Amazon Bedrock Guardrails vs Azure AI Content Safety (Prompt Shields)

Amazon Bedrock Guardrails

ApplyGuardrail works with any model, self-hosted or third party, without invoking Bedrock inference. Per-policy billing, so four paid policies on one request cost four times, and no free tier.

Azure AI Content Safety (Prompt Shields)

Prompt Shields checks up to five retrieved documents for indirect injection, not only the user prompt. Needs an Azure subscription with a card, a resource and a region that has the feature, before the first call.

Amazon Bedrock Guardrails

1. Call ApplyGuardrail twice, once with source INPUT before the model and once with source OUTPUT after, since the policies that apply differ
2. Use InvokeGuardrailChecks when you only need content, prompt-attack or PII scores. It needs no guardrail id and runs in detect-only mode
3. Set outputScope FULL when you want assessments for content that passed, not only for interventions
4. Budget in text units of 1,000 characters per policy. A 5,000-character tool result is five units on every paid policy
5. Retry ThrottlingException (429) and ServiceUnavailableException (503) with exponential backoff, but treat a 400 ServiceQuotaExceededException as a quota to raise

Azure AI Content Safety (Prompt Shields)

1. Send retrieved pages and tool results in the documents array of shieldPrompt, not in userPrompt, so document attacks are reported separately
2. Call text:shieldPrompt over REST with api-version=2024-09-01. The Python SDK 1.0.0 has no method for it
3. Keep each request under 10,000 characters across prompt and documents, and split long tool results
4. Create the resource in a region that lists Prompt Shields, since not every region has it
5. On F0 you get 5 requests a second. Queue checks or move to S0 before load testing