AWS’ 10 Coolest New Products And Tools Of 2025 (So Far)

From Aurora DSQL and Amazon Transform to the second generation of AWS Outpost and a new quantum computing chip, here are the 10 hottest new products from AWS launched in 2025 so far.

From new quantum chips to a slew of artificial intelligence and agentic AI launches, Amazon Web Services’ innovation engine has been roaring during the first half of 2025.

The $107 billion Seattle-based cloud giant unleashed new products and tools this year to help its thousands of customers and channel partners drive AI adoption and scale their cloud environments.

CRN breaks down the 10 coolest new AWS products launched in 2025 that everyone should know about including Aurora DSQL, Amazon Transform, the second generation of its AWS Outpost system, enhanced Amazon Bedrock capabilities, agentic AI tools and its new quantum computing chip Ocelot.

Amazon Transform

AWS launched Transform this year, calling it a revolutionary service that uses agentic AI to accelerate and simplify the migration and modernization of a clients’ infrastructure, applications and code.

“Transform uses agentic AI to automate transformation tasks, achieving what was previously not possible: modernizing Windows-based .NET applications to Linux four-times faster, converting VMware network configurations in hours versus weeks, and decomposing mainframe applications in minutes instead of months,” said AWS CEO Matt Garman on LinkedIn this year.

The new agentic AI service uses AWS foundational models, LLMs, machine learning, graph neural networks, automated reasoning, and AI infrastructure to deliver migrations and modernization.

AWS Transform leverages specialized AI agents to remove the heavy lifting and automate complex migration and modernization tasks for VMware, mainframe, and .NET workloads.

Click through to read the other nine coolest new AWS products and tools of 2025.

Amazon Aurora DSQL

Dubbed the fastest serverless distributed SQL database in the world, Amazon launched Aurora DSQL, which is now generally available.

Amazon said the new Aurora DSQL has virtually unlimited scale, the highest availability, and zero infrastructure management for always available applications.

“Aurora DSQL scales down to zero and up to the biggest workloads in the world,” said AWS CEO Matt Garman in a recent LinkedIn post.

“You get all this and the highest level of resilience whether your apps are single Region or multi-Region deployments,” he said. “This launch is truly remarkable as it’s solving a long-standing customer need for active-active high availability with multi-Region strong consistency without having to trade off performance.”

Unlike most traditional databases, Aurora DSQL is disaggregated into multiple independent components such as a query processor, adjudicator, journal, and crossbar. Customers can remove the operational burdens of patching, upgrading, and maintenance downtime to create a new database in just a few steps.

AWS Ocelot Quantum Chip

AWS announced its new quantum computing chip Ocelot.

“Ocelot, our groundbreaking quantum computing chip, reduces error correction resources by 90 percent,” said AWS’ CEO.

Ocelot’s building error correction technology was built from the ground up. AWS researchers combined technology and additional quantum error correction components onto a microchip that can be manufactured in a scalable fashion using processes borrowed from the microelectronics industry.

“With the recent advancements in quantum research, it is no longer a matter of if, but when practical, fault-tolerant quantum computers will be available for real-world applications. Ocelot is an important step on that journey,” said Oskar Painter, AWS’ director of quantum hardware, in a blog post. “In the future, quantum chips built according to the Ocelot architecture could cost as little as one-fifth of current approaches, due to the drastically reduced number of resources required for error correction.”

AWS Outposts Racks Second Generation

AWS launched the second generation of its AWS Outposts racks.

The new Outposts generation includes support for the latest x86-powered Amazon EC2 instances, new simplified network scaling and configuration, and accelerated networking instances designed for ultra-low latency and high-throughput workloads.

These enhancements provide greater performance for a broad range of on-premises workloads, such as core trading systems of financial services and telecom 5G Core workloads.

The second-generation Outposts includes an upgraded network rack that acts as a central hub for all compute and storage traffic, as well as support for C7i compute-optimized, M7i general-purpose instances, and R7i memory-optimized instances. It is powered by Intel Xeon Scalable 4th Gen processors.

Multi-Agent Collaboration For Bedrock

AWS launched multi-agent collaboration capabilities on Amazon Bedrock that enable developers to build, deploy and manage networks of AI agents that work together seamlessly to efficiently execute complex workflows.

Multi-agent collaboration lets customers create networks of specialized agents that communicate and coordinate under the guidance of a supervisor agent.

Each agent contributes its expertise to the larger workflow by focusing on a specific task.

This allows specialized agents to work within their domains of expertise, coordinated by a supervisor agent. The supervisor breaks down requests, delegates tasks, and consolidates outputs into a final response.

Model Context Protocol Servers

AWS recently unveiled specialized Model Context Protocol (MCP) servers for Amazon EC2, Amazon EKS and AWS Serverless.

AWS’ open-source solutions extend AI development assistants capabilities with real-time, contextual responses that go beyond their pre-trained knowledge.

While LLMs within AI assistant rely on public documentation, MCP servers deliver current context and service-specific guidance to help customers prevent common deployment errors and provide more accurate service interactions.

Whether customers are writing code for their environment or debugging production issues, the new MCP servers support AI code assistants with deep understanding of Amazon ECS, Amazon EKS, and AWS Serverless capabilities.

Amazon Nova Premier

Dubbed AWS’ most capable AI model for complex tasks, the company unveiled Amazon Nova Premier.

“Nova Premier shines as the best teacher model, with its ability to train other Nova models to be just as capable while being faster and more cost-effective,” said AWS’ CEO. “That means customers can create customized AI that fits their exact needs.”

Premier can process input text, images, and videos, but excels at complex tasks that require deep understanding of context, multistep planning, and precise execution across multiple tools and data sources.

With a context length of one million tokens, Nova Premier can process long documents or large code bases.

Nova Premier can also be used as a teacher model for distillation, which means users can transfer its advanced capabilities for a specific use case into smaller and more efficient models like Nova Pro, Micro, and Lite for production deployments.

AWS Pricing Calculator

One big tool for partners and customers is AWS new pricing calculator that supports discounts and purchase commitments.

The new pricing calculator inside the AWS console enables users to now create more accurate and comprehensive cost estimates by providing two types of cost estimates: cost estimation for a workload, and estimation of a full AWS bill.

Customers and partners can also import their historical usage or create net new usage when creating a cost estimate.

Additionally, with the new rate configuration inclusive of both pricing discounts and purchase commitments, users can gain a clearer picture of potential savings and cost optimizations for their cost scenarios.

SageMaker Unified Studio

Amazon’s SageMaker Unified Studio lets customers leverage it as their single data and AI development environment, where users can access all of their organization’s data and work using the best tools for specific needs.

The SageMaker Unified Studio is a single data and AI development environment that brings together functionality and tools from standalone studios, query editors, and visual tools such as Amazon Athena, AWS Glue and AWS Redshift.

SageMaker Unified Studio breaks down silos in data and tools, giving data engineers, data scientists, data analysts, ML developers and other data practitioners a single development experience. This aims to save development time and simplify access control management so data practitioners can focus on building data products and AI applications.

Strands Agents

AWS’ new Strands Agents is an open-source SDK that takes a model-driven approach to building and running AI agents in just a few lines of code.

Strands scales from simple to complex agent use cases, and from local development to deployment in production.

Compared with frameworks that require developers to define complex workflows for their agents, Strands simplifies agent development by embracing the capabilities of models to plan, chain thoughts, call tools, and reflect.

With Strands, developers can define a prompt and a list of tools in code to build an agent, then test it locally and deploy it to the cloud. Strands connects two core pieces of the agent together: the model and the tools. Strands plans the agent’s next steps and executes tools using the advanced reasoning capabilities of models.