I am running this error during the "DOWNLOAD_SOURCE" phase in CodeBuild:
"invalid pkt-len found"
No other information is provided. I have tried various things to rule out problems.
a) The CodeCommit repo clones successfully, and appears to be fully functional.
b) Building from an earlier revision on this CodeCommit repository that had previously built successfully now throw this error -- Fails with same error message
b) Building from a separate CodeCommit repository with a separate CodeBuild project that has previously built successfully AND has no new commits -- Fails with same error
c) A brand new CodeBuild project and CodeCommit repo -- Does not fail
d) Building the same CodeBuild job that fails, with a zip file (of the same code base) as source instead of CodeCommit, and it does not fail.
I was getting the same error in Codebuild. Turned out, I was using a URL of a sub-folder in the repository. Since it was not a proper Git repo URL, it was throwing an invalid pkt len error. I hope this helps somebody who stumbles onto the same error.
Got a response from AWS - this was an issue on their end, which they have resolved.
Related
I am not sure why this file cannot be found.
I am using Dagster to run the DBT Docs Generate command, upload those files to S3 so that they can be deployed via CI/CD to an ngnix server.
The documentation will sometimes load after a fresh deploy, but quickly will throw the above error. I can confirm, though, that the debug and docs generate CLI commands produce no error(s), and all the files (including the catalog.json) are present on the ngninx server.
I am not sure how to debug this weird issue. Thanks!
I tried running the docs generate command with the --no-compile flag, but it produces the same result.
If I check the 'Build phase' tab of a CodeBuild project called from CodePipeline using CODEBUILD_CLONE_REF, I get the following error:
Internal Service Error: CodeBuild is experiencing issues
AWS support responded that this can be caused by having too many 'git refs' in the repo. At the time of this writing, CodeBuild uses a go-lang -based library for handling git and the library has a known limitation.
AWS support recommended switching to the CODE_ZIP method of passing code between the CodePipeline 'source' stage and the CodeBuild stage at issue.
We might also try to reduce the number of refs in the repo.
When running dbt deps, I get back this error message:
Running with dbt=0.17.0
Error sending message, disabling tracking
Encountered an error:
Unable to connect to registry hub
What's happening here, and how can I work around it?
First of all, it's worth understanding what's going on here. It looks like you're trying to install a package from the dbt hub site (hub.getdbt.com) — if you open up your packages.yml file, you'll find something like this:
packages:
- hub: package-owner/package-name
version: 0.1.0
When you run dbt deps (at a high level):
dbt sends a request to hub.getdbt.com
From hub.getdbt.com, a request is sent to GitHub to download the package.
The package is copied into your project
This error occurs if dbt cannot connect to the hub site after sending a network request repeatedly. First off, we recommend you retry the dbt deps command — sometimes it's just a blip in connectivity that goes away on the second try.
If the error persists, there may be a few different reasons for it:
hub.getdbt.com might be unavailable. This happens but is relatively rare. You can navigate to hub.getdbt.com to check if this is the case. Also check the Netlify status page to see if there are any issues.
GitHub might be down — you can check this by going to the GitHub status page.
Finally, it may be that a firewall rule or antivirus software on your computer is rejecting the request. Talk to your IT team to find out if this is the case and whether that restriction can be removed.
We generally recommend using the hub syntax for packages, however if you need to work around it, you can consider using the git syntax (docs) or installing the package from a local directory (docs)
I've run into an issue using MLflow server. When I first ran the command to start an mlflow server on an ec2 instance, everything worked fine. Now, although logs and artifacts are being stored to postgres and s3, the UI is not listing the artifacts. Instead, the artifact section of the UI shows:
Loading Artifacts Failed
Unable to list artifacts stored under <s3-location> for the current run. Please contact your tracking server administrator to notify them of this error, which can happen when the tracking server lacks permission to list artifacts under the current run's root artifact directory.
But when I check in s3, I see the artifact in the s3 location that the error shows. What could possibly have started causing this as it used to work not too long ago and nothing was changed on the ec2 that is hosting mlflow?
I found the answer. The error was that mlflow could not find boto3, so a conda installation of that worked. The logs for this were buried and hard to find in stdout.
I am trying to create a deployment pipeline for Gitlab-CI on a react project. The build is working fine and I use artifacts to store the dist folder from my yarn build command. This is working fine as well.
The issue is regarding my deployment with command: aws s3 sync dist/'bucket-name'.
Expected: "Done in x seconds"
Actual:
error Command failed with exit code 2. info Visit https://yarnpkg.com/en/docs/cli/run for documentation about this command. Running after_script 00:01 Uploading artifacts for failed job 00:01 ERROR: Job failed: exit code 1
The files seem to have been uploaded correctly to the S3 bucket, however I do not know why I get an error on the deployment job.
When I run the aws s3 sync dist/'bucket-name' locally everything works correctly.
Check out AWS CLI Return Codes
2 -- The meaning of this return code depends on the command being run.
The primary meaning is that the command entered on the command line failed to be parsed. Parsing failures can be caused by, but are not limited to, missing any required subcommands or arguments or using any unknown commands or arguments. Note that this return code meaning is applicable to all CLI commands.
The other meaning is only applicable to s3 commands. It can mean at least one or more files marked for transfer were skipped during the transfer process. However, all other files marked for transfer were successfully transferred. Files that are skipped during the transfer process include: files that do not exist, files that are character special devices, block special device, FIFO's, or sockets, and files that the user cannot read from.
The second paragraph might explain what's happening.
There is no yarn build command. See https://classic.yarnpkg.com/en/docs/cli/run
As Anton mentioned, the second paragraph of his answer was the problem. The solution to the problem was removing special characters from a couple SVGs. I suspect uploading the dist folder as an artifact(zip) might have changed some of the file names altogether which was confusing to S3. By removing ® and + from the filename the issue was resolved.