This page shows you how to manage your existing serverless indexes.

For guidance on pod-based indexes, see Manage pod-based indexes.

​
List indexes

Use the list_indexes operation to get a complete description of all indexes in a project:

from pinecone.grpc import PineconeGRPC as Pinecone

pc = Pinecone(api_key="YOUR_API_KEY")

index_list = pc.list_indexes()

print(index_list)

The response will look like this:

[{
    "name": "docs-example-sparse",
    "metric": "dotproduct",
    "host": "docs-example-sparse-govk0nt.svc.aped-4627-b74a.pinecone.io",
    "spec": {
        "serverless": {
            "cloud": "aws",
            "region": "us-east-1"
        }
    },
    "status": {
        "ready": true,
        "state": "Ready"
    },
    "vector_type": "sparse",
    "dimension": null,
    "deletion_protection": "disabled",
    "tags": {
        "environment": "development"
    }
}, {
    "name": "docs-example-dense",
    "metric": "cosine",
    "host": "docs-example-dense-govk0nt.svc.aped-4627-b74a.pinecone.io",
    "spec": {
        "serverless": {
            "cloud": "aws",
            "region": "us-east-1"
        }
    },
    "status": {
        "ready": true,
        "state": "Ready"
    },
    "vector_type": "dense",
    "dimension": 1536,
    "deletion_protection": "disabled",
    "tags": {
        "environment": "development"
    }
}]

With the Python SDK, you can use the .names() helper function to iterate over the index names in the list_indexes() response, for example:

Python
from pinecone.grpc import PineconeGRPC as Pinecone
from pinecone import ServerlessSpec

for index_name in pc.list_indexes().names:
    print(index_name)

​
Describe an index

Use the describe_index endpoint to get a complete description of a specific index:

from pinecone.grpc import PineconeGRPC as Pinecone

pc = Pinecone(api_key="YOUR_API_KEY")

pc.describe_index(name="docs-example")

The response will look like this:

{'deletion_protection': 'disabled',
 'dimension': 1536,
 'host': 'docs-example-dense-govk0nt.svc.aped-4627-b74a.pinecone.io',
 'metric': 'cosine',
 'name': 'docs-example-dense',
 'spec': {'serverless': {'cloud': 'aws', 'region': 'us-east-1'}},
 'status': {'ready': True, 'state': 'Ready'},
 'tags': {'environment': 'development'},
 'vector_type': 'dense'}

Do not target an index by name in production.

When you target an index by name for data operations such as upsert and query, the SDK gets the unique DNS host for the index using the describe_index operation. This is convenient for testing but should be avoided in production because describe_index uses a different API than data operations and therefore adds an additional network call and point of failure. Instead, you should get an index host once and cache it for reuse or specify the host directly.

​
Delete an index

Use the delete_index operation to delete an index and all of its associated resources.

# pip install "pinecone[grpc]"
from pinecone.grpc import PineconeGRPC as Pinecone, PodSpec

pc = Pinecone(api_key="YOUR_API_KEY")

pc.delete_index(name="docs-example")

If deletion protection is enabled on an index, requests to delete it will fail and return a 403 - FORBIDDEN status with the following error:

Deletion protection is enabled for this index. Disable deletion protection before retrying.

Before you can delete such an index, you must first disable deletion protection.

You can delete an index using the Pinecone console. For the index you want to delete, click the three dots to the right of the index name, then click Delete.

​
Associate an embedding model

Integrated inference lets you upsert and search without extra steps for embedding data and reranking results.

To configure an existing serverless index for an embedding model, use the configure_index operation as follows:

The vector_type, metric, and dimension of the index must be supported by the specified embedding model.

# pip install --upgrade pinecone
from pinecone import Pinecone

pc = Pinecone(api_key="YOUR_API_KEY")

pc.configure_index(
    name="docs-example",
    embed={
      "model":"llama-text-embed-v2",
      "field_map":{"text": "chunk_text"}
    }
)

​
Configure deletion protection

This feature requires Pinecone API version 2024-07, Python SDK v5.0.0, Node.js SDK v3.0.0, Java SDK v2.0.0, or Go SDK v1.0.0 or later.

​
Enable deletion protection

You can prevent an index and its data from accidental deleting when creating a new index or after its been created. In both cases, you set the deletion_protection parameter to enabled.

Enabling deletion protection does not prevent namespace deletions.

To enable deletion protection when creating a new index:

# pip install "pinecone[grpc]"
# Serverless index
from pinecone.grpc import PineconeGRPC as Pinecone
from pinecone import ServerlessSpec

pc = Pinecone(api_key="YOUR_API_KEY")

pc.create_index(
  name="docs-example",
  dimension=1536,
  metric="cosine",
  spec=ServerlessSpec(
    cloud="aws",
    region="us-east-1"
  ),
  deletion_protection="enabled"
)

To enable deletion protection when configuring an existing index:

from pinecone.grpc import PineconeGRPC as Pinecone

pc = Pinecone(api_key="YOUR_API_KEY")

pc.configure_index(
   name="docs-example", 
   deletion_protection="enabled"
)

When deletion protection is enabled on an index, requests to delete the index fail and return a 403 - FORBIDDEN status with the following error:

Deletion protection is enabled for this index. Disable deletion protection before retrying.

​
Disable deletion protection

Before you can delete an index with deletion protection enabled, you must first disable deletion protection as follows:

from pinecone.grpc import PineconeGRPC as Pinecone

pc = Pinecone(api_key="YOUR_API_KEY")

pc.configure_index(
   name="docs-example", 
   deletion_protection="disabled"
)

​
Configure index tags

Tags are key-value pairs that you can use to categorize and identify the index.

​
Add tags

To add tags to an index, use the tags parameter when creating a new index or when configuring an existing index.

To add tags when creating a new index:

from pinecone.grpc import PineconeGRPC as Pinecone
from pinecone import ServerlessSpec

pc = Pinecone(api_key="YOUR_API_KEY")

pc.create_index(
    name="docs-example",
    dimension=1536,
    metric="cosine",
    spec=ServerlessSpec(
        cloud="aws",
        region="us-east-1"
    ),
    deletion_protection="disabled",
    tags={
        "example": "tag", 
        "environment": "development"
    }
)

You can add tags during index creation using the Pinecone console.

To add or update tags when configuring an existing index:

from pinecone.grpc import PineconeGRPC as Pinecone

pc = Pinecone(api_key="YOUR_API_KEY")

pc.configure_index(
    name="docs-example", 
    tags={
        example: "tag", 
        environment: "development" 
    }
)

You can add or update tags when configuring an existing index using the Pinecone console. Find the index to edit and click the ellipsis (..) menu > Add tags.

​
View tags

To view the tags of an index, list all indexes in a project or get information about a specific index.

​
Remove tags

To remove a tag from an index, configure the index and use the tags parameter to send the tag key with an empty value ("").

The following example removes the example: tag tag from docs-example:

from pinecone.grpc import PineconeGRPC as Pinecone

pc = Pinecone(api_key="YOUR_API_KEY")

pc.configure_index(
    name="docs-example", 
    tags={"example": ""}
)

You can remove tags from an index using the Pinecone console. Find the index to edit and click the ellipsis (..) menu > __ tags.

​
List backups for an index

Serverless indexes can be backed up. You can list all backups for a specific index, as in the following example:

from pinecone import Pinecone

pc = Pinecone(api_key="YOUR_API_KEY")

index_backups = pc.list_backups(index_name="docs-example")

print(index_backups)

The example returns a response like the following:

[{
    "backup_id": "8c85e612-ed1c-4f97-9f8c-8194e07bcf71",
    "source_index_name": "docs-example",
    "source_index_id": "f73b36c9-faf5-4a2c-b1d6-4013d8b1cc74",
    "status": "Ready",
    "cloud": "aws",
    "region": "us-east-1",
    "tags": {},
    "name": "example-backup",
    "description": "Monthly backup of production index",
    "dimension": 1024,
    "record_count": 98,
    "namespace_count": 3,
    "size_bytes": 1069169,
    "created_at": "2025-05-15T00:52:10.809305882Z"
}]

You can view the backups for a specific index from either the Backups tab or the Indexes tab in the Pinecone console.

This page shows you how to manage your existing serverless indexes.

For guidance on pod-based indexes, see Manage pod-based indexes.

​
List indexes

Use the list_indexes operation to get a complete description of all indexes in a project:

from pinecone.grpc import PineconeGRPC as Pinecone

pc = Pinecone(api_key="YOUR_API_KEY")

index_list = pc.list_indexes()

print(index_list)

The response will look like this:

[{
    "name": "docs-example-sparse",
    "metric": "dotproduct",
    "host": "docs-example-sparse-govk0nt.svc.aped-4627-b74a.pinecone.io",
    "spec": {
        "serverless": {
            "cloud": "aws",
            "region": "us-east-1"
        }
    },
    "status": {
        "ready": true,
        "state": "Ready"
    },
    "vector_type": "sparse",
    "dimension": null,
    "deletion_protection": "disabled",
    "tags": {
        "environment": "development"
    }
}, {
    "name": "docs-example-dense",
    "metric": "cosine",
    "host": "docs-example-dense-govk0nt.svc.aped-4627-b74a.pinecone.io",
    "spec": {
        "serverless": {
            "cloud": "aws",
            "region": "us-east-1"
        }
    },
    "status": {
        "ready": true,
        "state": "Ready"
    },
    "vector_type": "dense",
    "dimension": 1536,
    "deletion_protection": "disabled",
    "tags": {
        "environment": "development"
    }
}]

With the Python SDK, you can use the .names() helper function to iterate over the index names in the list_indexes() response, for example:

Python
from pinecone.grpc import PineconeGRPC as Pinecone
from pinecone import ServerlessSpec

for index_name in pc.list_indexes().names:
    print(index_name)

​
Describe an index

Use the describe_index endpoint to get a complete description of a specific index:

from pinecone.grpc import PineconeGRPC as Pinecone

pc = Pinecone(api_key="YOUR_API_KEY")

pc.describe_index(name="docs-example")

The response will look like this:

{'deletion_protection': 'disabled',
 'dimension': 1536,
 'host': 'docs-example-dense-govk0nt.svc.aped-4627-b74a.pinecone.io',
 'metric': 'cosine',
 'name': 'docs-example-dense',
 'spec': {'serverless': {'cloud': 'aws', 'region': 'us-east-1'}},
 'status': {'ready': True, 'state': 'Ready'},
 'tags': {'environment': 'development'},
 'vector_type': 'dense'}

Do not target an index by name in production.

When you target an index by name for data operations such as upsert and query, the SDK gets the unique DNS host for the index using the describe_index operation. This is convenient for testing but should be avoided in production because describe_index uses a different API than data operations and therefore adds an additional network call and point of failure. Instead, you should get an index host once and cache it for reuse or specify the host directly.

​
Delete an index

Use the delete_index operation to delete an index and all of its associated resources.

# pip install "pinecone[grpc]"
from pinecone.grpc import PineconeGRPC as Pinecone, PodSpec

pc = Pinecone(api_key="YOUR_API_KEY")

pc.delete_index(name="docs-example")

If deletion protection is enabled on an index, requests to delete it will fail and return a 403 - FORBIDDEN status with the following error:

Deletion protection is enabled for this index. Disable deletion protection before retrying.

Before you can delete such an index, you must first disable deletion protection.

You can delete an index using the Pinecone console. For the index you want to delete, click the three dots to the right of the index name, then click Delete.

​
Associate an embedding model

Integrated inference lets you upsert and search without extra steps for embedding data and reranking results.

To configure an existing serverless index for an embedding model, use the configure_index operation as follows:

The vector_type, metric, and dimension of the index must be supported by the specified embedding model.

# pip install --upgrade pinecone
from pinecone import Pinecone

pc = Pinecone(api_key="YOUR_API_KEY")

pc.configure_index(
    name="docs-example",
    embed={
      "model":"llama-text-embed-v2",
      "field_map":{"text": "chunk_text"}
    }
)

​
Configure deletion protection

This feature requires Pinecone API version 2024-07, Python SDK v5.0.0, Node.js SDK v3.0.0, Java SDK v2.0.0, or Go SDK v1.0.0 or later.

​
Enable deletion protection

You can prevent an index and its data from accidental deleting when creating a new index or after its been created. In both cases, you set the deletion_protection parameter to enabled.

Enabling deletion protection does not prevent namespace deletions.

To enable deletion protection when creating a new index:

# pip install "pinecone[grpc]"
# Serverless index
from pinecone.grpc import PineconeGRPC as Pinecone
from pinecone import ServerlessSpec

pc = Pinecone(api_key="YOUR_API_KEY")

pc.create_index(
  name="docs-example",
  dimension=1536,
  metric="cosine",
  spec=ServerlessSpec(
    cloud="aws",
    region="us-east-1"
  ),
  deletion_protection="enabled"
)

To enable deletion protection when configuring an existing index:

from pinecone.grpc import PineconeGRPC as Pinecone

pc = Pinecone(api_key="YOUR_API_KEY")

pc.configure_index(
   name="docs-example", 
   deletion_protection="enabled"
)

When deletion protection is enabled on an index, requests to delete the index fail and return a 403 - FORBIDDEN status with the following error:

Deletion protection is enabled for this index. Disable deletion protection before retrying.

​
Disable deletion protection

Before you can delete an index with deletion protection enabled, you must first disable deletion protection as follows:

from pinecone.grpc import PineconeGRPC as Pinecone

pc = Pinecone(api_key="YOUR_API_KEY")

pc.configure_index(
   name="docs-example", 
   deletion_protection="disabled"
)

​
Configure index tags

Tags are key-value pairs that you can use to categorize and identify the index.

​
Add tags

To add tags to an index, use the tags parameter when creating a new index or when configuring an existing index.

To add tags when creating a new index:

from pinecone.grpc import PineconeGRPC as Pinecone
from pinecone import ServerlessSpec

pc = Pinecone(api_key="YOUR_API_KEY")

pc.create_index(
    name="docs-example",
    dimension=1536,
    metric="cosine",
    spec=ServerlessSpec(
        cloud="aws",
        region="us-east-1"
    ),
    deletion_protection="disabled",
    tags={
        "example": "tag", 
        "environment": "development"
    }
)

You can add tags during index creation using the Pinecone console.

To add or update tags when configuring an existing index:

from pinecone.grpc import PineconeGRPC as Pinecone

pc = Pinecone(api_key="YOUR_API_KEY")

pc.configure_index(
    name="docs-example", 
    tags={
        example: "tag", 
        environment: "development" 
    }
)

You can add or update tags when configuring an existing index using the Pinecone console. Find the index to edit and click the ellipsis (..) menu > Add tags.

​
View tags

To view the tags of an index, list all indexes in a project or get information about a specific index.

​
Remove tags

To remove a tag from an index, configure the index and use the tags parameter to send the tag key with an empty value ("").

The following example removes the example: tag tag from docs-example:

from pinecone.grpc import PineconeGRPC as Pinecone

pc = Pinecone(api_key="YOUR_API_KEY")

pc.configure_index(
    name="docs-example", 
    tags={"example": ""}
)

You can remove tags from an index using the Pinecone console. Find the index to edit and click the ellipsis (..) menu > __ tags.

​
List backups for an index

Serverless indexes can be backed up. You can list all backups for a specific index, as in the following example:

from pinecone import Pinecone

pc = Pinecone(api_key="YOUR_API_KEY")

index_backups = pc.list_backups(index_name="docs-example")

print(index_backups)

The example returns a response like the following:

[{
    "backup_id": "8c85e612-ed1c-4f97-9f8c-8194e07bcf71",
    "source_index_name": "docs-example",
    "source_index_id": "f73b36c9-faf5-4a2c-b1d6-4013d8b1cc74",
    "status": "Ready",
    "cloud": "aws",
    "region": "us-east-1",
    "tags": {},
    "name": "example-backup",
    "description": "Monthly backup of production index",
    "dimension": 1024,
    "record_count": 98,
    "namespace_count": 3,
    "size_bytes": 1069169,
    "created_at": "2025-05-15T00:52:10.809305882Z"
}]

You can view the backups for a specific index from either the Backups tab or the Indexes tab in the Pinecone console.