Mainframe Flashcards
Cobol app SCM
COBOL (Common Business-Oriented Language) is a programming language that has been widely used in business, finance, and administrative systems for companies and governments. COBOL app SCM refers to the use of Source Code Management (SCM) systems specifically tailored for applications written in COBOL.
Source Code Management (SCM) is a critical part of software development, involving the tracking and management of changes to code. SCM systems help developers collaborate, maintain version control, and manage code changes efficiently. In the context of COBOL, SCM involves several key components and considerations:
Version Control: COBOL SCM systems track changes to COBOL code over time. This allows developers to maintain a history of code changes, revert to previous versions if necessary, and understand the evolution of the codebase.
Collaboration: SCM systems enable multiple developers to work on the same COBOL codebase simultaneously. They manage conflicts that arise from concurrent changes and merge code changes from different developers.
Build and Deployment Automation: COBOL SCM tools often include features for automating the build and deployment processes. This ensures that code is consistently compiled and deployed across different environments.
Integration with Mainframe Systems: Many COBOL applications run on mainframe systems. SCM tools for COBOL typically integrate with mainframe environments, supporting the specific needs of these platforms.
Compliance and Auditing: In many industries, especially those using COBOL, there are stringent regulatory and compliance requirements. SCM tools provide auditing capabilities to track who made changes, what changes were made, and when they were made.
Code Review and Quality Control: SCM systems facilitate code reviews and quality control processes, ensuring that COBOL code meets organizational standards and practices.
Popular SCM tools that support COBOL development include IBM Rational Team Concert, CA Endevor, and Micro Focus ChangeMan. These tools provide specialized features to handle the unique aspects of COBOL development and mainframe environments.
Program-to-Program Communication
Program-to-Program Communication
Program-to-program communication involves the exchange of data and instructions between two or more software programs. This type of communication can occur within a single system or across different systems and can be implemented in various ways:
APIs (Application Programming Interfaces):
APIs allow programs to communicate with each other by defining a set of rules and protocols for interactions.
RESTful APIs and SOAP APIs are common examples that enable web-based communication between programs.
RPC (Remote Procedure Call):
RPC allows a program to execute a procedure or subroutine in another program located on a different machine or system.
Examples include XML-RPC and JSON-RPC.
Message Queues:
Message queues enable asynchronous communication between programs by sending messages to a queue that other programs can read from.
Examples include RabbitMQ, Apache Kafka, and IBM MQ.
Inter-process Communication (IPC):
IPC mechanisms allow processes running on the same system to communicate.
Examples include shared memory, pipes, sockets, and message passing.
Program-to-Database Communication
Program-to-Database Communication
Program-to-database communication involves interactions between a software program and a database to perform operations such as querying, updating, inserting, and deleting data. This type of communication is essential for applications that need to store and retrieve persistent data. Key components and methods include:
SQL (Structured Query Language):
SQL is the standard language for interacting with relational databases.
Programs use SQL statements to perform CRUD (Create, Read, Update, Delete) operations on the database.
Examples of relational databases include MySQL, PostgreSQL, Oracle, and Microsoft SQL Server.
Database APIs/Drivers:
Programs use database-specific APIs or drivers to connect to and interact with databases.
Examples include JDBC (Java Database Connectivity) for Java applications and ODBC (Open Database Connectivity) for various languages.
ORM (Object-Relational Mapping):
ORM frameworks map objects in a programming language to database tables, simplifying database operations.
Examples include Hibernate for Java, Entity Framework for .NET, and SQLAlchemy for Python.
NoSQL Databases:
NoSQL databases offer alternative data models (e.g., document, key-value, graph) and are used for specific use cases where relational databases may not be ideal.
Examples include MongoDB (document-oriented), Redis (key-value store), and Neo4j (graph database).
Program-to-Program: Example
Program-to-Program: A microservices architecture where different services communicate via RESTful APIs to perform tasks like processing user requests, handling payments, and managing inventory.
Program-to-Database: Example
Program-to-Database: An e-commerce application where the web server interacts with a relational database to retrieve product information, process customer orders, and update inventory levels.
Eclipse based client
An Eclipse-based client refers to a software application that is built on or extends the Eclipse Integrated Development Environment (IDE) framework. Eclipse is an open-source platform that provides a robust and flexible foundation for developing integrated tools and rich client applications. Here’s an overview of what an Eclipse-based client entails:
Key Characteristics of an Eclipse-Based Client
Built on Eclipse RCP (Rich Client Platform):
Eclipse RCP is a platform for building and deploying rich client applications. It provides a set of frameworks and services for building complex applications with a rich graphical user interface (GUI).
RCP applications leverage the modularity and extensibility of the Eclipse platform, allowing developers to create highly customizable and scalable applications.
Plugin Architecture:
Eclipse-based clients use a plugin architecture, where functionality is divided into discrete units called plugins or bundles.
Plugins can be independently developed, tested, and deployed, making it easy to extend the application with new features or integrations.
Eclipse IDE Integration:
Eclipse-based clients can integrate seamlessly with the Eclipse IDE, providing tools and interfaces that developers can use within the familiar Eclipse environment.
This integration can include custom editors, views, perspectives, and other IDE components tailored to specific development tasks.
Extensive Use of SWT and JFace:
Eclipse-based clients typically use the Standard Widget Toolkit (SWT) and JFace libraries for building the user interface.
SWT provides a native look and feel by using the operating system’s GUI libraries, while JFace simplifies common UI tasks.
Examples of Eclipse-Based Clients
IBM Rational Application Developer (RAD):
RAD is an integrated development environment built on Eclipse that provides tools for developing Java, Web, and enterprise applications.
It includes features for web development, Java EE development, and integration with IBM WebSphere.
Spring Tool Suite (STS):
STS is an Eclipse-based development environment for building Spring applications.
It includes features for Spring framework development, such as project templates, code assistance, and Spring-specific views.
Aptana Studio:
Aptana Studio is an Eclipse-based IDE focused on web development.
It supports HTML, CSS, JavaScript, PHP, and other web technologies, offering tools for coding, debugging, and deploying web applications.
Talend Open Studio:
Talend Open Studio is an Eclipse-based client for data integration.
It provides a graphical environment for designing and deploying data integration jobs, with extensive support for data connectors and transformation components.
Benefits of Eclipse-Based Clients
Modularity and Extensibility:
The plugin architecture allows for easy extension and customization, enabling developers to add new features and integrations without modifying the core application.
Rich User Interface:
Eclipse-based clients can provide sophisticated and responsive user interfaces using SWT and JFace, offering a rich user experience.
Community and Ecosystem:
Eclipse has a large and active community, providing a wealth of plugins, tools, and resources that can be leveraged in Eclipse-based clients.
Integration with Development Tools:
Being built on Eclipse, these clients can integrate tightly with development tools and workflows, enhancing productivity and streamlining development processes.
What is PuTTY?
PuTTY is a free, open-source terminal emulator application that supports various network protocols, including SSH (Secure Shell), Telnet, rlogin, and raw socket connections. It is widely used for remote access to Unix/Linux servers from a Windows environment, but it also supports other platforms like macOS and Linux.
Fusion HCI
Fusion HCI (hyper converged infrastructure) a complete turnkey application platform for running both stateless and stateful container-based applications on-premises. It is designed to enable platform engineering team to deliver a true cloud operating model, API driven around a provider / consumer / self service operating model to their constituents in the enterprise: SRE teams and application developers. IBM stands behind the solution offering a wide range of services and support for all of your OpenShift based solutions.
Fusion HCI is fully integrated hardware and software to provide a seamless deployment and operations experience for delivering container environments on-premises. By combining Red Hat Advanced Cluster Manager with Fusion data services for stateful applications, Fusion makes it easier than ever to build and maintain environments for stateful applications, including application centric backup and restore, and data replication strategies across datacenters. Backups can be used to easily move applications across on-prem and public cloud environments. Integrated services for monitoring, updating, and maintaining the complete hardware and software stack enables fewer administrators to maintain more environments. With Red Hat Kubevirt KVM with Fusion data services, enterprises can run Windows and Linux VMs on a Fusion HCI. Fusion HCI offers GPU servers with NVIDIA L40S GPUs for inferencing and fine tuning LLMs.
CSI (Container Storage Interface) driver
standardized interface used in container orchestration systems like Kubernetes to manage storage resources. It allows Kubernetes to interact with various storage systems in a consistent way, enabling the dynamic provisioning and management of storage volumes for containerized applications.
Key Concepts of CSI Drivers:
Container Storage Interface (CSI):
CSI is an industry-standard API specification that defines how storage providers (like cloud providers, traditional storage arrays, or software-defined storage systems) can expose their storage capabilities to container orchestrators like Kubernetes.
The goal of CSI is to create a unified interface that decouples the Kubernetes storage system from the underlying storage providers, allowing for more flexibility and interoperability.
CSI Driver:
A CSI driver is a plugin implemented by storage vendors that adheres to the CSI specification. It translates Kubernetes storage operations (such as creating, attaching, detaching, and deleting volumes) into storage-specific commands that interact with the underlying storage system.
CSI drivers are installed and run as Kubernetes custom resources (usually as DaemonSets) within the cluster, enabling Kubernetes to manage storage across a wide variety of storage backends.
Functionality Provided by CSI Drivers:
Provisioning: CSI drivers can create new storage volumes dynamically when requested by Kubernetes.
Attachment/Detachment: CSI drivers handle the process of attaching and detaching volumes to and from the nodes where containers are running.
Mounting/Unmounting: CSI drivers ensure that the volumes are properly mounted to the containers’ file systems so that they can be used by applications.
Snapshotting: Some CSI drivers provide the ability to take snapshots of volumes for backup or cloning purposes.
Resizing: CSI drivers can allow the resizing of volumes to meet changing application needs.
CSI in Kubernetes:
In Kubernetes, the CSI drivers are deployed as part of the cluster infrastructure and are used by Kubernetes’ storage components to manage persistent volumes (PVs) and persistent volume claims (PVCs).
Kubernetes uses the CSI drivers to abstract the complexities of storage management, making it easier for developers to request and use storage resources without needing to know the specifics of the underlying storage technology.
Vendor-Specific and Generic Drivers:
Vendor-Specific Drivers: These are provided by specific storage vendors to support their storage solutions. Examples include CSI drivers for AWS EBS, Google Cloud Persistent Disks, Azure Disks, VMware vSphere, etc.
Generic or Community Drivers: These are open-source CSI drivers that can be used with a wide variety of storage systems, such as the CSI hostpath driver for testing or the NFS CSI driver for network file systems.
Benefits of CSI Drivers:
Interoperability: The CSI standard enables Kubernetes to work with a wide range of storage providers, making it easier to integrate new storage technologies into the Kubernetes ecosystem.
Flexibility: Developers and administrators can choose the best storage solution for their needs without being locked into a specific vendor or technology.
Modularity: CSI drivers can be developed, deployed, and maintained independently of the Kubernetes core, allowing for more rapid innovation and updates.
Example Usage:
In Kubernetes, a typical workflow using a CSI driver might involve:
A developer creates a Persistent Volume Claim (PVC) in a Kubernetes cluster.
Kubernetes uses the appropriate CSI driver to provision a Persistent Volume (PV) that satisfies the PVC.
The CSI driver manages the lifecycle of the PV, including attaching it to the appropriate node, mounting it to the container’s file system, and later detaching and deleting it when no longer needed.
Cloud Foundry
Cloud Foundry is an open-source Platform-as-a-Service (PaaS) that provides a cloud-based environment where developers can build, deploy, and manage applications efficiently without worrying about the underlying infrastructure. It was originally developed by VMware and later became part of Pivotal Software, with the project now being governed by the Cloud Foundry Foundation.
Key Features of Cloud Foundry:
Application-Centric Platform:
Cloud Foundry is designed to allow developers to focus on writing code and deploying applications. It abstracts away the complexities of managing servers, networking, and storage, enabling a faster and more streamlined development process.
Multi-Cloud and Multi-Language Support:
Cloud Foundry supports deployment on various cloud providers, including AWS, Azure, Google Cloud, and on-premises environments like OpenStack and VMware vSphere. It also supports multiple programming languages and frameworks, such as Java, Node.js, Ruby, Python, PHP, and more, through the use of buildpacks.
Scalability:
Applications deployed on Cloud Foundry can be easily scaled horizontally by adding more instances of an application, ensuring that the system can handle increased load.
Automated Application Management:
Cloud Foundry handles much of the operational tasks automatically, such as health monitoring, load balancing, and self-healing of applications. This reduces the need for manual intervention and helps maintain high availability.
Developer Productivity:
Developers can deploy applications using the cf CLI (command-line interface) with simple commands. The platform takes care of containerization, orchestration, and deployment, allowing developers to push code quickly and reliably.
Buildpacks:
Buildpacks are a key component of Cloud Foundry. They detect the language of an application, compile it, and package it with the necessary runtime dependencies. This makes it easy to deploy applications without worrying about the specific configurations of the underlying runtime environment.
Microservices Architecture:
Cloud Foundry is well-suited for building and running microservices-based applications. It supports distributed, stateless applications that can communicate over the network, which aligns with modern application development practices.
Integrated DevOps Tools:
Cloud Foundry integrates with continuous integration/continuous deployment (CI/CD) pipelines, source code management tools, and monitoring solutions, enabling a seamless DevOps workflow.
Service Broker Architecture:
Cloud Foundry uses a service broker architecture to integrate with external services such as databases, messaging systems, and caching solutions. These services can be easily bound to applications, providing necessary resources like storage or messaging capabilities.
Open-Source and Community-Driven:
Being open-source, Cloud Foundry benefits from a large community of contributors and a wide range of plugins, extensions, and third-party integrations. The Cloud Foundry Foundation oversees the project and ensures it remains vendor-neutral and widely supported.
Use Cases for Cloud Foundry:
Enterprise Applications: Large enterprises use Cloud Foundry to develop, deploy, and scale business-critical applications across multi-cloud environments.
Microservices: Organizations developing microservices architectures benefit from Cloud Foundry’s ability to manage distributed, stateless applications.
Continuous Delivery: Cloud Foundry’s integration with CI/CD tools makes it ideal for environments where continuous delivery and rapid iteration are crucial.
Legacy Application Modernization: Enterprises can use Cloud Foundry to modernize legacy applications by containerizing and running them on a cloud platform.
HA in context of Fusion
HA (High Availability):
High Availability ensures that the IBM Fusion environment is resilient and remains operational even in the face of hardware failures, software issues, or other disruptions. HA typically involves redundant components, failover mechanisms, and load balancing to ensure continuous service availability with minimal downtime.
DR
DR (Disaster Recovery):
Disaster Recovery refers to the strategies and solutions used to restore critical IT infrastructure and services after a major disruption or disaster, such as a natural disaster, cyberattack, or system failure.
ODF
What is OpenShift Data Foundation?
OpenShift Data Foundation is a highly available storage solution that consists of several open source operators and technologies like Ceph, NooBaa, and Rook. These operators allow you to provision and manage File, Block, and Object storage for your containerized workloads in Red Hat® OpenShift® on IBM Cloud® clusters. Unlike other storage solutions where you might need to configure separate drivers and operators for each type of storage, ODF is a unified solution capable of adapting or scaling to your storage needs. You can also deploy ODF on any OCP cluster.
Portworx DB
Portworx DB is a managed database-as-a-service (DBaaS) platform built on top of the Portworx Kubernetes Data Services platform. It simplifies the deployment, management, and scaling of databases on Kubernetes, enabling organizations to run stateful database workloads in cloud-native environments with ease. Portworx DB supports a wide variety of databases, providing a consistent operational experience across different types of databases running in containerized environments.
IBM Fusion
Fusion is an easy-to-use data services solution that is tightly integrated with Red Hat OpenShift. Its intuitive user interface and powerful APIs make it easy for anyone to get up and running quickly with on-demand provisioning.
Fusion is the infrastructure platform that supports application modernization on Red Hat OpenShift. Fusion provides the container-native services that allow data to scale with cloud-native applications by taking a container-centric approach to backup and restore, high availability and disaster recovery (HA/DR), and security. Fusion’s robust APIs enable integration with DevOps, artificial intelligence and machine learning (AI/ML), and data analytics pipelines for automation. When investing in the effort to transform monolithic applications based on virtual machines to cloud native applications based upon OpenShift containers, it’s critical to also design new data management approaches based on Fusion’s container-native data plane and resiliency services.
Fusion provides the data services that support scaling and resiliency of modern data workloads
Fusion is a platform to build the infrastructure for modern AI/ML data analytics pipelines by supporting graphics processing units (GPU) and all structured/semi-structured/unstructured data types for data ingest, inferencing, model training, and deep learning.
Fusion enhances IBM Cloud Paks with tightly integrated enterprise ready data services including backup, restore, and disaster recovery capabilities for Cloud Pak environments. Using automated policy-based recipes with application consistent backup and recovery, Fusion provides the best Recovery Time Objective & Recovery Point Objective (RTO/RPO) for cloud-native applications
