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.

Distributed sites hosting cloud services closer to end-users for reduced latency and improved performance.

Machine learning models deployed and executed on edge devices, often with cloud-based training or updates.

Techniques for reducing the size of AI models to run efficiently on resource-constrained edge devices.

Performing text analysis and language understanding tasks on edge devices with cloud support.

Managing and coordinating distributed edge computing resources and their interaction with the cloud.

Using AI on edge devices to forecast equipment failures, with cloud-based model updates and analysis.

Training AI agents on edge devices through interaction with the environment, supported by cloud resources.

Measures to protect data, devices, and applications at the network edge in cloud-connected systems.

Distributed network layer for managing service-to-service communication in edge computing environments.

Data storage systems designed for edge devices with intermittent connectivity to cloud backends.

Applying knowledge from pre-trained cloud models to new tasks on edge devices with limited data.

Creating applications specifically designed to run on edge devices with cloud integration capabilities.

Software development paradigms optimized for creating applications that run on edge devices.

Seamless integration of edge computing resources with centralized cloud infrastructure and services.

Cloud networking component allowing outbound internet communication while blocking inbound traffic.

Fully managed service for deploying and scaling web applications and services on AWS infrastructure.

Static public IP address that can be dynamically assigned to cloud resources, providing consistent access points for applications.

Virtual network interface that can be attached to instances in a VPC, providing flexible networking capabilities.

Virtual network cards that can be attached, detached, and moved between cloud instances.

Integration of analytical capabilities directly into cloud-based applications and workflows.

Cloud-based platforms for analyzing and responding to human emotions in various applications.

Cloud services using AI to detect and respond to user emotions for enhanced interactions.

Protecting data by encoding it both when stored and while moving between cloud systems.

Techniques for securing data both when stored in cloud systems and while being transmitted.

Cloud resource scaling that considers energy consumption alongside performance metrics.

Allocating cloud resources to tasks with consideration for energy consumption and efficiency.

Computing methods designed to minimize energy consumption in cloud environments.

Allocating cloud resources to optimize energy efficiency while meeting performance requirements.

Documenting cloud providers' sustainability and ethical practices for stakeholder transparency.

Open-source edge and service proxy designed for cloud-native applications, providing features like load balancing and observability.

Adherence to principles ensuring fair and responsible use of AI in cloud environments.

Fully managed event routing service for building event-driven applications in Azure.

Storing the state of a system as a sequence of events in cloud-based applications.

Real-time analysis of data streams in cloud environments for immediate insights.

System design where actions are triggered by events in cloud environments, enabling responsive and scalable applications.

Connecting cloud services and applications based on event occurrences, enabling real-time data flow and processing.

APIs that trigger or respond to events in cloud-native applications, enabling real-time data processing and integration.

Developing cloud applications that respond to and generate events, enabling reactive and scalable architectures.

Serverless event bus for building event-driven applications in AWS, facilitating communication between various services.

Data consistency model where all replicas eventually reach a consistent state in distributed cloud systems.

Cloud systems capable of at least one exaFLOPS, or a billion billion calculations per second.

The runtime context in which cloud functions or applications operate, including libraries, dependencies, and configurations.

Monitoring and recording parameters and results of machine learning experiments in cloud environments.

Cloud services for making AI decision-making processes more transparent and interpretable.

Tools for developing AI models with transparent decision-making processes in cloud environments.

Cloud services offering tools to make AI models' decision-making processes more understandable.

Service for creating private connections between Azure datacenters and on-premises infrastructure.

Data integration process where transformation occurs after loading data into the cloud target system.

Process of extracting data from sources, transforming it to fit operational needs, and loading into a target database in the cloud.

Extending cloud capabilities to devices at the extreme edge of the network, like IoT sensors.

Tools for dynamically enabling or disabling features in cloud applications without code deployments.

Centralized repository for storing, managing, and serving machine learning features in cloud environments.

Analyzing data across multiple cloud or edge locations without centralizing the raw data.

System allowing integrated data access across multiple autonomous database management systems in the cloud.

Machine learning technique that trains algorithms across decentralized devices or servers holding local data samples.

Coordinating federated learning processes across multiple edge devices or cloud nodes.

Cloud-based systems for implementing and managing federated learning across distributed datasets.

Applying federated learning techniques to train models on edge devices connected to cloud systems.

Tools for executing queries across multiple distributed databases or data sources in cloud environments.

Cloud service for storing and accessing file data through shared file systems, providing scalable and manageable data storage.

Cloud services providing scalable file storage accessible from multiple compute instances.

Tools and processes for automating financial operations and optimization in cloud environments.

Framework for managing and optimizing cloud costs across an organization, aligning financial and operational goals.

AI-driven tools for continuously optimizing cloud spend and resource allocation.

Security system that monitors and controls incoming and outgoing network traffic in cloud environments.

Open-source, Kubernetes-native serverless framework for building microservices in the cloud, simplifying application deployment.

Extending cloud computing to the edge of the network, bringing processing closer to data sources.

Using historical data and algorithms to predict future trends or values in cloud-based analytics.

Cloud-based encryption allowing computations on encrypted data without decryption.

Tools for building complex serverless applications by combining multiple cloud functions.

Cloud computing model where developers run and manage application functionalities without complex infrastructure.

Adhering to EU data protection regulations in cloud-based data processing and storage.

Cloud compute instances equipped with Graphics Processing Units for parallel processing tasks.

Cloud-based services for creating AI models that can generate new content or data.

Cloud-based systems for analyzing large volumes of location-based data efficiently.

User interfaces that interpret hand or body movements to interact with cloud services.

Methodology using Git repositories as the source of truth for declarative infrastructure and applications in the cloud.

Service that improves availability and performance of applications by optimizing traffic routing across cloud regions.

Database systems that replicate and distribute data across multiple geographic locations in the cloud.

Rules and constraints applied to resources within a Google Cloud organization, enforcing governance and compliance.

Cloud services for analyzing and visualizing complex relationships in large datasets using graph structures.

NoSQL databases designed to store and query data with complex relationships in cloud environments.

Practices and technologies aimed at reducing the environmental impact of cloud data centers and operations.

Practices for developing cloud software that minimizes energy consumption and environmental impact.

Techniques for developing cloud applications that optimize resource usage and reduce environmental impact.

Adhering to US healthcare data protection regulations in cloud-based systems and applications.

Transmitting touch and motion sensations through cloud-connected devices for immersive experiences.

Automated tests to verify the availability and proper functioning of cloud resources and services.

Utilizing excess heat generated by cloud data centers for other purposes, improving energy efficiency.

Packages of pre-configured Kubernetes resources for deploying applications in cloud environments.

Systems managing data across diverse database types and locations in cloud environments.

Using cloud resources for solving complex computational problems requiring significant processing power.

Advanced 3D visualization interfaces for interacting with cloud services and data.

Conceptual cloud data centers using holographic technology for data storage and processing.

Experimental technology using holograms to store data in cloud environments, potentially offering high density.

Experimental data storage technique using holograms in cloud systems for high-density, long-term preservation.

Cloud-based offerings that enable computations on encrypted data without decryption.

Cloud-based service offering encryption that allows computations on encrypted data.

Encryption technique allowing computations on encrypted data without decryption in cloud environments.

Adding more machines to a cloud system to distribute load and increase capacity.

Object storage gateway for Ceph, providing S3-compatible API for container storage needs in Kubernetes.

Linux kernel feature for limiting, prioritizing, and isolating resource usage of container groups.

Technique for tracking and capturing changes in databases, useful in microservices architectures.

Practice of intentionally injecting failures in CI/CD pipelines to improve system resilience.

Platform for simulating various abnormal scenarios in Kubernetes environments to test reliability.

Static code analysis tool for detecting misconfigurations in Infrastructure as Code deployments.

Open-source networking, observability, and security solution for container workloads based on eBPF.

eBPF-powered service mesh offering high-performance traffic management and security for microservices.

Observability platform for Kubernetes providing deep visibility into container network flows.

High-performance networking mode in Cilium using extended Berkeley Packet Filter for packet processing and security.

Continuous integration and delivery platform supporting containerized application testing and deployment.

Fault tolerance pattern preventing cascading failures in distributed containerized systems.

Technique to detect failures and prevent system overload in microservices architectures, enhancing resilience.

Design pattern for handling large payloads in microservices by storing data externally, improving efficiency.

Open-source tool for static analysis of vulnerabilities in container images, enhancing security.

Kubernetes component managing interactions between cluster and cloud provider APIs, enabling cloud integration.

Specification for packaging and managing distributed applications across different environments.

Tooling for building container images from source code without Dockerfiles, adhering to best practices.

Architectural patterns specifically tailored for distributed, containerized applications in cloud environments.

Specification for describing event data in common formats, facilitating event-driven architectures in cloud environments.

Isolation technique in containerized microservices to prevent failure propagation across the system.

Group of servers or other resources that work together as a single system to provide high availability.

Kubernetes project for declarative management and provisioning of clusters using Kubernetes-style APIs.

Implementation of Cluster API for specific infrastructure providers, enabling cluster lifecycle management.

Kubernetes component that automatically adjusts the size of a cluster based on resource demands.

Process of estimating and allocating resources needed for container workloads in a cluster.

Mechanism for coordinating multiple Kubernetes clusters, enabling multi-cluster application deployment and management.

Interconnected network of container clusters, enabling cross-cluster communication and resource sharing.

Network configuration and management within and between container clusters, enabling inter-container communication.

Procedure for updating the Kubernetes version and components of a cluster while minimizing disruptions.

Centralized logging solution capturing logs from all containers and nodes in a cluster, aiding in troubleshooting.

Kubernetes component that automatically adjusts the number of nodes in a cluster based on resource utilization.

Kubernetes service type that exposes the service on an internal IP within the cluster, facilitating internal communication.

Kubernetes services accessible only within the cluster, used for internal communication between pods.

Kubernetes RBAC resource defining permissions across an entire cluster, not limited to a single namespace.

Kubernetes RBAC resource that binds a ClusterRole to users, groups, or service accounts across all namespaces.

Custom resource in Operator Lifecycle Manager describing a specific version of an Operator.

GitOps platform for managing and automating containerized application deployments, streamlining CD workflows.

Techniques to reduce initialization time of containers, particularly important in serverless environments.

Design pattern for handling failures in distributed container-based systems by reversing or compensating actions.

Kubernetes API object used to store non-confidential data in key-value pairs, accessible by pods.

Service mesh feature of Consul providing secure service-to-service communication with automatic TLS encryption.

Standardized unit of software that packages code and all its dependencies for quick, reliable deployment.

Methods used by attackers to escape container isolation and access the host system, posing security risks.

Software responsible for managing container lifecycle, including creation, execution, and destruction.

Security vulnerability allowing a process to break out of container isolation and access the host system.

Security measures and best practices to prevent containers from breaking out of their isolation.

Weaknesses in container runtimes or configurations that could allow processes to escape isolation.

Mechanisms to verify the health and readiness of containerized applications, ensuring service availability.

Physical or virtual machine running the container runtime and hosting containers, providing the execution environment.

Process of moving container images through different environments (e.g., dev, test, prod) in a controlled manner.

Cryptographic process of digitally signing container images to ensure their integrity and authenticity during distribution.

Stages a container goes through from creation to termination, including running, paused, and stopped states.

Processes and tools for managing containers throughout their lifecycle, from creation to deletion.

Process of capturing and managing log output from containerized applications for monitoring and troubleshooting.

Configuration file specifying how to build a container image, including base image, commands, and environment setup.

Quantitative measures of container performance, resource usage, and health, used for monitoring and optimization.

Specification and libraries for configuring network interfaces in Linux containers, standardizing networking.

Standard for developing plugins to configure network interfaces in Linux containers, ensuring interoperability.

Architecture and principles governing how containers communicate within and across hosts in orchestrated environments.

Automated arrangement, coordination, and management of software containers, crucial in large-scale deployments.

Kubernetes mechanisms (liveness, readiness, startup) for checking container health and controlling lifecycle.

Technique for capturing and analyzing real user interactions with containerized applications.

Rules defining how containers should be restarted in case of failures or exits, enhancing application resilience.

Software responsible for running containers, managing their lifecycle from creation to deletion.

Measures and tools to protect containers during execution, preventing unauthorized access or malicious activities.

Lightweight processes that manage the lifecycle of containers and provide abstraction between runtimes.

Standardized interface for container orchestration platforms to interact with storage systems.

Standard for developing storage plugins for container orchestration platforms, enabling storage extensibility.

Process of identifying security vulnerabilities in container images and their dependencies.

Mechanism for verifying the integrity and authenticity of container images before deployment.

Automated process of releasing container images to production environments after passing tests.

Ongoing process of validating deployed containers against defined policies and expectations.

Container networking solution using VPP (Vector Packet Processing) for optimized performance.

Approach prioritizing API definition before implementation, crucial for microservices architecture.

Linux kernel feature for limiting, prioritizing, and isolating resource usage of container groups.

Components managing the overall state of a container cluster, including API server, scheduler, and controllers.

Process of updating the core components of a container orchestration system while maintaining cluster stability.

Kubernetes component running controller processes to regulate the state of the cluster, maintaining desired state.

Software framework for building Kubernetes controllers and operators, simplifying custom resource management.

Kubernetes feature allowing custom resource API version conversions via external webhooks.

Storage optimization technique used in container filesystems to reduce duplication and improve efficiency.

Process of marking a node as unschedulable in Kubernetes, preventing new pods from being assigned to it.

Flexible, extensible DNS server used for service discovery in Kubernetes clusters, replacing kube-dns.

Horizontally scalable, multi-tenant, long-term storage for Prometheus metrics, enhancing monitoring capabilities.

Use of Cortex to provide isolated Prometheus monitoring for multiple users or teams in shared environments.

Kubernetes object for creating time-based jobs, running containers on a schedule for automated tasks.

Kubernetes patterns for running batch processes and scheduled tasks in containerized environments.

Kubernetes operators capable of managing resources across multiple namespaces, enabling broader automation.

Kubernetes API extension allowing pods to consume custom metrics for autoscaling and monitoring.

Extension of the Kubernetes API that defines new, custom resource types specific to a cluster's needs.

Process of converting custom resources between different API versions in Kubernetes, enabling API evolution.

Kubernetes API extension allowing the definition of custom resources, enabling cluster customization.

Kubernetes feature for extending the API with custom resources, enabling cluster customization.

User-defined API objects in Kubernetes, extending the core functionality of the platform for specific use cases.

Alternative or additional scheduler implementation for Kubernetes, allowing custom pod placement logic.

Alternative scheduling implementations in Kubernetes for custom pod placement strategies, enabling specialized scheduling logic.

Kubernetes feature providing DNS-based service discovery for containers within the cluster.

Use of Data Plane Development Kit for high-performance packet processing in container networks.

Kubernetes object ensuring that all (or some) nodes run a copy of a specific pod, useful for cluster-wide services.