Data as of Sep 21, 2026 · Based on 353 AI responses from ChatGPT Search and Google AI Mode · See how Parse measures this
For ensuring high availability for legacy mainframe applications, 
Brands AI recommends here
Named in 58% of answers
Best for managed cloud migration using re-platforming or automated refactoring (COBOL to Java). It ensures high availability via automated data replication but requires a shift to cloud-native architectural patterns.
Named in 44% of answers
Best for managed services involving complex, mission-critical IBM z/OS migrations. It focuses on maintaining operational resilience and system security throughout the modernization lifecycle.
Named in 41% of answers
Named in 40% of answers
Source | Citation share |
|---|---|
AWS Mainframe Modernization: transforming telco from legacy ...https://aws.amazon.com/blogs/industries/aws-mainframe-modernization-transforming-telco-from-legacy-constraints-to-digital-innovation/ | 3% |
 Best Mainframe Upgrade and Modernization Solutions for 2026https://datastealth.io/blogs/best-mainframe-upgrade-and-modernization-solutions-for-2026 | 3% |
 Top Legacy Modernization Tools in 2025https://devoxsoftware.com/blog/top-legacy-modernization-tools-in-2025-a-comprehensive-guide/ | 2% |
AWS Mainframe Modernizationhttps://aws.amazon.com/mainframe-modernization/ | 2% |
 What is mainframe modernization? | IBMhttps://www.ibm.com/think/topics/mainframe-modernization | 2% |
 7 Best Tools for Mainframe App Modernization in 2026 | Adalohttps://www.adalo.com/posts/top-mainframe-application-modernization | 2% |
 Top Mainframe Modernization Services: A 2025 Guidehttps://www.linkedin.com/pulse/top-mainframe-modernization-services-2025-guide-9roqc | 1% |
 tierpoint.comhttps://www.tierpoint.com/blog/mainframe-modernization/ | 1% |
Best Mainframe Modernization Solutions 2026 | Top 5 Ratedhttps://datastealth.io/blogs/best-mainframe-upgrade-and-modernization-solutions | 1% |
Mainframe Migration Strategies, Benefits and Products - AWShttps://aws.amazon.com/mainframe/ | 1% |
Ensuring high availability (HA) for legacy mainframe applications depends heavily on whether you choose to **rehost/emulate** (running existing COBOL/PL/I code on distributed or cloud infrastructure) or **refactor/transform** (converting code to modern cloud-native microservices). The top-rated services and platforms…
Ensuring high availability (HA) for legacy mainframe applications depends heavily on whether you choose to rehost/emulate (running existing COBOL/PL/I code on distributed or cloud infrastructure) or refactor/transform (converting code to modern cloud-native microservices).
The top-rated services and platforms categorized by their approach to high availability include the following:
To help narrow down the ideal path, could you share:
If **high availability is the primary requirement**, I’d separate the decision into two architectures: 1. **Keep the mainframe, modernize around it** — usually the least disruptive path when the workloads are genuinely mission-critical. 2. **Emulate/replatform the mainframe workload onto distributed/cloud…
If high availability is the primary requirement, I’d separate the decision into two architectures:
There isn't one universally “best” service; the right choice depends heavily on whether you need mainframe-compatible execution or actual application transformation.
| Option | Approach | Best fit for HA | Key consideration |
|---|---|---|---|
| IBM Z + GDPS / Parallel Sysplex | Keep workloads on IBM Z | Very high availability with minimal application change | Best when reliability of the existing mainframe environment is paramount |
| Rocket Software Enterprise Server | Mainframe-compatible rehosting/emulation | HA through distributed infrastructure and clustering | Strong choice when you want to preserve COBOL/PL/I and minimize rewrites |
| AWS Mainframe Modernization / AWS Transform for mainframe | Replatform or refactor | Cloud-scale HA and incremental migration | Particularly attractive if AWS is already your strategic cloud |
| OpenText Enterprise Server | Mainframe application rehosting | Distributed HA while preserving much of the application | Worth evaluating for large COBOL estates |
| Automated refactoring platforms | Convert COBOL/PL/I into modern applications | Depends on the resulting architecture | Greater long-term modernization, but substantially more transformation risk |
AWS currently supports both replatforming and automated refactoring: replatforming can preserve COBOL/PL/I with relatively little source-code change, while AWS Transform for mainframe can transform legacy applications toward Java/cloud-native architectures.
One important current wrinkle: AWS's older Mainframe Modernization managed/self-managed experiences are no longer accepting new customers, so for a new AWS project I'd evaluate AWS Transform for mainframe and vendor-direct offerings rather than designing around the older service.
If these applications cannot tolerate downtime, I'd generally evaluate the options in this order:
For a 24×7 legacy workload, I would not choose a modernization vendor based simply on whether it can “run COBOL.” I'd specifically require a proof of concept demonstrating active/active or active/standby failover, transaction recovery, data consistency, batch restart/recovery, CICS/IMS compatibility, latency under load, and recovery-time/recovery-point objectives.
If you tell me which mainframe (IBM z/OS, Unisys, Fujitsu, etc.), languages (COBOL/PL/I/Assembler), transaction system (CICS/IMS), database (Db2/VSAM/IMS), and your target cloud/on-prem environment, I can narrow this to a concrete architecture and vendor comparison.
If **high availability (HA) is the primary requirement**, I’d favor **replatforming/emulation first**, rather than immediately rewriting the applications. It preserves COBOL/PL/I and business logic while giving you a path to redundant cloud infrastructure. ### My shortlist Option | Best fit | HA posture |…
If high availability (HA) is the primary requirement, I’d favor replatforming/emulation first, rather than immediately rewriting the applications. It preserves COBOL/PL/I and business logic while giving you a path to redundant cloud infrastructure.
| Option | Best fit | HA posture | Modernization depth |
|---|---|---|---|
| AWS Mainframe Modernization / AWS Transform for mainframe | Move workloads to AWS while retaining behavior | Excellent — HA clusters, load balancing, horizontal scaling | High |
| OpenText Enterprise Server | Mainframe-compatible COBOL workloads with minimal code change | Excellent | Moderate |
| IBM Z + watsonx Code Assistant for Z | Stay on IBM Z while progressively modernizing | Excellent on Z | High, but not primarily an emulator |
| AWS Blu Age / Transform refactoring | Convert COBOL/mainframe workloads to Java | Excellent when architected cloud-natively | Very high |
My default recommendation: AWS, particularly if your goal is eventually to get off the physical mainframe. AWS's current architecture explicitly supports HA clusters, and its runtime is designed around statelessness, load balancing and shared state so transactions can move between application nodes.
AWS also supports two quite different migration paths: replatforming with Micro Focus/Rocket technology, which keeps the programming language and business logic largely intact, or refactoring with AWS Transform/Blu Age toward Java and cloud-native services.
One important caveat: AWS's product packaging has changed recently—the older managed-runtime experience is no longer accepting new customers, so I'd evaluate the current AWS Transform/self-managed offerings, rather than relying on older AWS Mainframe Modernization architecture diagrams.
Bottom line: For a mission-critical legacy estate, I'd shortlist AWS Transform/Mainframe Modernization + OpenText Enterprise Server, with IBM Z/watsonx as the strongest choice if staying on IBM Z is strategically important. The "best" one depends heavily on whether you want emulation/rehosting, replatforming, or actual code transformation.
If you tell me IBM z/OS vs Unisys vs Fujitsu, the languages (COBOL/PL/I/Assembler), database (Db2/IMS/VSAM), and your target RTO/RPO, I can narrow this to a specific architecture and vendor recommendation.
One important caveat: AWS's product packaging has changed recently—the older managed-runtime experience is no longer accepting new customers, so I'd evaluate the current AWS Transform/self-managed offerings, rather than relying on older AWS Mainframe Modernization architecture diagrams.
Ensuring high availability (HA) for legacy mainframe applications without staying 100% bound to traditional, costly physical hardware typically comes down to choosing between **managed cloud modernization platforms (replatforming/refactoring)** or **enterprise-grade emulation/virtualization**. The "best" service…
Ensuring high availability (HA) for legacy mainframe applications without staying 100% bound to traditional, costly physical hardware typically comes down to choosing between managed cloud modernization platforms (replatforming/refactoring) or enterprise-grade emulation/virtualization.
The "best" service depends on whether you want to rehost/replatform (keep COBOL/PL/I running on modern cloud infrastructure) or refactor (convert code to modern microservices).
To help narrow down the best path, tell me:
Ensuring high availability (HA) for legacy mainframe applications depends heavily on whether you choose to **rehost/emulate** on distributed systems, **refactor** into cloud-native code, or **stay native** on modern hardware. `There is no single "best" service, but rather a set of industry leaders tailored to specific…
Ensuring high availability (HA) for legacy mainframe applications depends heavily on whether you choose to rehost/emulate on distributed systems, refactor into cloud-native code, or stay native on modern hardware. There is no single "best" service, but rather a set of industry leaders tailored to specific architectural strategies.
The top-tier options for achieving high availability are organized below by their primary modernization approach:
To help narrow down the ideal path for your organization, tell me:
If **high availability (HA)** is the primary requirement, I would not choose a platform based simply on “mainframe emulation.” The best option depends on whether you want to **keep the mainframe architecture**, **rehost it**, or **actually modernize the applications**. ### My shortlist Option | Best fit | HA potential…
If high availability (HA) is the primary requirement, I would not choose a platform based simply on “mainframe emulation.” The best option depends on whether you want to keep the mainframe architecture, rehost it, or actually modernize the applications.
| Option | Best fit | HA potential | Modernization depth |
|---|---|---|---|
| AWS Mainframe Modernization / Blu Age | Move COBOL/PL/I workloads to cloud | Excellent | High |
| Rocket Software Enterprise Server | Rehost COBOL/PL/I with minimal code changes | Excellent | Low–medium |
| IBM Z / hybrid cloud | Keep mission-critical workloads on IBM Z while modernizing around them | Excellent | Medium–high |
| Raincode | Large-scale incremental migration without rewriting source | Excellent | Medium–high |
If you're willing to move the workload off the mainframe, AWS Mainframe Modernization with Blu Age is probably the strongest starting point for an HA-focused modernization program.
Blu Age transforms legacy applications into Java-based applications that can run on AWS infrastructure. AWS documents architectures using multiple Availability Zones, load balancing and shared state, allowing transactions to move between healthy application nodes.
More importantly for your requirement, AWS has a documented warm-standby, multi-Region architecture for Blu Age. The primary environment runs across multiple AZs while a scaled-down secondary environment is maintained in another Region for disaster recovery.
That gives you a path roughly like:
Mainframe → Blu Age → Java/cloud application → Multi-AZ HA → Multi-Region DR
You can also use blue/green deployment to reduce cutover risk and maintain a rollback path during migration.
One important 2026 caveat: the AWS Mainframe Modernization managed-runtime experience is no longer open to new customers; AWS directs new customers toward its self-managed experience.
If the goal is “get off the physical mainframe without rewriting decades of COBOL”, I'd look closely at Rocket Software Enterprise Server.
AWS specifically supports replatforming COBOL/PL/I applications with Rocket Software, allowing existing applications to be recompiled and run on AWS with relatively little code change.
This is attractive when your priority is:
In that scenario, I'd generally favor Rocket over Blu Age.
For extremely stringent availability requirements—particularly banking, insurance, payments, government, or other systems where decades of operational hardening matter—I wouldn't automatically migrate the core transaction engine.
An IBM Z + hybrid-cloud strategy can preserve the mainframe's resiliency while exposing APIs/events and moving appropriate surrounding workloads to cloud. IBM explicitly positions hybrid IBM Z/cloud architectures as a way to retain mainframe performance, resiliency and security while modernizing applications.
Raincode is particularly interesting if you have a very large estate and want incremental migration rather than a big-bang rewrite. Its current approach compiles the original source rather than transforming/rewriting it and is designed for very large mainframe estates.
I'd make the decision this way:
If you tell me your mainframe platform (z/OS, IBM Z, Unisys, etc.), languages (COBOL/PL/I/Assembler), transaction system (CICS/IMS), databases (Db2/IMS/VSAM), and target RTO/RPO, I can narrow this to a specific architecture and compare AWS Blu Age vs Rocket vs IBM vs Raincode for your environment.
An IBM Z + hybrid-cloud strategy can preserve the mainframe's resiliency while exposing APIs/events and moving appropriate surrounding workloads to cloud. IBM explicitly positions hybrid IBM Z/cloud architectures as a way to retain mainframe performance, resiliency and security while modernizing applications.
That gives you a path roughly like:
Mainframe → Blu Age → Java/cloud application → Multi-AZ HA → Multi-Region DR
You can also use blue/green deployment to reduce cutover risk and maintain a rollback path during migration.
One important 2026 caveat: the AWS Mainframe Modernization managed-runtime experience is no longer open to new customers; AWS directs new customers toward its self-managed experience.
If the goal is “get off the physical mainframe without rewriting decades of COBOL”, I'd look closely at Rocket Software Enterprise Server.
If **high availability (HA) is the primary requirement**, I’d favor **replatforming/emulation with strong scale-out support** over a full rewrite. For most legacy COBOL/PL/I estates, my shortlist would be: Option | Best fit | HA/scalability | Modernization depth --- | --- | --- | ---
If high availability (HA) is the primary requirement, I’d favor replatforming/emulation with strong scale-out support over a full rewrite. For most legacy COBOL/PL/I estates, my shortlist would be:
| Option | Best fit | HA/scalability | Modernization depth |
|---|---|---|---|
| Rocket Software Enterprise Server | Closest mainframe-compatible replatform | Excellent — PAC/scale-out, load balancing, cloud deployment | Medium |
| AWS Transform for mainframe | Move toward Java/cloud-native while preserving behavior | Excellent — stateless runtime + horizontal scaling | High |
| Raincode | Very large estates needing incremental cloud migration | Excellent — compiled workloads can scale in cloud | High |
| Keep IBM Z / hybrid modernization | Extremely critical workloads where migration risk outweighs savings | Excellent with established z/OS HA architecture | Low–medium |
For a typical enterprise with existing COBOL/CICS/IMS/JCL applications, I'd start with Rocket Software Enterprise Server. It is specifically designed to run IBM mainframe applications on Linux/Windows/cloud platforms with minimal application changes. Its Performance and Availability Cluster (PAC) can distribute workloads across multiple instances, and AWS documents architectures combining Enterprise Server PAC with EC2 Auto Scaling for resilient production environments.
That makes it particularly attractive if your goal is:
AWS has also documented a production architecture where Enterprise Server supports IBM COBOL, PL/I, JCL, CICS and IMS workloads and is deployed for high availability and resiliency.
If your objective isn't simply "get off the mainframe" but "turn these applications into cloud-native software," I'd evaluate AWS Transform for mainframe more seriously.
Its runtime is designed around statelessness, shared state, load balancing and horizontal scaling, allowing modernized applications to run across multiple nodes and replace unhealthy nodes without losing transaction state.
AWS also distinguishes this from straightforward replatforming: its automated refactoring approach converts legacy programs toward Java-based applications, whereas Rocket's approach preserves much more of the original execution model.
One important current wrinkle: AWS's older Mainframe Modernization managed-runtime/self-managed experiences are no longer open to new customers, so for a new project I'd investigate the current AWS Transform/vendor-direct offerings rather than designing around the older service model.
Don't evaluate these products solely on whether the application runtime supports HA. Your target architecture should have:
Application tier: multiple runtime nodes across AZs → Load balancer → Shared/replicated state and data → Multi-AZ database/storage → Automated health checks + replacement → Cross-region DR
For example, AWS's documented replatforming architecture uses a Network Load Balancer distributing transactions across multiple EC2 instances, while maintaining connectivity to Db2 for z/OS.
If I had to pick one without knowing more about your environment: Rocket Software Enterprise Server/PAC is my first choice for HA-focused mainframe emulation/replatforming.
If you tell me (1) IBM z/OS vs. Unisys/Bull/etc., (2) COBOL/PL/I, (3) CICS/IMS, (4) DB2/VSAM, (5) current MIPS/workload size, and (6) whether you want cloud migration or simply HA, I can give you a much more precise Rocket vs. AWS Transform vs. Raincode vs. staying on IBM Z recommendation.
Ensuring high availability (HA) for legacy mainframe applications requires balancing operational risk, cost, and long-term viability. There is no single "best" service because the ideal path depends on whether you want to **emulate/rehost** (keep code as-is on modern scalable infrastructure) or **refactor/transform**…
Ensuring high availability (HA) for legacy mainframe applications requires balancing operational risk, cost, and long-term viability. There is no single "best" service because the ideal path depends on whether you want to emulate/rehost (keep code as-is on modern scalable infrastructure) or refactor/transform (convert COBOL/PL/I to Java/.NET).
The top modernization and emulation options are categorized below by their approach to high availability:
Choosing the Right Strategy for High Availability
To help narrow down the ideal path, tell me:
Ensuring high availability (HA) for legacy mainframe applications comes down to a choice between **staying in-place** (optimizing and automating on native hardware) or **replatforming/migrating** (moving to the cloud or distributed Linux/Unix environments via emulation or automated…
Ensuring high availability (HA) for legacy mainframe applications comes down to a choice between staying in-place (optimizing and automating on native hardware) or replatforming/migrating (moving to the cloud or distributed Linux/Unix environments via emulation or automated refactoring).
There is no single "best" service because high availability depends heavily on your risk tolerance, budget, and target architecture. The top-tier solutions and services are categorized below by their approach to high availability:
If your goal is to move off physical mainframes entirely and leverage cloud-native high availability, multi-region redundancy, and auto-scaling, the major cloud providers offer dedicated migration and emulation runtimes:
If moving off the mainframe is too high-risk, the gold standard for high availability is policy-driven automation and optimization on native hardware:
If you want to move away from proprietary mainframe pricing and run workloads on local or private Linux/Unix servers with high uptime:
Choosing the Right Path
To help narrow down the ideal service or vendor for your organization, please share:
If **high availability (HA)** is the primary requirement, I would not choose a modernization platform based on “how much code it can convert.” I’d choose based on **how safely you can run the workload redundantly while preserving COBOL/PL/I behavior, transaction semantics, batch scheduling, and data consistency**. ###…
If high availability (HA) is the primary requirement, I would not choose a modernization platform based on “how much code it can convert.” I’d choose based on how safely you can run the workload redundantly while preserving COBOL/PL/I behavior, transaction semantics, batch scheduling, and data consistency.
| Option | Best fit | HA / continuity approach | My take |
|---|---|---|---|
| AWS Mainframe Modernization + Rocket Software | Replatforming with minimal code change | Multi-AZ cloud architecture, horizontal scaling, replicated data | Best pragmatic choice for many enterprises |
| AWS Transform for mainframe | Deeper modernization/refactoring | Modern distributed/cloud architecture | Best if you're willing to transform the application, not merely emulate it |
| LzLabs Software Defined Mainframe | Very high compatibility / gradual migration | Run existing mainframe binaries on modern infrastructure while maintaining interoperability | Excellent when avoiding source-code changes is critical |
| IBM Z / Parallel Sysplex | Keep applications on IBM Z | Mature hardware/software HA, workload redundancy | Best if the goal is availability rather than leaving the mainframe |
AWS currently supports both automated refactoring and replatforming approaches; its replatforming path uses Rocket Software technology to preserve COBOL/PL/I applications while moving the runtime to AWS.
One important current wrinkle: don't base a new architecture on the old AWS managed Mainframe Modernization runtime. AWS says that experience is no longer open to new customers; AWS is steering new modernization work toward AWS Transform and vendor-direct/self-managed capabilities.
If these are mission-critical legacy applications where downtime is unacceptable, I'd start with replatforming rather than wholesale rewriting.
A good target architecture would look roughly like:
Existing mainframe → automated discovery/testing → Rocket/LzLabs-compatible runtime → redundant compute across AZs → replicated/HA database → automated failover → gradual modernization
That lets you establish HA before undertaking the riskier application transformation.
LzLabs is particularly interesting if you have a large installed base and want to minimize application changes: its Software Defined Mainframe is designed for binary compatibility, allowing existing applications to move without recompilation while remaining interoperable with workloads still on the mainframe.
AWS's own documentation also explicitly distinguishes a single-instance environment from a high-availability cluster with redundant instances across two Availability Zones, which illustrates the architecture I'd want to see in a serious replatforming design.
Bottom line:
If you tell me your mainframe platform (z/OS, z/VSE, Unisys, etc.), languages (COBOL/PL/I/Assembler), database (Db2/IMS/VSAM), current HA target (e.g. 99.99%/99.999%), and preferred cloud, I can narrow this to a specific architecture and vendor recommendation.
AWS currently supports both automated refactoring and replatforming approaches; its replatforming path uses Rocket Software technology to preserve COBOL/PL/I applications while moving the runtime to AWS.
One important current wrinkle: don't base a new architecture on the old AWS managed Mainframe Modernization runtime. AWS says that experience is no longer open to new customers; AWS is steering new modernization work toward AWS Transform and vendor-direct/self-managed capabilities.
If these are mission-critical legacy applications where downtime is unacceptable, I'd start with replatforming rather than wholesale rewriting.
A good target architecture would look roughly like:
Existing mainframe → automated discovery/testing → Rocket/LzLabs-compatible runtime → redundant compute across AZs → replicated/HA database → automated failover → gradual modernization
That lets you establish HA before undertaking the riskier application transformation.
LzLabs is particularly interesting if you have a large installed base and want to minimize application changes: its Software Defined Mainframe is designed for binary compatibility, allowing existing applications to move without recompilation while remaining interoperable with workloads still on the mainframe.
