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So far your data lives in DVC's local cache on one machine. Teammates and CI cannot reach it, so you need a shared place to store it.

A DVC remote is cloud or shared storage where your data cache is uploaded. Think of it like a Git remote, but for the heavy data instead of code.

DVC speaks to S3, Google Cloud Storage, Azure, SSH, and even a plain shared folder. You pick whatever storage your team already uses. ☁️

Use dvc remote add to register storage. The -d flag marks it as the default so push and pull use it automatically.

The remote setting lives in .dvc/config. Commit it to Git so every teammate inherits the same remote without extra setup.

DVC reads cloud credentials from your environment or AWS profile, never from the committed config. Secrets stay safe and out of version control.

Run dvc push to upload everything in your cache to the remote. Only files not already there are sent, so it stays fast.

A safe habit: push data first, then push code. That way the .dvc pointers in Git always point to data that already exists in the remote.

After cloning and git pull, a colleague runs dvc pull to download the exact datasets the .dvc files reference. Code and data reunite.

dvc fetch downloads data into the cache only, while dvc pull also restores it into your working folder. Pull is fetch plus checkout in one step.

Because the remote is content-addressed, unchanged files are never re-uploaded. Push only the bytes that are genuinely new. 🚀

Which command sends your tracked data from the local cache up to shared storage?

You added a DVC remote, committed its config, and used dvc push to upload data. Teammates run dvc pull to fetch the exact datasets your pointers reference.