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What permission is required to deploy release?

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Oba22 last edited by

What permission is required to allow a user to manually deploy (or redeploy) a stage in an Azure DevOps Release Pipeline?
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chanisef last edited by

Found it!

The permissions are set on each release pipeline itself:

"Manage Deployments" allows users to come in and deploy to their environment without allowing them to edit the pipeline.
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If you can keep one common deployment strategy across both that would be simpler and less effort from the ops side of things. Kubernetes seems to be a great choice for the cloud orchestration layer at this point in time. Does Kubernetes make sense for the on-prem side though? If you're not planning on each on-prem install including 5-10 servers to spread Kubernetes out over then it probably doesn't make sense to use it there. All hope is not lost. You could take the same Docker containers that you ran under Kubernetes and run them yourself for on-prem. You're going to be stuck dealing with service discovery, but if you're only installing on one server that can be solved in some old school way like picking and assigning ports to specific services.
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airtower-luna from GitHub community answered it here and it worked for me Answer pasted below: The command in your workflow file is not the same as the one in your sudoers file, sudo doesn’t know they are functionally equivalent. Use twentydb.service in the workflow, too. Also, is the user your runner runs as in the sudo group? If not, that entry won’t apply to it. However, I’d suggest using a separate entry for the user rather than adding the runner to the sudo group.
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Yes this happens frequently when debugging helm releases. The problem happens when a previously failed release is preventing you from updating it. If you run helm ls you should see a release in state FAILED. You might have deleted it in which case it might show up with helm ls -a. Such a release cannot be upgraded using the normal approach of having helm compare the new yaml to the old yaml to detect what objects to change as it is a failed release. As this normally happens when trying to get something new running I typically helm delete —purge the failed release. That is slightly drastic though so you may want to try to do the upgrade adding —force https://github.com/helm/helm/pull/2280
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Your question is a little bit confusing and led to some interpretations. First, for Jenkins, you should always run your pipelines using Jenkins agents, it is a good practice. The deploy stage is to - well, as the name -- deploy to somewhere. The way you are going to deploy totally depends on what you are deploying and where, you can use an API, a CLI, SSH, or even an SFTP. You can also store your artifact in a artifact server (Nexus, Docker Hub, Artifactory) and then tell your server to pull the image from there. Wrapping up: In the deploy stage, put the code to deploy the artifact (.exe, .war, .zip...) anywhere you want. The deploy stage will run inside an agent/runner, this runner will connect to the destination system through CLI, API... to deploy the artifact.
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This article very clearly explains how to deploy a nodejs app using Jenkins: https://blog.couchbase.com/create-continuous-deployment-pipeline-nodejs-jenkins/
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Using a shared virtualenv for automation while also expecting the virtualenv's content to be (automatically) updated without the automation's knowledge/control is not a good practice - opening up for all kinds of obscure/intermittent/hard to reproduce failures. So I wouldn't spend too much time trying to figure out a solid way of updating your package in the shared virtualenv without hitting the automation jobs - sooner or later they'll be hit by other problems stemming from the same root cause - using a shared virtualenv. Think back at the very reason(s) for using a virtualenv in the first place. For consistent results automation should ensure that the virtualenv content is updated as needed as a preliminary step and does not (unexpectedly) change while the job is performed. Which isn't really possible with a virtualenv shared across multiple independent automation jobs. It might be possible with coordinated jobs, all sharing a common step that performs the virtualenv updates in a controlled manner to ensure virtualenv's consistency during jobs, but IMHO it's just not worthy to build such complex system, it's much simpler to not share the virtualenv and keep the jobs independent. If, regardless of these considerations, the request for a shared virtualenv still stands then don't update the virtualenv outside (well defined and announced) maintenance windows during which execution of the automation jobs should be suspended. As a side note it's also not a good practice to not version your packages, unless maybe if you have a very clear and easily accessible indication of the exact code version being used in each particular case (the commit SHA for example) - when problems occur you'll most likely need that info when attempting to reproduce the problem, debug it and/or verify fixes with some degree of certainty.
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The stock Azure Pipelines app for Slack does not support that workflow of uploading artifacts to Slack. You could use this marketplace task and upload your release notes artifact with it. Bonus points suggestion, if you are going down the release notes path I would take a look at using Richard Fennell's Generate Release Notes task in combination with the Wiki Updater task. You can create a generalized Task Group or yaml template that you could pretty much re-use anywhere. For example in the Wiki updater task you can create a release name wiki page formatted like: $(Build.Repository.Name)\$(Release.EnvironmentName)\$(Release.ReleaseName).md And then in your Slack message send a generalized link to your release notes. Release Notes Wiki link ``` You could push them back into the Repo that the release originated from or a central release notes repository. Your release notes get source controlled and are nicely organized!
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Yes, disabling an application prevents charges, but only from the App Engine prospective, there could still be other changes from other Cloud products usage. From Disabling an application: Your app's resources in both the standard and flexible environment are disabled and therefore, won't incur charges. However, billing charges can still occur for the other services in your Cloud Platform project, for example you can still incur storage charges for your stored data. To completely end all Cloud billing for a project you can shut it down (i.e. mark it for deletion!). But please note that you won't be able to re-use its ID, ever.
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Quoting from the cookbook README: deploy_key – SSH key to use with git. Can be specified either as a path to key file already created or as a string value containing the key directly. And: The application_git resource deploys code from git. It extends the core git resource to support deploy keys and disabling strict host key verification. So checking the core git resource documentation: ssh_wrapper Ruby Type: String The path to the wrapper script used when running SSH with git. The GIT_SSH environment variable is set to this. so something like this (untested) should do (using the wrapper in the cookbook) : cookbook_file '/path/to/my/desired/ssh_wrapper.sh' do source 'my_ssh_wrapper.sh' end application 'accounts' do action :deploy path <somepath> owner 'nobody' group 'nogroup' git 'name' do repository <repopath> revision <value> ssh_wrapper '/path/to/my/desired/ssh_wrapper.sh' deploy_key deploy_key end end You can of course do the same with the deploy_key, but using something like chef_vault or an encrypted databag sounds better to avoid commiting deploy keys within the cookbook.
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Monorepos are nice because it eliminates the technical constraints between multiple projects. This does however open the door to other complications within your repository (naming conventions, cross-team dependencies, merge conflict increases, etc.). I do not have any experience with CircleCI, but I will provide some input based on other CI tools I have used. I don't see any reason why you wouldn't be able to. In your CI/CD system, instead of referencing your individual source repositories, you will use your main monorepo as the source repository and then reference the specific project directory within it. It looks like as of GitLab version 9.1 this is supported. In my opinion, this wouldn't be something that would happen on commit. You could do this, but I think it would slow down your development speed significantly and use up a lot of resources if you have many commits. The two key points to consider are: Before every production release, you should run a full suite test on all projects in your infrastructure. This is the only way to be certain that all project dependencies are non-breaking. Tests/provisionings must run in parallel. By doing this, your full repository testing speed will be the length of the longest test/provisioning in your repository. (As a side effect, this puts an emphasis on speeding up your slowest test)
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Since we go through the entire microservice spin-up process manually each time a new pod comes through, we're looking to automate as much of this as possible. This is typically what a Platform Team does. Its good to provide a "Self Serve Portal" - e.g. so that developers can just intiate these things themself - whenever they have a need for it. A project that tries to be an open source "developer portal" is Backstage, created by Spotify. Even if you don't choose to use Backstage, it can serve as inspiration. See e.g. Backstage: Spotify's platform developer experience
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IIRC tenants usually don't have privileges to see actual policy definitions, but depending on your configuration you should be able to see some info with openstack quota https://docs.openstack.org/python-openstackclient/xena/cli/command-objects/quota.html
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This is a general issue with react apps that is independent of what CI/CD stack you use that is discussed at https://stackoverflow.com/questions/49975735/rendering-an-environment-variable-to-the-browser-in-a-react-js-redux-production With the Azure family of CI/CD products it is expected you create a release artefact then release that same artefact into environments using a release workflow. That is a typical best practice and expected by ”enterprise” release management processes. The general manifesto of native cloud apps is 12factor.net, and it also advises to ”build once, deploy many times, configured by environment variables”. So its a bit of a surprise to me that the best practices isn't really known in the react community so you have to hunt around for solutions. In my case at that link above I didn't want to make deployments of our react apps different from our backend microservices where we have ”build once, run anywhere”. So we chanced the js code to fetch env vars from the server at page load. Also with this approach and by using containers we are guaranteed to always run the same front end libraries everywhere even if the front end build tool is misconfigured or buggy in terms of not always using the exact same dependency on every run. In your case you do have a release workflow where you can use all the same built-in and marketplace tasks of a build workflow. This means its straight forward to add a front-end compile task to the release workflows. On the downside a frontend build of a large react app can take a lot of time and a lot of memory. Memory probably won't be an issue for you. The time taken will be a little annoying. Yet the approach wouldn't be invasive so I would recommend it may be the least effort to set up and the easiest for colleagues to troubleshoot and maintain in the future as long as you have a stable frontend build. Historically npm was less reliable than other frontend builds at giving the exact same lib versions every run for the same package.json (e.g., npm vs. yarn). So you need to study that aspect and ensure that you are certain that every time you run the frontend build it is guaranteed to use the same exact dependency versions.
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I found the solution while trying to manually deploy the Lambda function as a jar file. These are the steps - Create your Lambda function as a Maven project using the AWS documentation. Create your Jenkins job as a Maven project and specify package in the goals section. Follow the Jenkins Lambda plugin documentation for deployment and specify target/your-project-1.0-SNAPSHOT.jar as the Artifact location. This should build your Lambda function with Maven and then deploy it to AWS.
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As you stated, requirements will differ based on company and industry policy; for us, the adjustment from "separation of duties" to automated deployments has been rough. As interim steps, we've started: Requiring multiple "sign-offs" before deployment; this is accomplished by both reviews for the PR in Azure DevOps and an audit log in Octopus. Monthly review of deployments by higher-ups. This is mostly a rubber-stamp activity, but it satisfies auditors.

What permission is required to deploy release?

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