This Guidance demonstrates how to achieve a lower recovery time objective (RTO) for mainframe workloads. Mainframes run mission critical enterprise workloads with stringent RTOs. The AWS Well-Architected Framework (WAF) provides prescriptive guidance on building highly resilient applications, helping you choose the right disaster recovery strategy based on RTO requirements.

Aligned to WAF, this Guidance integrates with AWS Mainframe Modernization and other AWS services to create a warm standby environment. This environment will be ready to fail over your business processes to a separate AWS Region, reducing RTO for high-priority workloads.

Please note: [Disclaimer]

Architecture Diagram

[Architecture diagram description]

Download the architecture diagram PDF 

Get Started

Try out this Guidance

Deploy this Guidance

Well-Architected Pillars

The AWS Well-Architected Framework helps you understand the pros and cons of the decisions you make when building systems in the cloud. The six pillars of the Framework allow you to learn architectural best practices for designing and operating reliable, secure, efficient, cost-effective, and sustainable systems. Using the AWS Well-Architected Tool, available at no charge in the AWS Management Console, you can review your workloads against these best practices by answering a set of questions for each pillar.

The architecture diagram above is an example of a Solution created with Well-Architected best practices in mind. To be fully Well-Architected, you should follow as many Well-Architected best practices as possible.

  • Amazon CloudWatch and Aurora provide real-time monitoring, customizable alerts, and anomaly detection. CloudWatch defines custom metrics and sets alarms for prompt response to performance issues. Aurora continuously monitors database health, generates events for failures or maintenance, and enables automated failover for disaster recovery, supporting operational excellence through proactive monitoring and automated actions.

    Read the Operational Excellence whitepaper 

  • Aurora PostgreSQL supports encryption at rest using AWS Key Management Service (AWS KMS) and encryption in transit through SSL/TLS connections, protecting sensitive data. Instances are deployed within virtual private clouds (VPCs) with network security groups for access control. Aurora automatically applies security patches and updates, reducing exposure to known vulnerabilities.

    Read the Security whitepaper 

  • Multi-AZ deployment provides redundancy, high availability, and disaster recovery capabilities, mitigating risks of single points of failure. Route 53 ARC continuously monitors application health, detects failures, and automates recovery actions like traffic rerouting or failover initiation. This reduces recovery time and enhances operational resilience.

    Read the Reliability whitepaper 

  • Multi-AZ deployment enables horizontal scaling by adding instances or resources across AZs as demand increases. Aurora PostgreSQL uses a distributed, shared storage architecture that automatically scales compute and storage based on workload demands. This scalable architecture, combined with the ability to handle high throughput and large transaction volumes, allows you to optimize performance and meet varying workload requirements efficiently.

    Read the Performance Efficiency whitepaper 

  • AWS Mainframe Modernization and Aurora offer pay-as-you-go pricing, meaning you only pay for the resources you consume, which eliminates upfront costs. Aurora's storage auto-scaling from 10 GB to 64 TB per instance optimizes utilization. This flexible pricing model allows you to scale resources up or down based on workload demands, minimizing unnecessary expenses from overprovisioning or underutilization.

    Read the Cost Optimization whitepaper 

  • Built on AWS's energy-efficient infrastructure with advanced cooling, efficient power distribution, and renewable energy sources, Aurora and AWS Mainframe Modernization minimize energy consumption. Aurora automatically scales compute and storage based on workload demands for efficient resource utilization and reduced wasted resources. This optimized resource allocation minimizes the environmental impact associated with excessive energy consumption and hardware provisioning.

    Read the Sustainability whitepaper 

Related Content

[Content Type]

[Title]

This [blog post/e-book/Guidance/sample code] demonstrates how [insert short description].

Disclaimer

The sample code; software libraries; command line tools; proofs of concept; templates; or other related technology (including any of the foregoing that are provided by our personnel) is provided to you as AWS Content under the AWS Customer Agreement, or the relevant written agreement between you and AWS (whichever applies). You should not use this AWS Content in your production accounts, or on production or other critical data. You are responsible for testing, securing, and optimizing the AWS Content, such as sample code, as appropriate for production grade use based on your specific quality control practices and standards. Deploying AWS Content may incur AWS charges for creating or using AWS chargeable resources, such as running Amazon EC2 instances or using Amazon S3 storage.

References to third-party services or organizations in this Guidance do not imply an endorsement, sponsorship, or affiliation between Amazon or AWS and the third party. Guidance from AWS is a technical starting point, and you can customize your integration with third-party services when you deploy the architecture.

Was this page helpful?

 Feedback