6 documented AWS Bedrock cost inefficiencies, each with how to detect it and how to fix it.
AWS BedrockCER-0276
Many Bedrock workloads involve low-complexity tasks such as tagging, classification, routing, entity extraction, keyword detection, document triage, or lightweight summarization. These tasks do not require the advanced reasoning or...
AWS BedrockCER-0256
AWS frequently updates Bedrock with improved foundation models, offering higher quality and better cost efficiency. When workloads remain tied to older model versions, token consumption may increase, latency may be higher, and output...
AWS BedrockCER-0502
Amazon Bedrock on-demand inference bills every input token sent and every output token generated. Applications often send much more than a task needs: the full conversation history on every turn, entire documents instead of the relevant...
AWS BedrockCER-0558
Amazon Bedrock Provisioned Throughput reserves dedicated inference capacity for a base or custom model at a fixed hourly price, whether or not any requests arrive. Capacity is bought in model units, each delivering a set number of input...
AWS BedrockCER-0565
Many Bedrock applications send the same large block of context on every request: a long system prompt, tool definitions, a reference document in a document Q&A flow, or an agent's growing conversation history. Bedrock prompt caching lets...
AWS BedrockCER-0566
Offline jobs such as document enrichment, classification and tagging backfills, summarizing archives, generating embeddings and running model evaluations are often implemented as loops of synchronous InvokeModel or Converse calls. Those...