Create a pod-based index ↗

pinecone guide intermediate configuration ide

Summary: Create and configure a pod-based Pinecone index

Original Documentation

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Fetch the complete documentation index at: https://docs.pinecone.io/llms.txt Use this file to discover all available pages before exploring further.

Create and configure a pod-based Pinecone index

Customers who sign up for a Standard or Enterprise plan on or after August 18, 2025 cannot create pod-based indexes. Instead, create serverless indexes, and consider using dedicated read nodes for large workloads (millions of records or more, and moderate or high query rates).

This page shows you how to create a pod-based index. For guidance on serverless indexes, see Create a serverless index.

Create a pod index#

To create a pod index, use the create_index operation as follows:

Provide a name for the index.
Specify the dimension and metric of the vectors you’ll store in the index. This should match the dimension and metric supported by your embedding model.
Set spec.environment to the environment where the index should be deployed. For Python, you also need to import the ServerlessSpec class.
Set spec.pod_type to the pod type and size that you want.

Other parameters are optional. See the API reference for details.

from pinecone.grpc import PineconeGRPC as Pinecone, PodSpec

pc = Pinecone(api_key="YOUR_API_KEY")

pc.create_index(
  name="docs-example",
  dimension=1536,
  metric="cosine",
  spec=PodSpec(
    environment="us-west1-gcp",
    pod_type="p1.x1",
    pods=1
  ),
  deletion_protection="disabled"

)

import { Pinecone } from '@pinecone-database/pinecone'

const pc = new Pinecone({
  apiKey: 'YOUR_API_KEY'
});

await pc.createIndex({
  name: 'docs-example',
  dimension: 1536,
  metric: 'cosine',
  spec: {
    pod: {
      environment: 'us-west1-gcp',
      podType: 'p1.x1',
      pods: 1
    }
  },
  deletionProtection: 'disabled',
});

import io.pinecone.clients.Pinecone;
import org.openapitools.db_control.client.model.IndexModel;
import org.openapitools.db_control.client.model.DeletionProtection;

public class CreateIndexExample {
    public static void main(String[] args) {
        Pinecone pc = new Pinecone.Builder("YOUR_API_KEY").build();
        pc.createPodsIndex("docs-example", 1536, "us-west1-gcp",
                "p1.x1", "cosine", DeletionProtection.DISABLED);
    }
}

package main

import (
    "context"
    "fmt"
    "log"

    "github.com/pinecone-io/go-pinecone/v4/pinecone"
)

func main() {
    ctx := context.Background()

    pc, err := pinecone.NewClient(pinecone.NewClientParams{
        ApiKey: "YOUR_API_KEY",
    })
    if err != nil {
        log.Fatalf("Failed to create Client: %v", err)
    }

    indexName := "docs-example"
  	metric := pinecone.Dotproduct
	  deletionProtection := pinecone.DeletionProtectionDisabled

    idx, err := pc.CreatePodIndex(ctx, &pinecone.CreatePodIndexRequest{
        Name:               indexName,
        Metric:             &metric,
        Dimension:          1536,
        Environment:        "us-east1-gcp",
        PodType:            "p1.x1",
        DeletionProtection: &deletionProtection,
    })
    if err != nil {
        log.Fatalf("Failed to create pod-based index: %v", idx.Name)
    } else {
        fmt.Printf("Successfully created pod-based index: %v", idx.Name)
    }
}

using Pinecone;

var pinecone = new PineconeClient("YOUR_API_KEY");

var createIndexRequest = await pinecone.CreateIndexAsync(new CreateIndexRequest
{
    Name = "docs-example",
    Dimension = 1536,
    Metric = MetricType.Cosine,
    Spec = new PodIndexSpec
    {
        Pod = new PodSpec
        {
            Environment = "us-east1-gcp",
            PodType = "p1.x1",
            Pods = 1,
        }
    },
    DeletionProtection = DeletionProtection.Disabled
});

PINECONE_API_KEY="YOUR_API_KEY"

curl -s "https://api.pinecone.io/indexes" \
  -H "Accept: application/json" \
  -H "Content-Type: application/json" \
  -H "Api-Key: $PINECONE_API_KEY" \
  -H "X-Pinecone-Api-Version: 2025-10" \
  -d '{
         "name": "docs-example",
         "dimension": 1536,
         "metric": "cosine",
         "spec": {
            "pod": {
               "environment": "us-west1-gcp",
               "pod_type": "p1.x1",
               "pods": 1
            }
         },
         "deletion_protection": "disabled"
      }'

Create a pod index from a collection#

You can create a pod-based index from a collection. For more details, see Restore an index.

Link last verified June 7, 2026. View original ↗

Source: Pinecone Docs

Link last verified: 2026-02-26