Treehouse Software – 40 Years and Still Moving Forward (Part 1)

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

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Introduction

Many readers know that Treehouse Software has been around since 1983, serving enterprises worldwide with industry-leading software products and outstanding technical support. However, this blog series will dig a little deeper into Treehouse Software’s origins and explore how founder and president, George Szakach blazed a trail from being a systems programmer in the early 60s, to creating and growing his own software company from the early 80s up to the present.

The beginnings… 1960’s.  Moon Landing, Flower Power, the Righteous Brothers, and Punched Cards

George is a Vietnam-era veteran and started working with mainframes in 1960 while in the Army. 

After programming school in Fort Monmouth, NJ, George was assigned to Fort Huachuca, Arizona where he wrote army related applications on the IBM 709.

Before leaving the army in 1963, George had many job offers.  Three years of programming experience was unheard-of back then, so his skillset was very valuable.  He was even offered a job by the president of Informatics, working in Houston at the NASA Johnson Space Center to “put a man on the moon.”  He declined.

Throughout the rest of the 60s, George worked at Burroughs, Univac, and Leasco. During the 70s through 1982, George worked for Ocean Data Systems, Data General, Optical Recognition Systems, Software AG (his longest stint – 7 years), and Superior Oil.

Punched card…

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IBM 709 Computer System…

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George’s archeological finds from his time at Univac…

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With all of this foundational mainframe experience combined with his skills honed at Software AG, the seeds were planted for George’s future: take those roots, move to the trees, and build a house… 

Coming soon… Part 2: Treehouse Software’s first generations.    


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About Treehouse Software

Since 1983, Treehouse Software has been serving enterprises worldwide with industry-leading mainframe software products and outstanding technical support. Today, Treehouse Software is a global leader in providing data replication, and integration solutions for the most complex and demanding heterogeneous environments, as well as feature-rich, accelerated-ROI offerings for information delivery, and application modernization.

Contact Treehouse Software

Treehouse Software Salutes Franco Harris

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

With the recent passing of Pittsburgh Steelers great running back and Pro Football Hall of Famer, Franco Harris, we would like to revisit April of 1993, when Treehouse Software held an international consultant’s symposium. The symposium brought together attendees and speakers from many consulting and technology companies, and schools from around the world. Since Treehouse Software is located in the greater Pittsburgh area, company president George Szakach was acquainted with Franco and invited him to deliver a fascinating and entertaining address, where he spoke about his career, several business ventures he was pursuing, as well as his budding interest in computer technology.

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Franco Harris at Treehouse Software’s Consultant’s Symposium (April 1993)

A few years ago, George reminded Franco about his visit to Treehouse back in 1993. He remembered and they shared some laughs and memories. 

We would also like to mention Franco’s well-known sense of community and accessibility in Pittsburgh. Many staff members have met Franco over the years and have fond memories of his friendliness and willingness to spend time engaging in conversations. Those who come in to the Pittsburgh International airpot can see a sculpture depicting Franco’s famous “Immaculate Reception” from 1972.  Thousands of people, especially recently, have selfies taken with the sculpture. Franco will be missed by his many friends and the community.

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Franco Harris sculpture at Pittsburgh International Airport.


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About Treehouse Software

Since 1982, Treehouse Software has been serving enterprises worldwide with industry-leading mainframe software products and outstanding technical support. Today, Treehouse Software is a global leader in providing data replication, and integration solutions for the most complex and demanding heterogeneous environments, as well as feature-rich, accelerated-ROI offerings for information delivery, and application modernization.

Contact Treehouse Software

5-Minute Video: Connecting a Mainframe IDMS Database to an AWS SQL Server Database with tcVISION

Treehouse Software is the worldwide distributor of tcVISION, the leading tool for using changed data capture (CDC) when transferring information between most mainframe data sources (IBM Db2, IBM VSAM, IBM IMS/DB, Software AG Adabas, CA IDMS, CA Datacom, or even sequential files) and Cloud and open systems-based databases and applications.

The following video takes a quick look at how tcVISION’s repository is used to import mainframe IDMS schema and builds out a target system on AWS:


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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.

7-Minute Video: Manage All of Your Mainframe-to-Cloud Data Replication Tasks from tcVISION’s Control Board

Treehouse Software is the worldwide distributor of tcVISION, the leading tool for using changed data capture (CDC) when transferring information between most mainframe data sources (IBM Db2, IBM VSAM, IBM IMS/DB, Software AG Adabas, CA IDMS, CA Datacom, or even sequential files) and Cloud and open systems-based databases and applications.

The following video briefly takes a look at how the tcVISION Control Board (a Windows-based GUI interface) functions as a central point of administration, data mapping and modeling, script generation, and overall monitoring. In this example, we show how to manage connectivity and data replication between a Mainframe database and AWS PostgreSQL using the tcVISION Control Board:


Further reading: tcVISION is featured on the AWS Partner Network Blog showing a walk-through of data replication between Mainframe and Amazon Aurora…

AWS Partner Network (APN) Blog: Real-Time Mainframe Data Replication to AWS with tcVISION from Treehouse Software.


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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.

tcVISION Video Demonstrations: Real-time Mainframe Data Replication on Three Popular Cloud SQL Databases

Treehouse Software is the worldwide distributor of tcVISION, the leading tool for using changed data capture (CDC) when transferring information between most mainframe data sources (IBM Db2, IBM VSAM, IBM IMS/DB, Software AG Adabas, CA IDMS, CA Datacom, or even sequential files) 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.

This video demonstrates real-time data replication between Db2 and PostgreSQL on AWS:

This video demonstrates real-time data replication between Db2 and Google Cloud SQL:

This video demonstrates real-time data replication between Db2 and Azure SQL:


Further reading: tcVISION is featured on the AWS Partner Network Blog showing a walk-through of data replication between Mainframe DB2 z/OS and Amazon Aurora…

AWS Partner Network (APN) Blog: Real-Time Mainframe Data Replication to AWS with tcVISION from Treehouse Software.


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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.

Replicating Enterprise Mainframe Data to Cloud-based SQL Databases with tcVISION

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

Treehouse Software has been helping enterprise mainframe customers since 1982, and in recent years, we have been developing a strong presence in the Mainframe-to-Cloud data replication market space. This blog takes a quick look at three of the most popular Treehouse-supported Cloud-based SQL database services…

Amazon RDS, a collection of managed services that makes it simple to set up, operate, and scale databases in the Cloud. Users can control the type of database, as well as where data is stored. Specific database formats that are supported include Amazon Aurora, PostgreSQL, MySQL, MariaDB, Oracle Database, and SQL Server:

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

Microsoft Azure SQL, a part of the Azure SQL family, Azure SQL Database is an always-up-to-date, fully managed relational database service built for the Cloud:


Wherever you want to target your mainframe data on the Cloud, Treehouse Software helps to make the process easy…

Treehouse Software is the worldwide distributor of tcVISION, the leading tool for using changed data capture (CDC) when transferring information between most mainframe data sources (IBM Db2, IBM VSAM, IBM IMS/DB, Software AG Adabas, CA IDMS, CA Datacom, or even sequential files) 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.

tcVISION_Overall_Diagram_Cloud_OS

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.

Sales and technical leaders at the major Cloud platform companies, as well as systems integrators are engaging with Treehouse Software to take advantage of our tcVISION data replication solution to help them tap into the mainframe data that customers want to be made available on new technologies.


Further reading: tcVISION is featured on the AWS Partner Network Blog showing a walk-through of data replication between Mainframe DB2 z/OS and Amazon Aurora…

AWS Partner Network (APN) Blog: Real-Time Mainframe Data Replication to AWS with tcVISION from Treehouse Software.


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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.

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.


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.

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:

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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:

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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.

Mainframe-to-Cloud Data Replication with tcVISION: Recommendations for Roadmapping Your Deployment on a Cloud Environment

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

Mainframe_To_Cloud_Roadmap

Careful planning must occur for a Mainframe-to-Cloud data modernization project, including how a customer’s desired Cloud environment will look. This blog serves as a general guide for organizations planning to replicate their mainframe data on Cloud platforms using Treehouse Software‘s tcVISION.

A successful move to the Cloud requires a number of post-migration considerations and solutions in order to modernize an application on the Cloud.  Some examples of these considerations and solutions include: 

Personnel Resource Considerations

Staffing for Mainframe-to-Cloud data replication projects depends on the scale and requirements of your replication project (e.g., bi-directional data replication projects will require more staffing).  

Most customers deploy a data replication product with Windows and Linux knowledgeable staff at varying levels of seniority.  For the architecture and setup tasks, we recommend senior technical staff to deal with complex requirements around the mainframe, Cloud architecture, networking, security, complex data requirements, and high availability.  Less senior staff are effective for the more repeatable deployment tasks such as mapping new database/file deployments.  Business staff and system staff are rarely required but can be necessary for more complex deployment tasks.  For example, bi-directional replication requires matching keys on both platforms and their input might be required.  Other activities would be PII consideration, specifics of data transformation and data verification requirements.

An example of staffing for a very large deployment might be one very part-time project manager, a part-time mainframe DBA/systems programmer, 1-2 staff to setup and deployment the environment and an additional 1-2 staff to manage the existing replication processes.

Environment Considerations

As part of the architecture planning, your team needs to decide how many tiers of deployment are needed for your replication project.  Much like with applications, you may want a Dev, QA, and Prod tier.  For each of these tiers, you will need to decide the level of separation.  For example, you might combine Dev and QA, but not Prod.  Many customers will keep production as a distinct environment.  Each environment will have its own set of resources, including mainframe managers (possibly on separate LPARs), Could VMs (e.g., EC2) for replication processing, and for managed Cloud RDBMSs (such as AWS RDS).  

After the required QA testing, changes are deployed to the production environment.  Object promotion test procedures should be detailed and documented, allowing for less experience personnel to work in some testing tasks.  Adherence to details, processes, and extended testing is most import when deploying bi-directional replication, due to the high impact of errors and difficult remediation.

Rollout Planning

A data replication product is typically deployed using Agile methods with sprints.  This allows for incrementally realized business value.  The first phase is typically a planning/architecture phase during which the technical architecture and deployment process are defined.   Files for replication are deployed in groups during sprint planning.  Initial sprint deployments might be low value file replications to shield the business from any interruptions due to process issues.  Once the team is satisfied that the process is effective, replication is working correctly, and data is verified on the source and targets, wide scale deployments can start.  The number of files to deploy in a sprint will depend on the customer’s requirements.  An example would be to deploy 20 mainframe files per 2–3-week sprint.  Technical personnel and business users need to work together to determine which files and deployment order will have the greatest business benefit.

Security

For security, both on-premises and to the major Cloud environments, there are several considerations:

  • Data will be replicated between a source and target. The data security for PII data must be considered.  In addition, rules such as HIPPA, FIPS, etc. will govern specific security requirements.
  • The path of the data must be considered, whether it is a private path, or if the data transverses the internet. For example, when going from on-premises to the Cloud the major Cloud providers have a VPN option which encrypts data going over the internet.  More secure options are also available, such as AWS Direct Connect and Azure ExpressRoute.  With these options, the on-premises network is connected directly to the Cloud provider edge location via a telecom provider, and the data goes over a private route rather than the internet.
  • Additionally, Cloud services such as S3, Azure Blob Storage, and GCP buckets default to route service connections over the internet. Creating a private end point (e.g., AWS PrivateLink) allows for a private network connection within the Cloud provider’s network.  Private connections that do not traverse the Internet provide better security and privacy.
  • Protecting data at rest is important for both the source and target environments. The modern Z/OS mainframe has advanced pervasive and encryption capabilities: https://www.redbooks.ibm.com/redbooks/pdfs/sg248410.pdf.  The major Cloud providers all provide extensive at-rest encryption capabilities.  Turning on encryption for Cloud Storage and databases is often just a parameter setting and the Cloud provider takes care of the encryption, keys, and certificates automatically.    
  • Protecting data in transit is equally important. There are often multiple transit points to encrypt and protect.  First, is the transit from the mainframe to on-premises to the Cloud VM instance.  A mainframe data replication product should provide protection employing TLS 1.2 to utilize keys and certificates on both the mainframe and Cloud.  Second is from the Cloud VM to the Cloud target database or service.  Encryption may be less important since often these services are in a private environment.  However, encryption can be achieved as required.

High Availability

  • During CDC processing, high availability must be maintained in the Cloud environment. The data replication product should keep track of processing position.  The first can be a Restart file, which keeps track of mainframe log position, target processing position, and uncommitted transactions.  The second can be a container stored on Linux or Windows to store committed unprocessed transactions.  Both need to be on highly available storage with a preference for storage across Availability Zones (AZs), such as Elastic File System (Amazon EFS) or Windows File Server (FSx).
  • The Amazon EC2 instance (or other Cloud instance) can be part of an Auto Scaling Group spread across AZs with minimum and maximum of one Amazon EC2 instance.
  • Upon failure, the replacement Amazon EC2 instance of the replication product’s administrator function is launched and communicates its IP address to the product’s mainframe administrator function. The mainframe then starts communication with the replacement Amazon EC2 instance.
  • Once the Amazon EC2 instance is restarted, it continues processing at the next logical restart point, using a combination of the LUW and Restart files.
  • For production workloads, Treehouse Software recommends turning on Multi-AZ target and metadata databases.

Scalable Storage

  • With scalable storage provided on most Cloud platforms, the customer pays only for what is used. The data replication product should require file-based storage for its files that can grow in size if target processing stops for an unexpected reason.  For example, Amazon EFS, and Amazon FSx provide a serverless elastic file system that lets the customer share file data without provisioning or managing storage.

Analytics

  • All top Cloud platform providers give customers the broadest and deepest portfolio of purpose-built analytics services optimized for all unique analytics use cases. Cloud analytics services allow customers to analyze data on demand, and helps streamline the business intelligence process of gathering, integrating, analyzing, and presenting insights to enhance business decision making.
  • A data replication product should replicate data to several data sources that can easily be captured by various Cloud based analytics services. For example, mainframe database data can be replicated to the various Cloud ‘buckets’ in JSON, CSV, or AVRO format, which allows for consumption by the various Cloud analytic services.  Bucket types include AWS S3, Azure BLOB Data, Azure Data Lake Storage, and GCP Cloud storage.  Several other Cloud analytics type services also support targets including Kafka, Elasticsearch, HADOOP, and AWS Kinesis.
  • Kafka has become a common target and can serve as a central data repository. Most customers target Kafka using JSON formatted replicated mainframe data.  Kafka can be installed on-premises, or using a managed Kafka service, such as the Confluent Cloud, AWS Managed Kafka, or the Azure Event Hub.

Monitoring

  • Monitoring is a critical part of any data replication process. There are several levels of monitoring at various points in a data replication project.  For example, each node of the replication including the mainframe, network communication, Cloud VM instances (such as EC2) and the target Cloud database service all can require a level of monitoring.  The monitoring process will also be different in development or QA vs. a full production deployment.
  • A data replication product should also have its own monitoring features. One important area to measure is performance and it is important to determine where any performance bottleneck is located.  Sometimes it could be the mainframe process, the network, the transformation computation process, or the target database.  A performance monitor helps to detect where the bottleneck is occurring and then the customer can drill down into specifics.  For example, if the bottleneck is the input data, areas to examine are the mainframe replication product component performance, or the network connection.  The next step is to monitor the area where the bottleneck is occurring using the data replication product’s statistics, mainframe monitoring tools, or Cloud monitoring such as AWS CloudWatch.
  • A data replication product should also allow the customer to monitor processing functions during the replication process. The data replication product should also have extensive logs and traces that allow for detailed monitoring of the data replication process and produce detailed replication statistics that include a numeric breakdown of processing statistics by table, type of operation (insert, update delete), and where these operations occurred (mainframe, or target database). 
  • CloudWatch collects monitoring and operational data in the form of logs, metrics, and events, providing customers with a unified view of AWS resources, applications, and services that run on AWS, and on-premises servers. You can use CloudWatch to set high resolution alarms, visualize logs and metrics side by side, take automated actions, troubleshoot issues, discover insights to optimize your applications, and ensure they are running smoothly.
  • Some customers are satisfied with a basic monitoring that polls every five minutes, while others need more detailed monitoring and can choose polls that occur every minute.
  • CloudWatch allows customers to record metrics for EC2 and other Amazon Cloud Services and display them in a graph on a monitoring dashboard. This provides visual notifications of what is going on, such as CPU per server, query time, number of transactions, and network usage.
  • Given the dynamic nature of AWS resources, proactive measures including the dynamic re-sizing of infrastructure resources can be automatically initiated. Amazon CloudWatch alarms can be sent to the customer, such as a warning that CPU usage is too high, and as a result, an auto scale trigger can be set up to launch another EC2 instance to address the load. Additionally, customers can set alarms to recover, reboot, or shut down EC2 instances if something out of the ordinary happens.

Disaster Recovery

  • IT disasters such as data center failures, or cyber attacks can not only disrupt business, but also cause data loss, and impact revenue. Most Cloud platforms offer disaster recovery solutions that minimize downtime and data loss by providing extremely fast recovery of physical, virtual, and Cloud-based servers.
  • A disaster recovery solution must continuously replicate machines (including operating system, system state configuration, databases, applications, and files) into a low-cost staging area in a target Cloud account and preferred region.
  • Unlike snapshot-based solutions that update target locations at distinct, infrequent intervals, a Cloud based disaster recovery solution should provide continuous and asynchronous replication.
  • Consult with your Cloud platform provider to make sure you are adhering to their respective best practices.
  • Example: https://docs.aws.amazon.com/whitepapers/latest/disaster-recovery-workloads-on-aws/introduction.html

Artificial Intelligence and Machine Learning

  • Many organizations lack the internal resources to support AI and machine learning initiatives, but fortunately the leading Cloud platforms offer broad sets of machine learning services that put machine learning in the hands of every developer and data scientist. For example, AWS offers SageMaker, GCP has AI Platform, and Microsoft Azure provides Azure AI.
  • Applications that are good candidates for AI or ML are those that need to determine and assign meaning to patterns (e.g., systems used in factories that govern product quality using image recognition and automation, or fraud detection programs in financial organizations that examine transaction data and patterns).

The list goes on…

  • Treehouse Software and our Cloud platform and migration partners can advise and assist customers in designing their roadmaps into the future, taking advantage of the most advanced technologies in the world.
  • Successful customer goals are top priority for all of us, and we can continue to work with our customers on a consulting basis even after they are in production.

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

Your Mainframe-to-Cloud Data Migration Partner…

Treehouse Software is a global technology company and Technology Partner with AWS, Google Cloud, and Microsoft. The company assists organizations with migrating critical workloads of mainframe data to the Cloud.

Further reading on tcVISION from AWS, Google Cloud, and Confluent:

More About tcVISION from Treehouse Software…

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

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


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Contact Treehouse Software for a tcVISION Demo Today…

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