Day 0: decide what would justify a gateway
Pick three representative workflows: one short interactive request, one long-context or tool-calling request, and one bursty production-like workload. Record the model, version, region, input size, expected output schema, traffic pattern and customer impact. Establish a direct-provider baseline using the same account or explain why a fair comparison is impossible. If your application uses images, audio or asynchronous batches, include those exact endpoint types rather than assuming chat-completion compatibility.
Define non-negotiable gates before running tests: approved data destinations, credential custody, retention, ability to revoke access, and a documented exit path. Then define numeric thresholds suited to your application, such as a maximum p95 latency regression, acceptable error rate and a minimum share of outputs passing human-reviewed quality checks. Do not borrow an arbitrary benchmark threshold from a vendor.
- Create a configuration manifest with model IDs, rate limits, retries and provider routing.
- Write down the cost denominator: successful task, not request or token alone.
- Assign one person to own the final go/no-go decision.
Days 1–3: establish direct-provider and gateway baselines
Replay a fixed, permissioned evaluation set through the direct provider and the gateway. Use the same prompt, tool schema, generation settings and model where supported. Measure total response time, time to first token for streaming, token usage, cache usage, retry count and correctness. Distinguish cold starts and warm connections. If the gateway selects a different provider or model, label that result as a routing comparison, not an overhead-only comparison.
Capture every failed request with its classification: network timeout, provider rate limit, invalid schema, gateway policy rejection or upstream refusal. An apparent speed win from silently dropping requests is not a win. Use confidence intervals or repeat runs at different times of day when the workload is small; report sample sizes and avoid claiming a universal percentage improvement.
Days 4–6: test degradation and fallback boundaries
Force a provider 429 and a recoverable 5xx in a controlled test. Verify retry limits, backoff, circuit-breaker behavior and the response your application receives. OpenRouter documents provider-layer failover separately from opt-in model fallback; LiteLLM documents model routing groups and fallback controls. Cloudflare documents versioned dynamic routing with fallback nodes. These features differ, so test the behavior of the product edition you intend to buy.
A fallback model may return different JSON, omit a tool call or violate an application's quality threshold. Treat compatibility as a gate: validate structured outputs, tool arguments, safety handling and any region restrictions after failover. A gateway that silently switches to an unapproved destination is not an acceptable recovery mechanism for a constrained workload.
- Record the actual provider and model serving each successful request.
- Confirm failures do not trigger unlimited retries or duplicate side effects.
- Test the exhausted-fallback path and verify a clean error.
Days 7–9: exercise spend controls and telemetry
Set small test budgets and send parallel requests near the boundary. Determine whether the system reserves estimated cost before admitting work, tallies only completed usage or blocks only after a periodic ledger update. Compare predicted token cost with provider-side usage reports, including cached-token rates when applicable. A request-level estimate is not the same as a provider invoice.
Inspect the observability interface: can operators distinguish model changes, provider failures, gateway overhead, prompt-cache hits and tenant identities without exposing secrets? Check who can read raw prompts and how retention or deletion requests work. Record every missing field and required manual step; the engineering burden is part of the total cost.
Days 10–12: calculate total cost and rehearse exit
Calculate monthly cost using your measured workload and an explicit forecast: upstream inference, gateway subscription, request or BYOK fees, logging, infrastructure, and staff operations. Include failed tasks, retries and quality rework. If you are evaluating AetherGate, use the current public subscription terms and direct-provider billing; do not assume an internal token-reduction test will reproduce as an invoice discount.
Run a reverse migration: switch one integration back to direct provider or to a second gateway, export configuration and request records where supported, and revoke credentials. Time the process. Record proprietary features that require code changes. A gateway that saves a little each month but makes an urgent exit expensive may not meet your risk appetite.
Days 13–14: issue a reproducible go/no-go memo
Create a scorecard with weighted criteria only after all hard gates pass. Suggested columns: criterion, pre-agreed threshold, direct baseline, gateway result, sample size, evidence link, owner and pass/fail. Weight quality, operational cost, resilience and developer effort to match the application. Never combine a failed privacy or authorization gate into a weighted average that still produces an overall pass.
State the limitations: short duration, provider incidents not observed, untested regions and feature flags, and any configuration drift. A useful conclusion may be no decision yet. Extend only the missing test rather than repeating the entire trial. Publish the methodology internally so a later vendor comparison can be rerun without relying on a sales deck.
- Approve only after hard gates and workload-specific thresholds pass.
- Keep the rollback plan and credential revocation owner attached to the decision.
- Retest after major model, routing or gateway version changes.