Does your data science team want to accelerate insights and bring advanced ML/AI capabilities to your mainframe data with Amazon Redshift? Sure they do—and Treehouse Software enables that…

by Joseph Brady, Director of Business Development at Treehouse Software, Inc. and Dan Vimont, Director of Innovation at Treehouse Software, Inc.

We are beginning to see a pleasant and welcomed trend with Treehouse customers who are looking to modernize their valuable mainframe legacy data on the Cloud—they are including their data science teams in the important planning phase of architecting new Cloud environments and targets. This is especially vital for customers who want to incorporate advanced analytics and ML/AI in their strategic data usage plans on the Cloud. Who can contribute better understandings of ultimate data usage than your resident data scientists?

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We have heard from many of these data scientists that a primary item on their “wish lists” is for a fully managed, AI powered, massively parallel processing (MPP) architecture to extract maximum value and insights. They specifically mention Amazon Redshift as the Cloud data warehouse (which is much more than a data warehouse) of choice for driving digitization across the enterprise, as well as help personalizing customer experiences. Redshift uses SQL to analyze structured and semi-structured data across data warehouses, operational databases, and data lakes, using AWS-designed hardware and ML to deliver the highest performance at any scale. To this desire/question, we can answer with a resounding, “Yes, Treehouse Software has got you covered with Redshift connectivity!”.

The Treehouse Software solution…

Enterprise customers have come to Treehouse Software, because we bring not only proven mainframe data replication tools, but deep subject matter expertise in mainframe technologies, as well as the know-how to target relevant AWS offerings, such as Redshift, S3 (including S3 Express One Zone – see our recent blog on S3 Express One Zone), etc.

The Rocket Data Replicate and Sync (RDRS) solution allows customers’ legacy mainframe environment to operate normally while replicating data on AWS. The technology focuses on changed data capture (CDC) when transferring information between mainframe data sources and Cloud-based databases and applications. Through an innovative set of technologies, changes occurring in any mainframe datastore are tracked and captured, and ultimately published to Redshift.

____0_Mainframe_To_RedshiftHow does it work?

  1. We start at the source – the mainframe – where an agent (with a very small footprint) extracts data (in the context of either bulk-load or CDC processing).
  2. The raw data is securely passed from the mainframe to RDRS, which speedily transforms mainframe-formatted data into Unicode/JSON and publishes the results to a Kafka topic.
  3. Our efficient, autoscaling microservices take it from there. Treehouse Dataflow Toolkit functions consume the data from Kafka and land it in S3 buckets, where Treehouse’s proprietary crawler technology is used to automatically prepare landing tables, views, and additional infrastructure in Redshift.  Thenthe mainframe data is loaded into Redshift (all the while adhering to AWS’ recommended “best practices” for massive data loading, thus assuring shortest and surest loads).  The inherent reliability and scalability of the entire pipeline infrastructure assure near-real-time synchronization between mainframe sources and Redshift target tables.

Redshift tables and views: something for everybody

Within this framework, the Redshift staging tables (often referred to as “delta tables”) are constantly accruing historical data, ideally suited for data scientists looking to do trend analysis, predictive analytics, ML, and AI work.  For business analysts and others who prefer structured data representations of potentially complex hierarchical data, the Treehouse framework also automatically provides structured user-views, providing the look and feel of a SQL database.

…as innovations move faster along the timeline, keep your options open!

Publishing both bulk-load and CDC data to a reliable and scalable framework like Kafka allows you to maintain a broad array of options to ultimately feed your legacy data to any number of JSON-friendly ETL tools, target datastores, and data analytics packages (some of which may not even have been invented yet!).  In addition to Redshift, the Treehouse Dataflow Toolkit also currently targets Snowflake, Amazon DynamoDB, and Amazon Athena/S3.

Video – Introduction to Data Warehousing on AWS with Amazon Redshift…


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Contact Treehouse Software today to discuss your project, or to schedule a demo of our Mainframe-to-AWS real-time and bi-directional data replication solution. 

Treehouse Software helps mainframe customers quickly take advantage of Amazon Redshift via Kafka and S3

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

Treehouse Software’s customer base of enterprises using mainframes for storing mission-critical data are asking for ways to take advantage of the most advanced Cloud-based data warehouses. Recently, one of our customers sent us an inquiry asking about how tcVISION can be used to move some of their data to Amazon Redshift, the fully-managed data warehouse from AWS, for reporting and analytics using their existing Business Intelligence (BI) tools. They also expressed concerned about scalability of the data warehouse, since they may increase their data movement quite quickly in the near future.

Fortunately, one of our Cloud experts has been testing out the fastest and cleanest ways to use tcVISION to pump z/OS mainframe data into Amazon Redshift.  His testing proved that tcVISION fully supports an AWS best practices framework of: Amazon MSK(Kafka)-to-Amazon S3-to-Amazon Redshift. To achieve this within the framework, tcVISION is used to convert mainframe-based data (Adabas, VSAM, Db2, etc.) to JSON format and publish it to Kafka topics (Amazon MSK), then ultimately to Amazon Redshift as seen here…

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About Amazon Redshift… 


Your journey to Amazon Redshift begins today with Treehouse Software and tcVISION…

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Treehouse Software is an AWS Technology Partner and tcVISION is a Validated AWS Qualified Software that helps customers replicate their mainframe data between a vast array of source databases and Cloud technologies, including Amazon S3, Amazon MSK (Kafka), Amazon RDS, Amazon Redshift, DynamoDB, and many more. 

tcVISION focuses on changed data capture (CDC) when transferring information between mainframe data sources AWS. Through an innovative technology, changes occurring in any mainframe application data are tracked and captured, and then published to AWS-based data stores. From there, the door is open for the enterprise to take advantage of the latest and most popular AWS AI and ML resources.

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


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Further reading: tcVISION is featured on the AWS Partner Network Blog…

The AWS Partner blog talks about tcVISION’s Mainframe-to-AWS data replication capabilities, including a technical overview, security, high availability, scalability, and a step-by-step example of the creation of tcVISION metadata and scripts for replicating mainframe data on AWS. Read the blog here: AWS Partner Network (APN) Blog: Real-Time Mainframe Data Replication to AWS with tcVISION from Treehouse Software.

AI is “IN” and Treehouse Software can help mainframe customers who want to add advanced intelligence to their enterprise data on AWS

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

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Artificial Intelligence (AI) and Machine Learning (ML) are not only revolutionizing the computing and business worlds in general, but the value proposition for Treehouse Software’s customer base who are replicating large amounts of mainframe data on AWS can be profound. AI/ML is proving to be a powerful force in improving customer experience, optimizing business operations, and accelerating innovation. For example, this powerful and predictive technology can help improve customer engagement and conversion by creating personalized web experiences that are based on data that shows individual preferences and behaviors. Additionally, business forecasting AI and ML tools can accurately predict demand and manage, optimize, and augment supply chain decisions by combining historical time series data with additional variables, such as new product features, pricing, holiday demand, etc.

AWS makes AI and ML technologies available at your fingertips… 

AWS is making incredible leaps in creating the most sophisticated AI tools available today — all literally at one’s fingertips. Never before has such powerful and useful technology been so easily available to so many, bringing the deepest set of ML services and supporting Cloud infrastructures instantly into the hands of developers and data scientists.

We are hearing first-hand how customers want to improve customer experience, optimize business processes, and accelerate innovation. For these purposes, businesses can use ready-made, purpose-built AI services, or customized models with AWS AI and ML offerings.


Examples of leading AI product available on AWS:


Your journey to AWS begins today with Treehouse Software and tcVISION…

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Treehouse Software is an AWS Technology Partner and tcVISION is a Validated AWS Qualified Software that helps customers replicate their mainframe data between a vast array of source databases and Cloud technologies, including Amazon S3, Amazon MSK (Kafka), Amazon RDS, Amazon Redshift, DynamoDB, and many more. 

tcVISION focuses on changed data capture (CDC) when transferring information between mainframe data sources AWS. Through an innovative technology, changes occurring in any mainframe application data are tracked and captured, and then published to AWS-based data stores. From there, the door is open for the enterprise to take advantage of the latest and most popular AWS AI and ML resources.

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


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Further reading: tcVISION is featured on the AWS Partner Network Blog…

The AWS Partner blog talks about tcVISION’s Mainframe-to-AWS data replication capabilities, including a technical overview, security, high availability, scalability, and a step-by-step example of the creation of tcVISION metadata and scripts for replicating mainframe data on AWS. Read the blog here: AWS Partner Network (APN) Blog: Real-Time Mainframe Data Replication to AWS with tcVISION from Treehouse Software.

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.

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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

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Amazon QuickSight

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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

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

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

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

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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.


Treehouse Software Customer Success: BMF uses tcVISION for Real-Time Data Replication Between Mainframe Adabas and PostgreSQL

BMF_Building

The Bundesministerium der Finanzen (BMF) is Germany’s Ministry of Finance and establishes sustainable fiscal policy that ensures financial empowerment of the federal budget. From tax policy via development of federal budget, to regulation of national and international financial markets – for these and other fiscal and economic questions of principle, the BMF creates strategies and concepts, and implements them. The Federal Tax Administration is part of BMF, and controls not only the cross-border goods traffic, but acts against illegal employment and other crimes. The tax administration also imposes consumer taxes (e.g., energy and tobacco tax, car tax, etc.). Financial relations between federation, countries, and communities are also coordinated by BMF.

Department II (federal budget) is part of the German government in charge of establishing the budget and financial planning of the federation. Throughout the year, it monitors execution of the budget for eventual intervention (e.g., with a budget freeze, or supplementary budget). After closing the fiscal year, the budget and balance sheet will be presented. The budget is a supplement of the budget act, legally binding.

The central service organization of BMF is the Informationstechnikzentrum Bund – ITZBund (Information technic center).

BUSINESS BACKGROUND

Drawing up the budget is a yearly, highly time consuming, and formalized business process. All departments are involved in nearly every sub-process, and budgeting and financial planning is supported by the application, “Haushaltsaufstellung / Budgetgeneration”. Using the generated reports, various addressees/receivers are supported (e.g., German Federal Government, German Federal Parliament, Federal Council of Germany, finance department in BMF, the employees in the departments, and the public).

Technically, the budget plan of the federation is based on technologies, including the IBM Mainframe with z/OS running Adabas and Natural.

The challenge was to provide an environment for employees in all departments that enables them to do their work quickly, easily, and efficiently. In the BMF, users must have an editorless, end-user driven, and real-time creation of ready-to-print products. An informative description of the workflow is shown on the website of the BMF.

The federal budget is available as download, or one can directly navigate through the data using the online application.

BUSINESS ISSUE

Some time ago, BMF decided to re-engineer the application for budget planning and port it to Open Source. To guarantee a seamless transition, the first step is propagation of data out of Adabas on z/OS to PostgreSQL, concluding with permanent synchronization.

The difficulties of this task are the complexities of setting up data definitions for the data structures in Natural and the propagation of data from Adabas on z/OS to PostgreSQL.

TECHNOLOGY SOLUTION: tcVISION

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After an analysis of the project, Treehouse Software proposed creating an extension to tcVISION’s change data capture (CDC) functionality for integration, so that tcVISION could enable BMF to continue using the implemented data definitions in a format suitable for the RDBMS.

The extension was developed within a few days, and a two-day on premise test demonstrated the solution fit the requirements of BMF.

BMF can now provide its data definitions from Natural LDA to the extension of tcVISION, and after the transformation, onto the PostgreSQL load process for processing. Another advantage of the tcVISION solution is that when needed, other targets can be integrated for propagation of data from the mainframe (e.g., Kafka, which BMF indicated is a future target environment).

Additionally, bi-directional propagation can be added in budget planning when BMF is ready.

Data structures are held in LDA, because this provides the advantages of higher flexibility in development and the adaption of new requirements to the data definitions. If definitions would have to be ported manually, in part, to PostgreSQL, it would have been a much bigger and error-prone effort.

Subsequent changes to Adabas structures can now use tcVISION’s newly developed extension to easily regenerate and load the correct definitions to the RDBMS, and tcVISION completely covers the customer’s requirements for special usage of *PEs and *MUs.

After thorough preparation and extensive testing, the solution was released to selected users first, then made available to all users.

* PEs and MUs are special Adabas formats for definition of tables. PE = Periodic Group, MU = Multiple Value Field.


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Contact Treehouse Software for a Demo Today…

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

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


Further reading: Treehouse Software Customer Success – ETS: tcVISION for Real-Time Synchronization Between Mainframe IDMS and AWS RDS for PostgreSQL

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

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

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

The Core Components:  Primary Instance & Failover Instance

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

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Use a Step Function to Automate the Failover Process

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

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

HA2

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

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

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Many More Details are Available Upon Request to Treehouse Customers

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

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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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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.

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

Just what is CDC anyway?

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

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

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

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

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

tcVISION_Db2_To_AWS_CDC

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

Bulk Transfer

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

Log Processing

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

Batch Compare

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

DBMS Extension

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

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

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


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Download the AWS and Treehouse Software Mainframe Data Replication Solution Brief

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

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


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Contact Treehouse Software for a tcVISION Demo Today…

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

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

Let’s Go Shopping – Treehouse Software’s Grocery List for Customers Who are Planning Mainframe Data Replication on AWS

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

When we begin working with customers who have chosen Treehouse Software’s tcVISION mainframe data replication tool to synch data on AWS, many are just beginning to explore AWS. Some customers haven’t even chosen their desired target database(s) or service(s) yet. This blog focuses on helping customers identify the most popular tools and services needed when planning a Mainframe-to-AWS data replication project.

tcVISION‘s data replication connectivity to AWS puts some of the world’s most advanced technologies at customers’ fingertips. On the Mainframe side, the customers’ familiar on-premises environment with their mission critical data resides on various databases, such as IBM Db2, IBM VSAM, IBM IMS/DB, Software AG Adabas, CA IDMS, CA Datacom, or flat files. On the AWS side, there are over 200 fully featured Cloud-based products, including compute, storage, databases, analytics, networking, mobile, developer tools, management tools, IoT, security, and enterprise applications.  How can customers choose what’s right for them?

It’s like a big, virtual grocery store…

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As we all know, in a grocery store there are many items that appear to do the same thing, but closer inspection shows that certain products can meet specific needs. Here is a list of some of the most popular AWS products and services that we have seen our customers explore and implement for their mainframe data modernization projects:

Amazon EC2Amazon EC2’s simple web service interface allows you to obtain and configure capacity with minimal friction. It provides you with complete control of your computing resources and lets you run on Amazon’s proven computing environment. Amazon EC2 reduces the time required to obtain and boot new server instances to minutes, allowing you to quickly scale capacity, both up and down, as your computing requirements change. Amazon EC2 changes the economics of computing by allowing you to pay only for capacity that you actually use. Amazon EC2 provides developers the tools to build failure resilient applications and isolate them from common failure scenarios.

Amazon RDSAmazon Relational Database Service (Amazon RDS) makes it easy to set up, operate, and scale a relational database in the Cloud. It provides cost-efficient and resizable capacity while automating time-consuming administration tasks such as hardware provisioning, database setup, patching, and backups. It frees you to focus on your applications so you can give them the fast performance, high availability, security and compatibility they need. Amazon RDS is available on several database instance types – optimized for memory, performance or I/O – and provides you with six familiar database engines from which to choose, including Amazon AuroraPostgreSQLMySQLMariaDBOracle Database, and SQL Server.

Amazon S3 – Amazon Simple Storage Service (Amazon S3) is an object storage service that offers industry-leading scalability, data availability, security, and performance. This means customers of all sizes and industries can use it to store and protect any amount of data for a range of use cases, such as websites, mobile applications, backup and restore, archive, enterprise applications, IoT devices, and big data analytics.

Amazon S3 Bucket – An Amazon S3 Bucket is a resource that the user creates in an Amazon region, in which to upload data (photos, videos, documents, etc.).

Amazon CloudWatchAmazon CloudWatch is a powerful Cloud infrastructure monitoring service that gives developers, system operators, site reliability engineers (SRE), and IT managers actionable insights to monitor applications, understand and respond to system-wide performance changes, optimize resource utilization, and obtain a unified view of operational health. 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.

AWS Direct ConnectAWS Direct Connect is a Cloud service solution that makes it easy to establish a dedicated, secure network connection from your on-premises computing environment to AWS. While in transit, your network traffic remains on the AWS global network and never touches the public internet.

Amazon KinesisAmazon Kinesis makes it easy to collect, process, and analyze real-time, streaming data so you can get timely insights and react quickly to new information. Amazon Kinesis offers key capabilities to cost-effectively process streaming data at any scale, along with the flexibility to choose the tools that best suit the requirements of your application. With Amazon Kinesis, you can ingest real-time data such as video, audio, application logs, website clickstreams, and IoT telemetry data for machine learning, analytics, and other applications. Amazon Kinesis enables you to process and analyze data as it arrives and respond instantly instead of having to wait until all your data is collected before the processing can begin.

AWS LambdaAWS Lambda is an event-driven, “serverless” computing platform provided by Amazon as a part of the Amazon Web Services. It is a computing service that runs code in response to events and automatically manages the computing resources required by that code.

AWS Machine LearningAWS Machine Learning Services offer the broadest and deepest set of machine learning services and supporting Cloud infrastructure, putting machine learning in the hands of every developer, data scientist and expert practitioner.

Amazon RedshiftAmazon Redshift is a popular and fastest growing Cloud data warehouse allowing customers to run and scale analytics in seconds on all of their data without having to manage a data warehouse infrastructure.


Video: tcVISION Mainframe-to-AWS data replication

tcVISION 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 on a variety of AWS targets. The product provides mainframe customers 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 AWS without disrupting the existing critical work on the legacy system.

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

In this video, an introductory overview to Treehouse Software’s tcVISION is shown, along with a live demonstration of mainframe data replication on AWS RDS for PostgreSQL:


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Contact Treehouse Software for a Demo Today…

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

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

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

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

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

In this video, Chris Rudolph, Treehouse Software’s tcVISION Product Manager shows an overview of the product, then demonstrates replication of mainframe data on AWS RDS for PostgreSQL:


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Contact Treehouse Software Today for a tcVISION Demonstration…

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

If interested in more information, please contact customer sales at +1.724.759.7070, email us at sales@treehouse.com, or fill out the Treehouse Software Product Demonstration Request Form and a Treehouse representative will contact you to set up a time for your online tcVISION demonstration.