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.

Treehouse Software Customer Success: ETS uses tcVISION for Real-Time Synchronization Between their Mainframe IDMS Data and AWS RDS for PostgreSQL

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

ETS_Graphic

This blog focuses on a current Treehouse Software customer – ETS. Headquartered in Princeton, New Jersey, ETS is a private, nonprofit organization with approximately 3,000 employees devoted to educational measurement and research. ETS develops and administer a broad range of educational products and services for government agencies, academic institutions and corporations, including the TOEFL® and TOEIC® tests, the GRE® General and Subject Tests, and the Praxis® assessments. At nonprofit ETS, our belief in the life-changing power of learning is at the root of everything we do — it’s behind the tools we develop to move learning forward, the research that inspires educational progress and the commitment we make to enable opportunity for learners everywhere. We’re with you on the journey to what’s possible.

Business Background

ETS products and services are available to institutions, businesses, organizations and governments in more than 180 countries around the world. The top industries served by ETS are K–12 Education, Higher Education, English-language Learning, Career Development, and Consulting Services.

Business Issue

Most of ETS’s high volume critical application data is stored on an IBM mainframe in IDMS databases.  The technology is very old, therefore it is difficult to recruit and retain qualified technical personnel to maintain applications.  ETS is moving to Cloud-based computing which will allow them to retire the mainframe environments and modernize the applications.  The data is used and shared across several applications.  ETS required a solution that would allow them to continue, uninterrupted, daily operations on their mainframe while replicating data to their AWS Cloud platform, where they could develop modern application features.  This solution enables ETS to maintain demanding daily processing while they modernize and develop innovative Cloud solutions to meet and exceed customer requirements.

The Technology Solution

ETS_Diagram

Treehouse Software and the ETS team developed a rigid testing plan to implement tcVISION and performed a Proof of Concept to measure the effectiveness of the data replication, considering the high volumes of data changes on the source databases.  We collaborated on architecture requirements and installation steps.  There were many considerations associated with this process, including monitoring, alarming, configuration options, high availability, measuring the impact to existing mainframe database performance, restart capability, and security.  Concurrently, a team of subject matter experts worked on data mappings and translation of database designs from the IDMS network databases to AWS PostgreSQL relational databases.  The goal was to be able to replicate two very large IBM mainframe IDMS databases real-time on two Cloud-based PostgreSQL databases. Implementation was done in phases, starting with one non-production database being replicated to the Cloud.  High-volume testing was performed on the source database to simulate peak processing, replicating millions of transactions to the target PostgreSQL databases.  Many technical challenges were encountered and resolved with outstanding technical assistance from the Treehouse Software support team.  Once in production, the tcVISION product was able to deliver real-time data to the Cloud platform with no interruptions to the customer’s daily processing. The customer was then able to develop modern application features and functions in the Cloud to achieve independence from the legacy mainframe systems.  Using new Cloud-based capabilities enabled the customer to be more agile with meeting new requirements.


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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.

Data_First_Overview_Google

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.

tcVISION from Treehouse Software: Replicate Data Between Mainframe, Cloud, or Hybrid Cloud While Maintaining Your Legacy Environment

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

tcVISION_Website

Visit Treehouse Software’s tcVISION dedicated website, where customers can learn how to keep data in synch in hybrid IT architectures with Z mainframe, distributed, and Cloud platforms through instructional videos, blog articles, and slide shows: https://www.tcvision.com/


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Contact Treehouse Software Today…

Treehouse Software is the worldwide distributor of tcVISION, which provides mainframe data replication between Db2, Adabas, VSAM, IMS/DB, CA IDMS, CA DATACOM, or sequential files, and many Cloud and Open Systems targets, including AWS, Google Cloud, Microsoft Azure, Kafka, PostgreSQL, etc. 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.

Treehouse Software is Helping Government Agencies with Mainframe Adabas Data Take Advantage of Cutting Edge Cloud-based Technologies

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

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Many government agencies have large volumes of mission critical and historical data stored in a variety of legacy mainframe databases (for this blog, we are focusing on Adabas). These government agencies combine a broad range human service programs, including employment assistance and job training, child and adult protection, child support enforcement, cash assistance, and services for the developmentally disabled, all of which constantly require accurate, up-to-date, and secure data.

To support the needs of clients, government agencies are generally broken into multiple divisions, including the division that Treehouse Software works with the most — Technology Services. The Technology Services divisions provide technical and systems services for the development, maintenance, and enhancement of automated business systems. They also ensure that the production and sub-production databases are running smoothly and efficiently by performing necessary maintenance of the databases.

Rapidly changing national health and economic conditions are making fast access to the most current information more important than ever for government agencies and the public.  As a result, a top priority for Technology Services divisions is modernizing critical data residing on long-standing mainframe databases. Unlocking the value of this important data can be difficult, because the data can be utilized by numerous interlinked and dependent programs that have been in place for many years, and sometimes decades.

Many Treehouse government customers 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, such as AWS, Google Cloud, and Microsoft Azure. tcVISION from Treehouse Software allows a “data-first” approach, whereby immediate data replication to the Cloud helps government agencies begin strategies to meet spikes in demand for vital information, especially in times of crisis.

Just what is it about Adabas?

Adabas is a mainframe database that is still heavily used by government sites throughout the U.S. and the world. Having specialized in tools and services complementary to Adabas/Natural applications since 1982, Treehouse has successfully encountered and addressed many unique issues within the Adabas environment. This excerpt from a Treehouse technical document outlines three primary issues with Adabas/Natural that must be considered:

  1. Adabas has no concept of “transaction isolation”, in that a program may read a record that another program has updated, in its updated state, even though the update has not been committed.  This means that programmatically reading a live Adabas database—one that is available to update users—will almost inevitably lead to erroneous extraction of data.  Record modifications (updates, inserts and deletes) that are extracted, and subsequently backed out, will be represented incorrectly—or not at all—in the target. Because of this, at Treehouse we say “the only safe data source is a static data source”—not the live database.
  2. Many legacy Adabas applications make use of “record typing”, i.e., multiple logical tables stored in a single Adabas file.  Often, each must be extracted to a separate table in the target RDBMS.  The classic example is that of the “code-lookup file”.  Most shops have a single file containing state codes, employee codes, product-type codes, etc.  Records belonging to a given “code table” may be distinguished by the presence of a value in a particular index (descriptor or superdescriptor in ADABAS parlance), or by a range of specific values.  Thus, the extraction process must be able to dynamically assign data content from a given record to different target tables depending on the data content itself.
  3. Adabas is most often used in conjunction with Software AG’s Natural 4GL, and “conveniently” provides for unique datatypes (“D” and “T”) that appear to be merely packed-decimal integers on the surface, but that represent date or date-time values when interpreted using Software AG’s proprietary Natural-oriented algorithm. The most appropriate way to migrate such datatypes is to recognize them and map them to the corresponding native RDBMS datatype (e.g., Oracle DATE) in conjunction with a transformation that decodes the Natural value and formats it to match the target datatype.

For discovery and analysis of legacy source data structures, tcVISION’s modeling and mapping facilities view and capture logical Adabas structures, as documented in Software AG’s PREDICT data dictionary, as well as physical structures as described in Adabas Field Definition Tables (FDTs).  Note that PREDICT is a “passive” data dictionary—there is no requirement that the logical and physical representations agree, so it is necessary to scrutinize both to ensure that the source structures are accurately modeled.

Furthermore, tcVISION generates specification and implementation of appropriate mappings and transformations for converting Adabas datatypes and structures to corresponding RDBMS datatypes and structures, including automatic handling of the proprietary “D” and “T” source datatypes.

There are three ways tcVISION can access Adabas data:

  1. ETL – read the active database nucleus
  2. ETL – read datasets containing unloaded Adabas files created by the ADAULD utility
  3. CDC – read the active and archived PLOGs datasets

It is important to note that the schema, mappings and transformations that result from metadata import can be tailored to any specific requirements after the fact.  It is even possible to import an existing RDBMS schema and retrofit it, via drag-and-drop, to the source Adabas elements.

Using the tcVISION Control Board, a Windows GUI interface, the most complex transformations can be specified. Source fields can be combined into a single column, decomposed into separate columns, and be subject to calculations, database lookups, string operations and even programmatic manipulation. Furthermore, mapping rules can be implemented to specify that data content from a source Adabas record be mapped to one or more target RDBMS tables—each with its own different structure, as desired—based on the data content itself. Target tables can even be populated from more than one source file.

tcVISION supports complex replication scenarios…

tcVISION_Complex_Replication_Scenarios

tcVISION GUI Control Board functions as a central point of administration…

tcVISION_Control_Board

Automatically apply target schema within the Control Board…

tcVISION_Target_Schema

It is impossible to discuss all the features and capabilities of tcVISION within a high-level overview.  Given the maturity, wealth of functionality and relative low cost of tcVISION, as compared to the effort, complexity and risk entailed in a “Do-It-Yourself”, solution there is no reason why a legacy renewal project should run aground on data migration.

tcVISION’s minimal footprint on the mainframe…

Customers are very happy with tcVISION‘s “staged processing” methodology, where the only processing occurring on the mainframe was the capture of changes from Adabas PLOGs. The bulk of the processing occurs on the target platform, minimizing tcVISION’s footprint on the mainframe as seen in this diagram…

tcVISION_Staged_Processing

The user defines on which platform stage their processing should be done. Do as little as possible on the mainframe: Stage 0 – capture data and send data (internal format) to target, and process data up to Stage 3 in receiving environment.

Moving forward with tcVISION…

Treehouse Software has been helping local, state, and federal government agencies with Adabas and Natural in the areas of data migration, security, control, auditing, performance enhancement, etc. for decades. Over the years, Treehouse has expanded its capabilities to address new requirements for modernizing legacy mainframe Adabas databases on various Cloud platforms. By using Treehouse Software’s tcVISION Mainframe-to-Cloud data replication product, our government customers are able to immediately utilize some of the most advanced Cloud tools and services in the world.

tcVISION enables government agencies to synchronize mainframe Adabas data with various highly available and secure Cloud databases, data warehouses. etc.. Additionally, bi-directional, real-time data synchronization will enable changes on either platform to be reflected on the other platform (e.g., a change to a PostgreSQL table is reflected back on the mainframe database). This allows governments to modernize  applications on Cloud platforms without disrupting the existing critical work on the legacy system, and modern tools can now be used in the new environment, greatly enhancing agility.

Replicating mainframe data on the Cloud can happen within days during a tcVISION Proof of Concept (POC)…

tcVISION_Overall_Diagram_General_Cloud01

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

By the end of the 10-day POC, customers can begin replicating mainframe data to their Cloud target database.  It can happen that fast!

Further Reading…

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Treehouse Software is an AWS Technology Partner, and the AWS Partner Network published a blog about tcVISION, our Mainframe-to-Cloud data replication product, which describes how tcVISION allows legacy mainframe environments to continue, while replicating data on highly available and secure Cloud platforms:

https://aws.amazon.com/blogs/apn/real-time-mainframe-data-replication-to-aws-with-tcvision-from-treehouse-software/


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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.

Replicate Data Between Mainframes and Cloud APIs for MongoDB with Treehouse Software’s tcVISION

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

Treehouse Software is helping enterprises with mainframe data explore modernizing with various Cloud APIs for MongoDB using tcVISION, our Mainframe-to-Cloud data replication product.

The MongoDB Atlas Database as a Service (DBaaS) is present across all major Cloud platforms (AWS, Azure, and Google). Automated infrastructure provisioning, setup, and deployment are fully automated with MongoDB Atlas.

Select a Cloud provider, region, instance size, memory, and additional configurations in the Cluster Builder or via the API and be on your way…

Video Demo: Moving Mainframe Data to MongoDB with tcVISION

Our video demonstrates integrating logically connected data to a document structure in MongoDB. This video shows how to transfer Db2 z/OS Mainframe Data To MongoDB using tcVISION…

Replicating mainframe data on the Cloud can happen within days during a tcVISION Proof of Concept (POC)…

tcVISION_Overall_Diagram_General_Cloud

An online tcVISION POC is approximately 5-10 business days, with the customer providing use cases, goals, and a representative sample of data for the POC. A Treehouse Software consultant will assist in downloading and installing tcVISION and conducting a limited-scope implementation of a tcVISION application. This application uses customer data and executes on customer facilities, usually in a non-production environment. A document is provided beforehand that outlines the requirements and agenda for the POC.

By the end of the 10-day POC, customers can begin replicating mainframe data to their Cloud target database.  It can happen that fast!

Further Reading…

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Treehouse Software is an AWS technology partner, and the AWS Partner Network published a blog about tcVISION, our Mainframe-to-Cloud data replication product, which describes how tcVISION allows legacy mainframe environments to continue, while replicating data on highly available and secure Cloud platforms:

https://aws.amazon.com/blogs/apn/real-time-mainframe-data-replication-to-aws-with-tcvision-from-treehouse-software/


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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 is Helping Higher Education Customers Modernize Long-standing Mainframe Data on the Cloud

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

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The Business Issue

Many higher education institutions have large volumes of mission critical and historical data stored in legacy mainframe databases (Db2, Adabas, IMS, IDMS, Datacom, VSAM, etc.). The cost to maintain these databases is high and they lack the features required for modernizing the data architecture. Additionally, the data is utilized by an extensive number of interlinked programs dependent on this legacy data.

Colleges and universities are searching for a solution that allows them to unlock their mainframe data within a Cloud-based data store, such as Amazon Simple Storage Service (Amazon S3), where they can use a wide array of analytics and machine learning services for easy access to all relevant data, without compromising security or governance.

Once mainframe data is on AWS, an institution can innovate quickly by creating new functions with Cloud speed, such as mobile users via Amazon API Gateway, or voice devices such as Amazon Alexa.

Additionally, data security is one of the biggest challenges facing most higher education organizations. Beyond the certifications and best practices that are part of having data reside on the AWS Cloud platform, there are also many security features and services designed to help an organization stay compliant with industry best practices and regulations.

The Solution: Mainframe-to-Cloud Data Replication 

Treehouse Software recently helped a large university with a requirement for a solution that allows their legacy mainframe database to continue while replicating data in real time on AWS. By using Treehouse Software’s tcVISION Mainframe-to-Cloud data replication product, the university was able to immediately utilize some of the most advanced Cloud tools and services in the world.

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tcVISION enables the university to synchronize mainframe data to Amazon RDS for PostgreSQL. Furthermore, bi-directional, real-time data synchronization will enable changes on either platform to be reflected on the other platform (e.g., a change to a PostgreSQL table is reflected back on the mainframe database). This allows the university to modernize the application on PostgreSQL without disrupting the existing critical work on the legacy system, and modern tools can now be used in the PostgreSQL environment, greatly enhancing business agility.

Moving Forward…

Having on-demand, Cloud-based services available can now help IT teams build secure environments for mission-critical applications for the University, freeing them to focus on student success and plan for growth or increased seasonal demand.

tcVISION provides the quality of service required by enterprise data workloads for security, availability, and scalability, and university staff and students can look forward to quickly and affordably accessing Cloud compute, storage, and application services.

Replicating mainframe data on the Cloud can happen within days during a tcVISION Proof of Concept (POC)…

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An online tcVISION POC is approximately 5-10 business days, with the customer providing use case and goals for the POC. A Treehouse Software consultant will assist in downloading and installing tcVISION and conducting a limited-scope implementation of a tcVISION application. This application uses customer data and executes on customer facilities, usually in a non-production environment. A document is provided beforehand that outlines the requirements and agenda for the POC.

By the end of the 10-day POC, customers can begin replicating mainframe data to their Cloud target database.  It can happen that fast!

Further Reading…

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Treehouse Software is an AWS technology partner, and the AWS Partner Network published a blog about tcVISION, our Mainframe-to-Cloud data replication product, which describes how tcVISION allows legacy mainframe environments to continue, while replicating data on highly available and secure Cloud platforms:

https://aws.amazon.com/blogs/apn/real-time-mainframe-data-replication-to-aws-with-tcvision-from-treehouse-software/


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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, Inc. Collaborates with Google Cloud to Offer Mainframe-to-Google Cloud Data Replication for Enterprise Transformation and Modernization

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

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Treehouse Software, Inc. is pleased to announce an agreement with Google Cloud as a technology partner in the Google Cloud Partner Advantage Program. As a technology partner, Treehouse Software Inc. will now offer enterprise customers a comprehensive Mainframe-to-Google Cloud data replication and migration solution. This relationship provides Google Cloud customers with Treehouse’s combination of decades worth of mainframe systems experience and comprehensive data replication capabilities, with Google Cloud’s platform.

The Google Cloud Enterprise Transformation Practice assists companies in migrating and modernizing workloads on Google Cloud’s global, secure, and reliable platform. Once an enterprise’s data is on Google Cloud, they can immediately take advantage of some of the most advanced artificial intelligence, machine learning, big data analytics, and data warehousing services in the world.

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The same technology that supports Google’s global network protects data while meeting rigorous industry-specific compliance standards, and Treehouse Software’s tcVISION product moves or syncs mainframe data with real-time and bi-directional data replication. tcVISION’s GUI modeling and mapping, and ease of migrating data to Google Cloud, makes it an ideal choice for modernizing large mainframe environments.

“Through this exciting new collaboration with Google Cloud, Treehouse Software expands its mature and proven mainframe data delivery capabilities, and customers benefit from modernization of their data on one of the most popular and advanced Cloud platforms in the world”, said Joseph Brady, Director of Business Development and Cloud Alliance Lead at Treehouse Software.


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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.