Deployment Infrastructure
The hardware and software environment used to deploy and manage applications and services. Essential for ensuring reliable and scalable application deployment.
27 topics found for:
“system deployment”
Production Environment
The setting where software and systems are actually put into operation for their intended use. Essential for ensuring that products are fully functional and meet user requirements in a real-world setting.
Higher Environment
An environment closer to production where final testing and validation occur. Crucial for ensuring that products are ready for production deployment.
Staging Environment
An environment that replicates the production environment, used for final testing before deployment. Crucial for ensuring that digital products are thoroughly tested and perform as expected before going live.
SDLC
Software Development Life Cycle (SDLC) is a process for planning, creating, testing, and deploying an information system. Essential for managing the complexities of software development and ensuring project success.
TRiSM
Trust, Risk, and Security Management (TRiSM) is a framework for managing the trust, risk, and security of AI systems to ensure they are safe, reliable, and ethical. Essential for ensuring the responsible deployment and management of AI technologies.
HITL
Human in the Loop (HITL) integrates human judgment into the decision-making process of AI systems. Crucial for ensuring AI reliability and alignment with human values.
ModelOps
ModelOps (Model Operations) is a set of practices for deploying, monitoring, and maintaining machine learning models in production environments. Crucial for ensuring the reliability, scalability, and performance of AI systems throughout their lifecycle, bridging the gap between model development and operational implementation.
Configuration Management
The process of handling changes to software, hardware, or documentation in a systematic way. Critical for maintaining consistency and ensuring system integrity.
Enrichments
Features or elements added to enhance the functionality or user experience of a system. Crucial for improving user engagement and satisfaction by adding valuable enhancements.
Burn-In
The process of running a system for an extended period to detect early failures and ensure reliability. Important for ensuring the stability and performance of digital products before full-scale deployment.
Ethical AI Maturity Model
A framework for assessing and improving an organization's ethical practices in the development and deployment of AI. Important for ensuring that AI systems are developed responsibly and ethically.
Servicing
The process of maintaining, updating, and improving a product or system after its initial deployment to ensure its continued functionality, performance, and relevance to users. Crucial for ensuring long-term user satisfaction, product reliability, and adaptation to changing user needs and technological advancements.
End-To-End Testing
A testing methodology that verifies the complete workflow of an application from start to finish, ensuring all components work together as expected. Important for ensuring the reliability and performance of digital products, leading to better user satisfaction and fewer post-launch issues.
DevOps
A set of practices that combines software development (Dev) and IT operations (Ops) to shorten the development lifecycle and deliver high-quality software continuously. Crucial for improving the speed, efficiency, and quality of software development and deployment.
ARA
Application Release Automation (ARA) is the process of automating the release of applications, ensuring consistency and reducing errors. Crucial for accelerating the delivery of software updates and maintaining high-quality digital products.
DAM
Digital Asset Management (DAM) is a system that stores, organizes, and manages digital assets, such as images, videos, and documents. Essential for maintaining and leveraging digital content efficiently in product design and marketing.
AI Transparency
The degree to which the operations and decisions of an AI system are understandable and explainable to users. Crucial for building trust and ensuring ethical AI use.
Hotfix
A quick and often temporary fix applied to a software product to address an urgent issue without going through the full development cycle. Essential for maintaining the stability and functionality of digital products in the face of critical issues.
Dev Environment
A development environment where software is created and modified. Crucial for allowing developers to build and experiment with new features.
Ethical AI Frameworks
Guidelines and principles designed to ensure that AI systems are developed and used in a manner that is ethical and responsible. Crucial for building trust and ensuring the responsible use of AI technologies.
Build Server
A server dedicated to automating the process of building and compiling code, running tests, and generating software artifacts. Crucial for ensuring continuous integration and maintaining the integrity of the codebase in digital product development.
UAT
User Acceptance Testing (UAT) is the final phase of the software testing process where actual users test the software to ensure it meets their requirements. Crucial for validating that the software functions correctly in real-world scenarios before its release.
TDD
Test-Driven Development (TDD) is a software development methodology where tests are written before the code that needs to pass them. Essential for ensuring high code quality and reducing bugs.
Shift-Right Testing
A practice of performing testing activities in the production environment to monitor and validate the behavior and performance of software in real-world conditions. Crucial for ensuring the stability, reliability, and user satisfaction of digital products in a live environment.
IDE
Integrated Development Environment (IDE) is a software suite that combines tools like code editors, debuggers, and compilers. Essential for improving developer productivity and ensuring efficient and error-free coding practices.
ALM
Application Lifecycle Management (ALM) is the process of managing an application's development, maintenance, and eventual retirement throughout its lifecycle. Important for ensuring the sustainability and effectiveness of digital products over time.