Namaste Developers! 👋
Welcome to Part 2 of Mastering Amazon S3 Vectors – The Desi Developer Series!
In Part 1, we explored what vectors are, the magic behind semantic search, and how Amazon S3 Vectors works in simple desi style.
Let's get hands-on immediately, but first we need to know where this service is available — because S3 Vectors is in preview 🔍, just like any new AWS service.
🧪⚠️ S3 Vectors is in Preview (Beta Zone Alert)
There may be changes before the complete release of Amazon S3 Vectors, which is in preview release for Amazon Simple Storage Service (S3).
For testing, learning, and early versions, this is ideal, but don't use it in production just yet.
🌍 Supported AWS Regions (Preview Phase)
You can currently create Vector Buckets only in the following AWS regions:
| Region Name | Region Code |
|---|---|
| US East (N. Virginia) | us-east-1 |
| US East (Ohio) | us-east-2 |
| US West (Oregon) | us-west-2 |
| EU Central (Frankfurt) | eu-central-1 |
| Asia Pacific (Sydney) | ap-southeast-2 |
💡 Choose one of these regions while experimenting. If you try to use another region, it simply won’t work yet.
🧠 Vector Bucket Naming Rules
When creating a vector bucket, follow these rules:
- Names must be between 3 and 63 characters, all lowercase (a to z, 0 to 9, -), and beginning and ending with a letter or number.
- Bucket names must be unique per Region within your AWS account.
🛠️ Creating Your First Vector Bucket (us-east-1)
For this demo, we’ll use the us-east-1 (N. Virginia) region.
Step 1: Select "Create vector bucket"
Step 2: Fill in bucket details and create
Step 3: Bucket successfully created
📌 Vector Bucket ARN Format
The ARN (Amazon Resource Name) format for a vector bucket looks like this:
arn:aws:s3vector:Region:AccountID:bucket/bucket-name
🔹 Example:
arn:aws:s3vector:us-east-1:123:bucket/my-vector-bucket
- Replace
<Region>with your AWS region (e.g.,us-east-1) - Replace
<AccountID>with your AWS account ID - Replace
<bucket-name>with your vector bucket name
🧠 What is a Vector Index?
Vector data is stored and arranged for quick similarity search using a Vector Index that resides inside a vector bucket.
When creating a vector index, you define:
-
Distance Metric:
CosineorEuclidean - Dimensions: Number of values in each vector (1–4096)
- Optional: Metadata fields to exclude from filtering
🧾Vector Index ARN Format
arn:aws:s3vectors:region:account-id:bucket/bucket-name/index/index-name
🧩 Naming Rules
- 3–63 characters
- Only lowercase letters, numbers, hyphens (-), and dots (.)
- Must start and end with a letter or number
📏 Dimension Rules
- All vectors must have the same number of dimensions
- Value must be between 1 and 4096
📐 Distance Metrics
- Cosine: Best for normalized vectors (direction-focused)
- Euclidean: Best when both magnitude and direction matter
🛠️ Creating Your First Vector Index (us-east-1)
For this demo, we’ll use the us-east-1 (N. Virginia) region.
Step 1: Select "Select vector bucket"
Step 2: Provide Index details and create
Step 3: Index successfully created
🏁 Wrap-Up
That’s it doston! 🎉 You’ve successfully learned how to create a Vector Bucket and a Vector Index using the AWS Console.
Here’s a quick recap:
- 📦 Vector Buckets help you store embeddings.
- 🧮 Vector Indexes organize those vectors for similarity search.
- 📏 Choose the right Distance Metric (
CosineorEuclidean) for your use case. - 🧠 Set the dimensions carefully (should match your embedding model).
- 🔐 Use the ARN format when integrating with IAM or APIs.
👉 Stay tuned, hit the ❤️ if you found this helpful, and drop your questions in the comments below!
📚 More Learning
👨💻 About Me
Hi! I'm Utkarsh, a Cloud Specialist & AWS Community Builder who loves turning complex AWS topics into fun chai-time stories ☕
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