tcVISION Mainframe Data Replication Solution is Featured in the Microsoft Azure Architecture Center

tcVISION is a data replication solution that provides an IBM mainframe integration solution for mainframe data replication, data synchronization, data migration, and change data capture (CDC) to multiple Azure data platform services.

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Contact Treehouse Software Today…

Treehouse Software is the worldwide distributor of tcVISION, a software product that allows immediate data replication between many Mainframe sources and Cloud and Open Systems targets, enabling government, healthcare, supply chain, financial, and a variety of public service organizations meet spikes in demand for vital information. 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.

Considerations for Planning Bi-Directional Mainframe Data Replication with tcVISION

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

Data_Modrnization

Many medium-to-large size enterprises use mainframe systems that are housing vast amounts of mission-critical data encompassing historical, customer, logistics, etc. information.  Each mainframe site is unique and can have decades worth of customizations requiring innovative approaches to establishing data replication on Cloud and open systems platforms. Fortunately for these customers, Treehouse Software has been in the mainframe software market since 1982, bringing deep experience in mainframe, Cloud, and open systems technologies, as well as delivering the tcVISION mainframe data replication product. Today, Treehouse Software is helping many enterprise mainframe customers accelerate digital transformation and successfully leverage Hybrid Cloud initiatives on the IBM Z platform, storing sensitive data on a private Cloud or local data center and simultaneously leveraging leading technologies on a managed public Cloud.

Treehouse Software’s tcVISION solution focuses on changed data capture (CDC) when transferring information between mainframe data sources and Cloud and open systems-based databases and applications. Changes occurring in the mainframe application data are then tracked and captured, and published to a variety of targets. Additionally, tcVISION supports bi-directional data replication, where changes on either platform are reflected on the other platform (e.g., a change to a PostgreSQL table in the Cloud is reflected back on mainframe), allowing the customer to modernize their application on the Cloud or open systems without disrupting the existing critical work on the legacy system. tcVISION’s bi-directional replication writes directly to the mainframe database, thereby bypassing all mainframe business logic, so this architecture requires careful planning, as well as thorough and repeated testing.

Plan carefully…

The following section offers some real-world customer examples, as well as considerations and recommendations when planning bi-directional replication for any mainframe/RDBMS environments. Bi-directional replication by its nature is a very complicated undertaking, so it is necessary that customers are fully educated in all environments, software, and processes before attempting to write data back to a mainframe database. It is always recommended that customers use a minimally effective measure of bi-directional replication required to accomplish their goal — and no more. An overblown project with unnecessary bi-directional data replication invites undue complexity and delays.

Real-world customer examples…

Treehouse Software has many customers performing bi-directional data replication, and each scenario is vastly different from the others, even if some have the same sources and targets as each other.  For example, some customers utilize a Master/Master, collision-heavy proposition, while others use uni-directional one way, then “flip a switch” uni-directional the other way. Another example is a customer who has a “grand circle,” where data hits multiple applications before it finally makes its way back to an RDBMS staging database that tcVISION replicates to the mainframe.

Example of a Treehouse customer’s bi-directional data replication environment using tcVISION:

tcVISION_Adabas_To_AWS_RDS

There are many planning and implementation stages that go into a successful mainframe replication environment, and performance testing is a vital part of a successful project.  For example, customers should do performance tests on how long it takes tcVISION to read a database log, transfer data, process data, etc.  During testing at one of our reference customer sites we found a significant difference in how long it took for their test and prod LPARs to transmit data to the Cloud, based on whether the mainframe TCP/IP stack used a 32-bit or 128-bit setting.

At another site, where we are helping a large government agency perform bi-directional replication on mainframe data, their original goal was for a significant percentage of mainframe objects to have bi-directional replication. It was determined that it would be impossible to extract business logic from the existing mainframe application for usage in the downstream application. Therefore, they have decided to use a middleware product to perform the “write-back” to the mainframe database.  Given the complexity of the mainframe application, this has proven the safest way for them to proceed.

Because of the variety of customer scenarios as described above, before any site can attempt bi-directional data replication, it is crucial that they have a well-tested uni-directional process with operational controls in place for a significant time period.  “Operational controls” means processes to restart scripts, evaluation of failed transactions, orchestration of mainframe/non-mainframe DBMS changes, etc.

Please contact Treehouse Software to discuss your Mainframe-to-Cloud and Open Systems modernization plans. We can help put in place a roadmap to modernization success.


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Contact Treehouse Software Today for a tcVISION Demo…

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.

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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.


Providing a High Availability Framework for Mainframe-to-AWS Data Replication

by Dan Vimont, Cloud Solutions Architect at Treehouse Software, Inc.

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Treehouse Software customers are using tcVISION to enable mission-critical mainframe-to-AWS data replication pipelines.  Some of these production pipelines are providing vital near-real-time synchronization between source and target, and thus can’t afford any significant downtime in the event of failure.  So it’s only natural that a number of our customers have been asking for advice in setting up a high availability configuration for their tcVISION components that run on AWS EC2 instances.  The High Availability Framework discussed here provides for a Failover EC2 instance to automatically pick up tcVISION processing should the Primary instance (running in another Availability Zone) go down.

The Core Components:  Primary Instance & Failover Instance

The core components of a tcVISION high availability framework consist of two EC2 instances running in different Availability Zones:  a Primary EC2 instance and a Failover EC2 instance.  Both identically-configured EC2 instances are attached to a shared working-storage file system (either an EFS or FSx volume), which allows the Failover instance to seamlessly and quickly pick up tcVISION processing should the Primary instance suddenly become unavailable.

HA1

Use a Step Function to Automate the Failover Process

In the event of failure of the Primary instance, the recommended framework calls for automatic triggering of a Step Function for reliable failover processing, with steps that include the following:

  • verify that the Primary instance is unavailable (The tcVISION service cannot be active on both instances simultaneously, so this verification is vital.)
  • redirect all network traffic from the Primary instance to the Failover instance (via Route 53)
  • start tcVISION processing on the Failover instance

HA2

When Ready, Use a Step Function to Automate the Restoration Process

After operations personnel have completed recovery of the Primary EC2 instance, another Step Function may be manually triggered to reliably transfer tcVISION processing back to the Primary instance.

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Many More Details are Available Upon Request to Treehouse Customers

Full details regarding our recommended High Availability Framework for tcVISION are available upon request to Treehouse customers.  AWS services utilized in the complete recommended framework include Step Functions, Lambda Functions, EventBridge rules, CloudWatch alarms, SNS topics, a Route 53 Private Hosted Zone, and more.  The following diagram is a partial visual inventory of the recommended framework components.

HA5

Interested in seeing a live, online demo of tcVISION?

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.


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Some are calling mainframes “dinosaurs”, but many of us see that as a good comparison!

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

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Since the dinosaur analogy has been used so much to describe mainframe computer systems in recent years, I would like to use this blog to take a look at the parallels of dinosaurs and mainframes as it relates to the current buzz about modernization on the Cloud.

Of course, dinosaurs and mainframes have been around for a long time and are extremely resilient and successful. I especially say “are” in relation to dinosaurs, because many are not extinct at all, and the fossil record shows that several types have adapted to the changing world by evolving into birds. Additionally, during the age of dinosaurs, they branched off into countless varieties during a span of about 165 million years – hardly a failed species. Also, like the dinosaurs, the mainframe has thrived and survived for over six decades and is continuing to adapt – albeit not nearly as long as the reign of the dinosaurs, but an impressive run, nonetheless.

And the mainframe isn’t finished yet! Mainframe systems are still very much in use, running major banking processes, healthcare systems, government IT services, and critical business operations of many Global 2000 companies. As a matter of fact, IBM has been reporting growth year after year, as the IBM Z platform continues to see important innovations, such as with Cloud-native development capabilities, as well as impressive improvements in processing power.

Looking up and moving forward…

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As with the dinosaurs who did not fear looking to the clouds and taking wing to ensure survival, the new breed of mainframers envision bold and exciting possibilities in Cloud computing. Many see remarkable opportunities for business advantage by modernizing their mainframe environments. This modernization includes replicating mainframe data on Cloud platforms in order to quickly capitalize on the latest Cloud services, such as analytics, auto scaling, machine learning and artificial intelligence (AI), high availability, advanced security, etc., or to move data to a variety of newer Cloud databases, streaming services, container services, and much more. With the proper data replication technology and planning, all of this modernization can occur while keeping the legacy mainframe environment active as long as it is needed!

The IBM Z mainframe isn’t going anywhere, and with visionary and daring leadership, it can continue to evolve and adapt to whatever develops in the Cloud… and beyond.

Ready to move forward, adapt, and evolve? Treehouse Software is here to help!

Treehouse Software is your partner on your journey into future mainframe modernization plans. With our “data first” approach, we can help accelerate digital transformation and successfully leverage Cloud and Hybrid Cloud initiatives on the IBM Z platform, storing sensitive data on a private Cloud or local data center, and simultaneously leveraging leading technologies on a managed public Cloud.

Bidirectional_Data_Replication

Through an innovative changed data capture (CDC) technology, our tcVISION product tracks and captures changes occurring in any mainframe application data, and then publishes them to a variety of Cloud targets. The customer moves only the right data to the right place at the right time – as much, or as little as they want.

The tcVISION data replication solution has a modular design, which enables it to support mass data load from one source to one or more targets, as well as continuous data exchange processes in real-time via CDC. This modular architecture and the provided APIs gives customers unlimited future potential for continued evolution, and use of new and emerging technologies.


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Want to see tcVISION in action?

You can schedule a live, online demonstration that shows tcVISION replicating data from the mainframe to a Cloud target database. Just fill out the Treehouse Software tcVISION Demonstration Request Form and a Treehouse representative will contact you to set up a time for your tcVISION Mainframe-to-Cloud data replication demonstration.

How to Synchronize Data in Real Time Between the Mainframe and AWS with Treehouse Software’s Enterprise CDC Tool

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

Bidirectional_Data_Replication

Many mainframe integration scenarios require continuous near-real-time replication of relational data to keep a copy of the data synched in the Cloud. Change Data Capture (CDC) is used for this near-real-time transactional replication by capturing change log activity to drive changes in the target dataset.

Just what is CDC anyway?

Simply put, and in relation to Mainframe-to-Cloud and open systems data replication, CDC is the use of processes to identify when data has been changed in a source system, so the replicated upstream or downstream (depending on how you look at it) target can be kept in sync with the changes.

In a recent AWS Architecture Blog, readers learn about integration using mainframe data to build Cloud native services with AWS, including transactional replication-based integration via CDC.

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As mentioned in the blog, AWS Partner CDC Tools are available for connecting data center mainframes to the various data targets, and Treehouse Software’s tcVISION is one of those tools available in the AWS Marketplace.

tcVISION allows changes occurring in any mainframe application data to be tracked and captured, and then published to a variety of target AWS databases and applications. tcVISION provides an easy and fast approach for Hybrid Cloud projects, enabling real-time and bi-directional data replication between the hardware and AWS.

Example of Db2-to-AWS CDC using tcVISION Mainframe Manager:

tcVISION_Db2_To_AWS_CDC

tcVISION supports several CDC methods available, depending on each customer’s use case:

Bulk Transfer

  • Efficient transfer of entire databases
  • Analysis for data consistency (verification)
  • Initial load (ETL) and periodic mass data transfer
  • One-step data transfer

Log Processing

  • Transfer of changed data near-realtime or scheduled time frame
  • Reads both active logs and archived logs

Batch Compare

  • Comparison of data snapshots using checksums
  • Efficient transfer of changed data since last processing
  • Flexible processing options (SORT etc.)
  • Automatic creation of deltas by tcVISION

DBMS Extension

  • Real-time capture of changed data directly from the DBMS
  • Secure data storage even across DBMS restart
  • Flexible propagation methods

Interested in seeing a live, online demo of tcVISION CDC?

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.


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Should You Stay, or Should You Go? You Can Do Both by Incrementally Replicating Your Mainframe Data on the Cloud While Keeping Both Sides Synchronized

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

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Many of Treehouse Software’s enterprise customers are not close to considering the retirement of their mainframe systems, but instead have long-term data replication projects, or want to indefinitely have their legacy systems co-exist with a new Cloud platform. These organizations are looking for solutions that allow their legacy mainframe environment to continue while replicating data – in real time and bi-directionally – to take advantage of the latest Cloud services, such as analytics, auto scaling, machine learning and artificial intelligence (AI), high availability, advanced security, etc., or move data to a variety of newer Cloud databases, streaming services, container services, and more.

The Transition Doesn’t Have to be a Sudden Big Bang

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 also difficult due to many very different types of mainframe databases (e.g., Db2, Adabas, CA Datacom, CA IDMS, etc.).

Immediate data replication on 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. The globalization of markets, increase of data volumes, 24×7 operations, changing business conditions, and high demand for up-to-date information also requires new data transfer and exchange solutions for heterogeneous IT architectures.

The Data-First Solution

Treehouse Software is here to help enterprise mainframe customers accelerate digital transformation and successfully leverage Hybrid Cloud initiatives on the IBM Z platform, storing sensitive data on a private Cloud or local data center and simultaneously leveraging leading technologies on a managed public Cloud. Our tcVISION replication solution focuses on changed data capture (CDC) when transferring information between mainframe data sources and modern 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 targets. The customer moves only the right data to the right place at the right time – as much, or as little as they want.

The tcVISION replication solution has a modular design, which enables it to support mass data load from one source to one or more targets, as well as continuous data exchange processes in realtime via CDC. This modular architecture and the provided APIs gives customers unlimited potential for growth and use of new technologies.

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 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.

In the following example high level architecture diagram, bi-directional data replication between Db2 z/OS and AWS using tcVISION is shown:

___tcVISON_Bidirectional_Db2

tcVISION utilizes a Windows-based GUI Control Board, which is ideal for non-mainframe programmers.  While mainframe experts are required in the design/architecture phase and occasionally during implementation, the requirement for their involvement is limited. The tcVISION Control Board acts as a single point of administration, data modeling and mapping, script generation, and monitoring. Comprehensive monitoring and logging of all data movements ensure transparency across all data exchange processes. In the following example, the mainframe can be seen communicating to an Amazon EC2-based tcVISION replication manager. The tcVISION Control Board shows the user a graphical representation of this replication:

___tcVISION_Control_Board_AWS_Agentless

Additionally, tcVISION supports complex data replication scenarios between multiple data sources and targets, as seen here:

tcVISION_Complex_Replication_Scenarios

With tcVISION, data replication projects can be implemented within a few of months, depending on the complexity of the project.  This includes the proof of concept and design/architecture stages.  After these stages are complete, the customer can start the first production implementation sprint, immediately providing business value.  We suggest successive agile sprints to allow for incremental deployment of additional file replication, sprint by sprint.

Supported Sources and Targets

tcVISION supports a vast array of integration scenarios throughout the enterprise, providing easy and fast data replication for Mainframe-to-Cloud and Open Systems application modernization projects.


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Contact Treehouse Software for a tcVISION Demo Today…

Just fill out the Treehouse Software tcVISION 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 target database.

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.

tcvision-mainframe-to-confluent-cloud-data-replication-1536x1042

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.

Video: Mainframe-to-Azure Data Replication with tcVISION from Treehouse Software

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

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Treehouse Software was recently invited by Microsoft Azure Mainframe Modernization technical teams to do a presentation and demonstration of tcVISION, our innovative Mainframe-to-Cloud data replication software product.

In this video, we show an overview of the product, then demonstrate replication of mainframe data on Azure SQL:

Click Here to View the Video


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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.

For more information, please contact customer sales at +1.724.759.7070, email us at sales@treehouse.com, or 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 on Azure SQL with tcVISION from Treehouse Software

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

tcVISION allows enterprise customers to replicate data between mainframe, Cloud, or Hybrid Cloud while maintaining their legacy environments.

We are currently working with a government site to architect bi-directional mainframe data replication on Azure SQL.  One of the customer’s requirements is for tcVISION to provide real-time data synchronization of changes on either platform reflected on the other platform (e.g., a change to an Azure SQL table is reflected back on mainframe). This way, the customer can modernize their application on the Azure Cloud without disrupting the existing critical work on their legacy system.

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VIDEO: See how tcVISION easily connects mainframe systems to Azure SQL…

The tcVISION solution focuses on changed data capture (CDC) when transferring information between mainframe data sources and modern 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 targets.

Azure SQL is a supported target in tcVISION, and in this instructional video, tcVISION is shown synchronizing data in real-time between Db2 on z/OS and Azure SQL:


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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.

Download the AWS and Treehouse Software Mainframe Data Replication Solution Brief

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

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Treehouse Software’s tcVISION data replication product provides connectivity between your mainframe and AWS, putting some of the world’s most advanced technologies at your fingertips. tcVISION is an innovative technology that provides real-time and bi-directional data replication between the mainframe and many AWS targets, including Amazon RDS Aurora, Amazon RDS PostgreSQL, Amazon RDS MySQL/MariaDB, Amazon RDS Oracle, Amazon RDS SQL Server, Amazon S3, Amazon Kinesis, Amazon Redshift, and more. By working with Treehouse Software and using AWS solutions, tools, programs, and databases, you can save time and automate processes. View and download the AWS tcVISION Solution Brief here.


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