Let us know how we can help
Sales & Pricing
Speak to a rep about your business needs
Help & Support
See our product support options
General inquiries and locations
Contact us
Most teams evaluating mainframe DevOps tools already have Jenkins, GitHub, or Azure DevOps in place. The real question is what's missing to run those workflows on z/OS.
What modern mainframe DevOps tools deliver
Velocity
Faster deployments, shorter lead times, and less manual effort moving code from commit to production.
Cost & Efficiency
Fewer deployment errors, less rework, and simpler toolchains, so developers spend less time on overhead and more on delivery.
Governance & Compliance
Complete audit trails, consistent approvals, and faster vulnerability response strengthen governance without slowing releases.
7 capabilities of modern mainframe DevOps tools
Assess where your toolchain is strong, where it falls short, and which gaps deserve priority.
Source code management and change control
Track changes from development through production with the traceability, governance, and auditability required for enterprise software delivery.
Automated testing
Automated testing validates application quality continuously by integrating COBOL, PL/I, batch, and CICS testing directly into the delivery pipeline.
Pipeline execution
Execute mainframe-specific delivery activities such as COBOL compilation, copybook dependency resolution, Db2 BINDs, promotions, and deployments directly on z/OS.
This is often the capability that differentiates enterprise DevOps platforms from mainframe delivery tooling. Distributed platforms orchestrate these activities while mainframe DevOps platforms execute them.
Software supply chain visibility and vulnerability management
Understand application composition, dependencies, and change impact through SBOM generation, component visibility, and CVE identification.
Delivery measurement and analytics
Measure how software moves through the delivery process using metrics such as deployment frequency, lead time, change failure rate, and mean time to restore.
Developer experience
Improve developer productivity with modern IDEs, debugging, code analysis, impact analysis, and Git-compatible workflows.
AI-assisted delivery
Extend software delivery with AI-assisted development, testing, and deployment while maintaining the same governance, approvals, and auditability required for production changes.
How existing toolchains are extended
If you're modernizing mainframe delivery, GitHub, GitLab, Azure DevOps, Jenkins, and Bitbucket are almost certainly staying in place. The opportunity is extending those workflows to cover pipeline execution, automated testing, deployment automation, and governance on z/OS.
Using GitHub enterprise?
- Keep GitHub and existing developer workflows.
- Add mainframe pipeline execution, automated testing, and deployment governance to support software delivery on z/OS.
Standardizing on Azure DevOps?
- Keep Azure Boards, Azure Repos, and Azure Pipelines as the control plane.
- Add z/OS execution, automated testing, and delivery analytics. Azure continues to orchestrate the workflow while mainframe tooling executes delivery activities on z/OS.
Running Jenkins across the enterprise?
- Keep existing orchestration and release processes.
- Add mainframe execution, testing, deployment automation, and auditability to extend established delivery workflows to z/OS.
What to evaluate when comparing mainframe DevOps tools
Feature comparisons only tell you so much. What matters is whether a solution executes on z/OS, connects to the toolchain you already run, and holds up under the governance mainframe delivery requires.
Quick evaluation checklist. Validate these capabilities early in the evaluation process:
| What to evaluate | What to ask |
|---|---|
|
z/OS execution |
Can it compile natively, resolve dependencies, and handle promotions and deployments directly on z/OS? |
|
Integration with existing platforms |
Does it integrate with GitHub, GitLab, Azure DevOps, Jenkins, and Bitbucket? |
|
Connected delivery workflows |
Do pipeline execution, testing, deployment, governance, and analytics operate as a connected process? |
|
Governed AI operations |
Do AI-assisted activities follow the same approvals, audit trails, and change controls as any other production change? |
|
Software supply chain visibility |
Does it provide SBOM generation, component visibility, and CVE identification. |
|
Delivery analytics |
Can it measure deployment frequency, lead time, change failure rate, and mean time to restore? |
|
Migration path |
Does it provide a practical approach for transitioning from existing SCM and release management environments? |
Distributed vs. integrated mainframe DevOps platforms
Mainframe DevOps tools are often evaluated side-by-side, even though they come from different starting points. Some evolved from change and release management. Some originated as distributed DevOps platforms later extended toward z/OS.
| Distributed DevOps platforms | Integrated mainframe DevOps platforms | |
|---|---|---|
|
Representative solutions |
GitHub, GitLab, Azure DevOps, Jenkins |
BMC AMI DevX |
|
Originally built for |
Distributed software delivery and workflow automation |
Modern software delivery across the mainframe lifecycle |
|
What it covers today |
Developer experience, collaboration, and workflow orchestration |
Connected workflows across development, testing, deployment, governance, and analytics |
|
Key evaluation question |
How are mainframe build, test, deployment, and governance activities executed on z/OS? |
Does an integrated platform simplify operations compared to assembling multiple tools? |
|
What it leaves you to solve on z/OS |
Extending existing enterprise DevOps investments |
Building a unified mainframe DevOps practice |
BMC AMI DevX: an integrated mainframe DevOps platform
One integrated platform delivers all seven capabilities in a connected workflow. Platform engineering and DevOps leaders choose BMC AMI DevX when they want development, testing, deployment, governance, analytics, and AI-assisted development to operate as one delivery process on z/OS.
Source Control & Change Management
Git-compatible development with concurrent development support, end-to-end lifecycle tracking, and governed change management.
Pipeline Execution
z/OS build, promotion, and deployment automation driven from your existing orchestrator through REST APIs, CLIs, and webhooks.
Automated Testing
Automated unit, functional, integration, and regression testing for COBOL, PL/I, and Assembler programs, with test coverage analysis and interactive debugging.
Software Supply Chain Visibility
SBOM generation during the build, component visibility for CVE identification, and Impact Analysis across programs, copybooks, and downstream components.
Delivery Measurement and Analytics
DORA metrics (deployment frequency, lead time, change failure rate, mean time to restore), delivery analytics, and pipeline visibility.
Developer Experience
Modern IDEs in Eclipse and VS Code, interactive debugging, graphical code analysis, and natural language explanation of COBOL, PL/I, JCL, and Assembler.
BMC AMI DevX Workbench, Code Insights, Code Debug, and BMC AMI Assistant.
AI-Assisted Delivery
AI-generated code explanation and program documentation that give developers the context to change unfamiliar code.
15x
more code changes per year
50%
reduction in toolchain administration costs
6x
faster deployment frequency (Fortune 100 Financial Firm)
$7.1M
in increased release frequency over three years
BMC AMI DevX awarded by TrustRadius
BMC AMI DevX has earned consecutive Top Rated awards and a Buyer's Choice award from TrustRadius, reflecting sustained customer satisfaction. Users recognized the solution for modernizing mainframe development, improving code quality, and enabling faster, more secure delivery across enterprise environments.