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Try running with -d detached flag docker run -td -p 3000:3000 -p 6379:6379 -p 8983:8983 my_dockerhub/image # here ^ Containers started in detached mode exit when the root process used to run the container exits. This will prevent the step to freeze at docker run stage. Docker docs -d flag

I found the answer in this github issue https://github.com/docker/cli/issues/1809 if DOCKER_HOST environment variable is set, we ignore the current context setting. Bitbucket sets this environment variable to the default context meaning I was unable to swap docker context. Once I added the command unset DOCKER_HOST the context switch succeeded and docker ...

You need to separate your daily authentication method of the CD authentication. You should start understanding the different methods that K8S offers https://kubernetes.io/docs/admin/authentication/ On the other hand if you use some cloud solution like GCP you can benefit of the service account that the platform puts in all your instances, setting the right ...

Unlike the declarative pipelines in Jenkins, bitbucket does not seem to have such functionality. In order to prevent code duplication a script was created and the current bitbucket-pipelines looks as follows: options: docker: true pipelines: default: - step: script: - ./build-script.sh API true true - step: script: ...

A bit too long for a comment, so converting to an answer: That's super broad and highly depends on your final needs IMHO, if you're full AWS and ok with being vendor locked down, then code commit/code build/code pipeline is great as it's nicely integrated now. If you have needs outside pure AWS services, that may get harder, for exemple if you plan on ...

Key issue with this approach is that applying commits selectively is extremely problematic. Basically, how do you know whether commits are dependent or independent? As you correctly mentioned, this is one of the issues with Gitflow itself, so the solution is shifting methodologies. Preferred way today is Trunk-Based Development (TBD) - https://...

the idea is for each team member to have his/her own environment assigned, but deploy using a shared parametrized pipeline You could use definitions for the steps for each environment. definitions: steps: - step: deploy to staging1 script: - echo "Staging 1" - step: deploy to staging2 script: - echo "Staging 2" ...

You can install the Heroku CLI via npm - which might be the simplest. Note that your Heroku API key has to have the env var name HEROKU_API_KEY for the Heroku CLI to accept it as an auth token (ie. to avoid having to do heroku login). - npm install -g heroku # build the Docker image (this will use the Dockerfile in the root of the ...

The author of the Q&A indicated that the issue has been solved since absolute paths were used.

You can be done this task using below steps: 1: Creating the Bitbucket Git Repository And Adding our Application and Docker Configurations in it 2: Integrating Bitbucket with ACR 3: Deploying The Application 4: Securing our Application with Let’s Encrypt SSL/TLS for full details check this:

I suspect that Bitbucket pipelines is enforcing this memory limit, not docker-compose. This is nothing to do with the Linux kernel's OOM killer. The page you linked is about memory limits in additional containers (e.g. for a database) used by the pipeline, not the pipeline itself. Some suggestions: Try editing bitbucket-pipelines.yml to include a size ...