Blueprint Released for Building Enterprise-Grade MLOps Pipelines on AWS

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A detailed architectural guide has been published outlining how to build a fully automated, production-grade MLOps pipeline using native AWS services. The blueprint addresses common production challenges such as data drift, training-serving mismatches, and risky manual rollbacks that arise without standardized workflows. The proposed architecture spans six functional layers, covering data ingestion, artifact versioning, pipeline orchestration, model governance, canary deployments, and continuous monitoring. Key AWS tools involved include SageMaker, Step Functions, EventBridge, CloudWatch, and API Gateway, among others. Security and compliance are central to the design, with all components operating inside private VPCs, TLS 1.3 encryption in transit, and AWS KMS-managed encryption at rest.

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ProgrammingDEV Community ·

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