newsAWS Machine LearningTrust 88 · LabPublished 1mo agoLive · 1mo ago
Monitor and debug generative AI inference with SageMaker detailed metrics and Insights dashboard on CloudWatch
Amazon SageMaker AI provides fully managed real-time inference hosting for machine learning models. You deploy a model to a SageMaker endpoint backed by one or more compute instances, and SageMaker handles provisioning and scaling. SageMaker supports multiple endpoint architectures. This post focuses on the two most relevant to generative AI workloads with detailed observability: Single-model endpoints (SME) and Inference component (IC) endpoints.
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- LinkedLinked via unknownmrreviewai/ai-tools-for-solopreneurs →
- LinkedLinked via unknownkrushna081/chakravyuh-ai →
- LinkedLinked via unknownHayredin950/SYNAPSE →
- LinkedLinked via unknownA Multi-Dataset Benchmark for Evaluating LLM Agents in Microservice Failure Diagnosis →
- LinkedLinked via unknownMirrorCode: AI can rebuild entire programs from behavior alone →
- LinkedLinked via unknownTwo AI Metrics Diverged: Will it Make All the Difference? →
- PossiblePossibly related (embedding) · 47%aws/sagemaker-spark →
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repoHayredin950/SYNAPSEpaperA Multi-Dataset Benchmark for Evaluating LLM Agents in Microservice Failure DiagnosispaperMirrorCode: AI can rebuild entire programs from behavior alonepaperScaling the Horizon, Not the Parameters: Reaching Trillion-Parameter Performance with a 35B AgentpaperTwo AI Metrics Diverged: Will it Make All the Difference?repoaws/sagemaker-sparkrepoaws/amazon-sagemaker-examplesrepoaws/sagemaker-python-sdkrepoautogluon/autogluon-cloudrepoSuperCowPowers/workbenchrepokubeai-project/kubeaireporcourtman/Pulserepoenvoyproxy/ai-gatewayrepoolonok69/LLM_Notebooksreponetdata/netdatareporocketride-org/rocketride-serverrepomlflow/mlflowrepokserve/kserverepoCloud-CV/EvalAIrepochigwell/llm7.iorepotensorflow/servingreposuperlinked/sierepocomet-ml/opikreposkypilot-org/skypilotrepoMETR/hawkrepotriton-inference-server/serverrepowandb/wandbrepoquic/efficient-transformersrepofeast-dev/feastrepoHaidra-Org/horde-sdkrepoupstash/context7repoadrianliechti/wingmanrepoSemiAnalysisAI/InferenceX-apprepoverygoodplugins/automemrepomicrosoft/Sicorepor-uby-dev/llmrepoalibaba/tair-kvcacherepoLightning-AI/LitServerepomlco2/ecologitsrepoORNL/flowceptrepousedotai/dot-loomrepoYoavMayer/babysitter-observer-dashboardrepostatmike/vertex-ai-mlopsreponiklasfrick/spark-dashboardrepoinclusionAI/AwexrepoAngel-ML/angel
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repoYoavMayer/babysitter-observer-dashboardrepomlflow/mlflowrepokubeai-project/kubeairepowandb/wandbpaperMirrorCode: AI can rebuild entire programs from behavior alonerepoupstash/context7repoAngel-ML/angelrepochigwell/llm7.iorepoSemiAnalysisAI/InferenceX-apprepoinclusionAI/AwexrepoLightning-AI/LitServerepostatmike/vertex-ai-mlopsrepotensorflow/servingrepoCloud-CV/EvalAIrepoaws/sagemaker-python-sdkreponiklasfrick/spark-dashboardrepoolonok69/LLM_Notebooksrepoaws/amazon-sagemaker-examplesrepoMETR/hawkrepofeast-dev/feastrepoadrianliechti/wingmanrepor-uby-dev/llmreporocketride-org/rocketride-serverreposuperlinked/siereposkypilot-org/skypilotpaperScaling the Horizon, Not the Parameters: Reaching Trillion-Parameter Performance with a 35B Agentrepoaws/sagemaker-sparkrepomicrosoft/Sicorepokrushna081/chakravyuh-airepoenvoyproxy/ai-gatewayrepocomet-ml/opikrepoverygoodplugins/automemreporcourtman/PulsepaperA Multi-Dataset Benchmark for Evaluating LLM Agents in Microservice Failure Diagnosisrepotriton-inference-server/serverrepoalibaba/tair-kvcacherepousedotai/dot-loomreponetdata/netdatarepomlco2/ecologitspaperTwo AI Metrics Diverged: Will it Make All the Difference?repokserve/kserverepomrreviewai/ai-tools-for-solopreneursrepoautogluon/autogluon-cloudrepoHayredin950/SYNAPSErepoHaidra-Org/horde-sdkrepoSuperCowPowers/workbenchrepoquic/efficient-transformersrepoORNL/flowcept
