AWS Weekly Update: Key Developments – July 28, 2025

BREAKING NEWS: AWS Organizations Simplifies Tagging with Wildcard Support

Las Vegas, NV – July 26, 2025 – In a significant move to streamline cloud resource management, amazon Web Services (AWS) today announced enhanced Tag Policies for AWS Organizations, now featuring wildcard support. This update empowers users to apply consistent tagging rules across all supported resource types within a service with a single, simple statement, a move set to dramatically cut down on policy complexity and manual effort.

Teh introduction of the ALL_SUPPORTED wildcard statement means administrators can now define broad tagging governance across their AWS accounts without needing to enumerate each individual resource type. This is a game-changer for organizations large and small looking to enforce compliance, improve cost allocation, and enhance security posture through standardized tagging practices.

Evergreen Insight: The Enduring importance of Tagging Strategy

While this latest AWS enhancement focuses on simplifying the implementation of tagging policies, the strategic importance of a robust tagging framework remains a constant in cloud governance. Even with simplified tools, a well-defined tagging strategy is foundational for:

Cost Management: Accurately attributing costs to specific projects, teams, or applications is crucial for budget control and optimization. Consistent tags enable detailed cost analysis.
Security and Access Control: Tags can be leveraged within IAM policies to grant permissions based on resource attributes, limiting access to only necessary resources and reinforcing the principle of least privilege.
Automation: Tagging is a primary enabler for automation. Scripts and services can dynamically identify and act upon resources based on their tags, from routine backups to automated scaling.
Operational Efficiency: Easily identifying and grouping resources by function, habitat, or owner simplifies troubleshooting, monitoring, and overall operational management.

This update from AWS Organizations is a clear signal that robust, scalable, and manageable tagging will continue to be a cornerstone of effective cloud operations. Organizations are encouraged to revisit and refine their tagging strategies to fully leverage these new simplifying capabilities.

Related Insights:

Beyond IAM Access Keys: AWS continues to champion modern security practices, advocating for a move away from conventional IAM access keys towards more secure authentication methods. This aligns with the broader trend of strengthening identity management to mitigate credential exposure risks.
Upcoming AWS Events: For those looking to dive deeper into AWS best practices and future innovations, key events like AWS re:Invent 2025 (December 1-5 in Las Vegas) and various AWS Summits and Community Days offer invaluable learning and networking opportunities.

What cost optimization benefit does the SageMaker Inference Recommender provide?

Amazon SageMaker Enhancements: Faster Model Training & Deployment

This week saw important updates to Amazon SageMaker, AWS’s fully managed machine learning service. Key improvements focus on accelerating both model training and deployment pipelines.

SageMaker jumpstart now supports pre-trained models for generative AI tasks: Specifically, models optimized for text-to-image and text-to-video generation are now readily available, reducing the time to experiment with cutting-edge AI. This is a boon for developers exploring generative AI applications.

New distributed training options: SageMaker now offers enhanced support for data parallelism and model parallelism, leading to up to 30% faster training times for large models. This is particularly relevant for deep learning workloads.

SageMaker Inference Recommender: A new feature that automatically identifies the optimal instance type and configuration for your machine learning models, reducing inference costs and improving performance. This directly impacts MLOps efficiency.

AWS Lambda Updates: Enhanced Container Image Support

AWS Lambda, the serverless compute service, received updates streamlining container image deployment.

increased container image size limit: The maximum container image size for Lambda functions has been increased to 10GB, allowing for more complex dependencies and larger models to be deployed serverlessly. This is a game-changer for serverless applications requiring ample resources.

Improved container image build times: AWS has optimized the container image build process, resulting in faster deployment cycles.

Enhanced support for custom runtimes: Developers now have greater versatility in defining custom runtimes for Lambda functions, enabling support for a wider range of programming languages and frameworks. This expands the possibilities for serverless computing.

Amazon RDS: PostgreSQL and MySQL Performance Boosts

Amazon RDS, the managed relational database service, saw performance improvements for both PostgreSQL and MySQL.

New Graviton3-based instance types for PostgreSQL: These new instances deliver up to 40% better price performance compared to previous generation instances. Leveraging AWS Graviton processors is a cost-effective strategy.

MySQL 8.0.35 now generally available: This release includes performance enhancements, security updates, and new features like improved JSON support. Staying current with MySQL versions is crucial for database health.

RDS Performance Insights enhancements: Improved visualizations and deeper diagnostics for identifying and resolving database performance bottlenecks. This is a key tool for database administration.

AWS Security Hub: Automated Compliance Checks

AWS security Hub, the central security management service, introduced automated compliance checks against industry standards.

Automated checks for PCI DSS 4.0: Security Hub now automatically assesses your AWS surroundings against the latest PCI DSS 4.0 requirements, simplifying compliance efforts. This is vital for businesses handling payment card data.

Expanded support for CIS Benchmarks: More CIS Benchmarks are now supported,providing a broader range of security best practices assessments.

Integration with Amazon Detective: Enhanced integration with Amazon Detective allows for faster examination of security findings. This strengthens cloud security posture.

AWS Training & Certification: New Learning paths for AI/ML

For those looking to upskill, AWS announced new learning paths focused on Artificial Intelligence and Machine Learning.

New “AI Foundations” learning path: Designed for beginners,this path provides a complete introduction to AI concepts and AWS AI services. A great starting point for learning AWS AI.

specialized learning paths for SageMaker: Deep dives into specific SageMaker features, such as data labeling, model training, and deployment. Useful for machine learning engineers.

Updated certification exams: The AWS Certified Machine Learning – specialty exam has been updated to reflect the latest AWS AI/ML services and best practices. Consider pursuing AWS certifications to validate your skills.

Resources for Further Learning:

Learning AWS – A helpful resource for beginners.

AWS What’s New: https://aws.amazon.com/new/ – official AWS announcements.

AWS Documentation: https://docs.aws.amazon.com/ – Comprehensive documentation for all AWS services.