Mainframe training course

IBM Mainframe Operation Training Course Modules

  • Introduction to z/OS
  • VSAM & Access Methods
  • Console Operations Overview
  • z/OS Concepts
  • Job Entry Subsystem
  • Case Studies and Lab Practices

IBM Mainframe Application Training Course Modules

  • Introduction to z/OS
  • VSAM & Access Methods
  • DB2 Fundamentals
  • SQL Workshop
  • DB2 Application Programming
  • CICS Fundamentals
  • CICS Application Programming
  • Project & Case Studies

Advanced IBM Mainframe Application Training Course Modules (Working Professionals)

  • PL/1 Programming
  • REXX Programming
  • CLIST Programming
  • IMS DB

Mainframe Application Programming:

Before you start this program, please check ms exchange server price This is a very comprehensive and intensive training program provides hands on experience on Live Mainframe Servers and covers from basic fundamentals of Mainframe to sufficiently advanced concept to make a person industry ready to enter the world of Mainframe.

Mainframe System Administration:

This course is designed for those who wish to gain a fundamental understanding of Mainframe System programming.

Mainframe Application Programming for Working Professionals:

Advanced Mainframe Application program offers training to working professionals who wish to enhance their existing skill or who are looking for a domain change.


The .NET Framework

  • It is a platform for application developers.
  • It is a Framework that supports Multiple Language and Cross language integration.
  • IT has IDE (Integrated Development Environment).
  • Framework is a set of utilities or can say building blocks of your application system.
  • .NET Framework provides GUI in a GUI manner.
  • .NET is a platform independent but with help of Mono Compilation System (MCS). MCS is a middle level interface.
  • .NET Framework provides interoperability between languages i.e. Common Type System (CTS) .
  • .NET Framework also includes the .NET Common Language Runtime (CLR), which is responsible for maintaining the execution of all applications developed using the .NET library.
  • The .NET Framework consists primarily of a gigantic library of code.

Cross Language integration

  • You can use a utility of a language in another language (It uses Class Language Integration).
  • .NET Framework includes no restriction on the type of applications that are possible.
  • The .NET Framework allows the creation of Windows applications, Web applications, Web services, and lot more.
  • The .NET Framework has been designed so that it can be used from any language, including C#, C++, Visual Basic, JScript, and even older languages such as COBOL.



Hadoop is an open source, Java-based programming framework that supports the processing and storage of extremely large data sets in a distributed computing environment. It is part of the Apache project sponsored by the Apache Software Foundation. Hadoop makes it possible to run applications on systems with thousands of commodity hardware nodes and to handle thousands of terabytes of data. Its distributed file system facilitates rapid data transfer rates among nodes and allows the system to continue operating in case of a node failure. This approach lowers the risk of catastrophic system failure and unexpected data loss, even if a significant number of nodes become inoperative. Consequently, Hadoop quickly emerged as a foundation for big data processing tasks, such as scientific analytics, business and sales planning and processing enormous volumes of sensor data, including from internet of things sensors. It was inspired by Google's Map Reduce, a software framework in which an application is broken down into numerous small parts. Any of these parts, which are also called fragments or blocks, can be run on any node in the cluster. After years of development within the open source community, Hadoop 1.0 became publically available in November 2012 as part of the Apache project sponsored by the Apache Software Foundation. Since its initial release, Hadoop has been continuously developed and updated. The second iteration of Hadoop (Hadoop 2) improved resource management and scheduling. It features a high-availability file-system option and support for Microsoft Windows and other components to expand the framework's versatility for data processing and analytics.

Hadoop also supports a range of related projects that can complement and extend Hadoop's basic capabilities. Complementary software packages include:

  • Apache Flume. A tool used to collect, aggregate and move huge amounts of streaming data into HDFS.
  • Apache HBase. An open source, nonrelational, distributed database;
  • Apache Hive. A data warehouse that provides data summarization, query and analysis;
  • Cloudera Impala. A massively parallel processing database for Hadoop, originally created by the software company Cloudera, but now released as open source software;
  • Apache Oozie. A server-based workflow scheduling system to manage Hadoop jobs;
  • Apache Phoenix. An open source, massively parallel processing, relational database engine for Hadoop that is based on Apache HBase;
  • Apache Pig. A high-level platform for creating programs that run on Hadoop;
  • Apache Sqoop. A tool to transfer bulk data between Hadoop and structured data stores, such as relational databases;
  • Apache Spark. A fast engine for big data processing capable of streaming and supporting SQL, machine learning and graph processing;
  • Apache Storm. An open source data processing system; and
  • Apache ZooKeeper. An open source configuration, synchronization and naming registry service for large distributed systems.

Java enterprise

Java Enterprise app for Devops

DevOps (development and operations) is an enterprise software development phrase used to mean a type of agile relationship between Development and IT Operations. The goal of DevOps is to change and improve the relationship by advocating better communication and collaboration between the two business units.

In an enterprise there is a need to break down silos, where business units operate as individual entities within the enterprise where management, processes and information are guarded. On the software development side -- and for those working in IT operations -- there needs to be better communication and collaboration to best serve the IT business needs of the organization.

One answer to breaking down enterprise silos is the move towards a DevOps-based culture that partners developers with operations staff to ensure the organization achieves optimal running of software with minimal problems. This culture is one that supports a willingness to work together and share.

The DevOps culture puts a focus on creating a fast and stable work flow through development and IT operations. One main goal of DevOps is to deploy features into production quickly and to detect and correct problems when they occur, without disrupting other services.

DevOps is not based on stringent methodologies and processes: it is based on professional principles that help business units collaborate inside the enterprise and break down the traditional silos. The guiding principles of DevOps include culture, measurement, automation and sharing.

DevOps is considered to be a new approach to the more traditional application lifecycle management (ALM) process.



Docker is a tool designed to make it easier to create, deploy, and run applications by using containers. Containers allow a developer to package up an application with all of the parts it needs, such as libraries and other dependencies, and ship it all out as one package. By doing so, thanks to the container, the developer can rest assured that the application will run on any other Linux machine regardless of any customized settings that machine might have that could differ from the machine used for writing and testing the code.

In a way, Docker is a bit like a virtual machine. But unlike a virtual machine, rather than creating a whole virtual operating system, Docker allows applications to use the same Linux kernel as the system that they're running on and only requires applications be shipped with things not already running on the host computer. This gives a significant performance boost and reduces the size of the application.

And importantly, Docker is open source. This means that anyone can contribute to Docker and extend it to meet their own needs if they need additional features that aren't available out of the box.