Switched our notification system from Google's TTS API to ElevenLabs. Voice quality is noticeably more natural, especially for longer announcements.
But the API uptime isn't matching Google's. Seeing sporadic 5xx errors and occasional latency spikes >2s. Have to implement retries with exponential backoff where Google didn't need them.
Our current wrapper:
```python
def synthesize_speech(text, voice_id):
for attempt in range(3):
try:
response = requests.post(
f"{BASE_URL}/v1/text-to-speech/{voice_id}",
headers={"xi-api-key": API_KEY},
json={"text": text, "voice_settings": {"stability": 0.3, "similarity_boost": 0.7}},
timeout=5
)
response.raise_for_status()
return response.content
except requests.exceptions.Timeout:
if attempt == 2:
raise
time.sleep(2 ** attempt)
```
Anyone else running ElevenLabs in production? What's your retry logic and error budget looking like? Considering going multi-region or failback to a cheaper TTS for non-critical alerts.
latency kills
I run TTS for automated voice notifications in a logistics platform handling around 200k synthesis requests daily. We evaluated both Google and ElevenLabs thoroughly before settling on a multi-provider setup.
* **Voice Naturalness & Output Control:** ElevenLabs clearly wins on expressiveness, especially for longer, paragraph-like text. Their `similarity_boost` and `stability` parameters provide fine-grained control Google lacks. However, Google's WaveNet voices are more consistent phonetically for short, technical terms.
* **API Reliability & Latency:** Google's SLA and global infrastructure are superior. In a 30-day test, we saw >99.95% uptime from Google Cloud TTS versus ~99.7% from ElevenLabs, with ElevenLabs' p99 latency often spiking to 1.8-2.2 seconds. Your retry logic is essential; we use a similar pattern but with jitter.
* **Real Pricing & Scaling:** Google's pricing is simpler per-character, while ElevenLabs' subscription tiers can be cheaper at high volume but create hard ceilings. Our ElevenLabs bill is ~$0.40 per 100k characters, but unexpected traffic over your tier limit causes immediate throttling, not graceful degradation.
* **Operational Overhead:** ElevenLabs requires more engineering. We built a failover system where non-critical alerts use a cached Google TTS fallback after two ElevenLabs failures. This added about two days of dev time but cut our critical alerts' failure rate to near zero.
Given your mention of non-critical alerts, I'd recommend sticking with ElevenLabs for the quality but implementing a failback to a cheaper, more reliable provider like Google or AWS Polly for lower-priority traffic. To be sure, tell us your monthly character volume and whether your announcements require dynamic text or can be pre-generated and cached.
Interesting trade-off you're hitting. We moved a customer-facing narration feature to ElevenLats for the same quality reasons, and the retry pattern became critical.
We ended up implementing a more granular failure check. The timeout in your wrapper is good, but we found some 200 OK responses with empty or malformed audio bytes. Adding a check on `response.content` length saved us from silently passing corrupt files downstream.
For critical notifications, we kept a circuit breaker pattern that would fail back to Google TTS after two consecutive ElevenLabs failures. It's extra plumbing, but it kept our error budget under 0.1% while still using the better voice for 95%+ of requests. Did you consider a similar failover, or is the cost difference prohibitive?
That's a smart addition, checking the actual content length. We hit a similar snag where the API would return a 200 with a tiny, corrupted MP3 fragment. Our fix looked like this:
```python
if len(response.content) < 1024: # Anything reasonable for audio
raise ValueError("Audio payload too small, likely malformed")
```
On the failover point, we did consider it, but the cost difference wasn't the blocker for us. It was more about maintaining consistent voice branding across notifications. Suddenly switching to a Google voice for a critical alert felt jarring.
We ended up with a different compromise: we use a queue with delayed retries for ElevenLabs failures. If it fails after the second retry, we generate a fallback using a simpler, cached "system alert" tone and log the text for manual review. It's not as seamless as your circuit breaker, but it keeps the voice uniform. Have you had any user feedback on the voice switching itself?
Backup first.
I'm curious about the timeout value you're using. You mentioned latency spikes over 2 seconds, but your wrapper's timeout is set to 5 seconds. Have you experimented with a shorter timeout, maybe 2 or 3 seconds, to trigger a retry faster? That might help smooth out the latency spikes for your users, even if it means more retries in the queue.
Our team handles a lower volume, but we saw similar patterns. We ended up adding a check for the specific error codes ElevenLabs returns during those 5xx blips, like 502 or 524, to retry more aggressively on those. Does their status page or API docs give any guidance on which errors are usually transient?