How to fix Antigravity servers are experiencing high traffic right now?

You’re hitting the “Our servers are experiencing high traffic right now, please try again in a minute” error in Antigravity. This usually points to service saturation or rate limiting and can impact all models at once.

How to fix Antigravity servers are experiencing high traffic right now?

When calling Antigravity, requests intermittently fail with the message: “Our servers are experiencing high traffic right now, please try again in a minute.” In some reports, all models are not responding (e.g., Claude/Sonnet/Pro/non‑Pro), indicating a broader outage and not a single-model issue.

If your local client also shows heavy memory pressure while retrying, see our quick Windows x64 notes here: memory spikes on Windows.

Solution Overview

How to fix Antigravity servers are experiencing high traffic right now?

Step-by-Step Solution

• 1) Check live service status

• Open the Antigravity status page: StatusGator – Antigravity.

• If there’s an ongoing incident, pause automated traffic and let your users know it’s transient.

• 2) Verify account and model usage limits

• In the console, navigate to: “Advanced Settings > Model” and confirm your current usage limits and any recent spikes.

• If you’re close to your cap, lower request rates or request a limit increase.

• Related reading if tokens get stuck or requests stall: Read More: tokens not progressing

• 3) Try an alternative model

• From the forum’s guidance: “please use a model other than Gemini.”

• If “All models are currently not responding,” treat it as a broader outage and proceed with the retry/backoff steps below.

• 4) Add automatic retries with exponential backoff (+ jitter)

• Honor HTTP 429/5xx and the Retry-After header when present. See HTTP 429 and Exponential backoff.

Bash/cURL (basic exponential backoff with jitter):

# Requires: bash, curl
API="https://api.antigravity.ai/v1/chat"
for i in 1 2 3 4 5 6; do
http_code=$(curl -sS -o out.json -w "%{http_code}" \
-H "Authorization: Bearer $ANTIGRAVITY_API_KEY" \
-H "Content-Type: application/json" \
-d '{"input":"hello"}' "$API")

if [ "$http_code" -eq 200 ]; then
cat out.json
break
elif [ "$http_code" -eq 429 ] || [ "$http_code" -ge 500 ]; then
# backoff: grows with each retry + small jitter
sleep_seconds=$(( i*2 + RANDOM % 3 ))
echo "Transient $http_code, retrying in ${sleep_seconds}s..."
sleep "$sleep_seconds"
else
echo "Failed with HTTP $http_code"
cat out.json
exit 1
fi
done

Python (requests + urllib3 Retry):

import os, requests
from requests.adapters import HTTPAdapter
from urllib3.util.retry import Retry

session = requests.Session()
retry = Retry(
total=8,
backoff_factor=0.8, # 0.8, 1.6, 3.2...
status_forcelist=[429, 500, 502, 503, 504],
allowed_methods=["GET", "POST", "PUT", "DELETE", "PATCH"]
)
adapter = HTTPAdapter(max_retries=retry)
session.mount("https://", adapter)

r = session.post(
"https://api.antigravity.ai/v1/chat",
headers={"Authorization": f"Bearer {os.environ['ANTIGRAVITY_API_KEY']}"},
json={"input": "hello"}
)
r.raise_for_status()
print(r.json())

Node.js (axios + axios-retry):

npm i axios axios-retry

const axios = require('axios');
const axiosRetry = require('axios-retry');

axiosRetry(axios, {
retries: 6,
retryDelay: axiosRetry.exponentialDelay,
retryCondition: (error) => {
const s = error.response && error.response.status;
return s === 429 || s === 500 || s === 502 || s === 503 || s === 504;
}
});

async function call() {
const res = await axios.post(
'https://api.antigravity.ai/v1/chat',
{ input: 'hello' },
{ headers: { Authorization: `Bearer ${process.env.ANTIGRAVITY_API_KEY}` } }
);
console.log(res.data);
}

call().catch(err => console.error(err.response?.status, err.response?.data || err.message));

• 5) Reduce concurrency and batch requests
• Lower parallelism to keep under burst limits. Increase only after stability returns.

Node.js (limit concurrency to 3):

npm i p-limit

const pLimit = require('p-limit');
const limit = pLimit(3);

async function callAntigravity(item) { /* ... */ }

await Promise.all(items.map(item => limit(() => callAntigravity(item))));

Python (asyncio semaphore):

import asyncio, os, aiohttp

sem = asyncio.Semaphore(3)

async def call(item):
async with sem:
async with aiohttp.ClientSession() as s:
async with s.post(
'https://api.antigravity.ai/v1/chat',
headers={'Authorization': f'Bearer {os.environ["ANTIGRAVITY_API_KEY"]}'},
json={'input': item}
) as r:
if r.status in (429, 500, 502, 503, 504):
raise RuntimeError(f"Transient {r.status}")
return await r.json()

• 6) Refresh session and network
• Sign out/in from the console, restart your client, and disable VPN/proxy temporarily.
• Flush DNS cache:
• Windows:

ipconfig /flushdns

• macOS:

sudo dscacheutil -flushcache
sudo killall -HUP mDNSResponder

• Linux (systemd-resolved):

sudo systemd-resolve --flush-caches

• 7) If you still see flakes, queue and retry
• Push requests to a queue with worker retries and dead-lettering. This prevents client storms during partial outages.

If your agents are getting killed mid-call, skim this quick fix: Read More: agent terminated during requests

Alternative Fixes & Workarounds

• Use cached or staged responses

• Cache frequent prompts for a short TTL (e.g., 60–300s) to avoid repeat calls during a spike.

• Time-shift bulk jobs

• Schedule heavy, non-urgent batches for off-peak hours; leave a generous retry window.

• Temporary provider/model switch

• If status is green but a specific family is flaky, keep a short allowlist of backup models and fail over automatically.

• Shorten requests

• Trim prompt/context size. Smaller requests often succeed when the service is tight on resources.

Read More: token stalls and short prompts

Troubleshooting Tips

• Check response headers for clues:

curl -i -H "Authorization: Bearer $ANTIGRAVITY_API_KEY" \
-H "Content-Type: application/json" \
-d '{"input":"hello"}' https://api.antigravity.ai/v1/chat

• Look for HTTP 429/503 and a Retry-After header.

• Confirm scope of impact

• If “All models are currently not responding,” focus on retries/backoff and status monitoring rather than code changes.

• Watch your metrics

• Plot request rate, error rate, and avg latency. If spikes match failures, throttle upstream callers.

For developers on Windows seeing memory growth from repeated retries, this quick primer can help: Read More: Windows x64 memory tips

Best Practices

• Implement client-side rate limits and idempotency keys to avoid duplicate side effects after retries.
• Always include exponential backoff and stop after a sane cap (e.g., 5–8 attempts).
• Respect Retry-After when present; otherwise, backoff with jitter to prevent synchronized retries.
• Keep concurrency and QPS configurable via environment variables for fast hotfixes.
• Add health checks and alerts tied to the Antigravity status page and your own error budgets.

If you still face agents failing during spikes, here’s a quick reference: Read More: agents failing under load

Final Thought

This issue is usually temporary. By checking status/quotas, switching models when needed, and adding retries with exponential backoff + reduced concurrency, you’ll stabilize calls quickly and protect users during traffic spikes. Once service returns to normal, you can safely scale back up.