Field notes for production AI
Choose who can use or edit your AI models, model groups, prompts, and tools in DeltaLLM. A simple guide to team sharing while keeping provider keys private.
Balance LLM traffic across deployments with DeltaLLM Route Groups — using weighted splits, failover, latency, cost, and rate-limit-aware routing.
Evaluate DeltaLLM as a self-hosted LiteLLM alternative: compare team controls, customer tiers, and routing, then test a migration with the same chat request.
DeltaLLM now has Tiers — reusable model packages that let you define which models, RPM/TPM limits, and pricing apply to each customer plan. One tier, many organizations.
Run an embedding batch through DeltaLLM: upload JSONL, track progress, and download results. Learn what async processing saves and what it does not discount.
You can't optimize what you can't measure. Here's how to monitor your LLM gateway with Prometheus, health checks, and callback integrations.
A practical guide to deploying DeltaLLM on Kubernetes — from a quick evaluation install to a production-ready HA setup with monitoring.
Many LLM requests are identical. Caching responses at the gateway saves money, reduces latency, and works without changing your application code.
Sharing LLM access across teams without controls is a security and cost risk. Here's how to set up multi-tenant RBAC for your AI gateway.
Hardcoded prompts break production AI. Here's how to manage prompts as versioned, deployable assets — with labels, bindings, and safe rollback.
Sensitive data and prompt injection are the biggest risks in LLM applications. Here's how to stop both at the gateway level — before they ever reach the model.
The Model Context Protocol (MCP) is changing how AI agents work. Here's how DeltaLLM's MCP gateway support lets your agents use any provider.
LLM costs can spiral quickly without visibility. Here's how to track spend across providers, set budget limits, and route to cheaper models strategically.
LLM providers have outages and rate limits. Here's how to architect automatic failover so your application stays up when providers go down.
A fair comparison of the leading LLM gateways — DeltaLLM, LiteLLM, Portkey, and Helicone — with clear recommendations based on use case.
Compare Portkey's managed, open-source, and enterprise deployment options with DeltaLLM. Evaluate hosting, team budgets, migration, and operating costs.
Learn how to add DeltaLLM as a gateway in front of your existing OpenAI API calls without changing your application code.
Direct LLM API calls create vendor lock-in, hidden costs, and single points of failure. Here's how an LLM gateway solves all three.