- `kubectl get pods` will show a Completed pod when a sidecar exits successfully
but an Error when the sidecar exits with an error. This is only apparent when
using `kubectl` to get the pods of a TaskRun, not when describing the Pod
using `kubectl describe pod ...` nor when looking at the TaskRun, but can be
quite confusing.
## How task results are defined and outputted by a task
Tasks can define results by adding a result on the task spec. This is an
example:
```yaml
apiVersion: tekton.dev/v1alpha1
kind: Task
metadata:
name: print-date
annotations:
description: |
A simple task that prints the date to make sure your cluster / Tekton is working properly.
spec:
results:
- name: "current-date"
description: "The current date"
steps:
- name: print-date
image: bash:latest
args:
- "-c"
- |
date > /tekton/results/current-date
```
The result is added to a file name with the specified result's name into the
`/tekton/results` folder. This is then added to the task run status. Internally
the results are a new argument `-results`to the entrypoint defined for the task.
A user can defined more than one result for a single task.
For this task definition,
```yaml
apiVersion: tekton.dev/v1alpha1
kind: Task
metadata:
name: print-date
annotations:
description: |
A simple task that prints the date to make sure your cluster / Tekton is working properly.
spec:
results:
- name: current-date-unix-timestamp
description: The current date in unix timestamp format
- name: current-date-human-readable
description: The current date in humand readable format
steps:
- name: print-date-unix-timestamp
image: bash:latest
script: |
#!/usr/bin/env bash
date +%s | tee /tekton/results/current-date-unix-timestamp
- name: print-date-human-readable
image: bash:latest
script: |
#!/usr/bin/env bash
date | tee /tekton/results/current-date-human-readable
```
you end up with this task run status:
```yaml
apiVersion: tekton.dev/v1alpha1
kind: TaskRun
# ...
status:
# ...
taskResults:
- name: current-date-human-readable
value: |
Wed Jan 22 19:47:26 UTC 2020
- name: current-date-unix-timestamp
value: |
1579722445
```
Instead of hardcoding the path to the result file, the user can also use a
variable. So `/tekton/results/current-date-unix-timestamp` can be replaced with:
`$(results.current-date-unix-timestamp.path)`. This is more flexible if the path
to result files ever changes.
### Known issues
- Task Results are returned to the TaskRun controller via the container's
termination message. At time of writing this has a capped maximum size of
["4096 bytes or 80 lines, whichever is smaller"](https://kubernetes.io/docs/tasks/debug-application-cluster/determine-reason-pod-failure/#customizing-the-termination-message).
This maximum size should not be considered the limit of a result's size.
Tekton uses the termination message to return other data to the controller as
well. The general advice should be that results are for very small pieces of
data. The exact size is going to be a product of the platform's settings and
the amount of other data Tekton needs to return for TaskRun book-keeping.
## How task results can be used in pipeline's tasks
Now that we have tasks that can return a result, the user can refer to a task
result in a pipeline by using the syntax
`$(tasks.<task name>.results.<result name>)`. This will substitute the task
result at the location of the variable.
```yaml
apiVersion: tekton.dev/v1alpha1
kind: Pipeline
metadata:
name: sum-and-multiply-pipeline
#...
tasks:
- name: sum-inputs
#...
- name: multiply-inputs
#...
- name: sum-and-multiply
taskRef:
name: sum
params:
- name: a
value: "$(tasks.multiply-inputs.results.product)$(tasks.sum-inputs.results.sum)"
- name: b
value: "$(tasks.multiply-inputs.results.product)$(tasks.sum-inputs.results.sum)"
```
This results in:
```shell
tkn pipeline start sum-and-multiply-pipeline
? Value for param `a` of type `string`? (Default is `1`) 10
? Value for param `b` of type `string`? (Default is `1`) 15
Pipelinerun started: sum-and-multiply-pipeline-run-rgd9j
In order to track the pipelinerun progress run:
tkn pipelinerun logs sum-and-multiply-pipeline-run-rgd9j -f -n default
```
```shell
tkn pipelinerun logs sum-and-multiply-pipeline-run-rgd9j -f -n default
[multiply-inputs : product] 150
[sum-inputs : sum] 25
[sum-and-multiply : sum] 30050
```
As you can see, you can define multiple tasks in the same pipeline and use the
result of more than one task inside another task parameter. The substitution is
only done inside `pipeline.spec.tasks[].params[]`. For a complete example
demonstrating Task Results in a Pipeline, see the
[pipelinerun example](../../examples/v1beta1/pipelineruns/task_results_example.yaml).
## Support for running in multi-tenant configuration
In order to support potential multi-tenant configurations the roles of the
controller are split into two:
`tekton-pipelines-controller-cluster-access`: those permissions needed cluster-wide by the controller.
`tekton-pipelines-controller-tenant-access`: those permissions needed on a namespace-by-namespace basis.
By default the roles are cluster-scoped for backwards-compatibility and
ease-of-use. If you want to start running a multi-tenant service you are able to
bind `tekton-pipelines-controller-tenant-access` using a `RoleBinding` instead
of a `ClusterRoleBinding`, thereby limiting the access that the controller has
to specific tenant namespaces.
## Adding feature gated API fields
We've introduced a feature-flag called `enable-api-fields` to the
[config-feature-flags.yaml file](../../config/config-feature-flags.yaml)
deployed as part of our releases.
This field can be configured either to be `alpha` or `stable`. This field is
documented as part of our
[install docs](../install.md#customizing-the-pipelines-controller-behavior).
For developers adding new features to Pipelines' CRDs we've got a couple of
helpful tools to make gating those features simpler and to provide a consistent
testing experience.
### Guarding Features with Feature Gates
Writing new features is made trickier when you need to support both the existing
stable behaviour as well as your new alpha behaviour.
In reconciler code you can guard your new features with an `if` statement such
as the following:
```go
alphaAPIEnabled := config.FromContextOrDefaults(ctx).FeatureFlags.EnableAPIFields == "alpha"
if alphaAPIEnabled {
// new feature code goes here
} else {
// existing stable code goes here
}
```
Notice that you'll need a context object to be passed into your function for
this to work. When writing new features keep in mind that you might need to
include this in your new function signatures.
### Guarding Validations with Feature Gates
Just because your application code might be correctly observing the feature gate
flag doesn't mean you're done yet! When a user submits a Tekton resource it's
validated by Pipelines' webhook. Here too you'll need to ensure your new
features aren't accidentally accepted when the feature gate suggests they
shouldn't be. We've got a helper function,
[`ValidateEnabledAPIFields`](../../pkg/apis/pipeline/v1beta1/version_validation.go),
to make validating the current feature gate easier. Use it like this:
```go
requiredVersion := config.AlphaAPIFields
// errs is an instance of *apis.FieldError, a common type in our validation code
errs = errs.Also(ValidateEnabledAPIFields(ctx, "your feature name", requiredVersion))
```
If the user's cluster isn't configured with the required feature gate it'll
return an error like this:
```
<your feature> requires "enable-api-fields" feature gate to be "alpha" but it is "stable"
```
### Unit Testing with Feature Gates
Any new code you write that uses the `ctx` context variable is trivially unit
tested with different feature gate settings. You should make sure to unit test
your code both with and without a feature gate enabled to make sure it's
properly guarded. See the following for an example of a unit test that sets the
feature gate to test behaviour:
```go
featureFlags, err := config.NewFeatureFlagsFromMap(map[string]string{
"enable-api-fields": "alpha",
})
if err != nil {
t.Fatalf("unexpected error initializing feature flags: %v", err)
}
cfg := &config.Config{
FeatureFlags: featureFlags,
}
ctx := config.ToContext(context.Background(), cfg)
if err := ts.TestThing(ctx); err != nil {
t.Errorf("unexpected error with alpha feature gate enabled: %v", err)
}
```
### Example YAMLs
Writing new YAML examples that require a feature gate to be set is easy. New
YAML example files typically go in a directory called something like
`examples/v1beta1/taskruns` in the root of the repo. To create a YAML that
should only be exercised when the `enable-api-fields` flag is `alpha` just put
it in an `alpha` subdirectory so the structure looks like:
```
examples/v1beta1/taskruns/alpha/your-example.yaml
```
This should work for both taskruns and pipelineruns.
**Note**: To execute alpha examples with the integration test runner you must
manually set the `enable-api-fields` feature flag to `alpha` in your testing
cluster before kicking off the tests.
When you set this flag to `stable` in your cluster it will prevent `alpha`
examples from being created by the test runner. When you set the flag to `alpha`
all examples are run, since we want to exercise backwards-compatibility of the
examples under alpha conditions.
### Integration Tests
For integration tests we provide the
[`requireAnyGate` function](../../test/gate.go) which should be passed to the
`setup` function used by tests:
```go
c, namespace := setup(ctx, t, requireAnyGate(map[string]string{"enable-api-fields": "alpha"}))
```
This will Skip your integration test if the feature gate is not set to `alpha`
with a clear message explaining why it was skipped.
**Note**: As with running example YAMLs you have to manually set the
`enable-api-fields` flag to `alpha` in your test cluster to see your alpha
integration tests run. When the flag in your cluster is `alpha` _all_
integration tests are executed, both `stable` and `alpha`. Setting the feature
flag to `stable` will exclude `alpha` tests.
## What and Why of `/tekton/steps`
`/tekton/steps/` is an implicit volume mounted on a pod and created for storing
the step specific information/metadata. There is one more subdirectory created
under `/tekton/steps/` for each step in a task.
Let's take an example of a task with three steps, each exiting with non-zero
exit code:
```yaml
kind: TaskRun
apiVersion: tekton.dev/v1beta1
metadata:
generateName: test-taskrun-
spec:
taskSpec:
steps:
- image: alpine
name: step0
onError: continue
script: |
echo "This is step 0"
ls -1R /tekton/steps/
exit 1
- image: alpine
onError: continue
script: |
echo "This is step 1"
ls -1R /tekton/steps/
exit 2
- image: alpine
name: step2
onError: continue
script: |
echo "This is step 2"
ls -1R /tekton/steps/
exit 3
```
The container `step-step0` for the first step `step0` shows three subdirectories
(one for each step) under `/tekton/steps/` and all three of them are empty.
```
kubectl logs pod/test-taskrun-2rb9k-pod-bphct -c step-step0
+ echo 'This is step 0'
+ ls -1R /tekton/steps/
This is step 0
/tekton/steps/:
0
1
2
step-step0
step-step2
step-unnamed-1
/tekton/steps/step-step0:
/tekton/steps/step-step2:
/tekton/steps/step-unnamed-1:
+ exit 1
```
The container `step-unnamed-1` for the second step which has no name shows three
subdirectories (one for each step) under `/tekton/steps/` along with the
`exitCode` file under the first step directory which has finished executing:
```
kubectl logs pod/test-taskrun-2rb9k-pod-bphct -c step-unnamed-1
This is step 1
+ echo 'This is step 1'
+ ls -1R /tekton/steps/
/tekton/steps/:
0
1
2
step-step0
step-step2
step-unnamed-1
/tekton/steps/step-step0:
exitCode
/tekton/steps/step-step2:
/tekton/steps/step-unnamed-1:
+ exit 2
```
The container `step-step2` for the third step `step2` shows three subdirectories
(one for each step) under `/tekton/steps/` along with the `exitCode` file under
the first and second step directory since both are done executing:
```
kubectl logs pod/test-taskrun-2rb9k-pod-bphct -c step-step2
This is step 2
+ echo 'This is step 2'
+ ls -1R /tekton/steps/
/tekton/steps/:
0
1
2
step-step0
step-step2
step-unnamed-1
/tekton/steps/step-step0:
exitCode
/tekton/steps/step-step2:
/tekton/steps/step-unnamed-1:
exitCode
+ exit 3
```
The entrypoint is modified to include an additional two flags representing the
step specific directory and a symbolic link:
```
step_metadata_dir - the dir specified in this flag is created to hold a step specific metadata
step_metadata_dir_link - the dir specified in this flag is created as a symbolic link to step_metadata_dir
```
`step_metadata_dir` is set to `/tekton/steps/step-step0` and
`step_metadata_dir_link` is set to `/tekton/steps/0` for the entrypoint of the
first step in the above example task.
Notice an additional entries `0`, `1`, and `2` showing under `/tekton/steps/`.
These are symbolic links created which are linked with their respective step
directories, `step-step0`, `step-unnamed-1`, and `step-step2`. These symbolic
links are created to provide simplified access to the step metadata directories
i.e., instead of referring to a directory with the step name, access it via the
step index. The step index becomes complex and hard to keep track of in a task
with a long list of steps, for example, a task with 20 steps. Creating the step
metadata directory using a step name and creating a symbolic link using the step
index gives the user flexibility, and an option to choose whatever works best
for them.
## How to access the exit code of a step from any subsequent step in a task
The entrypoint now allows exiting with an error and continue running rest of the
steps in a task i.e., it is possible for a step to exit with a non-zero exit
code. Now, it is possible to design a task with a step which can take an action
depending on the exit code of any prior steps. The user can access the exit code
of a step by reading the file pointed by the path variable
`$(steps.step-<step-name>.exitCode.path)` or
`$(steps.step-unnamed-<step-index>.exitCode.path)`. For example:
- `$(steps.step-my-awesome-step.exitCode.path)` where the step name is
`my-awesome-step`.
- `$(steps.step-unnamed-0.exitCode.path)` where the first step in a task has no
name.
The exit code of a step is stored in a file named `exitCode` under a directory
`/tekton/steps/step-<step-name>/` or `/tekton/steps/step-unnamed-<step-index>/`
which is reserved for any other step specific information in the future.
If you would like to use the tekton internal path, you can access the exit code
by reading the file (which is not recommended though since the path might change
in the future):
```shell
cat /tekton/steps/step-<step-name>/exitCode
```
And, access the step exit code without a step name:
```shell
cat /tekton/steps/step-unnamed-<step-index>/exitCode
```
Or, you can access the step metadata directory via symlink, for example, use
`cat /tekton/steps/0/exitCode` for the first step in a task.
## TaskRun Use of Pod Termination Messages
Tekton Pipelines uses a `Pod's`
[termination message](https://kubernetes.io/docs/tasks/debug-application-cluster/determine-reason-pod-failure/)
to pass data from a Step's container to the Pipelines controller. Examples of
this data include: the time that execution of the user's step began, contents of
task results, contents of pipeline resource results.
The contents and format of the termination message can change. At time of
writing the message takes the form of a serialized JSON blob. Some of the data
from the message is internal to Tekton Pipelines, used for book-keeping, and
some is distributed across a number of fields of the `TaskRun's` `status`. For
example, a `TaskRun's` `status.taskResults` is populated from the termination
message.
## Experimentally Disabling PipelineRef and TaskRef Resolution
In
[TEP-0060](https://github.com/tektoncd/community/blob/main/teps/0060-remote-resource-resolution.md)
we are exploring ways for the Tekton Pipelines controller to offload
resolution of `taskRefs` and `pipelineRefs` to external systems. The
idea is to allow for resolution of these resources from locations that
aren't supported directly by Pipelines, for example pulling in `Tasks`
and `Pipelines` from `git` repos.
To support this functionality Pipelines has an experimental flag to
allow a developer to disable resolution in the TaskRun and PipelineRun
reconcilers. To do so add `-experimental-disable-in-tree-resolution` as
an additional `arg` passed to the `tekton-pipelines-controller` in its
[Deployment YAML](../../config/controller.yaml). Once this is done
you're free to experiment with non-Pipelines resolution mechanisms.