Since Amazon Web Services (AWS) introduced Savings Plans, customers have been able to lower the cost of running sustained workloads while maintaining the flexibility to manage usage across accounts, resource types, and AWS Regions. Today, we’re extending this flexible pricing model to AWS managed database services with the launch of Database Savings Plans, which help customers reduce database costs by up to 35% when they commit to a consistent amount of usage ($/hour) over a 1-year term. Savings automatically apply each hour to eligible usage across supported database services, and any additional usage beyond the commitment is billed at on-demand rates.

As organizations build and manage data-driven and AI applications, they often use different database services, engines and deployment types, including instance-based and serverless options, to meet evolving business needs. Database Savings Plans provide the flexibility to choose how workloads run while maintaining cost efficiency. If customers are in the middle of a migration or modernization effort, they can switch database engines and adjust deployment types, such as from provisioned to serverless as part of ongoing cost optimization, while continuing to receive discounted rates. If a customer’s business expands globally, they can also shift usage across AWS Regions and continue to benefit from the same commitment. By applying a consistent hourly commitment, customers can maintain predictable spend even as usage patterns evolve and analyze coverage and utilization using familiar cost management tools.

New Savings Plans

Each plan defines where pricing applies, the range of available discounts, and the level of flexibility provided across supported database engines, instance families, sizes, deployment options, or AWS Regions.

The hourly commitment automatically applies to all eligible usage regardless of Region, with support for Amazon Aurora, Amazon Relational Database Service (Amazon RDS), Amazon DynamoDB, Amazon ElastiCache, Amazon DocumentDB (with MongoDB compatibility), Amazon Neptune, Amazon Keyspaces (for Apache Cassandra), Amazon Timestream, and AWS Database Migration Service (AWS DMS). As new eligible database offerings, instance types, or Regions become available, Savings Plans will automatically apply to that usage.

Discounts vary by deployment model and service type. Serverless deployments provide up to 35% savings compared to on-demand rates. Provisioned instances across supported database services deliver up to 20% savings. For Amazon DynamoDB and Amazon Keyspaces, on-demand throughput workloads receive up to 18% savings, and provisioned capacity offers up to 12%. Together, these savings help customers optimize costs while maintaining consistent coverage for database usage. To learn more about the pricing and eligible usage, visit the Database Savings Plans pricing page.

Purchasing Database Savings Plans

AWS Billing and Cost Management Console helps you choose Savings Plans and guides you through the purchase process. You can get started from the AWS Management Console or use the AWS Command Line Interface (AWS CLI) and the API. There are two ways to evaluate Database Savings Plans purchases, in the Recommendations view and in the Purchase Analyzer.

Recommendations – are automatically generated from your recent on-demand usage. To reach the Recommendations view in the Billing and Cost Management console, choose Savings and Commitments, Savings Plans, and Recommendations in the navigation pane. In the Recommendations view, select Database Savings Plans and configure the Recommendation options. AWS Savings Plans recommendations analyze your historical on-demand usage to identify the hourly commitment that delivers the highest overall savings.

The Purchase Analyzer – is designed for modeling custom commitment levels. If you want to purchase a different amount than the recommended commitment on the Purchase Analyzer page, select Database Savings Plans and configure Lookback period and Hourly commitment to simulate alternative commitment levels and see the projected impact on Cost, Coverage, and Utilization.

This way is preferred if your purchasing strategy includes smaller, incremental commitments over time or if you expect future usage changes that could affect your ideal purchase amount.

After reviewing the recommendations or running simulations in Savings Plans Recommendations or Savings Plans Purchase Analyzer, choose Add to cart to proceed with your chosen commitment. If you prefer to purchase directly, you can also navigate to the Purchase Savings Plans page. The console updates estimated discounts and coverage in real time as you adjust each setting, so you can evaluate the impact before completing your order.

You can learn more about how to choose and purchase Database Saving Plans by visiting the Savings Plans User Guide documents.

Now available

Database Savings Plans are available in all AWS Regions outside of China. Give them a try and start shaping your database strategy with more flexibility and predictable costs.

– Betty

The post Introducing Database Savings Plans for AWS Databases appeared first on The NOKIA Blog.

Earlier this year in May, we announced the general availability of AWS Transform for .NET, the first agentic AI service for modernizing .NET applications at scale. During the early adoption period of the service, we received valuable feedback indicating that, in addition to .NET application modernization, you would like to modernize SQL Server and legacy UI frameworks. Your applications typically follow a three-tier architecture—presentation tier, application tier, and database tier—and you need a comprehensive solution that can transform all of these tiers in a coordinated way.

Today, based on your feedback, we’re excited to announce AWS Transform for full-stack Windows modernization, to offload complex, tedious modernization work across the Windows application stack. You can now identify application and database dependencies and modernize them in an orchestrated way through a centralized experience.

AWS Transform accelerates full-stack Windows modernization by up to five times across application, UI, database, and deployment layers. Along with porting .NET Framework applications to cross-platform .NET, it migrates SQL Server databases to Amazon Aurora PostgreSQL-Compatible Edition with intelligent stored procedure conversion and dependent application code refactoring. For validation and testing, AWS Transform deploys applications to Amazon Elastic Compute Cloud (Amazon EC2) Linux or Amazon Elastic Container Service (Amazon ECS), and provides customizable AWS CloudFormation templates and deployment configurations for production use. AWS Transform has also added capabilities to modernize ASP.NET Web Forms UI to Blazor.

There is much to explore, so in this post I’ll provide the first look at AWS Transform for full-stack Windows modernization capabilities across all layers.

Create a full-stack Windows modernization transformation job

AWS Transform connects to your source code repositories and database servers, analyzes application and database dependencies, creates modernization waves, and orchestrates full-stack transformations for each wave.

To get started with AWS Transform, I first complete the onboarding steps outlined in the getting started with AWS Transform user guide. After onboarding, I sign in to the AWS Transform console using my credentials and create a job for full-stack Windows modernization.

After creating the job, I complete the prerequisites. Then, I configure the database connector for AWS Transform to securely access SQL Server databases running on Amazon EC2 and Amazon Relational Database Service (Amazon RDS). The connector can connect to multiple databases within the same SQL Server instance.

Next, I set up a connector to connect to my source code repositories.

Furthermore, I have the option to choose if I would like AWS Transform to deploy the transformed applications. I choose Yes and provide the target AWS account ID and AWS Region for deploying the applications. The deployment option can be configured later as well.

After the connectors are set up, AWS Transform connects to the resources and runs the validation to verify IAM roles, network settings, and related AWS resources.

After the successful validation, AWS Transform discovers databases and their associated source code repositories. It identifies dependencies between databases and applications to create waves for transforming related components together. Based on this analysis, AWS Transform creates a wave-based transformation plan.

Assessing database and dependent applications

For the assessment, I review the databases and source code repositories discovered by AWS Transform and choose the appropriate branches for code repositories. AWS Transform scans these databases and source code repositories, then presents a list of databases along with their dependent .NET applications and transformation complexity.

I choose the target databases and repositories for modernization. AWS Transform analyzes these selections and generates a comprehensive SQL Modernization Assessment Report with a detailed wave plan. I download the report to review the proposed modernization plan. The report includes an executive summary, wave plan, dependencies between databases and code repositories, and complexity analysis.

Wave transformation at scale

The wave plan generated by AWS Transform consists of four steps for each wave. First, it converts the SQL Server schema to PostgreSQL. Second, it migrates the data. Third, it transforms the dependent .NET application code to make it PostgreSQL compatible. Finally, it deploys the application for testing.

Before converting the SQL Server schema, I can either create a new PostgreSQL database or choose an existing one as the target database.

After I choose the source and target databases, AWS Transform generates conversion reports for my review. AWS Transform converts the SQL Server schema to PostgreSQL-compatible structures, including tables, indexes, constraints, and stored procedures.

For any schema that AWS Transform can’t automatically convert, I can manually address them in the AWS Database Migration Service (AWS DMS) console. Alternatively, I can fix them in my preferred SQL editor and update the target database instance.

After completing schema conversion, I have the option to proceed with data migration, which is an optional step. AWS Transform uses AWS DMS to migrate data from my SQL Server instance to the PostgreSQL database instance. I can choose to perform data migration later, after completing all transformations, or work with test data by loading it into my target database.

The next step is code transformation. I specify a target branch for AWS Transform to upload the transformed code artifacts. AWS Transform updates the codebase to make the application compatible with the converted PostgreSQL database.

With this release, AWS Transform for full-stack Windows modernization supports only codebases in .NET 6 or later. For codebases in .NET Framework 3.1+, I first use AWS Transform for .NET to port them to cross-platform .NET. I’ll expand on this in a following section.

After the conversion is completed, I can view the source and target branches along with their code transformation status. I can also download and review the transformation report.

Modernizing .NET Framework applications with UI layer

One major feature we’re releasing today is the modernization of UI frameworks from ASP.NET Web Forms to Blazor. This is added to existing support for modernizing model-view-controller (MVC) Razor views to ASP.NET Core Razor views.

As mentioned previously, if I have a .NET application in legacy .NET Framework, then I continue using AWS Transform for .NET to port it to cross-platform .NET. For legacy applications with UIs built on ASP.NET Web Forms, AWS Transform now modernizes the UI layer to Blazor along with porting the backend code.

AWS Transform for .NET converts ASP.NET Web Forms projects to Blazor on ASP.NET Core, facilitating the migration of ASP.NET websites to Linux. The UI modernization feature is enabled by default in AWS Transform for .NET on both the AWS Transform web console and Visual Studio extension.

During the modernization process, AWS Transform handles the conversion of ASPX pages, ASCX custom controls, and code-behind files, implementing them as server-side Blazor components rather than web assembly. The following project and file changes are made during the transformation:

Other new features in AWS Transform for .NET

Along with UI porting, AWS Transform for .NET has added support for more transformation capabilities and enhanced developer experience. These new features include the following:

• Port to .NET 10 and .NET Standard – AWS Transform now supports porting to .NET 10, the latest Long-Term Support (LTS) release, which was released on November 11, 2025. It also supports porting class libraries to .NET Standard, a formal specification for a set of APIs that are common across all .NET implementations. Furthermore, AWS Transform is now available with AWS Toolkit for Visual Studio 2026.
• Editable transformation report – After the assessment is complete, you can now view and customize the transformation plan based on your specific requirements and preferences. For example, you can update package replacement details.
• Real-time transformation updates with estimated remaining time – Depending on the size and complexity of the codebase, AWS Transform can take some time to complete the porting. You can now track transformation updates in real-time along with the estimated remaining time.
• Next steps markdown – After the transformation is complete, AWS Transform now generates a next steps markdown file with the remaining tasks to complete the porting. You can use this as a revised plan to repeat the transformation with AWS Transform or use AI code-companions to complete the porting.

Things to know

Some more things to know are:

• AWS Regions – AWS Transform for full-stack Windows modernization is generally available today in the US East (N. Virginia) Region. For Regional availability and future roadmap, visit the AWS Capabilities by Region.
• Pricing – Currently, there is no added charge for Windows modernization features of AWS Transform. Any resources you create or continue to use in your AWS account using the output of AWS Transform are billed according to their standard pricing. For limits and quotas, refer to the AWS Transform User Guide.
• SQL Server versions supported – AWS Transform supports the transformation of SQL Server versions from 2008 R2 through 2022, including all editions (Express, Standard, and Enterprise). SQL Server must be hosted on Amazon RDS or Amazon EC2 in the same Region as AWS Transform.
• Entity Framework versions supported – AWS Transform supports the modernization of Entity Framework versions 6.3 through 6.5 and Entity Framework Core 1.0 through 8.0.
• Getting started – To get started, visit AWS Transform for full-stack Windows modernization User Guide.

– Prasad

The post AWS Transform announces full-stack Windows modernization capabilities appeared first on The NOKIA Blog.

AWS Developer Day 2025, held on February 20th, showcased how to integrate responsible generative AI into development workflows. The event featured keynotes from AWS leaders including Srini Iragavarapu, Director Generative AI Applications and Developer Experiences, Jeff Barr, Vice President of AWS Evangelism, David Nalley, Director Open Source Marketing of AWS, along with AWS Heroes and technical community members. Watch the full event recording on Developer Day 2025.

Applications are now open through March 6th for the 2025 AWS Cloud Clubs Captains program. AWS Cloud Clubs are student-led groups for post-secondary and independent students, 18 years old and over. Find a club near you on our Meetup page.

Last week’s launches
Here are some launches that got my attention:

Amplify Hosting announces support for IAM roles for server-side rendered (SSR) applications –  AWS Amplify Hosting now supports AWS Identity and Access Management (IAM) roles for SSR applications, enabling secure access to AWS services without managing credentials manually. Learn more in the IAM Compute Roles for Server-Side Rendering with AWS Amplify Hosting blog.

AWS WAF enhances Data Protection and logging experience –  AWS WAF expands its Data Protection capabilities allowing sensitive data in logs to be replaced with cryptographic hashes (e.g. ‘ade099751d2ea9f3393f0f’) or a predefined static string (‘REDACTED’) before logs are sent to WAF Sample Logs, Amazon Security Lake, Amazon CloudWatch, or other logging destinations.

Announcing AWS DMS Serverless comprehensive premigration assessments – AWS Database Migration Service Serverless (AWS DMS Serverless) now supports premigration assessments for replications to identify potential issues before database migrations begin. The tool analyzes source and target databases, providing recommendations for optimal DMS settings and best practices.

Amazon ECS increases the CPU limit for ECS tasks to 192 vCPUs – Amazon Elastic Container Service (Amazon ECS) now supports CPU limits of up to 192 vCPU for ECS tasks deployed on Amazon Elastic Compute Cloud (Amazon EC2) instances, an increase from the previous 10 vCPU limit. This enhancement allows customers to more effectively manage resource allocation on larger Amazon EC2 instances.

AWS Network Firewall introduces automated domain lists and insights – AWS Network Firewall now provides automated domain lists and insights by analyzing 30 days of HTTP/S traffic. This helps create and maintain allow-list policies more efficiently, at no extra cost.

AWS announces Backup Payment Methods for invoices – AWS now enables you to set up backup payment methods that automatically activate if primary payment fails. This helps prevent service interruptions and reduces manual intervention for invoice payments.

Get updated with all the announcements of AWS announcements on the What’s New with AWS? page.

Other AWS news
Here are additional noteworthy items:

AWS Partner Network: Essential training resources for ISV partners – To help scale solutions effectively, AWS provides essential training resources for Software Vendors (ISVs) partners in four key areas: AWS Marketplace fundamentals, Foundational Technical Review (FTR), APN Customer Engagement (ACE) program and co-selling, and Partner funding opportunities.

How Formula 1® uses generative AI to accelerate race-day issue resolution – Formula 1® (F1) uses Amazon Bedrock to speed up race-day issue resolution, reducing troubleshooting time from weeks to minutes through a chatbot that analyzes root causes and suggests fixes.

Reducing hallucinations in LLM agents with a verified semantic cache using Amazon Bedrock Knowledge Bases – This blog introduces a solution using Amazon Bedrock Knowledge Bases and Amazon Bedrock Agents to reduce Large language models (LLMs) hallucinations by implementing a verified semantic cache that checks queries against curated answers before generating new responses, improving accuracy and response times.

Orchestrate an intelligent document processing workflow using tools in Amazon Bedrock – This blog demonstrates an intelligent document processing workflow using Amazon Bedrock tools that combines Anthropic’s Claude 3 Haiku for orchestration and Anthropic’s Claude 3.5 Sonnet (v2) for analysis to handle structured, semi-structured, and unstructured healthcare documents efficiently.

From community.aws
Here are my personal favorites posts from community.aws:

Tracing Amazon Bedrock Agents – Learn how to track and analyze Amazon Bedrock Agents workflows using AWS X-Ray for better observability, by Randy D.

Testing Amazon ECS Network Resilience with AWS FIS – This article demonstrates how to test network resilience in Amazon ECS using AWS FIS with guidance from Amazon Q Developer, by Sunil Govindankutty

Stop Using Default Arguments in AWS Lambda Functions – Discover why your AWS Lambda costs might be spiralling out of control due to a common Python programming practice, by Stuart Clark.

Amazon Nova Prompt Engineering on AWS: A Field Guide by Brooke – A field guide for using Amazon Nova models, covering prompt engineering patterns and best practices on AWS, by Brooke Jamieson.

Creating Deployment Configurations for EKS with Amazon Q – Amazon Q Developer helps create EKS deployments by providing templates and best practices for Kubernetes configs, by Ricardo Tasso.

Processing WhatsApp Multimedia with Amazon Bedrock Agents: Images, Video, and Documents – I invite you to read my latest blog, which explains how to create a WhatsApp AI assistant using Amazon Bedrock and Amazon Nova models to process multimedia content such as images, videos, documents, and audio.

Upcoming AWS events
Check your calendars and sign up for these upcoming AWS events:

AWS GenAI Lofts – GenAI Lofts offer collaborative spaces and immersive experiences for startups and developers. You can join in-person GenAI Loft San Francisco events such as Hands-on with Agentic Graph RAG Workshop (February 25), Unstructured Data Meetup SF (February 26 – 27) and AI Tinkerers – San Francisco – February 2025 Demos + Science Fair (February 27 – 28). GenAI Loft Berlin has events and workshops on February 24 to March 7 that you can’t miss!

AWS Community Days – Join community-led conferences that feature technical discussions, workshops, and hands-on labs led by expert AWS users and industry leaders from around the world: Milan, Italy (April 2), Bay Area – Security Edition (April 4), Timișoara, Romania (April 10), and Prague, Czeh Republic (April 29).

AWS Innovate: Generative AI + Data – Join a free online conference focusing on generative AI and data innovations. Available in multiple geographic regions: APJC and EMEA (March 6), North America (March 13), Greater China Region (March 14), and Latin America (April 8).

AWS Summits – Join free online and in-person events that bring the cloud computing community together to connect, collaborate, and learn about AWS. Register in your nearest city: Paris (April 9), Amsterdam (April 16), London (April 30), and Poland (May 5).

AWS re:Inforce – AWS re:Inforce (June 16–18) in Philadelphia, PA our annual learning event devoted to all things AWS cloud security. Registration opens in March, and be ready to join more than 5,000 security builders and leaders.

Create your AWS Builder ID and reserve your alias. Builder ID is a universal login credential that gives you access–beyond the AWS Management Console–to AWS tools and resources, including over 600 free training courses, community features, and developer tools such as Amazon Q Developer.

You can browse all upcoming in-person and virtual events.

That’s all for this week. Stay tuned for next week’s Weekly Roundup!

— Eli

This post is part of our Weekly Roundup series. Check back each week for a quick roundup of interesting news and announcements from AWS!

The post AWS Weekly Roundup: Cloud Club Captain Applications, Formula 1®, Amazon Nova Prompt Engineering, and more (Feb 24, 2025) appeared first on The NOKIA Blog.