What's New Cloud: The Biggest AWS Releases from re:Invent
AWS just dropped a wave of major updates across AI, compute, DevOps, and storage, some of the most impactful changes we've seen in years.
Welcome back to this new edition of the What’s New Cloud Newsletter, where I share my insights on topics covering AI/ML, Terraform automation, and the latest AWS/Azure releases.
This week’s spotlight is on the massive batch of announcements that landed during AWS re:Invent 2025 and why they matter.
What’s New
AWS introduced a series of heavyweight capabilities across Support, Lambda, S3, AI infrastructure, and autonomous engineering agents.
Here are the 10 standout updates shaping the future of cloud operations:
1. New AI-Enhanced AWS Support Plans
AWS Support now blends AI-powered diagnostics with expert human guidance, helping teams identify issues before they hit production.
This shifts support from reactive troubleshooting to proactive system health.
2. Database Savings Plans, Up to 35% Cheaper
A new pricing model lets teams save up to 35% on database spend by committing to predictable usage over one year.
A simple, flexible way to reduce RDS and Aurora costs without refactoring.
3. Lambda Durable Functions for Multi-Step Workflows
Lambda can now handle long-running, multi-step, and fault-tolerant workflows that pause and resume without Step Functions.
Great for order pipelines, approval workflows, and AI agent tasks.
4. Amazon S3 Now Supports 50 TB Objects
You can store single files up to 50 TB, eliminating the need for chunking large datasets, training data, backups, or media assets.
5. Amazon S3 Vectors, 2 Billion Vectors per Index
S3 Vector Indexes now scale to 2B vectors per index, with improved performance and lower cost.
Perfect for RAG, semantic search, and large-scale similarity workloads.
6. S3 Batch Operations, Up to 10× Faster
Bulk copy, tagging, and lifecycle tasks now run up to 10× faster, even across datasets with tens of billions of objects with no configuration changes.
7. AWS AI Factories for On-Prem AI
AWS now allows enterprises to deploy full AI infrastructure inside their own data center, including Trainium, NVIDIA GPUs, fast networking, Bedrock, and SageMaker.
On-prem meets hyperscale AI.
8. Kiro Autonomous Agent
Kiro is a fully autonomous engineering agent that:
writes code
runs tests
coordinates across repos
opens pull requests
and works continuously for hours or days.
A new category of hands-off software execution.
9. AWS Security Agent
An AI-driven security layer that reviews architectures, scans code, and performs continuous security analysis across the SDLC.
Designed to catch vulnerabilities early.
10. AWS DevOps Agent
An autonomous operator that triages incidents, finds root causes, and recommends improvements across AWS, hybrid, and multi-cloud environments.
Essentially, a tireless DevOps engineer.
Why This Matters
These updates signal a major shift:
AI-native operations across support, security, DevOps, and development
Massive improvements in S3 scalability and performance
Cheaper, more flexible database economics
Easier orchestration of multi-step workloads with Lambda
Enterprise-grade AI running on-prem, fully AWS-integrated
This is AWS leaning into automation, scale, and hybrid AI, all at once.
My Take
AWS didn’t just release features, they pushed the cloud closer to autonomous operations.
Lambda durable functions reduce the need for Step Functions in many workflows.
S3’s upgrades (50 TB objects, 2B-vector indexes, faster batch jobs) unlock new data patterns.
AI Factories show AWS is serious about hybrid AI infrastructure.
And the new AWS engineering agents (Kiro, Security, DevOps) hint at a future where cloud maintenance is increasingly automated.
Quiet or loud, these updates will reshape how teams build and run systems in 2025 and beyond.
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