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Guidance for Warm Standby Using AWS Mainframe Modernization Refactor with AWS Blu Age

Overview

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.

How it works

This architecture diagram shows how to implement a warm standby disaster recovery environment for a refactored application.

Download the architecture diagram

Well-Architected Pillars

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

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.