Engineering Glossary

A method of submitting contributions to a Git project, proposing changes from a forked repository or branch.

Customizable files that automatically populate the body of new pull requests, guiding contributors.

Alternative terms for the same concept of proposing and reviewing changes in Git-based collaboration.

A Git command used to upload local repository changes to a remote repository, sharing updates with collaborators.

A file in a Git repository that provides information about the project, its purpose, and how to use or contribute to it.

A Git operation that moves or combines a sequence of commits to a new base commit, often used to maintain a linear history.

A Git rebase mode allowing users to modify, reorder, or squash commits before applying them to the target branch.

A Git mechanism that records updates to branch tips and other references in a repository.

A string that specifies the mapping between remote and local references when fetching or pushing in Git.

A strategy where a separate branch is created for release preparation, allowing continued development on the main branch.

A Git repository hosted on a server, allowing collaboration and synchronization between multiple developers.

Centralized location where software packages or modules are stored and managed, facilitating version control and collaboration.

A data structure containing all the files, history, and metadata for a Git-managed project.

Source Control Management, a system for tracking and managing changes to code, of which Git is an example.

The cryptographic hash function used by Git to generate unique identifiers for objects in the repository.

A secure authentication method using a pair of cryptographic keys for accessing remote systems or services.

A Git clone that only fetches a limited number of recent commits, reducing download size for large repositories.

The process of combining multiple commits into a single commit in Git, often used to simplify history.

The process of preparing changes to be committed in Git, also known as "adding to the index."

A Git feature for temporarily storing uncommitted changes, allowing you to switch branches without committing work in progress.

A Git feature for temporarily saving uncommitted changes, allowing you to switch contexts without committing incomplete work.

A Git command that shows the state of the working directory and staging area, indicating which files are modified or staged.

A Git repository nested within another repository, allowing you to include external projects in your own project.

A named reference to a specific point in Git history, typically used to mark release points or important milestones.

A subscription level for GitHub designed for collaborative groups or small organizations.

The original repository from which a fork is created, or the branch that a local branch is tracking.

Terms describing the flow of changes in Git, with upstream being the source and downstream the destination.

A temporary commit indicating unfinished work, often used to save progress or facilitate code reviews.

A secure alternative to passwords, used for authentication in Git operations, providing limited access to specific resources or actions.

A secondary location where Git stores object files, useful for optimizing storage and performance in large repositories.

A dedicated hardware or virtual machine optimized for running Git services, often used in enterprise environments for improved performance.

The person responsible for addressing an issue or pull request in a Git repository, helping to organize and prioritize tasks.

A temporary code used in two-factor authentication to verify a user's identity when accessing Git repositories or services.

The primary branch in a Git repository from which feature branches are created and into which they are merged after development.

A simple authentication method in Git using a username and password, often discouraged in favor of more secure methods.

The recurring period for which Git hosting services charge users or organizations for their subscriptions and usage.

The email address associated with a Git account or organization for receiving invoices and billing-related communications.

A user role in Git hosting platforms responsible for managing billing information, subscriptions, and payments for an organization.

A subscription package offered by Git hosting services, defining features, storage limits, and pricing for users or organizations.

A brief description of a user's profile on Git platforms, typically including their role, interests, or expertise in software development.

A Git object type representing the contents of a file, stored as a sequence of bytes without any metadata or file attributes.

An action on Git platforms to restrict a user's ability to interact with a repository, often used to manage disruptive behavior.

A set of rules applied to Git branches to control who can push changes, merge, or perform certain actions, enhancing code quality.

A command-line tool often used with Git to transfer data and interact with APIs, supporting various protocols including HTTPS.

A visual representation of an issue or pull request in Git project management tools, used for organizing and prioritizing work.

A series of connected commits in Git, representing a sequence of changes that build upon each other in a repository's history.

A group of changes made to files in a Git repository, typically represented by a commit and including additions, modifications, and deletions.

An automated test or verification process run on Git repositories to ensure code quality, security, or compliance with project standards.

A nested team within a Git organization's hierarchy, inheriting permissions and access rights from its parent team.

A Git command used to remove untracked files and directories from a working directory, helping to maintain a tidy repository.

A technique used in Git hosting services to distribute repository data across multiple servers for improved performance and reliability.

A visual representation of code additions and deletions over time in a Git repository, useful for tracking project activity.

A document outlining expected behavior and guidelines for contributors in a Git repository, promoting a positive community.

A designated person or team responsible for reviewing and approving changes to specific files or directories in a Git repository.

A user with read and write access to a Git repository, able to contribute code and participate in project discussions.

A unique identifier (SHA-1 hash) assigned to each commit in Git, used to reference specific points in a repository's history.

The person who originally created a commit in Git, distinct from the committer who may have applied the changes on behalf of the author.

A visual representation of the commit history in a Git repository, showing the relationships between different branches and merges.

The underlying structure and visual representations of Git's commit history, used for understanding project evolution.

A descriptive text associated with a Git commit, explaining the purpose and details of the changes made in that commit.

A Git object type containing metadata about a commit, including the author, committer, date, and a pointer to the tree object.

A file used by Git to store commit graph information, optimizing performance for operations that traverse the commit history.

A term referring to any Git object that can be resolved to a commit, including commit IDs, branch names, and tags.

A Git feature allowing users to view differences between two branches, often used before merging to review changes.

A visual representation of a user's Git activity over time, showing the frequency and distribution of their contributions to repositories.

A document in a Git repository outlining best practices, coding standards, and procedures for contributors to follow when submitting changes.

The collective changes, commits, issues, and pull requests made by a user to Git repositories, showcasing their involvement in projects.

Any person who has made contributions to a Git repository, whether through code, documentation, or other forms of project support.

A visual representation of all contributors to a Git repository, showing their relative contributions over time and by type.

The fundamental set of Git commands and functionality, excluding third-party extensions or hosting platform-specific features.

A promotional code offering discounts or credits for Git hosting services, often used to attract new users or upgrade existing accounts.

A time-based job scheduler used in Git hosting platforms to automate tasks such as backups, notifications, or periodic code checks.

A Git object not reachable from any reference (branch, tag, etc.), often created during rebasing or other history-altering operations.

A central interface in Git platforms providing an overview of a user's repositories, activities, and notifications.

The primary branch in a Git repository, typically named "main" or "master," serving as the base for new branches and deployments.

A visual representation of a project's dependencies, showing relationships between different components or external libraries.

A visualization of other projects or repositories that depend on a given Git repository, useful for understanding its impact.

An SSH key granting read-only access to a specific Git repository, commonly used for automated deployments or CI/CD processes.

The process of resolving a Git reference (like a branch or tag) to its corresponding commit object or SHA-1 hash.

A state in Git where the HEAD pointer references a specific commit rather than a branch, often used for temporary work.

Tools and features in Git used to identify and troubleshoot issues with repositories, commits, or configuration settings.

A folder within a Git repository containing files and potentially other subdirectories, organized hierarchically.

A term describing a Git working directory that contains uncommitted changes, indicating modifications that haven't been saved to the repository.

Alerts sent via email by Git platforms to inform users about repository activities, mentions, or updates.

A high-tier account type offered by Git hosting services, providing advanced features and support for large organizations.

A problematic merge in Git where conflicts are resolved incorrectly, potentially introducing subtle bugs or inconsistencies.

A type of Git merge where the target branch's pointer is simply moved to the latest commit of the source branch, without creating a new commit.

A temporary branch in Git created to develop a specific feature or fix, typically merged back into the main branch upon completion.

A markdown syntax used in Git documentation and comments to display formatted code snippets with syntax highlighting.

The underlying structure used by Git to store repository data, including objects, refs, and configuration files.

A feature in Git platforms allowing users to receive updates and notifications about other users' activities.

A file containing a Git repository's object database, used in certain Git operations.

A text file specifying intentionally untracked files that Git should ignore, customizable for different project types.

A technique in Git to join two unrelated commit histories, typically used for repository repair or history modification.

A unique identifier (SHA-1) for Git objects, used to ensure data integrity and create content-addressable storage.

The default branch that is checked out when a repository is cloned, typically 'main' or 'master'.

A reference to the tip of a branch, representing the most recent commit in that branch's history.

A characteristic of Git hosting systems designed to ensure continuous operation and minimal downtime.

A script that Git executes before or after events such as commit, push, and receive, used for automating or controlling Git processes.

The unique name assigned to a device on a network, used for identification and communication purposes.

High-density memory architecture using vertically stacked chips, enhancing performance and capacity in cloud server hardware.

Cloud infrastructure optimized for 5G networks, supporting high-speed, low-latency services and applications.

Technique to create multiple virtual networks on a shared physical 5G infrastructure, each optimized for specific use cases.

Integration of 5G networks with edge computing to enable low-latency, high-bandwidth applications closer to end-users.

Future convergence of 6G networks with cloud computing, promising ultra-high speeds and advanced capabilities.

Database transaction properties (Atomicity, Consistency, Isolation, Durability) ensuring data integrity in cloud environments.

Software ensuring AI systems adhere to ethical guidelines and regulations in cloud deployments.

Software for identifying and mitigating ethical issues and biases in AI models deployed in cloud environments.

Solutions for managing ethical considerations and regulatory compliance in cloud-based AI systems.

Structured approaches for managing AI development, deployment, and use in cloud environments.

Comprehensive solutions for managing, monitoring, and controlling AI models in cloud-based systems.

Cloud-based tools for explaining and understanding the decision-making processes of AI models.

Software for analyzing and explaining AI model decisions, crucial for transparency in cloud AI services.

Cloud platforms for discovering, sharing, and monetizing pre-trained AI models and algorithms.

Tools for tracking AI model performance and identifying deviations from expected behavior in cloud environments.

Systems for managing different versions of AI models and enforcing governance policies in cloud deployments.

Cloud-based development environments that use AI to assist programmers in writing and optimizing code.

Integration of AI capabilities into data analytics processes in cloud environments for enhanced insights.

Use of AI algorithms to predict and optimize resource allocation in cloud infrastructures.

Application of AI techniques to improve efficiency, performance, and cost-effectiveness of cloud resources.

Automated distribution of cloud resources using AI to optimize performance and cost-efficiency.

AI-based automation of cloud service selection and integration for complex workflows.

Automated creation of source code using AI models, often integrated into cloud development platforms.

Automated categorization and labeling of data using AI algorithms in cloud storage and processing systems.

Use of AI to improve network performance, efficiency, and security in cloud environments.

Intelligent distribution of computing resources in cloud environments using AI algorithms.

Enhanced SIEM systems using AI for improved threat detection and response in cloud environments.

Use of AI algorithms to identify and analyze potential security threats in cloud systems.

Proactive search for hidden threats in cloud environments using AI-powered analytics and automation.

Cloud infrastructure components designed or configured to enhance AI workload performance.

Database systems tailored for AI workloads, often featuring in-memory processing and distributed architectures.

Use of AI algorithms to identify unusual patterns or behaviors in cloud systems and data.

Intelligent automation of data and application integration processes in cloud environments using AI.

Cloud-based offering of AI capabilities, allowing businesses to leverage AI without extensive in-house expertise.

Cloud-based AI capabilities offered as a service, enabling easy integration of AI into applications.

Application of AI for automating and enhancing IT operations management in cloud environments.

Integrated solutions leveraging AI for automated monitoring, analysis, and management of cloud IT operations.

Use of AI-driven analytics to forecast and prevent system failures in cloud infrastructure.

Service that protects APIs in cloud environments by managing access, monitoring traffic, and preventing attacks.

Dedicated services for securing and managing APIs in cloud environments, including access control and threat protection.

Design approach prioritizing API creation before implementation, common in cloud-native application development.

Integration strategy using purpose-built APIs to connect data, devices, and applications in cloud ecosystems.

Persistent 3D digital content overlaid on the physical world, accessible via cloud infrastructure for augmented reality applications.

Cloud-based tools for analyzing user behavior and performance in augmented and virtual reality environments.

Cloud-hosted services enabling multi-user interaction in shared augmented or virtual reality spaces.

Specialized CDN optimized for delivering AR/VR content with low latency and high bandwidth.

Cloud-based tools and services for creating, testing, and deploying augmented and virtual reality applications.

JSON-based files defining infrastructure and configuration for Azure resource deployment.

Dynamic UIs that adjust based on user behavior, device capabilities, and context in cloud applications.

Techniques to identify and mitigate attacks on ML models in cloud-based AI systems.

Systems for informing administrators or users about important events or issues in cloud environments.

Process of examining AI algorithms for bias, errors, or unintended consequences in cloud-based systems.

Seamless, context-aware interaction methods for accessing cloud services in IoT environments.

Tools for identifying unusual patterns or behaviors in cloud systems, often using machine learning techniques.

Network management approach that optimizes performance based on specific application requirements in cloud environments.

Technique for quickly estimating query results in large-scale cloud databases, trading accuracy for speed.

Low-cost cloud storage for infrequently accessed data with longer retrieval times, e.g., Amazon Glacier, Azure Archive Storage.

Cloud-based storage for software build outputs, dependencies, and related metadata.

Hypothetical cloud offering of human-level AI capabilities across various domains.

Cloud-based environments for developing and testing advanced AI systems approaching human-level intelligence.

Systematic recording of actions and events in cloud systems for security and compliance purposes.

Chronological records of system activities for reconstructing and examining the sequence of events in cloud environments.

Integration of machine learning and natural language processing in cloud-based data analytics workflows.

Shared, persistent digital content overlaid on the physical world, accessible via cloud infrastructure.

Cloud-based systems for managing and delivering AR content and experiences, enabling scalable AR applications.

Cloud-powered generation of AR graphics and content, offloading processing from end-user devices.

Collections of EC2 instances that automatically adjust capacity based on defined conditions.

Automatic adjustment of cloud resources to match workload demands, ensuring optimal performance and cost-efficiency.

Automated machine learning processes for model selection, hyperparameter tuning, and feature engineering in cloud environments.

Cloud-based services automating the machine learning pipeline from data preparation to model deployment and monitoring.

AI-driven tools for improving efficiency and performance of machine learning workflows in the cloud.

Systems that automatically implement and maintain cloud resource policies and compliance.

Continuous, AI-driven assessment of cloud systems against regulatory and security standards.

AI-powered tools for identifying, categorizing, and mapping data assets in cloud environments.

AI-driven systems for managing data quality, security, and compliance in cloud environments.

Cloud-based tools using AI to clean, transform, and prepare data for analysis, streamlining data preparation processes.

AI-powered generation and selection of features for machine learning models in cloud environments.

AI-driven coordination of security incident detection and resolution in cloud systems, automating response workflows.

Cloud services that automate the process of creating and optimizing machine learning models, from data prep to deployment.

Cloud-based systems that automate the end-to-end machine learning model development process, including feature engineering and model selection.

AI-driven tools for simulating cyberattacks to identify vulnerabilities in cloud systems and applications.

AI-powered analysis of cloud architectures to identify potential security risks and attack vectors.

Self-managing, self-healing cloud services requiring minimal human intervention, leveraging AI for operations.

Ultra-low latency edge computing extensions of Azure for 5G networks, bringing cloud resources closer to users.

Service for creating, assigning, and managing policies to control Azure resources and ensure compliance.

Cloud-based services facilitating data exchange and process integration between business partners.

Architectural approach creating backend services tailored to specific frontend application needs in cloud environments.

Physical server dedicated to a single tenant, offering direct hardware access in cloud environments.

Dedicated physical servers without virtualization, offered as a cloud service for high-performance workloads.

Execution of series of jobs without user interaction, often for large-scale data processing in the cloud (e.g., AWS Batch, Azure Batch).

Distributed computing environments for processing and analyzing massive datasets in the cloud.

Interface for monitoring and managing cloud service usage and costs, providing detailed breakdowns and forecasts.

Use of cloud resources for computational biology and genomics research, enabling large-scale analysis and modeling.

Evaluation of cloud data center effects on local ecosystems and wildlife to ensure sustainable operations.

Cloud storage that provides fixed-size raw storage volumes, typically used for databases or file systems.

Cloud services providing persistent block-level storage volumes for use with compute instances.

Cloud-based tools for analyzing and visualizing blockchain data and transactions, offering insights into network activity.

Distributed databases using blockchain technology for enhanced security and immutability in cloud environments.

Software for managing and enforcing rules, permissions, and consensus mechanisms in blockchain networks deployed on cloud platforms.

Cloud-based solutions for connecting blockchain networks with existing enterprise systems and applications.

Integration of 5G mobile edge computing with container platforms for low-latency applications and services at network edges.

Application of AI and machine learning for automated operations, monitoring, and management of containerized environments.

Guidelines for phasing out older API versions in Kubernetes, ensuring smooth transitions for users.

Mechanisms to extend the Kubernetes API with custom resources and functionalities, enhancing platform capabilities.

Containerized service that acts as a single entry point for all client requests to a microservices architecture.

Core component of Kubernetes that exposes the cluster's API and handles all administrative operations.

Kubernetes feature allowing the API server to be extended with additional APIs without modifying core Kubernetes code.

Approach prioritizing API design before implementation, crucial for developing scalable containerized microservices.

Serverless compute engine for containers, allowing you to run containers without managing the underlying infrastructure.

Design pattern in containerized microservices that wraps a service's interface to make it compatible with other services.

Plugins that intercept requests to the Kubernetes API server before object persistence, enforcing policies or modifying objects.

Admission controllers specifically focused on enforcing security policies and validating security-related configurations.

HTTP callbacks that receive admission requests and can modify or validate objects before they are persisted.

Use of admission webhooks within Kubernetes operators to enforce custom policies or modify resources.

Kubernetes feature providing detailed logging of all requests processed by the API server for security and compliance.

Extension of the Kubernetes API server to include custom resources and functionalities without modifying core Kubernetes.

Combination of multiple ClusterRoles into a single role, simplifying RBAC management in Kubernetes.

Container registries isolated from public networks, used in secure or restricted environments.

Open-source project for exposing heterogeneous leaf devices as resources in Kubernetes clusters.

Setup and management of Prometheus Alertmanager for handling alerts from monitoring systems.

Fully managed Docker container registry provided by AWS for storing, managing, and deploying container images.

Microservices design pattern where a dedicated service acts as an API gateway for other services.

Service mesh implementation that doesn't require sidecars, reducing resource overhead and simplifying deployment.

Open-source tool for deep inspection of container images, including vulnerability scanning and policy enforcement.

Kubernetes operators implemented using Ansible for automating application lifecycle management.

Network policies specific to the Antrea CNI plugin, offering fine-grained control over pod-to-pod communication.

Kubernetes networking solution using Open vSwitch for improved performance and advanced networking features.

Open-source serverless platform that executes functions in response to events or direct invocations.

Security profiles for Linux that restrict program capabilities, enhancing container isolation and security.

Logging implemented within applications, providing detailed insights into application behavior and performance.

Platform providing security and compliance for container-based and cloud-native applications throughout their lifecycle.

Comprehensive security solution for containerized and cloud-native environments, offering vulnerability management and runtime protection.

GitOps continuous delivery tool for Kubernetes, automating application deployment and lifecycle management.

Kubernetes controller for advanced deployment strategies like canary and blue-green deployments.

Declarative GitOps tool for Kubernetes, automating application deployment and synchronization with Git repositories.

Process of storing, organizing, and managing container images and related artifacts in container registries.

Open-source platform for fine-grained access control and authentication in distributed systems.

Access control paradigm where authorization decisions are based on attributes of users, resources, and environment.

Additional metadata added to Kubernetes audit events for enhanced context and analysis, improving audit trails.

Components responsible for processing and storing Kubernetes audit logs, supporting various storage and analysis options.

Records of requests and activities within a Kubernetes cluster, used for security monitoring and compliance.

Configurable detail levels for Kubernetes audit logs, ranging from metadata-only to full request and response details.

Process of recording API server requests and responses for security, troubleshooting, and compliance purposes.

Detailed records of activities and operations within a Kubernetes cluster, used for security and compliance monitoring.

Configuration defining which events should be recorded in Kubernetes audit logs and at what level of detail.

Predefined set of audit policy rules for common use cases in Kubernetes, simplifying audit configuration.

Different phases of request processing where audit events can be generated in Kubernetes, providing comprehensive auditing.

Setup for sending Kubernetes audit events to external webhook endpoints for processing or analysis.

Process of systematically recording and examining activities within a Kubernetes cluster for security and compliance purposes.

Intermediary service that handles authentication before forwarding requests to the Kubernetes API server.

Pluggable components in container orchestration platforms for verifying user identities using various methods.

Rules defining access permissions for users and services in container orchestration platforms.

Serverless container hosting service in Azure, offering rapid deployment of containers without cluster management.

Managed Docker registry service for storing and managing container images in Azure cloud environments.

Implementation of Border Gateway Protocol within containerized network environments for advanced routing.

In container networks, BGP (Border Gateway Protocol) manages routing information between containers and external networks for efficient traffic routing.

Microservices design pattern where a dedicated service acts as an API gateway for specific frontend needs.

Processes for preserving and recovering container data and configurations in orchestration platforms.

Foundation Docker image upon which other images are built, containing core OS and runtime components.

Process of choosing appropriate foundation images for container builds, balancing size, security, and functionality.

Kubernetes quality of service class for pods with no resource guarantees, scheduled when resources are available.

Deployment strategy using two identical environments to minimize downtime and risk during updates.

Temporary tokens used for secure cluster initialization and node joining in Kubernetes, simplifying cluster setup.

Minimalist Linux-based operating system optimized for running containers in cloud environments.

Advanced container image building toolkit offering improved performance and caching capabilities.

Use of BuildKit for efficient, concurrent, and cache-optimized container image creation, improving build performance.

Isolation technique in microservices to contain failures and prevent system-wide cascading failures.

The Bulkhead Pattern in microservices isolates failures by dividing services into separate compartments, preventing issues in one from affecting others.

Kubernetes quality of service class for pods that can use more resources than requested when available.

Security configuration guidelines for deploying containers securely in various environments.

Technique of using multiple Container Network Interface plugins together for advanced networking capabilities.

Kubernetes feature for fine-grained CPU resource management and allocation to containers, optimizing performance.

Technique to limit CPU usage of containers to prevent resource monopolization and ensure fair allocation.

Architectural pattern separating read and write operations in distributed systems, often used in microservices.

Architectural pattern separating read and write operations in distributed systems, often used in microservices.

Standard interface between container runtimes and Kubernetes, allowing pluggable runtime implementations.

Functionality within CRI for pulling, inspecting, and removing container images, standardizing image operations.

Standardized logging interface for container runtimes implementing the Container Runtime Interface.

Performance and resource usage data exposed by container runtimes adhering to the CRI specification.

Kubernetes feature allowing selection of different runtime configurations for containers, enabling specialized runtimes.

Unix domain socket used for communication between Kubelet and the CRI-compatible container runtime.

Process of verifying that a container runtime correctly implements the CRI specification, ensuring compatibility.

Lightweight container runtime specifically designed for Kubernetes, implementing the CRI specification.

Core components and architecture of the CRI-O container runtime, including its interaction with Kubernetes.

Use of CRI-O, a lightweight container runtime, as the primary runtime in a Kubernetes cluster.

Component of CSI responsible for volume provisioning and attachment operations in container orchestration systems.

Plugins implementing the Container Storage Interface for various storage systems in Kubernetes.

Short-lived volumes in Kubernetes, created and deleted alongside a pod using CSI drivers, for temporary storage.

Process of transitioning from in-tree volume plugins to CSI drivers in Kubernetes, improving storage extensibility.

Component of CSI responsible for mounting volumes and making them available to containers.

Feature allowing storage provisioning based on topology constraints in Kubernetes, optimizing data locality.

Caching strategy where the application checks the cache before retrieving data from the main data store.

Techniques for implementing and managing caches in containerized applications for improved performance.

Open-source networking and network security solution for containers, providing a rich set of security policies.

High-performance networking mode in Calico using extended Berkeley Packet Filter for packet processing.

Technique of releasing new versions to a subset of users or servers to minimize risk and gather feedback.

Fine-grained privileges that can be assigned to containers, enhancing security by limiting root-level access.

Mechanisms for managing and restricting Linux capabilities assigned to containers for improved security.

Groupings or classifications of container-related resources or components for easier management and discovery.

Ceph's block storage system, often used for persistent volumes in container orchestration platforms.