Amazon Web Services (AWS)

Overview

AWS dominates enterprise AI infrastructure with comprehensive services spanning the entire ML lifecycle. Amazon Bedrock provides serverless access to foundation models (Claude, Llama, Mistral, Amazon Nova) with pay-per-token pricing. SageMaker AI offers unified studio for data preparation, model training, fine-tuning, and deployment with built-in MLOps. EC2 P5 instances deliver H100 GPU clusters (8× H100 SXM5) for large-scale training. Specialized AI services include Rekognition (computer vision), Comprehend (NLP), Textract (document AI), and Transcribe (speech-to-text). Global infrastructure ensures low-latency access worldwide.

AWS's $100M Generative AI Innovation Center (2025) accelerates enterprise AI adoption with consulting, proof-of-concepts, and technical guidance. Bedrock AgentCore (announced 2025) enables secure enterprise-scale AI agents with seven core services. Integration with AWS ecosystem (S3, Lambda, API Gateway, CloudWatch) provides complete application infrastructure. Security features include VPC isolation, encryption, IAM policies, and compliance certifications (SOC, HIPAA, FedRAMP).

Key AI/ML Services

• **Amazon Bedrock**: Serverless foundation models (Claude, Llama, Mistral, Nova) with RAG, agents, guardrails
• **SageMaker AI**: End-to-end ML platform with unified studio, AutoML, custom training, deployment
• **EC2 P5 Instances**: 8× H100 SXM5 GPUs, 640GB HBM3, 3.2TB/s NVLink for large-scale training
• **EC2 P4 Instances**: 8× A100 80GB, proven reliability for production workloads
• **Amazon Rekognition**: Computer vision API for image/video analysis, face recognition
• **Amazon Comprehend**: NLP service for sentiment analysis, entity extraction, document classification
• **Amazon Textract**: Document AI for OCR, table extraction, form processing
• **Amazon Transcribe**: Speech-to-text with speaker identification and custom vocabulary
• **Amazon Polly**: Text-to-speech with neural voices in 60+ languages
• **Amazon Translate**: Neural machine translation for 75+ languages
• **AWS Deep Learning AMIs**: Pre-configured GPU instances with PyTorch, TensorFlow, CUDA
• **AWS Trainium**: Custom AI training chips for cost-effective large model training

Use Cases

• Foundation model deployment with Bedrock for chatbots, content generation, code assistance
• Large-scale LLM training on P5 instances (GPT-scale models)
• Production ML pipelines with SageMaker for recommendation engines, fraud detection
• Computer vision applications with Rekognition for retail, security, media
• Document processing with Textract for finance, healthcare, legal industries
• Real-time inference APIs with Lambda + Bedrock for serverless AI
• Data lakes with S3 + Athena + SageMaker for ML on petabyte-scale data
• MLOps with SageMaker Pipelines, Model Registry, and monitoring
• Compliance-sensitive AI for healthcare (HIPAA), government (FedRAMP), finance (PCI DSS)
• Global AI applications with multi-region deployment for low latency
• Cost optimization with spot instances, reserved capacity, Savings Plans
• Hybrid cloud AI with AWS Outposts for on-premise + cloud workflows

Pricing and Economics

AWS offers flexible pricing models: pay-as-you-go (no upfront cost), reserved instances (up to 75% discount for 1-3 year commitments), and spot instances (up to 90% discount for interruptible workloads). Bedrock charges per token (input/output) with no infrastructure management. SageMaker charges for compute (training/inference), storage, and data processing. EC2 P5 instances cost $32/hr on-demand ($98.30/hr for p5.48xlarge with 8× H100). Free tier includes 250 hours of ML compute monthly for 2 months. Cost optimization tools (Cost Explorer, Trusted Advisor) help manage spending. Total cost of ownership often lower than on-premise due to no hardware refresh cycles and elastic scaling.

Integration with 21medien Services

21medien architects AWS-based AI infrastructure for enterprise clients. We design SageMaker pipelines for custom model training, deploy Bedrock-powered applications with RAG and agents, optimize costs through spot instances and reserved capacity, implement MLOps with CI/CD automation, configure security (VPC, IAM, encryption), and provide ongoing management. Our AWS certifications (Solutions Architect, ML Specialty) ensure best practices. We handle multi-region deployments for global applications, hybrid cloud setups with AWS Outposts, and compliance configurations (GDPR, HIPAA, SOC 2). For businesses migrating to AWS or scaling AI workloads, 21medien provides architecture consulting, migration services, and managed operations.