
Learn to build and orchestrate serverless generative AI applications using AWS services like Amazon Bedrock and Step Functions. Explore integration techniques, error handling, and human feedback loops in AI workflows.

Explore operational excellence for LLMs using Amazon Bedrock. Learn design principles, LLMOps, model lifecycle, customization, and architectural patterns for effective implementation and evaluation.

Explore LLM observability maturity in AWS, from foundational concepts to advanced AIOps, covering metrics, performance, security, and best practices for effective implementation.

Explore AWS-powered RAG systems for LLMs, covering vector embeddings, databases, and services. Learn to leverage Amazon's AI capabilities for enhanced language model performance.

Explore a secure, scalable AWS serverless solution using Bedrock for generative AI tasks. Learn architecture, deployment, cost estimation, and advanced features for efficient platform engineering.

Explore AWS observability using Datadog, covering challenges, fundamentals, implementation as code, and advanced techniques for effective platform engineering and monitoring.

Enhance RAG systems and deploy LLM applications rapidly using AWS lambda aliases. Learn to evaluate production systems and overcome LLM limitations for safer, faster iterations.

Learn to train and deploy NLP Transformer models using Amazon SageMaker and Hugging Face. Gain hands-on experience with cutting-edge deep learning techniques for natural language processing.

Explore Java's speed in serverless environments, debunk cold start myths, and learn optimization techniques for AWS Lambda using modern frameworks like Quarkus and Piranha Cloud.

Discover strategies to optimize Java on AWS Lambda, addressing cold starts, cost management, and performance issues for scalable serverless applications.

Explore serverless API creation in AWS, Azure, and GCP using API Gateway and cloud functions. Compare solutions, discuss security, and understand limitations.

Explore serverless Java's advantages, from infrastructure as code to energy savings, with live deployments and pragmatic event-driven architectures.

Explore Philips' journey to cloud-based CI/CD, leveraging serverless runners for 8000+ developers. Learn about scaling, cost optimization, and improved developer experience in this open-source solution.

Implement once, execute anywhere with Spring and Functions. Learn to create versatile applications deployable across various platforms and environments.

Explore secure methods for cross-database access, optimizing rights management and enhancing data protection in database environments.

Design a data strategy and choose the optimal database for modern cloud applications. Learn about managed instances, Postgres, MySQL, and database engines across platforms.

Design, implement, and maintain scalable lakehouse architectures using Apache Spark, Kafka, Flink, Delta Lake, AWS, and open-source tools. Enhance data potential through advanced analytics and machine learning.

Discover how OpenShift Database Access simplifies database management, enabling self-service provisioning and access control across providers while enhancing visibility and governance for admins.

Deploy Java serverless functions across multiple cloud platforms using Quarkus Funqy, a portable API for creating functions compatible with AWS, Azure, Google Cloud, and KNative.

Explore data modernization with Confluent and AWS. Learn migration strategies, cloud capabilities, and real-time streaming potential. Gain insights from success stories and best practices for unlocking data value.

Aprende a desplegar aplicaciones Serverless, contenedores y Kubernetes en Amazon AWS. Configura AWS CLI, redes EC2, clusters EKS y realiza despliegues en ECS para dominar DevOps en la nube.