Enabling Skills Transformation with PropelZ™

From Mainframe Specialists to Cloud-Native Teams

How PropelZ’s cloud-integration approach solves the mainframe skills shortage by enabling existing DevOps teams to manage mainframe data flows using familiar tools and techniques.

The mainframe skills crisis is real. Experienced COBOL developers are retiring faster than new ones are entering the field. REXX scripting expertise is increasingly rare. Knowledge of JCL, VSAM, and mainframe operational procedures is concentrated in a shrinking group of specialists.

Meanwhile, the demand for mainframe data integration keeps growing. Cloud migrations, analytics initiatives, security modernization — all require moving data between mainframes and modern platforms. But who’s going to implement and maintain these integrations?

The traditional answer — hire more mainframe specialists or train existing staff in mainframe technologies — isn’t working. Mainframe skills are expensive, hard to find, and becoming increasingly isolated from the rest of enterprise IT.

PropelZ takes a different approach: instead of requiring mainframe expertise, we enable your existing cloud-native teams to manage mainframe integration using the tools and skills they already have.

The Skills Mismatch Problem

Modern enterprises face a fundamental skills mismatch:

• What’s Available: DevOps engineers who know Kubernetes, Python, REST APIs, cloud platforms, and modern monitoring tools. These skills are abundant, constantly evolving, and well-compensated but accessible.
• What’s Needed for Mainframe Integration: COBOL copybook creation, JCL scripting, VSAM file management, REXX automation, mainframe security models, and z/OS operational procedures. These skills are rare, expensive, and getting rarer.
• The Gap: Projects that could be implemented by existing teams in weeks require months of specialized training or expensive consultant engagement because they cross the mainframe-distributed system boundary.

This mismatch creates artificial project delays, inflated costs, and operational risks when specialized knowledge is concentrated in too few people.

The Traditional Skill Transfer Approach

Most organizations try to solve the skills problem through training:

• Send Cloud Teams to Mainframe School: Expensive, time-consuming, and often ineffective. Learning COBOL and JCL when you’re fluent in Python and Kubernetes feels like going backward.
• Cross-Train Mainframe Teams in Cloud: Equally challenging in the opposite direction. Mainframe specialists often resist learning what they perceive as inferior technologies.
• Hire Hybrid Specialists: People with deep expertise in both mainframe and cloud technologies are extremely rare and expensive.
• Use Consultants: External specialists can implement solutions but don’t transfer knowledge effectively, creating ongoing dependencies.

None of these approaches scale well or provide sustainable solutions to the skills problem.

PropelZ’s Skills Bridge Strategy

Instead of forcing skills transfer, PropelZ enables skills utilization. Your cloud-native teams can manage mainframe integration using familiar tools and techniques:

• REST APIs Instead of JCL: Configure mainframe data flows using standard REST APIs that any DevOps engineer understands, rather than learning JCL syntax and mainframe job submission procedures.
• JSON Configuration Instead of COBOL: Define data structures using JSON schemas rather than creating and maintaining COBOL copybooks.
• Standard Monitoring Instead of SDSF: Monitor mainframe data flows using Splunk, Prometheus, Grafana, or whatever monitoring stack your team already knows.
• Cloud-Native Automation Instead of REXX: Implement automation using Python scripts, Kubernetes jobs, or cloud functions rather than learning REXX and mainframe automation tools.
• Familiar Deployment Models: Deploy and manage PropelZ using containerization, infrastructure-as-code, and CI/CD pipelines rather than mainframe-specific deployment procedures.

Real-World Skills Translation

Here’s how common mainframe integration tasks translate to cloud-native approaches:

Data Movement Configuration

• Traditional: Write JCL to allocate datasets, configure COBOL copybooks to describe data structures, submit batch jobs to move data.
• PropelZ: POST a JSON configuration to an API endpoint describing source, target, and transformation requirements.

Error Handling and Monitoring

• Traditional: Parse JCL output, check SDSF for job status, write REXX scripts to handle failures.
• PropelZ: Check standard HTTP response codes, monitor through existing observability stack, handle failures with standard exception handling patterns.

Automation and Orchestration

• Traditional: Create complex JCL procedures, write REXX automation scripts, integrate with mainframe schedulers.
• PropelZ: Use existing CI/CD pipelines, orchestrate with Kubernetes CronJobs, automate with familiar scripting languages.

Security and Access Control

• Traditional: Understand RACF profiles, mainframe security models, dataset permissions.
• PropelZ: Use standard authentication tokens, role-based access control, and cloud security models.

Performance Optimization

• Traditional: Tune JCL parameters, optimize COBOL programs, understand mainframe resource constraints.
• PropelZ: Use standard performance monitoring tools, optimize through familiar configuration parameters, scale using cloud-native approaches.

The Console Logging Example: REXX to Python

PropelZ’s console logging connector illustrates this skills transformation perfectly. Traditional mainframe console automation requires:

• REXX Expertise: Write complex REXX scripts that parse console messages, make decisions based on message content, and trigger appropriate responses.
• Ops/MVS Knowledge: Understand how to configure message trapping, create automation tables, and integrate with mainframe operational procedures.
• Mainframe Integration: Work within the constraints of mainframe automation tools and operational models.
• PropelZ’s approach enables the same functionality using cloud-native skills:
• Python Scripts: Process console messages using familiar Python libraries, with full access to the Python ecosystem for text processing, API calls, and integration.
• Cloud Functions: Deploy console message processing as serverless functions in AWS Lambda, Azure Functions, or Google Cloud Functions.
• Standard Integration: Use REST APIs, message queues, and standard integration patterns to trigger responses and integrate with existing tools.
• Modern Monitoring: Leverage existing monitoring and alerting infrastructure rather than learning mainframe-specific operational procedures.

The same person who automates cloud infrastructure can now automate mainframe operations — without learning REXX or Ops/MVS.

Economic Impact: Skills Efficiency

This skills bridge approach delivers significant economic benefits:

• Faster Implementation: Teams can implement mainframe integration using existing skills rather than spending months learning mainframe technologies.
• Lower Labor Costs: Use abundant cloud-native skills rather than expensive mainframe specialists for integration projects.
• Reduced Training Investments: No need for extensive mainframe training programs or expensive consultant engagements.
• Better Resource Utilization: Existing team members can work across the entire technology stack rather than being limited to specific platforms.
• Knowledge Sustainability: Solutions implemented using standard technologies are easier to maintain and transfer than mainframe-specific implementations.

Operational Benefits: Unified Management

When mainframe integration uses the same operational model as other infrastructure, several benefits emerge:

• Consistent Procedures: Teams use the same deployment, monitoring, and troubleshooting procedures for mainframe and cloud integration.
• Unified Dashboards: Monitor mainframe data flows alongside other infrastructure in existing dashboards and alerting systems.
• Standard Security: Apply the same security policies, access controls, and audit procedures across all integration platforms.
• Integrated Incident Response: Handle mainframe integration issues using existing incident management procedures and escalation processes.
• Seamless Knowledge Transfer: Team members can transfer between projects without learning completely different technology stacks.

The Career Development Advantage

This approach benefits individual team members as well as organizations:

• Broader Skill Sets: Team members develop expertise that applies across multiple platforms rather than being pigeonholed into mainframe-only roles.
• Market Value: Cloud-native skills remain valuable as technology evolves, while mainframe-specific skills become increasingly niche.
• Career Flexibility: Professionals can work on diverse projects rather than being limited to mainframe-only opportunities.
• Continuous Learning: Skills development focuses on evolving cloud technologies rather than stable (but declining) mainframe technologies.
• Innovation Opportunities: Teams can apply modern development practices — DevOps, infrastructure-as-code, microservices — to mainframe integration challenges.

Implementation Strategy: Gradual Skills Bridge

Organizations can implement this skills transformation gradually:

• Phase 1: Start with simple mainframe integration projects using PropelZ’s REST APIs and familiar tools. Build confidence with cloud-native approaches.
• Phase 2: Expand to more complex integration scenarios, leveraging existing DevOps practices and automation capabilities.
• Phase 3: Implement comprehensive mainframe integration strategies using cloud-native teams and standard operational procedures.
• Phase 4: Reduce dependency on mainframe specialists for integration projects while maintaining them for core mainframe operations.

This approach minimizes risk while maximizing the value of existing team capabilities.

What This Means for Your Organization

If you’re struggling with the mainframe skills shortage, PropelZ’s skills bridge approach offers several advantages:

• Faster Project Delivery: Use existing teams for mainframe integration rather than waiting for specialized resources or training.
• Lower Costs: Leverage abundant cloud-native skills rather than expensive mainframe specialists.
• Reduced Risk: Avoid single points of failure that occur when only one or two people understand critical integration systems.
• Future Flexibility: Build integration capabilities that evolve with your team’s skills rather than being locked into declining skill sets.
• Better Operations: Manage mainframe integration using the same tools and procedures used for other infrastructure.

The result: mainframe integration that leverages your team’s strengths rather than exposing their knowledge gaps.

Next Steps

• Schedule a PropelZ briefing.
• Learn more about PropelZ 2.0.
• Watch a demo of PropelZ.
• Try PropelZ.

Learn More

• Visit our Customer Briefing Center.
• Review all VirtualZ Use Cases, Thought Leadership papers, and Solution Briefs.
• Explore our YouTube channel, podcasts, and blog.
• Still have questions? Contact us.