Merge pull request #1616 from iterative/july_gems

July gems

content/blog/2020-07-22-july-20-community-gems.md

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+---
+title: July '20 Community Gems
+date: 2020-07-31
+description: |
+  A roundup of technical Q&A's from the DVC community. This month, we discuss 
+  getting started with CML, configuring your DVC cache, and how to request a 
+  tutorial video.
+descriptionLong: |
+  A roundup of technical Q&A's from the DVC community. This month, we discuss 
+  getting started with CML, configuring your DVC cache, and how to request a 
+  tutorial video.
+picture: 2020-07-31/Gems_July_20.png
+author: elle_obrien
+commentsUrl: https://discuss.dvc.org/t/july-20-community-gems/460
+tags:
+  - Discord
+  - Gems
+  - CML
+  - GCP
+  - DVC 1.0
+---
+
+Here are some of our top Q&A's from around the community. With the launch of
+[CML](https://cml.dev) earlier in the month, we've got some new ground to cover!
+
+## DVC questions
+
+### [Q: Recently, I set up a global DVC remote. Where can I find the config file?](https://discordapp.com/channels/485586884165107732/563406153334128681/717673618217238598)
+
+When you
+[create a global DVC remote](https://dvc.org/doc/command-reference/remote/list#options),
+a config file will be created in `~/.config/dvc/config` instead of your project
+directory (i.e., `.dvc/config`).
+
+Note that on a Windows system, the config file will be created at
+`C:\Users\<username>\AppData\Local\iterative\dvc\config`.
+
+### [Q: I'm working on a collaborative project, and I use `dvc pull` to sync my local workspace with the project repository. Then, I try running `dvc repro`, but get an error: `dvc.yaml does not exist`. No one else on my team is having this issue. Any ideas?](https://discordapp.com/channels/485586884165107732/485596304961962003/731188065078345799)
+
+This error suggests there is no `dvc.yaml` file in your project. Most likely,
+this means your teammates are using DVC version 0.94 or earlier, before the
+`dvc.yaml` standard was introduced. Meanwhile, it sounds like you're using
+version 1.0 or later. You can check by running
+
+```dvc
+$ dvc version
+```
+
+The best solution is for your whole team to upgrade to the latest version- and
+there's an easy
+[migration script to help you make the move](https://towardsdatascience.com/automatically-migrate-your-project-from-dvc-0-94-to-dvc-1-x-416a5b9e837b).
+If for some reason this won't work for your team, you can either downgrade to a
+previous version, or use a workaround:
+
+```dvc
+$ dvc repro <.dvc stage file>
+```
+
+substituting the appropriate `.dvc` file for your pipeline. DVC 1.0 is backwards
+compatible, so pipelines created with previous versions will still run.
+
+### [Q: Does the DVC installer for Windows also include the dependencies for using cloud storage, like S3 and GCP?](https://discordapp.com/channels/485586884165107732/485596304961962003/715717911574216735)
+
+If you're installing DVC from binary-such as the `dvc.exe`
+[downloadable on the DVC homepage](https://dvc.org/)- all the standard
+dependencies are included. You shouldn't need to use `pip` to install extra
+packages (like `boto` for S3 storage).
+
+### [Q: Is there a way to setup my DVC remote so I can manually download files from it without going through DVC?](https://discordapp.com/channels/485586884165107732/563406153334128681/717458695709130764)
+
+When DVC adds a file to a remote repository (such as an S3 bucket, or an SSH
+file server), there's only one change happening: DVC calculates an md5 for the
+file and renames it with that md5. In technical terms, it's storing files in a
+"content-addressable way". That means if you know the hash of a file, you can
+locate it in your DVC remote and manually download it.
+
+To find the hash for a given file, say `data.csv`, you can look in the
+corresponding DVC file:
+
+```dvc
+$ cat data.csv.dvc
+```
+
+Another approach is using a built-in DVC function:
+
+```dvc
+$ dvc get --show-url . data.csv
+```
+
+You can read more about `dvc get --show-url` in
+[our docs](https://dvc.org/doc/command-reference/get#options). Note that this
+functinality is also part of our Python API, so you can locate the path to a
+file in your remote within a Python environment.
+[Check out our API docs!](https://dvc.org/doc/api-reference/get_url)
+
+### [Q: By default, each DVC project has its own cache in the project repository. To save space, I'm thinking about locally creating a single cache folder and letting multiple project repositories point there. Will this work?](https://discordapp.com/channels/485586884165107732/563406153334128681/736164141701791815)
+
+Yes, we hear from many users who have created a
+[shared cache](https://dvc.org/doc/use-cases/shared-development-server#configure-the-external-shared-cache).
+Because of the way DVC uses content-addressable filenames, you won't encounter
+issues like accidentally overwriting files from one project with another.
+
+A possible issue is that a shared cache will grant all teammates working on a
+given project access to the data from all other projects using that cache. If
+you have sensitive data, you can create different caches for projects involving
+private and public data.
+
+To learn more about setting your cache directory location,
+[see our docs](https://dvc.org/doc/command-reference/cache/dir).
+
+## CML questions
+
+### Q: I use Bitbucket. Will CML work for me?
+
+The first release of CML is compatible with GitHub and GitLab. We've seen
+[many requests for Bitbucket support](https://github.com/iterative/cml/issues/140),
+and we're actively investigating how to add this. Stay tuned.
+
+### [Q: I have on-premise GPUs. Can CML use them to execute pipelines?](https://discordapp.com/channels/485586884165107732/728693131557732403/730070747388706867)
+
+Yep! You can use on-premise compute resources by configuring them as self-hosted
+runners. See
+[GitHub](https://docs.github.com/en/actions/hosting-your-own-runners/about-self-hosted-runners)
+and [GitLab](https://docs.gitlab.com/runner/)'s official docs for more details
+and setup instructions.
+
+### [Q: I'm building a workflow that deploys a GCP Compute Engine instance, but I can only find examples with AWS EC2 in the CML docs. What do I do?](https://discordapp.com/channels/485586884165107732/728693131557732403/730688592787275806)
+
+There is a slight difference in the way CML handles credentials for AWS and GCP,
+and that means you'll have to modify your workflow file slightly. We've added an
+example workflow for GCP to our
+[project README](https://github.com/iterative/cml#allocating-cloud-resources-with-cml).
+
+We've updated our
+[cloud compute use case repository docs](https://github.com/iterative/cml_cloud_case#using-a-different-cloud-service)
+to cover a GCP example.
+
+Note that for Azure, the workflow will be the same as for AWS. You'll only have
+to change the arguments to `docker-machine`.
+
+### [Q: I don't see any installation instructions in the CML docs. Am I missing something?](https://discordapp.com/channels/485586884165107732/728693131557732403/733659483758133269)
+
+Nope, there's no installation unless you wish to install CML in your own Docker
+image. As long as you are using GitHub Actions or GitLab CI with the CML Docker
+images, no other steps are needed.
+
+If you're creating your own Docker image to be used in a GitHub Action or GitLab
+CI pipeline, you can add CML to your image via npm:
+
+```bash
+$ npm i -g @dvcorg/cml
+```
+
+### [Q: Can I use CML with MLFlow?](https://www.youtube.com/watch?v=9BgIDqAzfuA&lc=Ugw-VxQqAaqi9hmqB3t4AaABAg)
+
+CML is designed to integrate with lots of tools that ML teams are already
+familiar with. For example, we set up a wrapper to use CML with Tensorboard, so
+you get a link to your Tensorboard in a PR whenever your model is training
+([check out the use case](https://github.com/iterative/cml_tensorboard_case/pull/3)).
+
+While we haven't yet tried to create a use case with MLFlow in particular, we
+think a similar approach could work. We could imagine using MLFlow for
+hyperparameter searching, for example, and then checking in your best model with
+Git to a CI system for evaluation in a production-like environment. CML could
+help you orchestrate compute resources for model evaluation in your custom
+environment, pulling the model and any validation data from cloud storage, and
+reporting the results in a PR.
+
+If this is something you're interested in, make an issue on our project
+repository to tell us more about your project and needs- that lets us know it's
+a priority in the community.
+
+### Q: Are there more tutorial videos coming?
+
+Yes! We recently launched
+[our first CML tutorial video](https://dvc.org/blog/first-mlops-tutorial), and a
+lot of folks let us know they want more. We're aiming to release a new video
+every week or so in the coming months. Topics will include:
+
+- Using DVC to push and pull data from cloud storage to your CI system
+- Using CML with your on-premise hardware
+- Building a data dashboard in GitHub & GitLab for monitoring changes in dynamic
+  datasets
+- Provisioning cloud compute from your CI system
+- Creating a custom Docker container for testing models in a production-like
+  environment
+
+We really want to know what use cases, questions, and issues are most important
+to you. This will help us make videos that are most relevant to the community!
+If you have a suggestion or idea, no matter how small, we want to know. Leave a
+[comment on our videos](https://youtu.be/9BgIDqAzfuA),
+[reach out on Twitter](https://twitter.com/dvcorg), or
+[ping us in Discord](https://discord.gg/bzA6uY7).