AWS Services Provide Advanced Monitoring and Analytics of tcVISION’s Mainframe CDC Processing

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

Many Treehouse Software mainframe modernization customers have requirements for continuous near-real-time replication of mainframe data in order to keep a copy of the data synchronized on the Cloud. These customers are using tcVISION from Treehouse Software for changed data capture (CDC) for this synchronization, which allows changes occurring in any mainframe application data to be tracked and captured, and then published to a variety of AWS targets, including Amazon Simple Storage Service (S3). Some of these customers are also now asking us to recommend the best Cloud-based tools and methods to monitor and gain insights to these complex data processes. Coincidentally, while working with a current tcVISION customer, our technicians are testing out two particularly good, fully managed AWS services that can work hand-in-hand to address this need:

Amazon Athena

Since tcVISION supports Amazon S3 as a target, customers modernizing their mainframe systems on AWS can use Amazon Athena for monitoring and analysis of CDC processing from an S3 bucket.

Amazon Athena is a serverless, interactive analytics service built on open-source frameworks, supporting open-table and file formats. Athena provides a simplified, flexible way to analyze data from an S3 Bucket, as well as many other data sources, including on-premises data sources or other Cloud systems. Athena is built on open-source Trino and Presto engines and Apache Spark frameworks, with no provisioning or configuration effort required.

Figure 1: Example of an Athena query showing bulk-load statistics per table

Amazon QuickSight

Once Athena is setup for monitoring an S3 Bucket, users can easily view their CDC processing and analytics with Amazon QuickSight. QuickSight utilizes advanced machine learning-powered insights and intuitive dashboards, so end users can make the best and quickest data-driven business decisions.

Figure 2: Example of Amazon QuickSight monitoring the throughput of our data to Snowflake

Figure 3: Example of Amazon QuickSight pie chart showing the resulting rows loaded for each Snowflake table:

Figure 4: Example of Amazon QuickSight chart showing statistics for our data bulk-load into Snowflake:

Figure 5: Example of Amazon QuickSight chart showing our load time into Snowflake per table:

View the Amazon QuickSite video here…

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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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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.

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:

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.

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

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

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.

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

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.

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.

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.

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…

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.

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.

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.

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 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.

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:

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:

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

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.

Treehouse Software Customer Case Study: A State Government Agency’s Real-time Data Synchronization Between IBM Mainframe Adabas and AWS

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

Software AG’s Adabas is a mainframe database that is still heavily used by government sites throughout the U.S. and the world, and this blog focuses on a current Treehouse Software customer – a U.S. State Government Agency that uses Adabas on their mainframe system.

Business Issue

The Agency’s modernization team was looking for a Change Data Capture (CDC) technology solution that enables them to synchronize their mainframe Adabas data on AWS, particularly an Amazon RDS. As with most Treehouse customers, the State’s mainframe contains vital data that must always be highly available, so rather than attempting a complete migration from the mainframe, the modernization teams decided to implement a multi-year data replication plan. This allows the mainframe legacy teams to maintain existing critical applications, while the modernization team develops new applications on AWS.

After researching various technologies, the Agency discovered tcVISION on the AWS Parter Network Blog and contacted Treehouse Software to discuss their project and to see a demonstration of Mainframe-to-AWS data replication.

Addressing the Uniqueness of Adabas

Having specialized in tools and services complementary to Adabas/Natural applications since 1982, Treehouse Software has successfully encountered and addressed many unique scenarios within the Adabas environment. The Treehouse technical team documented three primary issues with Adabas/Natural that the Agency needed to consider when they began planning data replication on AWS:

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.

The tcVISION Technology Solution...

After technical discussions and a successful proof of concept (POC) that proved out a set of use cases, all teams at the Agency determined that tcVISION real-time mainframe data replication capabilities were the perfect fit for meeting their goals.

tcVISION‘s modeling and mapping facilities are utilized to 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).  Given that PREDICT is a “passive” data dictionary (there is no requirement that the logical and physical representations agree), it was necessary to scrutinize both to ensure that the source structures were accurately modeled.

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

The teams examined the three ways that 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 was decided to access the data by reading the active and archived PLOGs datasets. The schema, mappings, and transformations from the metadata import were tailored to the customer’s specific requirements.  It is also now possible to import an existing RDBMS schema and retrofit it, via drag-and-drop in tcVISION, to the source Adabas elements.

Additionally, the Agency’s teams are very pleased with tcVISION‘s minimal usage of mainframe resources. The product’s “staged processing” methodology accomplishes this, whereby the only processing occurring on the mainframe is the capture of changes from Adabas PLOGs. The bulk of the processing occurs on the AWS side, minimizing tcVISION’s footprint on the mainframe as seen in this diagram:

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 in Stages 1 – 3 in AWS.

Customer Outcome

All requirements were met by tcVISION, which led to a successful project implementation.

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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 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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Further reading:

Many more mainframe data migration and replication customer case studies can be read on the Treehouse Software Website.

What are the Benefits of Replicating Mainframe Data on Cloud or Hybrid Cloud Systems?

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

Enterprise customers with mainframe systems have begun their movement of data to the Cloud or hybrid Cloud (a mixed computing, storage, and services environment made up of on-premises infrastructure, private Cloud services, and public Cloud) to benefit from new and powerful technologies that deliver significant business benefits and competitive advantage. Compared to the number of mainframe shops that are in the planning stages of their Cloud projects, existing adopters’ numbers are still relatively small.

Today, it is easier than ever for customers to take advantage of cutting edge, Cloud-based technologies, changing the way they manage, deploy, and distribute mission-critical data currently residing on mainframe systems. During the planning phase of a Cloud or hybrid Cloud modernization strategy, some benefits that are quickly discovered include:

Trade Capital Expense for Variable Expense – Instead of having to invest heavily in data centers and servers before customers know how they are going to use them, they pay only when they consume computing resources, and pay only for how much they consume.

Global Deployments – Cloud platforms span many geographic regions globally. Enterprises can easily deploy applications in multiple regions around the world with just a few clicks. This means there can be lower latency and a better experience for customers at minimal cost.

Economies to Scale – By using Cloud computing, customers can achieve a lower variable cost than they can get on their own, because usage from hundreds of thousands of customers is aggregated in the Cloud. Providers such as AWS, Google Cloud, etc. can achieve higher economies of scale, which translates into lower pay as-you-go prices.

Scale of Services – Cloud-based products offer a broad set of global services including compute, storage, databases, analytics, machine learning and AI, networking, mobile, developer tools, management tools, IoT, security, and enterprise applications. These services help organizations move faster, lower IT costs, and scale.

World Class Security – All major Cloud platforms offer advanced and strict security that complies with the most stringent government and private sector requirements.

Extreme High Availability (HA) – Major Cloud platforms span many geographic regions around the world.  By designing services and applications to be redundant across regions, HA is enhanced far beyond a single on-premises data center.

Testing at Scale – Cloud servers and services can be created and charged on demand for a specific amount of time.  This allows customers to create temporary large-scale test environments prior to deployment that are not practical for on-premises environments.  Large scale testing reduces deployment risks and helps to provide a better customer experience.

Auto Scaling and Serverless Deployments – Major Cloud platforms have many serverless and autoscaling options available, allowing for scalable computing capacity as required.  Customers pay only for the compute time they consume – there is no charge when the code is not running. Another example is the ability for a Cloud database to automatically start up, shut down, and scale capacity up or down based on the application’s needs.

Customer Agility and Innovation – In a Cloud computing environment, new IT resources are only a click away, which means that customers reduce the time to make those resources available to developers from weeks to just minutes. This results in a dramatic increase in agility for the organization, since the cost and time it takes to experiment and develop is significantly lower.

Many companies who haven’t started their modernization journeys yet are looking for tools that allow their legacy mainframe environments to continue, while replicating data – in real time – on a variety of Cloud and open systems platforms. Treehouse Software is the worldwide distributor of tcVISION, a software tool that provides an easy and fast approach for Cloud and hybrid Cloud projects, enabling bi-directional data replication between the hardware source and many targets, including (mainframe): Db2 z/OS, Db2 z/VSE, Adabas, VSAM, IMS/DB, CA IDMS, CA DATACOM, etc. and (Cloud and open systems): AWS, Google Cloud, Microsoft Azure, Kafka, PostgreSQL, etc..

If your enterprise is planning on a Mainframe-to-Cloud data modernization project, we would welcome the opportunity to help get you moving immediately with an online demonstration of tcVISION. Contact Treehouse Software for a tcVISION demonstration today!

Video Demo: Mainframe Data Replication on AWS with tcVISION from Treehouse Software

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

Whether your enterprise wants to take advantage of the latest AWS services, such as analytics, artificial intelligence (AI) and machine learning, scalable storage, security, high availability, etc., or move your data to a variety of newer databases, the transition doesn’t have to occur immediately. tcVISION allows 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 the mainframe source database). The customer can then modernize their application on AWS without disrupting the existing critical work on the legacy system. 

tcVISION on AWS architecture overview:

tcVISION’s Control Board is a Windows Graphical User Interface (GUI) that allows users to configure the replication stream between the IBM mainframe and AWS. Using the Control Board and built-in wizards, users can define the metadata and mappings between the mainframe and AWS database target.

The following video shows the steps required to create the tcVISION metadata and scripts for replicating mainframe Db2 z/OS data to AWS PostgreSQL:

Where do you want to go?

With Treehouse Software’s tcVISION, mainframe data can be replicated between IBM Db2 z/OS, Db2 z/VSE, Adabas, VSAM, IMS/DB, CA IDMS, CA DATACOM, or sequential files, and many Cloud and Open Systems targets.

tcVISION is an innovative technology that 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 on-premise and Cloud-based. A complete list of tcVISION supported environments for data replication can be seen here.

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Further Reading…

Treehouse Software is an AWS Technology Partner, and the AWS Partner Network published a blog about tcVISION, which shows a screen walk-through of tcVISION data replication from Db2 z/OS to Amazon Aurora:

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

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Moving the right data, to the right place, at the right time. Start your 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.

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.

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.