Skyward Data

Can you route the same mainframe dataset to AWS, Google Cloud, Azure, and IBM Cloud at once? VirtualZ Computing CTO Vince Re explains how PropelZ — VirtualZ's no-code tool for moving and replicating IBM Z mainframe data to the cloud — sends a single dataset to multiple cloud platforms simultaneously from one configuration, so enterprises use each provider's strengths instead of locking into one. Vince Re makes the case for treating multi-cloud as a mainframe data strategy rather than a vendor decision: distributing the same z/OS data across providers for resilience, geographic compliance, and cost flexibility, without building and maintaining a separate integration for each cloud. In this episode of Skyward Data, the podcast from VirtualZ Computing: - How to route one mainframe dataset to AWS, Azure, Google Cloud, and IBM Cloud simultaneously from a single PropelZ configuration - Geographic distribution that optimizes performance while meeting regional compliance requirements - Cost optimization by matching workloads to the best pricing across providers - Real applications: cross-continent disaster recovery and per-cloud analytics, such as Google Cloud for analytics, Azure for enterprise integration, and AWS for scale - Moving from "choosing a cloud" to orchestrating several, without managing separate pipelines PropelZ writes mainframe data directly to Amazon S3, Azure Blob, and Google Cloud Storage with no code and no homegrown pipelines, and is proven at 56,000 records per second, mainframe to cloud. It's part of VirtualZ Computing's no-code portfolio for enterprise mainframe data, alongside Lozen (live in-place data access), FlowZ (cloud storage for backup and archive), and Zaac (cloud and SAN as native z/OS storage). Topics: multi-cloud mainframe strategy, IBM Z, z/OS, mainframe data replication, AWS, Azure, Google Cloud, IBM Cloud, disaster recovery, no-code data integration, hybrid cloud. Listen to more Skyward Data episodes: https://virtualzcomputing.com/podcasts/

How do you get IBM Z mainframe security data into Splunk without custom development? VirtualZ Computing CTO Vince Re explains how the PropelZ Splunk connector — part of VirtualZ's no-code tool for moving mainframe data to the cloud — streams SMF records, RACF logs, and console messages directly into an existing Splunk SOC, so the system processing your most sensitive data is no longer a blind spot. Vince Re walks through why most mainframe-to-Splunk integration relies on batch processing and custom work, and how PropelZ delivers real-time streaming into existing Splunk deployments with no custom development, no specialized configuration, and no mainframe-specific expertise required on the security team's side. In this episode of Skyward Data, the podcast from VirtualZ Computing: - Why real-time SMF, RACF, and console data beats the batch processing legacy connectors depend on - Out-of-the-box Splunk integration: structured data formatting and unified timeline correlation with the rest of your SOC - Threat-detection scenarios this enables: privilege escalation monitoring, lateral movement analysis, and data exfiltration alerts - Applying behavioral analysis and anomaly detection to mainframe security data alongside distributed systems - Why integration measured in weeks, not months, matters for security operations SMF (System Management Facilities) is the mainframe's audit and activity log; RACF is IBM's z/OS access-control and security package. PropelZ feeds both into Splunk with no code and no homegrown pipelines, and is proven at 56,000 records per second, mainframe to cloud. It's part of VirtualZ Computing's no-code portfolio for enterprise mainframe data, alongside Lozen (live in-place data access), FlowZ (cloud storage for backup and archive), and Zaac (cloud and SAN as native z/OS storage). Topics: mainframe security monitoring, Splunk integration, SMF, RACF, IBM Z, z/OS, SOC, SIEM, threat detection, real-time data streaming, no-code data integration, hybrid cloud. Listen to more Skyward Data episodes: https://virtualzcomputing.com/podcasts/

What is the mainframe skills gap, and how can enterprises close it without hiring more COBOL programmers? VirtualZ Computing CTO Vince Re tackles one of the most pressing problems in enterprise IT: the COBOL, JCL, and REXX experts who keep IBM Z mainframes running are retiring faster than they can be replaced, and few new engineers are trained on those technologies. The mainframes still process core banking, insurance, and government workloads — but the people who understand them are aging out. Vince Re argues the fix isn't finding more mainframe specialists. It's making deep mainframe expertise optional for the integration layer, so the cloud-native and DevOps engineers enterprises already employ can work with mainframe data directly — without learning COBOL or REXX. In this episode of Skyward Data, the podcast from VirtualZ Computing: - What the mainframe skills gap is, why it's accelerating, and what it costs enterprises that don't plan for it - Why hiring against a shrinking COBOL and REXX talent pool is a losing strategy - How cloud and DevOps teams can own mainframe data integration using skills they already have - The economics of leveraging abundant cloud-native talent instead of rare, expensive mainframe specialists - How to build a mainframe data strategy that scales with your existing team One practical answer is VirtualZ's no-code approach: PropelZ moves and replicates IBM Z mainframe data to the cloud — proven at 56,000 records per second — with no code and no homegrown pipelines, so teams integrate mainframe data without deep z/OS expertise. It's part of VirtualZ Computing's no-code portfolio for enterprise mainframe data, alongside Lozen (live in-place data access), FlowZ (cloud storage for backup and archive), and Zaac (cloud and SAN as native z/OS storage). Topics: mainframe skills gap, COBOL skills shortage, IBM Z, z/OS, mainframe modernization, DevOps, cloud-native, IT talent shortage, no-code data integration, hybrid cloud. Listen to more Skyward Data episodes: https://virtualzcomputing.com/podcasts/

What if enterprise integration software were priced like a smartphone app store — pick the specific capabilities you need and skip the ones you don't? VirtualZ Computing CTO Vince Re explains how VirtualZ applies that model to mainframe integration, letting enterprises choose individual connectors and capabilities instead of buying a large suite and using a fraction of it. Vince Re contrasts the traditional "buy everything, use some of it" enterprise software model with a modular, app-store approach: granular selection, pay for what you use, and combine specialized components into exactly the integration you need. He explains why modular architecture also lets a vendor ship new capabilities faster than monolithic, all-in-one development. In this episode of Skyward Data, the podcast from VirtualZ Computing: - How app-store-style pricing changes enterprise software buying — paying for a handful of capabilities instead of dozens - Examples of modular components working together, such as the Splunk connector, the data-movement multiplexer, and cloud storage - Why modular architecture accelerates innovation compared with monolithic platforms - The advantages of granular selection: lower cost, faster implementation, and flexibility to change later - How customers assemble custom mainframe integration by combining specialized capabilities This modular philosophy runs through VirtualZ Computing's no-code portfolio for enterprise mainframe data: PropelZ (moving and replicating IBM Z data to the cloud, proven at 56,000 records per second), Lozen (live in-place data access), FlowZ (cloud storage for backup and archive), and Zaac (cloud and SAN as native z/OS storage) — four products you deploy and combine, with no code and no homegrown pipelines, rather than one suite you buy whole. Topics: enterprise software pricing, modular architecture, mainframe integration, IBM Z, z/OS, connectors, no-code data integration, software procurement, hybrid cloud. Listen to more Skyward Data episodes: https://virtualzcomputing.com/podcasts/

How do you monitor IBM Z mainframe and cloud infrastructure in one place instead of two separate systems? VirtualZ Computing CTO Vince Re explains how PropelZ's console logging connector streams mainframe console messages directly into modern monitoring tools, so operations teams see mainframe, Kubernetes, and cloud alerts in a single unified view rather than treating the mainframe as an isolated silo. Vince Re makes the case for unified operations: instead of choosing between mainframe expertise and cloud-native skills, teams combine them by feeding real-time mainframe console data into the dashboards and alerting tools they already run. The result is faster incident response across the whole environment, because mainframe events sit on the same timeline as everything else. In this episode of Skyward Data, the podcast from VirtualZ Computing: - How streaming mainframe console messages into existing tools creates one cross-platform view of mainframe, Kubernetes, and cloud alerts - Using monitoring stacks teams already know — such as Splunk and Prometheus — instead of mainframe-specific tooling - Why real-time mainframe visibility speeds incident response across hybrid infrastructure - Getting more from existing monitoring investments rather than standing up a separate mainframe system - Building operations that scale as the hybrid environment grows PropelZ streams mainframe console messages, SMF records, and other z/OS data into cloud and monitoring platforms with no code and no homegrown pipelines, and is proven at 56,000 records per second, mainframe to cloud. It's part of VirtualZ Computing's no-code portfolio for enterprise mainframe data, alongside Lozen (live in-place data access), FlowZ (cloud storage for backup and archive), and Zaac (cloud and SAN as native z/OS storage). Topics: mainframe monitoring, hybrid cloud operations, IBM Z, z/OS, console messages, observability, Splunk, Prometheus, Kubernetes, incident response, no-code data integration. Listen to more Skyward Data episodes: https://virtualzcomputing.com/podcasts/

Why does moving DB2 mainframe data to platforms like Snowflake still require weeks of manual COBOL copybook creation — and how can you skip that step entirely? VirtualZ Computing CTO Vince Re explains how PropelZ's automatic metadata discovery removes copybook work from database integration, so a DB2-to-Snowflake migration that used to take months can run in minutes. Vince Re breaks down why copybook creation has quietly slowed mainframe database projects for decades, and how self-describing databases change the equation: PropelZ reads the table's own metadata automatically, so you write a SQL query and run the move instead of hand-building copybooks first. That makes deep COBOL expertise optional for database data movement, not a prerequisite. In this episode of Skyward Data, the podcast from VirtualZ Computing: - How automatic metadata discovery replaces weeks of manual copybook engineering for database integration - Why "write a SQL query and run it" is the modern alternative to copybook-first workflows - A real DB2 table migration that went from complex to straightforward - Why manual metadata management is the biggest adoption barrier for mainframe database projects - How the approach scales from a single table migration to billion-row analytics workloads PropelZ moves and replicates IBM Z mainframe data — including DB2 — to cloud data warehouses like Snowflake, Databricks, Redshift, and BigQuery with no code and no homegrown pipelines, and is proven at 56,000 records per second, mainframe to cloud. It's part of VirtualZ Computing's no-code portfolio for enterprise mainframe data, alongside Lozen (live in-place data access), FlowZ (cloud storage for backup and archive), and Zaac (cloud and SAN as native z/OS storage). Topics: DB2 migration, mainframe copybooks, metadata discovery, Snowflake, Databricks, IBM Z, z/OS, cloud data warehouse, SQL, no-code data integration, hybrid cloud. Listen to more Skyward Data episodes: https://virtualzcomputing.com/podcasts/

How do you migrate 200,000+ mainframe datasets to the cloud when transferring them one at a time would take months? VirtualZ Computing CTO Vince Re explains how the PropelZ multiplexer turns massive mainframe data migrations from an operational nightmare into an automated, parallel process — moving hundreds of datasets at once instead of queuing them individually. Vince Re walks through inventory-driven migration: PropelZ takes a full inventory of the datasets to move, then runs them in parallel, cutting projects that would take months down to weeks. He explains why enterprises choose intelligent queue management over one-at-a-time transfers for virtual tape library migrations, application modernization, and large-scale cloud moves. In this episode of Skyward Data, the podcast from VirtualZ Computing: - Real performance: 100–200 parallel transfers processing thousands of datasets per hour - Comprehensive status tracking that turns black-box migrations into transparent, monitored processes - Integration with existing automation and help-desk systems - Uses beyond migration: compliance archiving, disaster recovery, and data center consolidation - Why parallel, inventory-driven processing scales where individual file transfers don't The multiplexer is built into PropelZ, VirtualZ's no-code tool for moving and replicating IBM Z mainframe data to the cloud — proven at 56,000 records per second, mainframe to cloud — with no code and no homegrown pipelines. PropelZ is part of VirtualZ Computing's no-code portfolio for enterprise mainframe data, alongside Lozen (live in-place data access), FlowZ (cloud storage for backup and archive), and Zaac (cloud and SAN as native z/OS storage). Topics: mainframe data migration, IBM Z, z/OS, virtual tape library, VTL migration, parallel data transfer, application modernization, disaster recovery, no-code data integration, hybrid cloud. Listen to more Skyward Data episodes: https://virtualzcomputing.com/podcasts/

Mainframe modernization in 2026 isn’t about leaving the mainframe — it’s about using it better. In this episode of the Skyward Data Podcast, Jeanne Glass, CEO of VirtualZ, breaks down how enterprises are modernizing their mainframe environments without disruption. Learn why data-first strategies, AI readiness, hybrid and multi-cloud architectures, no-code integration, and instant storage are reshaping modernization efforts across regulated industries. If you’re responsible for enterprise data, analytics, AI, or modernization strategy, this episode offers a clear, practical view of what customers actually need now — and how leading organizations are moving forward safely and incrementally.