Enterprise Mainframe Change Data Capture (CDC) to Apache Kafka with tcVISION and Confluent

by Joseph Brady, Director of Business Development and Cloud Alliance Leader at Treehouse Software, Inc. and Ram Dhakne, Solutions Engineer at Confluent

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This blog focuses on using Treehouse Software’s tcVISION to replicate data in real time between mainframes and Confluent, allowing for new use cases and truly setting data in motion.

Why mainframe modernization? Benefits and use cases

Mainframe data stores often hold large amounts of complex and critical data in proprietary legacy formats, making this data difficult to extract and incompatible with modern databases, data types, and data tools.

Enterprises are looking to take advantage of the latest cloud services, such as analytics, artificial intelligence (AI) and machine learning, scalable storage, security, high availability, etc., or move data to a variety of newer databases. Additionally, many customers want to modernize their application on a cloud or open systems platform without disrupting the existing critical work on the legacy system.

How tcVISION syncs legacy data for the cloud

tcVISION is a data replication software product that performs real-time synchronization of mainframe data sources and cloud and open systems, allowing critical mainframe data to be consumed by a variety of leading cloud services.

tcVISION supports many mainframe data sources for both online and offline scenarios. Data can be replicated from IBM Db2 z/OS, Db2 z/VSE, VSAM, IMS/DB, CA IDMS, CA Datacom, or Software AG ADABAS. tcVISION can replicate data to many targets including Confluent Platform, Apache Kafka®, AWS, Google Cloud, Microsoft Azure, PostgreSQL, Snowflake, etc. To learn more, see the complete list of supported tcVISION sources and targets.

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tcVISION focuses on CDC (change data capture) when transferring information between mainframe data sources and cloud and open systems databases and applications. Through innovative technology, changes occurring in any mainframe application data are tracked and captured, and then published to a variety of cloud and open systems targets.

tcVISION stores metadata in a relational database and the tcVISION manager components are administered by the tcVISION control board, a Windows GUI interface, which can be installed on premises or in the cloud. This allows tcVISION users to create metadata, create and control replication scripts, and control database interactions. tcVISION’s architecture is designed to minimize mainframe resource utilization.

Using the tcVISION control board, the most complex transformations can be specified, and it facilitates the mapping of the mainframe copybooks, redefines, data dictionaries, data catalogs, codepages, data type mapping, and more via the user-friendly interface. The repository editor allows users to control data transformations.

What is Confluent?

Confluent Cloud is a real-time data in motion platform that can be deployed in any public cloud, in any region of your choice. It comes with an SLA and uptime of 99.95%, and fully managed components like ZooKeeper, Kafka brokers, 120+ Kafka connectors, Schema Registry, and ksqlDB so you can leverage it on any cloud without having to worry about how it runs and scales.

Kafka Connect, Connect API, connectors, and tcVISION IBM Db2 connector

Kafka comes with three core APIs:

  • Kafka producer/Consumer API
  • Connect API
  • KStreams API

Kafka Connect is a tool for scalably and reliably streaming data between Kafka and other data systems. It makes it simple to quickly define connectors that move large data sets into and out of Kafka. Kafka Connect can ingest entire databases or collect metrics from all your application servers into Kafka topics, making the data available for stream processing with low latency. Kafka Connect connects APIs under the hood with fully managed connector support in Confluent Cloud.

Step-by-step guide on how to use tcVISION and Confluent

This example discusses the integration of tcVISION replication of data from Db2 to Confluent Cloud.

Set up tcVISION access to Confluent

Create an account with Confluent to make a Confluent user ID/password; the user ID is generally your email address. To sign on to Confluent, go to the Confluent Cloud login and enter your user ID:

Confluent Cloud welcome page

Then, enter your password:

Enter your password

When you log in, you’ll be in a Confluent environment called “default”:

Confluent environment called “default”

A Confluent environment is a type of container that holds clusters which in turn hold topics. If you are familiar with messaging systems, Confluent/Kafka will seem familiar. A cluster will need to be created to serve as a target for the data produced by tcVISION. The first attribute to be selected is the type of cluster. Confluent offers three types: Basic, Standard, and Dedicated. For the purposes of this demonstration, Basic will be used. A Basic cluster does not incur charges for simply existing, but does for data transmission and data storage.

Select "Basic cluster" and begin configuration

Select Begin configuration.

Select a cloud provider

Here, a cloud provider can be chosen—AWS, Google Cloud, or Microsoft Azure. For this example, AWS is used. Select Continue and the characteristics of the new cluster are displayed, which we’ve named “tcVISION_cluster_0”:

Cluster characteristics

After entering your payment information (not shown), you can click on the cluster name to launch the cluster overview.

Cluster overview

In order to use Confluent with tcVISION, the user must provide tcVISION with information about the cluster they intend to use. Specifically, the user must supply the hostname and port of the Confluent AWS virtual machine, and the credentials needed to access the cluster.

Confluent refers to the hostname and port as a bootstrap server. There can be multiple bootstrap servers for the purpose of load balancing, but a single server is used for this demonstration.

To find bootstrap server information, click Cluster Settings on the left-hand side:

Cluster settings

The bootstrap server will be listed under “Identification,” and includes both the AWS hostname and the port.

Credentials in Confluent consist of an API Key and an API Secret. These are generated for the cluster and take the place of the Confluent user ID and password used to log in. To generate a key/secret pair, click API Access on the left:

API Keys page

Followed by Create Key:

Select API Key scope

For this example, we use “Global Access” here, so click Next:

API Key and secret

Pay particular attention to the tip about saving the key and secret somewhere safe, because once this panel is exited, there is no way to display the secret again. A descriptive string for this key/secret pair can be filled in. The key or secret text to be copied can be selected, or use the convenient icons at the end of the field to copy. Once the key/secret has been safely stored, check the box that says it has been done, and click Save. You will return to the “API Keys” panel, and the key is now displayed:

API Key displayed

Set up Confluent and define the topic

The last thing to do is define a topic within the cluster. Confluent producers have the capability to define their own topics within a cluster, but this capability can be disabled by a Confluent configuration and is disabled in the configuration used here.

Go back to the cluster Overview:

Cluster Overview

On the left sidebar, click Topics:

Topics

Then Create Topic:

Create a topic

The topic name is filled in (“CONFLUENT_CLOUD_TOPIC1”), overriding the number of partitions from 6 to 1, since that is what the Confluent demo uses. Click Create with defaults:

Cloud topic

A topic is now available, which can be populated with Db2 data.

Set up tcVISION and run a bulk load of Db2 data

tcVISION’s control board is a Windows graphical user interface (GUI) that allows users to configure the replication stream between various database platforms, including the IBM mainframe and Confluent. Using the control board and built-in wizards, users can define the metadata and the mappings between the mainframe and target.

The following sequence of screens shows the steps required to create the tcVISION metadata and scripts for replicating mainframe Db2 z/OS data to Confluent.

Access the tcVISION control board:

tcVISION control board

Log on to Db2 z/OS:

Db2 z/OS

Create metadata that is specific to the input (Db2) and output (Kafka) and the replication definition. In this example, the Db2 table is mapped to the Confluent Cloud Kafka topic using JSON:

Import of structure definitions

The tcVISION metadata wizard asks for the information required for the replication of the mainframe database to Confluent Cloud. For Db2 z/OS, it asks for the mainframe Db2 subsystem:

Source type for structure definition import

Db2 subsystem

tcVISION presents the tables contained in the Db2 z/OS catalog on the mainframe. Select the schemas and associated tables for replication:

Select the schemas and associated tables for replication

Once the required tcVISION wizard-based screens are completed, the tool automatically defines the mappings between the source and target. tcVISION’s metadata import wizard creates a default mapping that handles data type conversion issues, such as EBCDIC to ASCII, Endianness conversion, codepages, redefines data types, and more:

Default mapping

tcVISION data scripts are created through wizards. Data scripts control the replication of data from the source (Db2 z/OS) to the target (Confluent Cloud Kafka JSON). tcVISION bulk load scripts are a type of data script that performs the initial load of the Kafka topic. The following script shows data being accessed directly from the mainframe Db2 z/OS database. Another alternative to reduce MIPS consumption is to read the data from a Db2 image copy.

Data script

Bulk load script running:

Bulk load script running

After execution of the bulk load script, replication statistics of the Db2 bulk load into the Confluent Cloud Kafka topic can be viewed:

Replication statistics of the Db2 bulk load

Now that the topic has been loaded with data from Db2, it can be displayed in Confluent. To do this, navigate to the topics panel again:

Notice that there are now statistics indicating that the tcVISION producer uploaded some data to the topic. On the horizontal menu, switch from “Overview” to “Messages” to display the messages (data records) that the tcVISION bulk load placed in the topic. The display can be filtered in various ways, but for this example, the default is used: “Jump to Offset,” which says “start displaying sequentially from this offset.” Here, an offset of 0 (start at the beginning) is specified, since we just want to verify that the Db2 data uploaded by tcVISION was actually delivered:

Messages (data records) from tcVISION bulk load

Run a change script in tcVISION to show the changes in Confluent

To capture ongoing changes to Db2 in real time, a Db2 z/OS CDC replication script is created.

This script captures the changes on the Db2 z/OS side and applies them into the repository where the output target is Confluent Cloud topic.

Replication script

Replication script

Target database Confluent Cloud topic

The CDC replication is initiated from the tcVISION control board. The tcVISION control board shows a graphical representation of the replication:

Graphical representation of the replication

The CDC replication is now actively capturing and replicating data changes whenever they occur on the Db2 z/OS side. You can test it by making a change in the Db2 z/OS table:

 
********************************* Top of Data **********************************
---------+---------+---------+---------+---------+---------+---------+---------+
UPDATE SXE1.TVKFKATB                                                    00010004
SET DEPT = '696969'                                                     00040029
WHERE PERS_ID = 5;                                                      00050004
---------+---------+---------+---------+---------+---------+---------+---------+
DSNE615I NUMBER OF ROWS AFFECTED IS 1                                           
DSNE616I STATEMENT EXECUTION WAS SUCCESSFUL, SQLCODE IS 0                       
---------+---------+---------+---------+---------+---------+---------+---------+
--COMMIT;                                                               00060019
---------+---------+---------+---------+---------+---------+---------+---------+
DSNE617I COMMIT PERFORMED, SQLCODE IS 0                                         
DSNE616I STATEMENT EXECUTION WAS SUCCESSFUL, SQLCODE IS 0                       
---------+---------+---------+---------+---------+---------+---------+---------+
DSNE601I SQL STATEMENTS ASSUMED TO BE BETWEEN COLUMNS 1 AND 72                  
DSNE620I NUMBER OF SQL STATEMENTS PROCESSED IS 1                                
DSNE621I NUMBER OF INPUT RECORDS READ IS 4                                      
DSNE622I NUMBER OF OUTPUT RECORDS WRITTEN IS 17                                 
******************************** Bottom of Data ********************************

This change is processed and replicated by tcVISION. The tcVISION control board shows the statistics highlighting that one update was performed:

Display of extended statistics

Checking in Confluent, the Db2 z/OS change has successfully been propagated to the Confluent Cloud topic:

Db2 z/OS change successfully propagated to Confluent Cloud topic

tcVISION and Confluent are better together

With tcVISION’s groundbreaking Db2 CDC connector and Confluent’s ability to serve as the multi-tenant data hub, this combination creates a very powerful solution to aggregate data from multiple sources and have data published into various Kafka topics. Sourcing events from any kind of Db2 via a connector into Confluent will set data in motion for the entire organization. Simplicity and agility are key elements of the tcVISION and Confluent “better together” story.


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Video: tcVISION Demonstration…

In this video, we show a tcVISION overview, then a demonstration of replication of mainframe data on AWS RDS for PostgreSQL:

Contact Treehouse Software for a tcVISION Demo Today!

No matter where you want your mainframe data to go – the Cloud, open systems, or any LUW target – tcVISION from Treehouse Software is your answer.

Just fill out the Treehouse Software tcVISION Demonstration Request Form and a Treehouse representative will contact you to set up a time for your online tcVISION demonstration.

Google Blog: Treehouse Software’s tcVISION is one of Google’s select solutions for mainframe data replication on the Google Cloud Platform

by Joseph Brady, Director of Business Development / Cloud Alliance Lead at Treehouse Software, Inc.

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For many enterprises, the venerable mainframe is home to decades’ worth of data about the company’s customers, processes and operations. And it goes without saying that the business would like access to that mainframe data — to report on it, to analyze it with big data analysis tools, or to use it as the basis of new machine learning and artificial intelligence initiatives.

READ THE ENTIRE GOOGLE CLOUD BLOG HERE


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Contact Treehouse Software Today…

Treehouse Software has been helping mainframe enterprises since 1982, and our extensive experience, deep knowledge, and wide-ranging capabilities in mainframe technologies makes us a valued partner and a trusted advisor to customers.

No matter where you want your mainframe data to go – the Cloud, open systems, or any LUW target – tcVISION from Treehouse Software is your answer.

Just fill out the Treehouse Software Product Demonstration Request Form and a Treehouse representative will contact you to set up a time for your online tcVISION demonstration.

Mainframe VSAM Change Data Capture (CDC) to Cloud and Open Systems with tcVISION from Treehouse Software

by Joseph Brady, Director of Business Development and AWS and Cloud Alliance Leader at Treehouse Software, Inc.

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Treehouse Software is the worldwide distributor of tcVISION, the innovative software product that allows immediate data replication between an impressive array of Mainframe sources and Cloud and Open Systems targets. This blog focuses on tcVISION‘s support of VSAM mainframe data sources (batch and CICS on z/OS, and CICS on z/OS and z/VSE).

tcVISION performs VSAM Change Data Capture (CDC) either via its own “DBMS-Extensions”, or via IBM’s CICS VR product. tcVISION has separate DBMS-Extensions to capture changes from CICS (using the CICS External Interface) and batch (via a JCL wrapper). All captured changes, regardless of whether they are performed by tcVISION or CICS VR are written to the z/OS Logstream on the mainframe. tcVISION then reads the Logstream and transfers the transactions to a tcVISION server running in the Cloud or on-prem, which is responsible for queueing, transforming, and applying the captured changes to the specified target.

Additionally, when planning VSAM CDC there are a number of operational items to consider, such as volume of batch transactions, data changes that occur during periods of time while the VSAM file is offline, etc.

In this instructional video, tcVISION is shown capturing changes from VSAM on z/OS and writing them to SQL Server on Windows:

 


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Contact Treehouse Software Today for a tcVISION Demonstration…

No matter where you want your mainframe data to go – the Cloud, Open Systems, or any LUW target – tcVISION from Treehouse Software is your answer.

Just fill out the Treehouse Software Product Demonstration Request Form and a Treehouse representative will contact you to set up a time for your online tcVISION demonstration.

How to Replicate Mainframe Data to a Big Data Environment via Kafka with tcVISION

by Joseph Brady, Director of Business Development and AWS and Cloud Alliance Leader at Treehouse Software, Inc.

tcVISION from Treehouse Software allows enterprise customers to replicate data between mainframe, Cloud, or Hybrid Cloud while maintaining their legacy environments, and one of the more popular targets for mainframe modernization that we have been seeing is Apache Kafka®.

tcVISION_Mainframe_To_Kafka

What is Kafka? 

Kafka is an open-source distributed event streaming platform used by thousands of companies for high-performance data pipelines, streaming analytics, data integration, and mission-critical applications. A data pipeline processes and moves data from one system to another, and a streaming application is an application that consumes streams of data.

Kafka is reliable, stable, flexible, robust, and scales well with numerous consumers, working seamlessly with most popular data warehouses and data lakes like Hadoop, Redshift, S3, BigQuery, Azure, etc. Kafka can also be used for real-time analytics, as well as to process real-time streams to collect Big Data.

See how tcVISION easily connects mainframe systems to Kafka…

Kafka handles massive volumes of data and remains responsive, making Kafka a preferred platform when the volume of the data at the mainframe level –> BIG.

Kafka is a supported target in tcVISION, and in this instructional video, tcVISION is shown synchronizing data in real-time from Db2 on z/OS via Kafka to a Big Data environment:

Additional Reading: Treehouse Software is a Confluent technology partner and we recently co-authored a blog entitled, “Enterprise Mainframe Change Data Capture (CDC) to Apache Kafka with tcVISION and Confluent”.


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Contact Treehouse Software Today…

No matter where you want your mainframe data to go – the Cloud, Open Systems, or any LUW target – tcVISION from Treehouse Software is your answer.

Just fill out the Treehouse Software Product Demonstration Request Form and a Treehouse representative will contact you to set up a time for your online tcVISION demonstration.

New Faces at Treehouse Software

by Joseph Brady, Director of Business Development and Cloud Alliance Leader at Treehouse Software, Inc.

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Treehouse Software is growing and on the move! We are proud to have many staff members who have been here for 20+ years, and we have recently brought on several experienced business, mainframe, and Cloud experts. Meet our newest team members:

John Szakach, Chief Operating Officer

John joined Treehouse as a Business Strategy Consultant and in 2021 was promoted to Chief Operating Officer. While new to Treehouse, John brings over 40 years of relevant work experience to the organization and is an AWS Certified Cloud Practitioner as well as a Certified Project Management Professional. John has held a variety of management roles in different industries including VP of Organizational Effectiveness, VP of Quality Assurance, and VP of New Product Development. He has also held positions as Director of Flight Standards and Quality Control, and Director of Operations. In addition to over 51 years of total flight experience, including 20 years as a pilot for United Airlines, he has received numerous awards including the United Airlines Captain of the Year and the FAA Master Pilot Award, the FAA’s highest award for safety and compliance. John has a Bachelor’s Degree in aviation management.

Dan Miley, Product Support

Dan is a software engineer with deep experience and understanding of IBM Assembler, COBOL, JCL, IDMS, SAP ECC. He has worked with some of the world’s largest organizations, including president/consultant of his own company for over 10 years. Dan has already been instrumental in landing some major mainframe-to-Cloud data modernization customers for Treehouse Software.

Sasha Efron, Senior Technical Representative

Sasha is a mainframe technical specialist and DBA with over 25 years experience in in systems analysis, design, development, enhancement, testing, implementation and maintenance in insurance and banking systems with specialization in Software AG and IBM Mainframe technologies. He also has been involved in legacy modernization projects for several worldwide companies.

Joseph Rogan, Senior Technical Representative

Joseph is a Senior Technology Leader with 30+ years experience working in multiple industries, including transportation (specifically rail), logistics, education, financial services (banking, re-insurance, and trading systems), commercial insurance, and state government. His core competencies include database design and implementation, OLTP, OLAP, and data warehouse design, project planning, and project management. Joseph is also a highly trusted, conceptual, business partner and leader with excellent presentation, negotiating, management, mentoring, and strategic planning skills.

Daniel Vimont, Senior Technical Representative

Daniel brings 30+ years experience in multiple computer languages, databases, frameworks, and distributed processing for mainframe, Cloud, and open systems. He is very familiar with the principles of ETL and CDC in mainframe data transformation and migration. Dan is a Certified AWS Cloud Practitioner and has experience in designing and developing AWS/SDK (boto3) framework for on-premises invocation/monitoring of AWS services. Additionally, Dan’s versatile background as a data and software engineer, educator, and business advisor is a valuable asset to Treehouse’s vision of being a close partner in our customers’ planning and modernization efforts.

Treehouse Software Experts are Our Best Assets

management-team

When asked by prospective customers, “What are your primary differentiators?”, we immediately point to our people who have decades worth of experience in helping mainframe customers with innovative tools, services, and training. Our extensive experience, deep knowledge, and wide-ranging capabilities in mainframe technologies make the company a valued partner for third-party solution providers and a trusted advisor to customers.

We are fortunate to have a staff with a wealth of knowledge and skills that span not only Mainframe, but Cloud, LUW, and Open Systems technologies. Treehouse Software‘s technicians have installed products and trained end-users in some of the largest mainframe sites around the world, and our highly-rated 24X7 technical support is second to none.

The Treehouse Team Approach

Treehouse Software’s expert staff has proven its ability to work effectively as part of a larger team to meet clients’ complex business goals. AWS, Google, Microsoft, IBM, Oracle, Deloitte, Accenture, Confluent, and other large vendors have selected our expertise, technology, services, and training for their mainframe data modernization practices.


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Contact Treehouse Software Today…

Treehouse Software has been helping enterprises mainframe customers since 1982, and in recent years, we have been developing a strong presence in the Cloud market space relating to mainframe data replication and modernization. As a result, Treehouse Software is currently working with technical and sales leaders from all popular Cloud platform companies and major systems integrators to take advantage of our deep mainframe skills and our tcVISION Mainframe-to-Cloud data replication solution.

No matter where you want your mainframe data to go – the Cloud, Open Systems, or any LUW target –Treehouse Software is here to help. Contact us to discuss your needs.

Replicating Mainframe Data on Cloud-based Relational Databases

by Joseph Brady, Director of Business Development / AWS and Cloud Alliance Leader at Treehouse Software, Inc.

Right_Data_Right_Place_Time02

Treehouse Software has been helping enterprises mainframe customers since 1982, and in recent years, we have been developing a strong presence in the emerging Cloud market space relating to mainframe data replication and modernization. As a result, Treehouse Software is currently working with technical and sales leaders from all popular Cloud platform companies and major systems integrators to take advantage of our deep mainframe skills and our tcVISION Mainframe-to-Cloud data replication solution.

The Choice is Yours…

tcVISION provides the means for customers to easily replicate relevant data between most mainframe data sources (IBM Db2, IBM VSAM, IBM IMS/DB, Software AG Adabas, CA IDMS, CA Datacom, or even sequential files) and the most popular Cloud platforms, including AWS, Google Cloud, Microsoft Azure, Confluent Cloud, and Oracle Cloud

Today, customers are finding it easier than ever to set up, operate, and scale relational databases in the Cloud. Here is a quick look at some Cloud relational database systems that tcVISION supports…

Amazon Aurora relational database, a MySQL and PostgreSQL-compatible relational database built for the Cloud that combines the performance and availability of traditional enterprise databases with the simplicity and cost-effectiveness of open source databases:

Google Cloud SQL, a fully managed relational database service for MySQL, PostgreSQL, and SQL server. You can connect with nearly any application, anywhere in the world. Cloud SQL automates backups, replication, and failover to ensure your database is reliable, highly available, and flexible to your performance needs:

Azure SQL Database is an intelligent, scalable, relational database service built for the Cloud. Optimize performance and durability with automated, AI-driven features that are always up to date. Focus on building new applications without worrying about storage size or resource management with serverless compute and Hyperscale storage options that automatically scale resources on demand:

How Does tcVISION Work?

tcVISION focuses on changed data capture (CDC) when transferring information between mainframe data sources and Cloud-based databases and applications. Through an innovative technology, changes occurring in any mainframe application data are tracked and captured, and then published to the targets.

tcVISION allows bi-directional, real-time data synchronization of changes on either platform to be reflected on the other platform (e.g., a change to a Cloud PostgreSQL table is reflected back on mainframe). The customer can then modernize their application on the cloud, open systems, etc. without disrupting the existing critical work on the legacy system.

Here is a high-level walkthrough of tcVISION mainframe data replication on Cloud and open systems…


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Contact Treehouse Software Today…

No matter where you want your mainframe data to go – the Cloud, Open Systems, or any LUW target – tcVISION from Treehouse Software is your answer.

Just fill out the Treehouse Software Product Demonstration Request Form and a Treehouse representative will contact you to set up a time for your online tcVISION demonstration.

Starting a Mainframe Data Replication Project? Consider Your Use Cases Carefully

by Joseph Brady, Director of Business Development and Cloud Alliance Leader at Treehouse Software

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Planning for Real-time and Bi-directional Mainframe Data Replication with tcVISION

A customer’s mainframe data may be utilized by many interlinked and dependent programs that have been in place for several years, and sometimes, decades, so unlocking the value of this legacy data can be difficult. Therefore, careful planning must occur for a mainframe data modernization project, beginning with identifying uses cases for the project and a Proof of Concept (POC) of data replication software, such as tcVISION, the Mainframe-to-Hybrid Cloud and Open Systems data replication product from Treehouse Software.

This blog serves as a general guide for organizations planning to replicate their mainframe data on Cloud and/or Open Systems platforms using tcVISION.

Questions and Considerations for Your Use Cases

A general principle should be to prove out the data replication technology (tcVISION) by using identified use cases. Listed below are some examples of questions and use cases to assist customers in planning and experiencing successful Mainframe-to-Cloud and/or Open Systems data replication projects:

  • What is/are the mainframe source database(s)? Obvious, yes, but the software solution vendor and outside consultants need this information.
  • What are the critical issues you need to test? Are there any areas that you believe that would be challenging for the vendor? Examples would be specific transformations, data types (e.g., BLOB), required CDC SLAs, field/column changes, specific security requirements, data volume requirements, etc. Document all of the critical test items.
  • Select the minimal set of files (generally 3-10) with representative conditions that will enable you to test all of your critical items. If there are multiple source databases, ensure specific test use cases are defined for each source.
  • What are the target databases? Will you be replicating to a Cloud database manager, such as AWS RDS? Are there additional requirements to replicate to S3, Azure BLOB, GCP Cloud Storage, Kinesis, and Kafka? What needs to be tested?
  • What are your bulk or initial load requirements? tcVISION can load data directly from mainframe databases, mainframe unloads, or image copies. What are the data volumes? Do you have sufficient bandwidth between your mainframe manager and on-premises or Cloud VM to handle your volume requirements?
  • What are your Change Data Capture (CDC) requirements?
  • Do you have plans for bi-directional replication in the future. What are your specific requirements? Since bi-directional replication can be complex and greatly lengthen a modernization project, the customer generally will perform one bi-directional use case for conceptual proof. Will this suffice for your organization?
  • What are your specific high availability requirements? Can they be handled by a technical discussion, or is a specific use case required?
  • What are your general security requirements for data at rest and data in transit? Do you have any specific security regulations to follow, such as HIPPA or FIPS? What are your PII / data masking requirements?
  • What are your schema requirements? For example, tcVISION creates a default schema based on your input mainframe data. Major changes to the default schema usually require a staging database.
  • Do you have staff available to perform the required tasks for the project? For example, for the length of a tcVISION POC you will need part-time staff, 2-4 hours per day. A part-time mainframe administrator will generally require 2-8 elapsed hours. Other staff will include Windows/Linux/Cloud administrators. 2-4 hours of project management may also be required.
  • Are business data transformations required? tcVISION handles minor transformation via point and click (e.g., date format transformations). Major transformations can require C++ or product scripting.
  • Are there any triggers or stored procedures? tcVISION performs CDC replication processing using a database that utilizes these database features.

Of course, each project will have unique environments, goals, and desired use cases. It is important that specific use cases are determined and documented prior to the start of a project and a tcVISION POC. This planning will allow the Treehouse Software team and the customer develop a more accurate project timeline, have the required resources available, and realize a successful project. 

More About tcVISION from Treehouse Software…

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tcVISION supports a vast array of integration scenarios throughout the enterprise, providing easy and fast data migration for mainframe application modernization projects. This innovative technology offers comprehensive abilities to identify and capture changes occurring in mainframe and relational databases, then publish the required information to an impressive variety of targets, both Cloud and on-premises.

tcVISION acquires data in bulk or via CDC methods from virtually any IBM mainframe data source (Software AG Adabas, IBM Db2, IBM VSAM, IBM IMS/DB, CA IDMS, CA Datacom, and sequential files), and transform and deliver to a wide array of Cloud and Open Systems targets, including AWS, Google Cloud, Microsoft Azure, Confluent, Kafka, PostgreSQL, MongoDB, etc. In addition, tcVISION can extract and replicate data from a variety of non-mainframe sources, including Adabas LUW, Oracle Database, Microsoft SQL Server, IBM Db2 LUW and Db2 BLU, IBM Informix, and PostgreSQL.


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Contact Treehouse Software for a tcVISION Demo Today…

Simply fill out our Product Demonstration Request Form and a Treehouse representative will be contacting you to set up a time for your requested demonstration.

What’s Your Mix?

Real-time and Bi-directional Data Replication Between Mainframes and Virtually Any Target

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tcVISION from Treehouse Software — Enterprise ETL and Real-Time Data Replication Through Change Data Capture (CDC)

Planning a data replication project between Mainframe, Cloud, and Open Systems platforms? tcVISION supports a vast array of integration scenarios throughout the enterprise, providing easy and fast data migration for mainframe application modernization projects. This innovative technology offers comprehensive abilities to identify and capture changes occurring in mainframe and relational databases, then publish the required information to an impressive variety of targets, both Cloud and on-premises.

tcVISION acquires data in bulk or via CDC methods from virtually any IBM mainframe data source (Software AG Adabas, IBM Db2, IBM VSAM, IBM IMS/DB, CA IDMS, CA Datacom, and sequential files), and transform and deliver to a wide array of Cloud and Open Systems targets, including AWS, Google Cloud, Microsoft Azure, Confluent, Kafka, PostgreSQL, MongoDB, etc. In addition, tcVISION can extract and replicate data from a variety of non-mainframe sources, including Adabas LUW, Oracle Database, Microsoft SQL Server, IBM Db2 LUW and Db2 BLU, IBM Informix and PostgreSQL.

Whatever your mix, Treehouse Software has got it covered with tcVISION.


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Moving the right data to the right place at the right time

Visit the Treehouse Software website for more information on tcVISION, or contact us to discuss your needs.

Quickly Begin Replicating Mainframe Data on Cloud and Open Systems During a tcVISION Proof of Concept.

by Joseph Brady, Director of Business Development / Cloud Alliance Leader at Treehouse Software, Inc.

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Customers can start moving mainframe data within days during a tcVISION POC…

An online tcVISION Proof of Concept (POC) is approximately 10 business days, with the customer providing a representative subset of data, use cases, and goals for the POC. A Treehouse Software consultant will assist in downloading and installing tcVISION, and conduct a limited-scope implementation of a tcVISION application. This application uses customer data and executes on customer facilities, in a non-production environment. A document is provided beforehand that outlines the requirements and agenda for the POC.

By the end of the POC, customers can begin replicating mainframe data to their Cloud or Open Systems target database.  It can happen that fast!.

About tcVISION

More Cloud, Open Systems, and Systems Integration partners are recommending tcVISION, Treehouse Software’s Mainframe-to-Cloud data replication product for modernization projects. tcVISION focuses on changed data capture (CDC) when transferring information between mainframe data sources and Cloud and Open System databases and applications. Through an innovative technology, changes occurring in any mainframe application data are tracked and captured, and then published to a variety of RDBMS and other targets.

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Further reading…

Treehouse Software is an AWS, Google Cloud, and Microsoft Technology Partner, and the AWS Partner Network published a blog about tcVISION, which describes how tcVISION allows legacy mainframe environments to continue, while replicating data on highly available and secure Cloud platforms.


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Contact Treehouse Software for a tcVISION Demo Today…

Simply fill out our Product Demonstration Request Form and a Treehouse representative will be contacting you to set up a time for your requested demonstration.

Treehouse Software White Paper: Mainframe-to-Hybrid Cloud – The “Data First” Approach

by Joseph Brady, Director of Business Development / Cloud Alliance Lead at Treehouse Software, Inc.

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Data First Approach to Mainframe Modernization

This white paper serves as a guide for organizations planning to replicate their mainframe data on a Cloud platform. Much of an enterprise’s mission critical mainframe data is stored in legacy mainframe databases, and the cost to maintain these databases is high. An added complication is that the data is utilized by many interlinked and dependent programs that have been in place for many years, and sometimes, decades. Unlocking the value of this legacy data is difficult due to many very different types of mainframe databases.

Many organizations are now looking for modernization solutions that allow their legacy mainframe environments to continue, while replicating data in real time on highly available Cloud-based platforms. With a “data-first” approach, immediate data replication to the Cloud is enabling government, healthcare, supply chain, financial, and a variety of public service organizations to meet spikes in demand for vital information, especially in times of crisis.

Download the White Paper Here


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Contact Treehouse Software for a Demo Today…

Just fill out the Treehouse Software Product Demonstration Request Form and a Treehouse representative will contact you to set up a time for your tcVISION demonstration. This will be a live, on-line demonstration that shows tcVISION replicating data from the mainframe to a Cloud or Open Systems target.