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Is Pinecone Down?

Check live Pinecone status — vector upsert, query API, index creation, and serverless endpoints. See recent incidents and set up free email alerts.

Pinecone live status

Pinecone — live status

Updated every 5 minutes. Full incident history at prismix.dev/service/pinecone.

Full status →

Quick check: is Pinecone down right now?

  1. Prismix: prismix.dev/service/pinecone — live status + 30-day uptime + incidents.
  2. Pinecone official status: status.pinecone.io — Pinecone's own status page with per-service breakdown.
  3. API call: curl https://prismix.dev/api/v1/statuses | jq '.services[] | select(.id=="pinecone")'

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  1. 1

    Sign in

    Go to prismix.dev/sign-in — email OTP or GitHub sign-in.

  2. 2

    Star Pinecone

    On prismix.dev/service/pinecone, click the ☆ star icon.

  3. 3

    Alerts are live

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Monitor Pinecone programmatically

Python (Pinecone SDK health check)

{`import httpx, sys
from pinecone import Pinecone

# 1. Check Prismix for platform-level outage first
resp = httpx.get("https://prismix.dev/api/v1/statuses", timeout=5)
svc = next((s for s in resp.json()["services"] if s["id"] == "pinecone"), {})
if svc.get("indicator", "none") != "none":
    print(f"Pinecone platform issue: {svc.get('description')}")
    sys.exit(1)

# 2. Verify your specific index is ready before upserting
pc = Pinecone(api_key="YOUR_API_KEY")
index_desc = pc.describe_index("my-index")
if not index_desc.status.ready:
    print("Index not ready yet — wait and retry")
    sys.exit(1)

# 3. After upsert, wait for eventual consistency
import time
index = pc.Index("my-index")
index.upsert(vectors=[("vec1", [0.1] * 1536)])
for _ in range(10):
    stats = index.describe_index_stats()
    if stats.total_vector_count >= 1:
        break
    time.sleep(3)  # vectors appear within 5-30 seconds`}

curl

{`curl https://prismix.dev/api/v1/statuses | jq '.services[] | select(.id=="pinecone")'`}

Common causes of "Pinecone API not working"

If Prismix shows Pinecone as "Operational" but your upserts or queries are failing:

  • Index not found (404) right after creation — new indexes take 1–3 minutes to become ready. The SDK's create_index() call returns before the index is usable. Poll GET /indexes/{name} until status.ready == true before upserting.
  • Upsert returns 200 but vectors not searchable — Pinecone upsert is eventually consistent. After a large batch upsert, vectors appear in query results within 5–30 seconds. Use describe_index_stats() to wait until vector_count matches your expectation before querying.
  • Dimension mismatch on upsert (400) — the index was created with a fixed dimension (e.g. 1536 for text-embedding-3-small). You cannot change dimensions on existing indexes — if your embedding model changes, you must create a new index.
  • Serverless vs pod-based endpoint confusion — serverless indexes (launched 2024) use https://{{index-host}} from the describe_index response. Legacy pod-based indexes use environment URLs like us-east1-gcp. Mixing these formats causes 404 errors.
  • Free tier quota exceeded — Pinecone free tier allows 1 index, 100k vectors, and 1GB storage. Exceeding any limit causes upsert failures with a quota error. Upgrade at app.pinecone.io.
  • Query returning empty results despite vectors existing — metadata filters are case-sensitive and exact-match only. Ensure filter keys and values match exactly what was stored during upsert. Also verify that top_k is set and include_values is configured as expected.

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Monitor other vector DB and AI infrastructure?

Full status dashboard: prismix.dev/status