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
šØ LLMs in Production: Day 3
āHope isnāt a strategy.ā
When your LLM provider goes downāand trust us, it willāhow ready are you?Today, weāre sharing fresh data from 650+ orgs on LLM provider reliability, downtime strategies, and how to keep things running smoothly (whileā¦
ā Portkey (@PortkeyAI) December 13, 2024
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Before that, hereās a recap from Part 1 of LLMs in Prod:
ā¢ @OpenAI dominance is eroding, with Anthropic slowly but steadily gaining ground
ā¢ @AnthropicAI requests are growing at a staggering 61% MoM
ā¢ @Google Vertex AI is finally gaining momentum after a rocky start.Now,ā¦ pic.twitter.com/4MjD63EWyJ
ā Portkey (@PortkeyAI) December 13, 2024
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Remember the OpenAI Outage?
In just one day, they reminded the world how critical they areāby taking everything offline for ~4 hours. š
But hereās the thing: this wasnāt an anomaly.
Outages like these are a recurring pattern across ALL providers.Which begs the question: whyā¦ pic.twitter.com/HYNVeZlSpo
ā Portkey (@PortkeyAI) December 13, 2024
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š Over the past year, error spikes hit every providerāfrom 429s to 5xxs, no one was spared.
The truth?
Thereās no pattern, no guarantees, and no immunity.If youāre not prepared with multi-provider setups, youāre inviting downtime.
Reliability isnāt optionalāitās tableā¦ pic.twitter.com/MDpSfSrYftā Portkey (@PortkeyAI) December 13, 2024
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Rate Limit Reality Check:
ā¢ @GroqInc : 21.11%
ā¢ @Perplexity: 12.24%
ā¢ @AnthropicAI : 5.60%
ā¢ @Azure OpenAI: 1.74%Translation: If you're not handling rate limits gracefully, you're gambling with user experience.
Your customers wonāt wait for infra to catch up. Are youā¦ pic.twitter.com/GiJwXdPMuQ
ā 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:
ā¢ Groq: 0.67%
ā¢ Anthropic: 0.56%
ā¢ Perplexity: 0.39%
ā¢ Gemini: 0.32%
ā¢ Bedrock: 0.28%Even "small" error rates = thousands of failed requests at scale.
These arenāt just numbersātheyāreā¦ pic.twitter.com/0CqdEGfYc0
ā Portkey (@PortkeyAI) December 13, 2024
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So, whatās the solution?
The hard truth? Your users don't care why your AI features failed.
They just know you failed.
The key isnāt choosing the ābestā providerāitās building a system that works when things go wrong:š” Diversify providers.
š” Implement caching.
š” Build smartā¦ā Portkey (@PortkeyAI) December 13, 2024
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6/ Why caching matters:
Performance optimization is critical, and hereās where caching delivers results:
ā¢ 36% average cache hit rate (peaks for Q&A use cases)
ā¢ 30x faster response times
ā¢ 38% cost reductionCaching isn't optional at scaleāit's your first line of defense. pic.twitter.com/YX7YvwkmMS
ā Portkey (@PortkeyAI) December 13, 2024
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Thatās it for today! Follow @PortkeyAI for more on LLMs in Prod Series
ā Portkey (@PortkeyAI) December 13, 2024
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ā Portkey (@PortkeyAI) December 13, 2024
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