Skyward Data

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139

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Aug 2026

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About the show

Conversations That Power Smarter Data Strategies for AI, Cloud, and Innovation. Skyward Data brings you exclusive conversations with experts shaping the future of enterprise data. Discover how organizations are transforming data access, storage, and AI integration to fuel faster innovation and smarter decisions. Each episode explores how to unlock the full power of your enterprise data—whether it lives on IBM Z, in the cloud, or deep in decades-old tape archives. We dive into real-world stories, bold ideas, and practical strategies for making mainframe and legacy data instantly accessible for AI, analytics, compliance, and modernization. If you're building smarter systems, training better models, or powering transformation with trusted data—Skyward Data is your guide. No fluff. No jargon. Just smart conversations about enterprise data, done right. Learn more at virtualzcomputing.com #AI #Mainframe #EnterpriseData #HybridCloud #DataAccess #SkywardData #VirtualZComputing

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60 recent

August 25, 20261 hr 0 min

Why ETL and Change Data Capture Break at Mainframe Scale — and What Replaces Them

VirtualZ Computing Executive Chairman Marc Sokol and CTO Vince Re break down how a Fortune 500 retailer moved a 60-million-record VSAM file from z/OS to PostgreSQL in the cloud at a sustained 56,000 records per second — with no staging database, no change data capture, and zero lines of custom code. The same file on their previous solution ran for two days. VSAM (Virtual Storage Access Method) is the mainframe's core file structure, and getting it into a relational database has traditionally meant one of three things: hand-built ETL scripts that break whenever a copybook changes, a change data capture deployment that demands VSAM logging and RLS, or a staged gateway architecture that reads and writes the same data four times. Vince Re explains why all three break down at enterprise scale — including one customer who spent two years on a CDC approach and never got it working. In this episode of Skyward Data, the podcast from VirtualZ Computing: The real benchmark environment — a mid-sized z/OS system, 4K+ record sizes, a shared 10 Gb link, and GCP-hosted PostgreSQL, using no more than 3–5% of available bandwidth Why single-pass processing beats staged architectures that touch the data four times How COBOL copybook metadata drives field-level transformation declaratively — packed decimal, binary, floating point, and EBCDIC into relational columns with no code Why JDBC bulk operations, large batches, and deferred commits outperform per-record HTTP and web services approaches What VSAM logging actually costs in I/O, journal storage, batch window, and deadlock risk How the multiplexer processes thousands of files in parallel instead of serially Running PropelZ on z/OS, on Linux, or anywhere with a Java environment Licensing that is per platform — not per LPAR, not per MIPS, not by data volume PropelZ is VirtualZ Computing's no-code tool for extracting and transforming IBM Z mainframe data to any target. It's part of a four-product portfolio alongside Lozen (real-time read-write access to live mainframe data without moving it), FlowZ (mainframe files to cloud object storage), and Zaac (cloud and SAN presented as native z/OS disk and tape). Topics: VSAM to PostgreSQL migration, mainframe data migration, IBM Z, z/OS, change data capture alternatives, no-code ETL, COBOL copybook transformation, EBCDIC conversion, zIIP offload, VSAM to Db2, mainframe modernization, hybrid cloud data integration, AI data pipelines, Snowflake, Databricks. Listen to more Skyward Data episodes: https://virtualzcomputing.com/podcasts/

August 11, 20267 min

Building PropelZ: Customer-Driven Mainframe Integration

How does customer-driven development shape an enterprise mainframe data integration product? VirtualZ Computing CTO Vince Re explains how the most important features of PropelZ — VirtualZ's no-code tool for moving and replicating IBM Z mainframe data to the cloud — came directly from real enterprise customer problems rather than internal feature speculation. Vince Re walks through specific origin stories: how a Microsoft Azure monitoring requirement led to the PropelZ Splunk connector, and how database teams' integration challenges drove automatic JDBC metadata discovery. The throughline is a development philosophy where each capability is built to solve a named customer's production problem first, then becomes a feature that serves an entire market. In this episode of Skyward Data, the podcast from VirtualZ Computing: - Why the PropelZ Splunk connector was built from Microsoft's Azure monitoring use case - How database team challenges produced automatic JDBC metadata discovery - Customer-first vs. feature-speculation product development, and the trade-offs of each - Why production-tested integrations outperform theoretically designed features - How solving one enterprise's mainframe data problem scales to a whole segment 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). PropelZ is proven at 56,000 records per second, mainframe to cloud. Topics: mainframe modernization, IBM Z, no-code data integration, ETL alternatives, Splunk integration, JDBC, customer-driven product development, hybrid cloud. Listen to more Skyward Data episodes: https://virtualzcomputing.com/podcasts/

July 28, 202611 min

Real-Time SMF Archiving vs. Batch: Mainframe Audit Data

Why do most enterprises still archive mainframe SMF records in daily batches when the records are created continuously? VirtualZ Computing CTO Vince Re explains how real-time SMF archiving with PropelZ — VirtualZ's no-code tool for moving IBM Z mainframe data to the cloud — eliminates the data-loss window that batch processing leaves open, and unlocks capabilities batch simply can't deliver. SMF (System Management Facilities) records are the mainframe's audit, security, and performance log. Batch SMF processing was designed for 1990s constraints — expensive bandwidth and local storage — and Vince Re makes the case that the same approach now creates operational risk: batch transfer failures, delayed audit access, and gaps an attacker or outage can fall into. Streaming SMF data continuously to the cloud closes that gap. In this episode of Skyward Data, the podcast from VirtualZ Computing: - How real-time SMF streaming removes batch transfer failures, delayed audit access, and recovery complexity - Capabilities batch can't match: continuous security monitoring, immediate compliance reporting, multi-cloud redundancy - Why cloud economics favor continuous streaming over large scheduled batch transfers - Tamper detection through immediate archiving, cross-platform incident correlation, and faster regulatory response - The shift from SMF archiving as a compliance checkbox to a real-time operational intelligence source PropelZ writes mainframe SMF 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: mainframe SMF archiving, IBM Z, z/OS, real-time data streaming, mainframe security monitoring, compliance reporting, audit data, no-code data integration, hybrid cloud. Listen to more Skyward Data episodes: https://virtualzcomputing.com/podcasts/

July 7, 202612 min

Mainframe Cloud Backup with FlowZ: Cheaper, Faster, Off-Site

How cheap and how fast can mainframe-to-cloud backup actually be? VirtualZ Computing CTO Vince Re shows how VirtualZ backs up its own IBM Z mainframe — system backups, source code, and operational logs — by streaming them straight to cloud object storage with FlowZ, VirtualZ's no-code tool for using Amazon S3, Azure Blob, and Google Cloud as mainframe backup and archive storage, for pennies a month. Vince Re explains exactly how it works: FlowZ makes cloud object storage look like a normal output target to z/OS, so the mainframe writes to the cloud as if it were a local device — with no custom code and nothing running on the cloud side. He also answers the objection everyone raises about cloud backup: isn't the network too slow? It isn't, and he walks through why. In this episode of Skyward Data, the podcast from VirtualZ Computing: - How cloud object storage becomes a native mainframe output target with no custom code - Real numbers on volume backup speeds and compression, mainframe to cloud - Why network bandwidth is not the bottleneck most teams assume it is - How the approach scales from a small shop to a site moving terabytes a day - Replacing fragile, expensive local tape and disk media with cheaper, off-site cloud backup FlowZ is part of VirtualZ Computing's no-code portfolio for enterprise mainframe data, alongside PropelZ (moving and replicating mainframe data, proven at 56,000 records per second), Lozen (live in-place data access), and Zaac (cloud and SAN as native z/OS storage). For banks, insurers, retailers, and any enterprise running IBM Z, it's a practical path to durable, low-cost, off-site backup and tape replacement. Topics: mainframe cloud backup, IBM Z, z/OS, cloud object storage, S3, Azure Blob, Google Cloud, tape replacement, mainframe archive, no-code data integration, hybrid cloud. Listen to more Skyward Data episodes: https://virtualzcomputing.com/podcasts

June 23, 202612 min

Multi-Cloud Mainframe Data with PropelZ: One Pipeline

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/

June 9, 202613 min

Mainframe Security in Splunk: PropelZ SMF & RACF Feeds

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/

June 2, 202613 min

he Mainframe Skills Gap: Closing It Without COBOL

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/

May 26, 202612 min

App Store Economics for Mainframe Integration Software

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/

May 19, 202611 min

Unified Mainframe + Cloud Monitoring with PropelZ

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/

May 12, 20267 min

Skip the Copybooks: Automated DB2-to-Snowflake Migration

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/