- Kubernetes v1.26 on VKE causes error when creating persistent volume
claim because of uppercase characters in name field
This patch is trivial just in order to get it working - happy to
implement differently.
The error in question:
```
The PersistentVolumeClaim "wp-01G1131R63FWBSPMA4ZAZTKLE-0-clone-0" is invalid: metadata.name: Invalid value: "wp-01G1131R63FWBSPMA4ZAZTKLE-0-clone-0": a lowercase RFC 1123 subdomain must consist of lower case alphanumeric characters, '-' or '.', and must start and end with an alphanumeric character (e.g. 'example.com', regex used for validation is '[a-z0-9]([-a-z0-9]*[a-z0-9])?(\.[a-z0-9]([-a-z0-9]*[a-z0-9])?)*')
```
close#1114
As long as the `VersionResponse` type is not changed the check will
fail/pass gracefully
example output:
```
{"level":"error","error":"GRPC version mismatch","time":"2023-03-19T19:49:09+01:00","message":"Server version next-6923e7ab does report grpc version 2 but we only understand 1"}
GRPC version mismatch
```
Closes https://github.com/woodpecker-ci/woodpecker/issues/1617
The `woodpecker exec` auto-detects the backend by iterating over a map
of backends. However, since Go 1 the runtime randomizes map iteration
order, so a random backend might be chosen during each execution.
PR changes to auto-detection to iterate over the backends list with
predefined priority: `docker`, `local`, `ssh`, `kubernetes`.
---------
Signed-off-by: Alexander Matyushentsev <AMatyushentsev@gmail.com>
Closes https://github.com/woodpecker-ci/woodpecker/issues/1615
The error described in
https://github.com/woodpecker-ci/woodpecker/issues/1615 is happening
because `Tail` method of the docker backend closes the instance of
`io.ReadCloser` it returns in `defer` function. As a result anything
that try to read data returned by `Tail` method eventually will attempt
to read from closes reader and get an error:
2171212c5a/pipeline/backend/docker/docker.go (L229)
The fix is just don't close returned reader and let the consumer of
`Tail` method do it. Good thing is that `Tail` is used only in one place
and reader is correctly closed:
2171212c5a/pipeline/pipeline.go (L231-L237)
Example of `woodpecker exec` output using pipeline from
https://github.com/woodpecker-ci/woodpecker/issues/1615 with the fix:
```
woodpecker exec .woodpecker.yaml
[step1:L0:0s] + echo step1
[step1:L1:0s] step1
[step2:L0:0s] + echo step2
[step2:L1:0s] step2
```
Signed-off-by: Alexander Matyushentsev <AMatyushentsev@gmail.com>
Co-authored-by: Lauris BH <lauris@nix.lv>
Try to fix#1495
It's very hard to reproduce it and only way to fix when it gets in this
state is woodpecker agent restart.
This anyway fixes problem if step mounts and
`WOODPECKER_BACKEND_DOCKER_VOLUMES` conflict
Since "success" and "failure" are the only two possible values, and
"success" is considered to be included by default, the existing code can
also be simplified a little.
This has the side effect of ignoring the "exclude" part of the
constraint completely. I put it in the tests just to make sure the
workaround in
https://github.com/woodpecker-ci/woodpecker/issues/1181#issuecomment-1347253585
continues to work as expected, but couldn't think of any legitimate use
cases for it.
Fixes#1181
Provide up to date drone compatibility environment variables to each step execution.
closes#1416
Before a step is executed, some environemnt variables are updated.
This ensures, that the updated environment variables are copied to their corresponding `DRONE_` environemt variables.
Side effect is that the `DRONE_` environemnt variables are no longer available in the metadata which should not harm as they are not used inside woodpecker.
closes#1181closes#834
Adds `ignore_failure` to pipeline steps. When it's set to true,
if the step fails the following steps continue to execute as if no failure had occurred.
---
failure enums idea:
* fail (default) = if other steps run in parallel, wait for them and
then let workflow fail
* cancel = if other steps run in parallel, kill them
* ignore = we mark the step as failed but it wont have any impact
at the moment we compile a script that we can pipe in as single command
this is because of the constrains the docker backend gives us.
so we move it into the docker backend and eventually get rid of it altogether
