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.

Design pattern using specialized containers that run before app containers in a pod, used for setup or dependency management.

Specialized containers that run to completion before other containers in a Kubernetes pod, used for initialization tasks.

Specification of CPU and memory limits for initialization containers in Kubernetes pods, ensuring efficient resource utilization.

Deprecated Kubernetes feature for dynamically modifying resource configurations before they become visible to the system.

Methods and patterns for containers within a pod to exchange data and signals, utilizing shared volumes or localhost networking.

Architectural designs for deploying and managing containerized applications on edge devices in Internet of Things scenarios.

Open-source service mesh providing traffic management, security, and observability for cloud-native applications.

Core services of the Istio service mesh responsible for configuring proxies and implementing policies.

Istio traffic management resource defining policies that apply to traffic intended for a service after routing has occurred.

Istio resources managing inbound and outbound traffic for the service mesh, providing fine-grained control over traffic flow.

Istio design that removes the Mixer component, improving performance and scalability of the service mesh.

Istio resources allowing the addition of entries to the service registry, enabling traffic to external dependencies.

Istio traffic management resources defining a set of traffic routing rules to apply when a host is addressed.

Istio feature providing a sidecar-less service mesh implementation, reducing resource overhead and simplifying deployment.

Open-source, end-to-end distributed tracing system for monitoring and troubleshooting microservices-based distributed systems.

Kubernetes operator for automated deployment and management of Jaeger tracing infrastructure in container environments.

Implementation of distributed tracing using Jaeger to monitor and optimize performance in microservices architectures.

Cloud-native CI/CD solution for Kubernetes, automating the entire software development lifecycle for containerized applications.

Tool for building optimized Docker and OCI images for Java applications without the need for a Docker daemon.

Kubernetes resource that creates one or more pods to perform a specific task and ensures they successfully complete, ideal for batch processes.

Lightweight Kubernetes distribution designed for edge, IoT, and resource-constrained environments, simplifying cluster deployment.

Terminal-based UI for managing and monitoring Kubernetes clusters, providing an intuitive interface for cluster operations.

Kubernetes-based Event Driven Autoscaling, enabling fine-grained autoscaling for event-driven workloads based on event sources.

Kubernetes Universal Declarative Operator, a toolkit for writing operators using a declarative spec, simplifying complex application management.

Tool for building container images from a Dockerfile inside a container or Kubernetes cluster, without requiring a Docker daemon.

Framework for application-level data management in Kubernetes, ensuring consistent backups of stateful apps.

Open-source project for multi-cluster application management in Kubernetes, facilitating resource distribution across clusters.

Lightweight virtual machines that feel and perform like containers, but provide the workload isolation and security of VMs.

Major update to Kata Containers, introducing improved performance, reduced footprint, and enhanced security features.

Cloud-native application lifecycle orchestration tool, automating deployment, testing, and remediation for containerized apps.

Technique allowing network packets to bypass the kernel, improving performance in container networking scenarios.

Linux feature providing isolation for system resources, fundamental to container implementation and resource separation.

CNI plugin using WireGuard to create a mesh overlay network for Kubernetes, enhancing security and simplicity.

Kubernetes-based platform for building, deploying, and managing serverless workloads, simplifying serverless application development.

Knative component providing tools for routing events between publishers and subscribers in cloud-native applications.

Knative component for deploying and managing serverless workloads, handling scaling and routing of containerized applications.

Tool allowing WebAssembly modules to run in Kubernetes clusters, enabling language-agnostic workloads.

Network virtualization solution for Kubernetes integrating the Open vSwitch software switch to provide advanced networking features.

Implementation of Kube-OVN to leverage Open vSwitch for flexible, high-performance container networking.

Tool for checking whether Kubernetes deployments adhere to Center for Internet Security (CIS) best practices.

Use of kube-bench to perform automated security audits of Kubernetes clusters against established benchmarks.

Kubernetes networking solution providing direct container-to-container networking with BGP-based routing.

Tool for static code analysis of Kubernetes object definitions, identifying misconfigurations and potential issues.

Service that listens to the Kubernetes API server and generates metrics about the state of Kubernetes objects.

Open-source system extending native containerized application orchestration capabilities to hosts at Edge.

Tool for bootstrapping a minimum viable Kubernetes cluster, simplifying the process of setting up a production-grade cluster.

Open-source tool for auditing Kubernetes clusters and workloads for potential security issues and best practice violations.

Framework for building Kubernetes APIs using custom resource definitions (CRDs), simplifying the creation of operators and controllers.

Tool providing real-time cost visibility and insights for running applications on Kubernetes, optimizing resource allocation.

Kubernetes Cluster Federation, enabling resource management across multiple Kubernetes clusters from a single control plane.

Kubernetes-native serverless framework, allowing deployment of small bits of code (functions) without managing underlying infrastructure.

System for evolving the Kubernetes API over time, allowing for backwards compatibility and gradual feature deprecation.

Plugins intercepting requests to the Kubernetes API server before object persistence, enforcing policies.

Feature allowing the Kubernetes API to be extended with additional APIs, enabling custom resources and controllers.

Key-value pairs for attaching non-identifying metadata to objects, used for tooling and client retrieval.

Mechanisms (HPA, VPA, Cluster Autoscaler) for automatically adjusting resources based on demand and metrics.

CNCF initiative ensuring consistency and portability across Kubernetes distributions and installations.

API objects automatically created when other objects change state, providing a cluster activity audit trail.

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

Field on resources preventing accidental deletion, ensuring proper cleanup of related resources or external dependencies.

Process of automatically deleting objects that no longer have owners, preventing resource leaks.

Evolved ingress and service networking, providing a more expressive, extensible way to configure traffic routing.

Key-value pairs attached to objects for identification and selection, crucial for organizing and selecting object subsets.

Cluster-wide aggregator of resource usage data, providing CPU and memory metrics for Horizontal Pod Autoscaler.

Software extensions to Kubernetes that use custom resources to manage applications and their components.

Relationship between API objects where one object owns another, used for cascading deletion and orphan handling.

Label query over a set of resources, used for identifying and grouping API objects based on their labels.

Policies and timelines for Kubernetes version releases, support, and deprecation, guiding upgrade planning.

Fully functional Kubernetes clusters running on top of other Kubernetes clusters, enabling multi-tenancy.

Web-based tool for security risk analysis of Kubernetes resource manifests, identifying vulnerabilities.

Kubernetes native configuration management tool that allows customization of YAML manifests without templating.

Technique in Kustomize for creating variations of a common base of Kubernetes resources, enabling environment-specific configs.

Method in Kustomize for modifying existing Kubernetes resources without directly editing the original YAML files.

Cloud security platform providing compliance monitoring and threat detection for containerized environments.

Unit of a container image representing a set of files or changes, crucial for image building and optimization.

Storage mechanism used by container runtimes, allowing efficient storage and quick updates of container images.

Design pattern ensuring only one instance of a distributed application component is active at a time.

Process where multiple instances of an operator elect a leader to prevent conflicts in resource management.

Security concept of giving a user or process only the minimum levels of access necessary to perform its function.

User-friendly, open-source IDE for managing Kubernetes clusters, providing a unified interface for multiple clusters.

Observability platform providing insights into the behavior of highly distributed software systems and microservices.

Kubernetes policy for constraining resource allocations (CPU and memory) for pods or containers in a namespace.

Kubernetes object defining the min, max, and default compute resources for pods and containers in a namespace.

Lightweight service mesh for Kubernetes, providing observability, reliability, and security for microservices.

Component of Linkerd responsible for proxying traffic between services, implementing service mesh functionality.

Linkerd resource providing service-specific traffic metrics and control, enhancing observability and management.

High-performance, minimal-footprint proxy used in Linkerd's data plane for efficient service mesh operations.

Framework allowing various security models to be plugged into the Linux kernel, enhancing container isolation.

Process of connecting external load balancers with Kubernetes services for distributing incoming traffic.

Methods used by load balancers to distribute traffic across multiple container instances or pods.

Kubernetes service type that provisions an external load balancer in cloud environments for routing external traffic to services.

Kubernetes volume type for locally attached storage, providing high-performance storage options for stateful workloads.

Technique for routing traffic to geographically or topologically closer endpoints in distributed container deployments.

Techniques for collecting, processing, and storing logs from distributed containerized applications for centralized analysis.

Design of systems for capturing, storing, and analyzing logs from containers and orchestration platforms.

Horizontally-scalable, multi-tenant log aggregation system designed for use with Prometheus and Kubernetes.

Cloud-native distributed block storage system for Kubernetes, providing persistent storage for stateful workloads.

Implementation of Longhorn for providing resilient, replicated block storage in Kubernetes clusters.

Comparison of container runtimes operating at different abstraction levels, balancing performance and features.

Technique for precomputing and storing query results, improving performance in microservices architectures.