This is Part 2 of our series analyzing Portkey's critical insights from production LLM deployments. Today, we're diving deep into provider reliability data from 650+ organizations , examining outages, error rates, and the real impact of downtime on AI applications. From the infamous OpenAI outage to the daily challenges of rate limits, we'll reveal why 'hope isn't a strategy' when it comes to LLM infrastructure
🚨 LLMs in Production: Day 3
“Hope isn’t a strategy.”
When your LLM provider goes down—and trust us, it will—how ready are you?Today, we’re sharing fresh data from 650+ orgs on LLM provider reliability, downtime strategies, and how to keep things running smoothly (while…
— Portkey (@PortkeyAI) December 13, 2024
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Before that, here’s a recap from Part 1 of LLMs in Prod:
• @OpenAI dominance is eroding, with Anthropic slowly but steadily gaining ground
• @AnthropicAI requests are growing at a staggering 61% MoM
• @Google Vertex AI is finally gaining momentum after a rocky start.Now,… pic.twitter.com/4MjD63EWyJ
— Portkey (@PortkeyAI) December 13, 2024
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Remember the OpenAI Outage?
In just one day, they reminded the world how critical they are—by taking everything offline for ~4 hours. 😛
But here’s the thing: this wasn’t an anomaly.
Outages like these are a recurring pattern across ALL providers.Which begs the question: why… pic.twitter.com/HYNVeZlSpo
— Portkey (@PortkeyAI) December 13, 2024
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📊 Over the past year, error spikes hit every provider—from 429s to 5xxs, no one was spared.
The truth?
There’s no pattern, no guarantees, and no immunity.If you’re not prepared with multi-provider setups, you’re inviting downtime.
Reliability isn’t optional—it’s table… pic.twitter.com/MDpSfSrYft— Portkey (@PortkeyAI) December 13, 2024
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Rate Limit Reality Check:
• @GroqInc : 21.11%
• @Perplexity: 12.24%
• @AnthropicAI : 5.60%
• @Azure OpenAI: 1.74%Translation: If you're not handling rate limits gracefully, you're gambling with user experience.
Your customers won’t wait for infra to catch up. Are you… pic.twitter.com/GiJwXdPMuQ
— Portkey (@PortkeyAI) December 13, 2024
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But rate limits are just the tip of the iceberg.
Server Error (5xx) rates this year:
• Groq: 0.67%
• Anthropic: 0.56%
• Perplexity: 0.39%
• Gemini: 0.32%
• Bedrock: 0.28%Even "small" error rates = thousands of failed requests at scale.
These aren’t just numbers—they’re… pic.twitter.com/0CqdEGfYc0
— Portkey (@PortkeyAI) December 13, 2024
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So, what’s the solution?
The hard truth? Your users don't care why your AI features failed.
They just know you failed.
The key isn’t choosing the “best” provider—it’s building a system that works when things go wrong:💡 Diversify providers.
💡 Implement caching.
💡 Build smart…— Portkey (@PortkeyAI) December 13, 2024
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6/ Why caching matters:
Performance optimization is critical, and here’s where caching delivers results:
• 36% average cache hit rate (peaks for Q&A use cases)
• 30x faster response times
• 38% cost reductionCaching isn't optional at scale—it's your first line of defense. pic.twitter.com/YX7YvwkmMS
— Portkey (@PortkeyAI) December 13, 2024
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That’s it for today! Follow @PortkeyAI for more on LLMs in Prod Series
— Portkey (@PortkeyAI) December 13, 2024
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— Portkey (@PortkeyAI) December 13, 2024
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