---
title: "Quickstart"
slug: "dev-datastore-quickstart"
updated: 2026-10-28T02:15:03Z
published: 2026-10-28T02:15:03Z
canonical: "docs.vastdata.com/dev-datastore-quickstart"
---

> ## Documentation Index
> Fetch the complete documentation index at: https://docs.vastdata.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Quickstart

*Applies to VAST Cluster 5.5.*

In this quickstart you'll connect to VAST S3 with boto3, write an object with metadata, list it, read it back and delete it. Everything happens under the key prefix `docs-quickstart/` in a bucket you already have, and the last step removes what the quickstart created. It takes about 10 minutes once your platform team has given you a bucket and a key pair.

Each code block is complete on its own: it imports what it needs and connects. Below each block is the output you should see.

## Before you start

You need:

- **A bucket you can write to,** and its name. **Admin task: send to your platform team:** a view with the S3 Bucket protocol, with you (or your application's user) as the bucket owner or granted access through an identity policy. See [access](/develop/docs/dev-datastore-operations-access).
- **An S3 access key pair** for that user, and **an endpoint:** the DNS name or a virtual IP of a virtual IP pool that serves S3, with `http://` or `https://` in front. The port isn't configurable: use 80 for HTTP and 443 for HTTPS, which is what leaving it out does.
- Python 3.10 or later, and boto3:

```
pip install "boto3>=1.36"
```

Put your connection details in environment variables:

```
export AWS_S3_ENDPOINT_URL="http://s3.example.com"   # your endpoint
export AWS_ACCESS_KEY_ID="<access key>"
export AWS_SECRET_ACCESS_KEY="<secret key>"
export DATASTORE_BUCKET="<your bucket>"
```

If your endpoint uses HTTPS with a certificate your system doesn't trust, also set `AWS_CA_BUNDLE` to a file with the certificate. See [Python clients](/develop/docs/dev-datastore-integrations-python#https-and-certificates).

![Five items, in order, then your client connects. 1, platform team: a view with the S3 Bucket protocol, and NFS or SMB on the same view if you need them, with a host rule for NFS clients; or an S3 Endpoint view under which you may create buckets. 2, platform team: the view policy&apos;s security flavor, S3 Native for S3-first applications, which decides whose permissions apply. 3, platform team: an endpoint, the DNS name or virtual IPs of a pool that serves your tenant and protocols, over HTTP or HTTPS. 4, platform team: a VAST user with an S3 access key pair. 5, platform team: an identity policy on that user, and bucket policies if you need them. Then your client connects: boto3, the AWS CLI or Spark with the endpoint and key, or an NFS mount of the view.](https://cdn.us.document360.io/89b91113-5dc6-49db-86ec-57b16dc8ce56/Images/Documentation/ds-setup-flow.svg?sv=2026-02-06&spr=https&st=2026-11-08T08%3A54%3A34Z&se=2026-11-08T09%3A54%3A34Z&sr=c&sp=r&sig=OJYDiyCTM7MGkjQGO3S4EW4EH9hMNLb1DjNfU6Lrbi0%3D)

*What your platform team sets up, in order, before you connect.*

## Connect

Create a client and check that you can reach the bucket. The client uses path-style addressing (`http://endpoint/bucket/key`) and Signature Version 4, the configuration to use with VAST:

```
import os

import boto3
from botocore.config import Config

s3 = boto3.client(
    "s3",
    endpoint_url=os.environ["AWS_S3_ENDPOINT_URL"],
    region_name="us-east-1",  # any string works; SigV4 needs one
    config=Config(signature_version="s3v4", s3={"addressing_style": "path"}),
)
bucket = os.environ["DATASTORE_BUCKET"]

s3.head_bucket(Bucket=bucket)
print("bucket", bucket, "is reachable")
```

```
bucket dst-data is reachable
```

If this fails with `403`, your key can't access the bucket; with `404`, the bucket doesn't exist or isn't in your key's tenant. See [troubleshooting](/develop/docs/dev-datastore-troubleshooting-index).

## Write an object

Write a small object with a content type and one piece of your own metadata. The ETag the cluster returns for a single-part upload is the MD5 checksum of the data:

```
import hashlib
import os

import boto3
from botocore.config import Config

s3 = boto3.client(
    "s3",
    endpoint_url=os.environ["AWS_S3_ENDPOINT_URL"],
    region_name="us-east-1",
    config=Config(signature_version="s3v4", s3={"addressing_style": "path"}),
)
bucket = os.environ["DATASTORE_BUCKET"]

body = b"hello from the VAST DataStore quickstart\n"
resp = s3.put_object(
    Bucket=bucket,
    Key="docs-quickstart/hello.txt",
    Body=body,
    ContentType="text/plain",
    Metadata={"source": "quickstart"},
)
print("ETag is the MD5 of the data:", resp["ETag"].strip('"') == hashlib.md5(body).hexdigest())
```

```
ETag is the MD5 of the data: True
```

## List objects

List what's under the prefix. A listing returns up to 1,000 keys at a time; the paginator asks for the next page for you:

```
import os

import boto3
from botocore.config import Config

s3 = boto3.client(
    "s3",
    endpoint_url=os.environ["AWS_S3_ENDPOINT_URL"],
    region_name="us-east-1",
    config=Config(signature_version="s3v4", s3={"addressing_style": "path"}),
)
bucket = os.environ["DATASTORE_BUCKET"]

for page in s3.get_paginator("list_objects_v2").paginate(Bucket=bucket, Prefix="docs-quickstart/"):
    for obj in page.get("Contents", []):
        print(obj["Key"], obj["Size"])
```

```
docs-quickstart/hello.txt 41
```

## Read it back

Read the object, and then only its metadata with `head_object`:

```
import os

import boto3
from botocore.config import Config

s3 = boto3.client(
    "s3",
    endpoint_url=os.environ["AWS_S3_ENDPOINT_URL"],
    region_name="us-east-1",
    config=Config(signature_version="s3v4", s3={"addressing_style": "path"}),
)
bucket = os.environ["DATASTORE_BUCKET"]

obj = s3.get_object(Bucket=bucket, Key="docs-quickstart/hello.txt")
print(obj["Body"].read().decode(), end="")

head = s3.head_object(Bucket=bucket, Key="docs-quickstart/hello.txt")
print(head["ContentType"], head["ContentLength"], head["Metadata"])
```

```
hello from the VAST DataStore quickstart
text/plain 41 {'source': 'quickstart'}
```

Your metadata comes back without its `x-amz-meta-` prefix, as on AWS. More on metadata, tags and ranged reads is in [S3 objects](/develop/docs/dev-datastore-guides-s3-objects).

## Clean up

Delete everything under the prefix:

```
import os

import boto3
from botocore.config import Config

s3 = boto3.client(
    "s3",
    endpoint_url=os.environ["AWS_S3_ENDPOINT_URL"],
    region_name="us-east-1",
    config=Config(signature_version="s3v4", s3={"addressing_style": "path"}),
)
bucket = os.environ["DATASTORE_BUCKET"]

keys = [
    {"Key": obj["Key"]}
    for page in s3.get_paginator("list_objects_v2").paginate(Bucket=bucket, Prefix="docs-quickstart/")
    for obj in page.get("Contents", [])
]
if keys:
    s3.delete_objects(Bucket=bucket, Delete={"Objects": keys})
print("deleted", len(keys), "objects")
```

```
deleted 1 objects
```

## Next steps

- [Concepts](/develop/docs/dev-datastore-concepts-index): how buckets, views and keys relate, and what decides your permissions.
- [S3 objects](/develop/docs/dev-datastore-guides-s3-objects): metadata, tags, ranged reads, presigned URLs, conditional requests and renames.
- [Multiprotocol access](/develop/docs/dev-datastore-guides-multiprotocol): read the same objects as files over NFS.
- [Python clients](/develop/docs/dev-datastore-integrations-python): s3fs and PyArrow.