Starting today, AWS Partner Central agents qualify every co-sell opportunity in real time and make recommendations that drive AWS engagement and accelerate deal progression. Building on the AWS Partner Central agents released on March 16, 2026, the agent can act on the partner’s behalf through conversation to enrich the opportunity details. This eliminates waiting for manual review, so partners build a stronger pipeline and progress deals faster.

Now, each opportunity is matched to a co-sell motion that determines AWS engagement: AWS field-engaged, where an AWS sales team collaborates directly; Agent-engaged, where the agent strengthens the submission to increase AWS engagement; and Partner-led, where the partner drives the deal with agent support. Across all motions, the agent provides customer insights, recommendations, and sales plays, and each opportunity receives an Opportunity Quality Score that measures co-sell readiness and directly influences how AWS engages. The agent recommends how to improve this score, and as the opportunity improves, the score and motion recalculate in real time, moving it closer to AWS engagement.

The new enhanced experience is available today to AWS Partners in all commercial AWS Regions. To get started, log in to AWS Partner Central and access opportunity management. Partners can also use the agentic experience in native AI tools like Amazon Quick and Kiro, or through MCP in their own CRM. See the Partner Central agents MCP server guide to get started.

 

​Starting today, AWS Partner Central agents qualify every co-sell opportunity in real time and make recommendations that drive AWS engagement and accelerate deal progression. Building on the AWS Partner Central agents released on March 16, 2026, the agent can act on the partner’s behalf through conversation to enrich the opportunity details. This eliminates waiting for manual review, so partners build a stronger pipeline and progress deals faster. Now, each opportunity is matched to a co-sell motion that determines AWS engagement: AWS field-engaged, where an AWS sales team collaborates directly; Agent-engaged, where the agent strengthens the submission to increase AWS engagement; and Partner-led, where the partner drives the deal with agent support. Across all motions, the agent provides customer insights, recommendations, and sales plays, and each opportunity receives an Opportunity Quality Score that measures co-sell readiness and directly influences how AWS engages. The agent recommends how to improve this score, and as the opportunity improves, the score and motion recalculate in real time, moving it closer to AWS engagement. The new enhanced experience is available today to AWS Partners in all commercial AWS Regions. To get started, log in to AWS Partner Central and access opportunity management. Partners can also use the agentic experience in native AI tools like Amazon Quick and Kiro, or through MCP in their own CRM. See the Partner Central agents MCP server guide to get started.  

Amazon CloudWatch now natively supports OpenTelemetry metrics. You can send metrics via the OpenTelemetry Protocol (OTLP) and query them using Prometheus Query Language (PromQL), with per-GB ingestion pricing and 15 months of storage included.

This allows you to consolidate custom application metrics and AWS vended metrics from more than 70 services in a single solution, queryable together in PromQL. CloudWatch exposes a Prometheus-compatible query API, so teams already using OpenTelemetry, Prometheus, or Grafana can use CloudWatch as a destination that fits seamlessly with their existing tools.

Available in all commercial AWS Regions except Middle East (UAE), Middle East (Bahrain), and Israel (Tel Aviv). For pricing details, see the Amazon CloudWatch pricing page. To get started, see the Amazon CloudWatch metrics documentation.

 

​Amazon CloudWatch now natively supports OpenTelemetry metrics. You can send metrics via the OpenTelemetry Protocol (OTLP) and query them using Prometheus Query Language (PromQL), with per-GB ingestion pricing and 15 months of storage included.
This allows you to consolidate custom application metrics and AWS vended metrics from more than 70 services in a single solution, queryable together in PromQL. CloudWatch exposes a Prometheus-compatible query API, so teams already using OpenTelemetry, Prometheus, or Grafana can use CloudWatch as a destination that fits seamlessly with their existing tools.
Available in all commercial AWS Regions except Middle East (UAE), Middle East (Bahrain), and Israel (Tel Aviv). For pricing details, see the Amazon CloudWatch pricing page. To get started, see the Amazon CloudWatch metrics documentation.  

Today, AWS Marketplace announces AI-assisted product listing in Partner Assistant chat, helping Independent Software Vendors (ISVs) and Consulting Partners create high-quality product listings on AWS Marketplace using their existing digital assets. This new capability helps partners create listings optimized for discovery by buyers, while eliminating the time-consuming manual data entry and guesswork around meeting AWS Marketplace requirements.

Partner Assistant automatically generates and validates product listing content by importing information from your existing digital assets, including website URLs, PDFs, case studies, and product documentation. The AI-powered assistant creates content across all required product information fields, validates it against AWS Marketplace size and format requirements, and optimizes it for search. You’ll receive field-level recommendations based on AWS Marketplace best practices, with a quality score indicating where your listing stands relative to the standards that drive buyer engagement. Whether you’re creating your first listing or managing multiple products, Partner Assistant streamlines the process while helping ensure your listings are best positioned to be discoverable and considered by customers in AWS Marketplace.

AI-assisted product listing capability is available through the Partner Assistant chat in AWS Partner Central and the AWS Marketplace Management Portal (AMMP). For programmatic access, you can use the Partner Agent MCP server. This feature is not available in AWS GovCloud (US) Regions or China Regions.

To learn more about creating product listings with AI assistance, visit AI-assisted Product Listing. 

 

​Today, AWS Marketplace announces AI-assisted product listing in Partner Assistant chat, helping Independent Software Vendors (ISVs) and Consulting Partners create high-quality product listings on AWS Marketplace using their existing digital assets. This new capability helps partners create listings optimized for discovery by buyers, while eliminating the time-consuming manual data entry and guesswork around meeting AWS Marketplace requirements.
Partner Assistant automatically generates and validates product listing content by importing information from your existing digital assets, including website URLs, PDFs, case studies, and product documentation. The AI-powered assistant creates content across all required product information fields, validates it against AWS Marketplace size and format requirements, and optimizes it for search. You’ll receive field-level recommendations based on AWS Marketplace best practices, with a quality score indicating where your listing stands relative to the standards that drive buyer engagement. Whether you’re creating your first listing or managing multiple products, Partner Assistant streamlines the process while helping ensure your listings are best positioned to be discoverable and considered by customers in AWS Marketplace.
AI-assisted product listing capability is available through the Partner Assistant chat in AWS Partner Central and the AWS Marketplace Management Portal (AMMP). For programmatic access, you can use the Partner Agent MCP server. This feature is not available in AWS GovCloud (US) Regions or China Regions.
To learn more about creating product listings with AI assistance, visit AI-assisted Product Listing.   

AWS Partner Central now supports the Business Value Realization (BVR) motion, a new experience and funding motion for partners who drive customer adoption and business outcomes after deploying strategic AWS services. BVR helps partners drive business outcomes for their customers by structuring the AWS service adoption journey across defined stages, with funding tied to proven demonstrated value realization.

Partners can now enroll in BVR through a self-service registration flow in AWS Partner Central, nominate customer opportunities, and track customer progress towards value realization. The new experience enables partners to track customer progression across structured adoption stages, with guided activities to help customers achieve desired outcomes. As partners drive customer adoption, AI agents in AWS Partner Central generate weekly adoption reports that surface highlights, risks, and recommendations, helping partners identify where customer users drop off and how tooling adoption is accelerating. When partners complete stages, funding is automatically disbursed through the AWS Partner Funding Portal without requiring separate requests.

BVR is available in AWS Partner Central for consulting, system integrator, and managed services partners with advance or premier tier status and a qualifying domain competency. Learn more in the APN blog or visit AWS Partner Central guide for Business Value Realization.

 

​AWS Partner Central now supports the Business Value Realization (BVR) motion, a new experience and funding motion for partners who drive customer adoption and business outcomes after deploying strategic AWS services. BVR helps partners drive business outcomes for their customers by structuring the AWS service adoption journey across defined stages, with funding tied to proven demonstrated value realization. Partners can now enroll in BVR through a self-service registration flow in AWS Partner Central, nominate customer opportunities, and track customer progress towards value realization. The new experience enables partners to track customer progression across structured adoption stages, with guided activities to help customers achieve desired outcomes. As partners drive customer adoption, AI agents in AWS Partner Central generate weekly adoption reports that surface highlights, risks, and recommendations, helping partners identify where customer users drop off and how tooling adoption is accelerating. When partners complete stages, funding is automatically disbursed through the AWS Partner Funding Portal without requiring separate requests. BVR is available in AWS Partner Central for consulting, system integrator, and managed services partners with advance or premier tier status and a qualifying domain competency. Learn more in the APN blog or visit AWS Partner Central guide for Business Value Realization.  

AWS Partners co-selling with AWS can now use express private offers to automate pricing within co-sell workflows. Partners configure their pricing rules, discount boundaries, and eligible products once, and when AWS sales representatives identify their solution as a fit for a customer’s needs, the deal can move from opportunity to private offer in minutes rather than weeks of manual negotiation.

As AWS sellers identify relevant Partner solutions through co-sell tools, they can see which Partners have express private offers enabled and directly invite customers to receive personalized pricing. Customers specify their purchase requirements, contract duration, and configuration needs, and receive a tailored private offer based on the Partner’s pre-configured pricing rules. Partners receive the customer’s contact details and can follow up at any time to assist with offer acceptance or provide additional context. This gives Partners increased visibility in AWS-led sales motions, faster deal conversion, and the ability to engage with customers who have expressed purchase intent, while giving AWS sellers confidence that matched Partners can deliver customized pricing without delays.

To get started, Partners can onboard their products to express private offers by following the AWS Marketplace Seller Guide. For best practices on co-selling with AWS, review this guide on improving your visibility to AWS Sales.

 

​AWS Partners co-selling with AWS can now use express private offers to automate pricing within co-sell workflows. Partners configure their pricing rules, discount boundaries, and eligible products once, and when AWS sales representatives identify their solution as a fit for a customer’s needs, the deal can move from opportunity to private offer in minutes rather than weeks of manual negotiation.
As AWS sellers identify relevant Partner solutions through co-sell tools, they can see which Partners have express private offers enabled and directly invite customers to receive personalized pricing. Customers specify their purchase requirements, contract duration, and configuration needs, and receive a tailored private offer based on the Partner’s pre-configured pricing rules. Partners receive the customer’s contact details and can follow up at any time to assist with offer acceptance or provide additional context. This gives Partners increased visibility in AWS-led sales motions, faster deal conversion, and the ability to engage with customers who have expressed purchase intent, while giving AWS sellers confidence that matched Partners can deliver customized pricing without delays.
To get started, Partners can onboard their products to express private offers by following the AWS Marketplace Seller Guide. For best practices on co-selling with AWS, review this guide on improving your visibility to AWS Sales.  

Today, AWS announces the public preview of a new storage migration capability for AWS Transform that enables application owners, database administrators, and cloud migration teams to migrate block storage workloads from any on-premises or cloud source to Amazon FSx for NetApp ONTAP (FSx for ONTAP), alongside the existing Amazon EBS option. AWS Transform for migrations is an agentic AI service that automates the discovery, planning, and migration of workloads, accelerating infrastructure modernization with increased speed and confidence. FSx for ONTAP is a fully managed shared storage service built on NetApp’s ONTAP file system, allowing you to migrate on-premises applications that rely on NetApp ONTAP or other storage appliances to AWS without having to change how you manage your data.

Customers migrating to AWS have traditionally managed storage migration separately, using additional tools and workflows. With this new capability, AWS Transform replicates block storage data directly to FSx for ONTAP volumes as part of the same migration wave that handles compute and network, eliminating the need for intermediate storage platforms, separate migration tools, and the additional cost and risk they introduce. Whether migrating from NetApp ONTAP or any other storage platform, including block storage or NFS datastores in VMware environments, customers access a fully managed service that combines ONTAP’s enterprise capabilities with the scalability and resiliency of AWS.

To get started, visit AWS Transform for migrations. To learn more about the storage destination service, see the Amazon FSx for NetApp ONTAP product page.

 

​Today, AWS announces the public preview of a new storage migration capability for AWS Transform that enables application owners, database administrators, and cloud migration teams to migrate block storage workloads from any on-premises or cloud source to Amazon FSx for NetApp ONTAP (FSx for ONTAP), alongside the existing Amazon EBS option. AWS Transform for migrations is an agentic AI service that automates the discovery, planning, and migration of workloads, accelerating infrastructure modernization with increased speed and confidence. FSx for ONTAP is a fully managed shared storage service built on NetApp’s ONTAP file system, allowing you to migrate on-premises applications that rely on NetApp ONTAP or other storage appliances to AWS without having to change how you manage your data.
Customers migrating to AWS have traditionally managed storage migration separately, using additional tools and workflows. With this new capability, AWS Transform replicates block storage data directly to FSx for ONTAP volumes as part of the same migration wave that handles compute and network, eliminating the need for intermediate storage platforms, separate migration tools, and the additional cost and risk they introduce. Whether migrating from NetApp ONTAP or any other storage platform, including block storage or NFS datastores in VMware environments, customers access a fully managed service that combines ONTAP’s enterprise capabilities with the scalability and resiliency of AWS.
To get started, visit AWS Transform for migrations. To learn more about the storage destination service, see the Amazon FSx for NetApp ONTAP product page.  

Today, AWS announces the availability of xAI’s Grok 4.3 model on Amazon Bedrock. With this launch, xAI joins Amazon Bedrock as a model provider, giving you even more choice as you build generative AI applications across reasoning, agentic, and enterprise workflows.

Grok 4.3 is a reasoning-first model that offers always-on and configurable reasoning effort (none, low, medium, high). Because reasoning is always active rather than optional, it behaves more consistently across multi-step agent loops than models that can skip thinking. It also offers strong tool use and instruction-following capabilities for building multi-step agents, and token efficiency to help keep high-volume inference cost-effective. Grok 4.3 is especially well suited to enterprise workloads such as contract review, case law research, credit agreement analysis, and financial document Q&A, while delivering consistent, high-quality results across conversational AI, search, chat, and multi-turn workflows. Grok 4.3 runs on Mantle, a new inference engine in Amazon Bedrock designed for price performance, with support for tool calling, structured output, and response streaming.

See region availability of Grok 4.3 for list of supported regions. To get started, visit the Grok 4.3 model detail page in our documentation.

 

​Today, AWS announces the availability of xAI’s Grok 4.3 model on Amazon Bedrock. With this launch, xAI joins Amazon Bedrock as a model provider, giving you even more choice as you build generative AI applications across reasoning, agentic, and enterprise workflows.
Grok 4.3 is a reasoning-first model that offers always-on and configurable reasoning effort (none, low, medium, high). Because reasoning is always active rather than optional, it behaves more consistently across multi-step agent loops than models that can skip thinking. It also offers strong tool use and instruction-following capabilities for building multi-step agents, and token efficiency to help keep high-volume inference cost-effective. Grok 4.3 is especially well suited to enterprise workloads such as contract review, case law research, credit agreement analysis, and financial document Q&A, while delivering consistent, high-quality results across conversational AI, search, chat, and multi-turn workflows. Grok 4.3 runs on Mantle, a new inference engine in Amazon Bedrock designed for price performance, with support for tool calling, structured output, and response streaming.
See region availability of Grok 4.3 for list of supported regions. To get started, visit the Grok 4.3 model detail page in our documentation.  

AWS Management Console Private Access now enables customers to access the AWS Console from VPCs without internet connectivity, allowing enterprises to manage their AWS infrastructure through the console while maintaining strict network security controls in air-gapped environments.

Previously, AWS Management Console Private Access allowed customers to restrict console access to authorized AWS accounts and corporate networks but still required internet connectivity. With this launch, AWS Console traffic can flow through VPC endpoints for the supported service consoles, eliminating the need for any internet access. This capability is particularly valuable for customers in regulated industries such as financial services, government and defense, and healthcare, and for enterprises with strict security requirements who need to access sensitive data only from controlled environments and use the console in classified or networks without internet connectivity.

AWS Management Console Private Access uses AWS PrivateLink to establish secure network paths between customer VPCs and the console. Customers can apply VPC endpoint policies to restrict access to specific AWS accounts and organizations, and use IAM, Service Control, and Resource Control policies to require that employees access resources only from authorized networks.

This capability is available in all AWS commercial regions. You pay only for the underlying AWS PrivateLink VPC endpoint usage and data processing. To get started and learn about the supported services, visit the Management Console Private Access documentation.

 

​AWS Management Console Private Access now enables customers to access the AWS Console from VPCs without internet connectivity, allowing enterprises to manage their AWS infrastructure through the console while maintaining strict network security controls in air-gapped environments. Previously, AWS Management Console Private Access allowed customers to restrict console access to authorized AWS accounts and corporate networks but still required internet connectivity. With this launch, AWS Console traffic can flow through VPC endpoints for the supported service consoles, eliminating the need for any internet access. This capability is particularly valuable for customers in regulated industries such as financial services, government and defense, and healthcare, and for enterprises with strict security requirements who need to access sensitive data only from controlled environments and use the console in classified or networks without internet connectivity. AWS Management Console Private Access uses AWS PrivateLink to establish secure network paths between customer VPCs and the console. Customers can apply VPC endpoint policies to restrict access to specific AWS accounts and organizations, and use IAM, Service Control, and Resource Control policies to require that employees access resources only from authorized networks.
This capability is available in all AWS commercial regions. You pay only for the underlying AWS PrivateLink VPC endpoint usage and data processing. To get started and learn about the supported services, visit the Management Console Private Access documentation.  

Amazon FSx for OpenZFS now supports on-demand data replication across AWS opt-in Regions, enabling you to easily and efficiently transfer incremental point-in-time snapshots of your volumes beyond AWS Regions that are enabled by default. On-demand data replication provides a simple and resilient way to implement disaster recovery, replicate production data to a different Region or account, and enable lower latency data access for your global customer base or workforce.

Amazon FSx for OpenZFS provides fully managed, cost-effective, shared file storage powered by the popular OpenZFS file system, with rich data management capabilities like snapshots, data cloning, and compression, along with sub-millisecond latencies and up to 10 GB/s of throughput. Opt-in Regions are AWS Regions that are disabled by default, in contrast to regions that are enabled by default. Previously, on-demand data replication was supported only between accounts in AWS Regions that are enabled by default. Starting today, you can replicate snapshots to and from opt-in Regions, expanding the AWS Regions where you can build cross-Region disaster recovery and data distribution architectures.

On-demand data replication across opt-in Regions is available in all AWS Regions where Amazon FSx for OpenZFS is offered, including the supported opt-in Regions. There is no additional charge for on-demand data replication. Standard AWS data transfer charges apply when replicating across AWS Regions or accounts. To get started, visit the Amazon FSx console or refer to the on-demand replication documentation. To learn more, visit the Amazon FSx for OpenZFS product page.

 

​Amazon FSx for OpenZFS now supports on-demand data replication across AWS opt-in Regions, enabling you to easily and efficiently transfer incremental point-in-time snapshots of your volumes beyond AWS Regions that are enabled by default. On-demand data replication provides a simple and resilient way to implement disaster recovery, replicate production data to a different Region or account, and enable lower latency data access for your global customer base or workforce.
Amazon FSx for OpenZFS provides fully managed, cost-effective, shared file storage powered by the popular OpenZFS file system, with rich data management capabilities like snapshots, data cloning, and compression, along with sub-millisecond latencies and up to 10 GB/s of throughput. Opt-in Regions are AWS Regions that are disabled by default, in contrast to regions that are enabled by default. Previously, on-demand data replication was supported only between accounts in AWS Regions that are enabled by default. Starting today, you can replicate snapshots to and from opt-in Regions, expanding the AWS Regions where you can build cross-Region disaster recovery and data distribution architectures.
On-demand data replication across opt-in Regions is available in all AWS Regions where Amazon FSx for OpenZFS is offered, including the supported opt-in Regions. There is no additional charge for on-demand data replication. Standard AWS data transfer charges apply when replicating across AWS Regions or accounts. To get started, visit the Amazon FSx console or refer to the on-demand replication documentation. To learn more, visit the Amazon FSx for OpenZFS product page.  

Amazon Bedrock AgentCore Memory extracts useful information from short-term memory and stores it as long-term memory records. Metadata on these records helps organize, filter, and route them for retrieval. Previously, metadata values could only be inferred by the LLM during extraction. Now, you can also attach metadata values directly from your application, ensuring they pass through extraction and consolidation exactly as supplied with no LLM inference. When you set a metadata key’s extraction type to STRICTLY_CONSISTENT, the value you provide on the short-term memory event is the value that lands on the resulting long-term memory record unchanged.

Strictly consistent metadata also isolates how events are grouped. Events sharing the same values are extracted together and consolidated together. Records with different values are never merged, even if semantically similar. This enables department-scoped retrieval, compliance boundaries between regulated and standard records, and multi-tenant memory where each tenant’s data is processed independently.

You can configure up to three strictly consistent keys per strategy. The feature is supported on semantic, user preference, and episodic strategies, including custom overrides. Keys must be of type STRING and declared in the memory’s indexed keys. Both LLM-inferred and strictly consistent keys can coexist on the same memory resource. To get started, see Long-term memory metadata. Amazon Bedrock AgentCore Memory strictly consistent metadata is available in all AWS Regions where AgentCore Memory is supported.

 

​Amazon Bedrock AgentCore Memory extracts useful information from short-term memory and stores it as long-term memory records. Metadata on these records helps organize, filter, and route them for retrieval. Previously, metadata values could only be inferred by the LLM during extraction. Now, you can also attach metadata values directly from your application, ensuring they pass through extraction and consolidation exactly as supplied with no LLM inference. When you set a metadata key’s extraction type to STRICTLY_CONSISTENT, the value you provide on the short-term memory event is the value that lands on the resulting long-term memory record unchanged.
Strictly consistent metadata also isolates how events are grouped. Events sharing the same values are extracted together and consolidated together. Records with different values are never merged, even if semantically similar. This enables department-scoped retrieval, compliance boundaries between regulated and standard records, and multi-tenant memory where each tenant’s data is processed independently.
You can configure up to three strictly consistent keys per strategy. The feature is supported on semantic, user preference, and episodic strategies, including custom overrides. Keys must be of type STRING and declared in the memory’s indexed keys. Both LLM-inferred and strictly consistent keys can coexist on the same memory resource. To get started, see Long-term memory metadata. Amazon Bedrock AgentCore Memory strictly consistent metadata is available in all AWS Regions where AgentCore Memory is supported.