Use cases
Start with the Bedrock failure your team has to explain right now.
Every path opens the same investigation surface. Pick the one that matches the error in front of you: quota pressure and throttling, Knowledge Base failures, a promotion decision, or a multi-signal incident review.
Trial is $0 for 7 days through AWS Marketplace. Connect with a read-only cross-account IAM role.
Use case switchboard
Which Amazon Bedrock production failure are you debugging?
Why is Bedrock returning 429 ThrottlingException?
Requests are failing and nobody can tell whether it is TPM pressure, RPM pressure, a retry storm, or AWS-side capacity.
- Quota burn attributed to a caller and workload
- 429 versus 503 classification, TPM versus RPM pressure
- Retry amplification and connection pool saturation
- The next step for that failure class
Why did my Bedrock Knowledge Base sync fail?
Ingestion jobs fail, answers get worse, or reranking and metadata filters behave differently than they did last week.
- Failed documents and repeated ingestion failure patterns
- Retrieval configuration validation
- Retrieval quality tracked over time
- Tenant isolation checks across Knowledge Bases
Is this Knowledge Base change safe to promote?
A chunking, embedding or rerank change looks fine in a notebook, and nobody wants to promote it to production on that evidence.
- Candidate versus live comparison on one probe set
- Audit-logged promotion with an owner and a timestamp
- Rollback to the previous Knowledge Base
- Evidence attached to the promotion record
What actually caused this Bedrock incident?
The incident spans runtime throttling, retrieval quality and a deployment, and the review needs one timeline instead of four consoles.
- One unified incident timeline
- Ranked probable causes with evidence
- Linked events across runtime, Knowledge Base and deploys
- A review artifact once the incident closes
Why these overlap
A Bedrock incident is rarely one signal
A throttle spike turns into a quota story. A retrieval drop turns into a promotion story. A quality complaint turns into a deployment story. BedrockOps is built for that overlap, so the investigation does not restart every time it crosses a boundary.
Where teams start
Most teams arrive with one sentence
“We are getting throttled and nobody knows why.”
Start with quota burn attributed to a caller, then the 429 versus 503 split.
Bedrock quota and throttling investigations“Our Knowledge Base changed and answers are worse.”
Start with failed documents by reason, then retrieval quality over time.
Knowledge Base failures and retrieval degradation“We need evidence before we promote this change.”
Start with candidate versus live on one probe set, with rollback kept open.
Knowledge Base promotion and comparison“We need one timeline across four consoles.”
Start with the unified incident timeline and the ranked cause list.
Cross-signal incident reviewPick the use case that matches your Bedrock problem
Start the trial in AWS Marketplace, connect AWS with a read-only role, and run BedrockOps against the real signals behind the issue you are trying to explain.