Start with an integration inventory, not a vendor demo
Document every production request path: provider, model identifier, endpoint family, SDK version, system and user message structure, maximum output, streaming mode, tools, structured output, attachments, timeouts and retry policy. An OpenAI-compatible chat endpoint may not implement every provider-native feature. A gateway that passes a simple text request can still fail a tool call or silently alter an unsupported parameter.
Capture a representative fixture set with synthetic or permissioned data. Include long context, Unicode, tool calls, JSON schema output, provider errors, cancellation and multi-turn sessions. Record which behavior is contractual to the application. Separate exact-format requirements from statistical model-quality expectations; an LLM answer will not be byte-identical on every run.
- List request schemas and required response fields.
- Mark which features are provider-native rather than OpenAI-compatible.
- Preserve a known-good direct-provider path for rollback.
Choose an architecture and define trust boundaries
A self-hosted proxy such as LiteLLM puts runtime operations, database availability and key custody on your team. Its virtual-key documentation describes database-backed key management and model restrictions. A managed gateway can reduce hosting work but adds a vendor data-processing and availability dependency. A marketplace model introduces different billing and provider selection arrangements. These choices should be compared as architectures, not just subscription prices.
Map where provider keys are stored and decrypted, who can issue paid requests, and which services see prompts and outputs. Verify that application credentials cannot manage administrator functions. If a vendor says it offers BYOK, ask whether upstream keys stay in your provider account and which runtime can use them. AetherGate's current public materials position it as provider-direct BYOK; validate the actual deployment and security controls rather than relying on product labels.
- Document credential ownership, rotation and revocation.
- Verify retention and logging defaults before sending sensitive traffic.
- Specify a separate staging key and spending ceiling.
Build a parity harness before switching traffic
Run each fixture through the direct API and the proposed gateway with matching model, parameters and regional routing. Compare status codes, tool-call arguments, JSON validity, token accounting, time to first token and tail latency. Evaluate semantic correctness against task-specific rubrics; do not mistake identical wording for the only definition of parity. For nondeterministic outputs, use repeated trials and report sample sizes.
Include forced rate limits, unavailable models and broken streams. Portkey's published fallback documentation explicitly notes that alternative models can differ in capability, latency and price and that multiple provider invocations can occur. A retry or fallback may therefore alter both behavior and cost. Test when the fallback happens and what the application receives if output has already started.
- Capture provider attempts, not just final HTTP status.
- Compare p50 and p95 latency under realistic concurrency.
- Treat partial streams and external tool side effects as distinct failure states.
Migrate credentials, identifiers and budgets safely
Do not copy an unrestricted provider key into a new system without reviewing its scope and spending exposure. Create a new provider credential where the provider supports it, use a separate application-facing gateway key, and establish model allowlists. Record which key belongs to each environment. A staged cutover should make it possible to revoke the new gateway credential without disrupting the original direct integration.
Translate model identifiers explicitly rather than assuming a model alias means the same revision everywhere. Add cost accounting that separates upstream provider charges from gateway fees. If the gateway reports estimated spend, reconcile it with the provider's invoice before using it for customer billing or strict financial decisions. Budget counters can lag or differ under concurrency, retries and cached-token classes.
- Use least-privilege application keys and environment-specific ownership.
- Confirm model aliases and version pinning.
- Set conservative alerts and verify actual limit behavior.
Roll out in measured stages
Begin with a small internal or low-risk workload and observe at least one normal traffic cycle. If possible, shadow requests only with permission and a defined extra-cost budget; shadow traffic can duplicate provider charges and should never duplicate external tool actions. Then route a limited production percentage while comparing quality, latency, error rate, support incidents and provider invoice totals to the control group.
Define rollback thresholds before launch: for example a material increase in failed requests, malformed structured outputs, missing traces or unexpected provider charges. The rollback action should restore the previous endpoint and credentials without requiring a database migration. Test it once during staging, including a deployment restart. A migration is not complete until the reverse path works.
- Canary one application or tenant before expanding.
- Keep a changelog of model, policy and key changes.
- Rehearse rollback, then document the actual recovery time.
Evaluate total migration cost and the purchase decision
Total cost includes engineering hours, tests, gateway subscription, hosting, provider usage, monitoring and incident response. A free-core self-hosted proxy is not zero-cost to operate; a paid managed gateway must justify its fee with operational value. Compare at least one month of representative workloads and include the time needed to leave the vendor later.
For AetherGate, the public Team subscription is listed at $249.99 monthly before direct provider charges. This is not a claim that it beats free tiers or marketplaces on entry price. A useful trial would demonstrate measurable reduction in operational friction, better attribution or acceptable workload-specific inference savings while preserving output quality. If the gateway adds complexity without measurable benefit, retain direct provider integrations.