August 31, 2026 · Engineering · 8 min read
Beyond 429s: Designing a Zero-Downtime Multi-Provider LLM Fallback Pipeline
Single-provider integrations turn every upstream incident into your outage. How to classify retryable failures, normalize schemas across four providers, and serve cached answers in under 25ms, with production Go and Python code.
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August 14, 2026 · Engineering · 9 min read
Why We Built Sentinel in Go: Concurrency at 10,000 Requests Per Second
Python proxies run into GIL lock contention once streaming request volume spikes. Here is the benchmark data from our k6 load tests and why compiled memory safety matters for an AI gateway.
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June 29, 2026 · FinOps & Caching · 6 min read
Cutting OpenAI Spend by 82% Using Redis Vector Caching
Exact match caching misses whenever a user rephrases a sentence. We run a two-tier lookup using fast SHA-256 keys followed by text-embedding-3-small vector similarity to return cached responses in under 25ms.
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May 12, 2026 · Security & Compliance · 5 min read
Sanitizing PII in Memory Before Upstream LLM Transmission
Once customer data leaves your servers, you lose control over where it gets logged. We built an in-flight scanner that detects and masks SSNs, payment cards, and secret keys directly in RAM before the prompt hits the network.
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April 03, 2026 · Engineering · 4 min read
Universal Fallbacks: Surviving OpenAI 429 Errors Without User Downtime
Upstream provider outages happen weekly. A breakdown of how we classify retryable errors, normalize payloads across model families, and reroute active streams to backup models automatically.
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February 18, 2026 · Product Releases · 5 min read
Why Bring-Your-Own-Key is the Right Model for Enterprise Gateways
Charging a 10% token tax on top of LLM provider costs does not scale for production workloads. We moved to a flat infrastructure model where your keys stay in your own encrypted vault.
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January 15, 2026 · Architecture · 7 min read
Why Traditional API Gateways Struggle With LLM Workloads
Traditional API gateways assume requests complete in 50ms and count raw HTTP hits. AI traffic requires token-aware rate limiting, streaming SSE buffers, and semantic deduplication.
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