Engineering Glossary

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.

A visual representation of a hash value, often used as a default avatar in Git platforms.

A service that creates, maintains, and manages identity information for users, often integrated with Git platforms.

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.

Cloud-based systems facilitating communication between humans and robots or AI agents.

Kubernetes scheduling constraint that prevents pods from being co-located with other pods based on labels.

Kubernetes object that limits the number of pods of a replicated application that can be down simultaneously.

Stages a pod goes through from creation to termination, including pending, running, succeeded, failed, and unknown phases.

Custom resources in Prometheus Operator for declaratively defining how groups of pods should be monitored.

Mechanisms and configurations for enabling network communication between pods in a Kubernetes cluster.

Additional resources consumed by pod infrastructure on top of the container requests and limits.

High-level summary of where a pod is in its lifecycle, used for pod status reporting and monitoring.

Kubernetes feature allowing importance-based scheduling and eviction of pods when resources are constrained.

Kubernetes object defining privilege and access control settings for a pod or container, enhancing security.

Deprecated Kubernetes feature for cluster-level control over pod security sensitive aspects.

Kubernetes-defined levels (privileged, baseline, restricted) of security settings for pods.

Kubernetes object limiting the number of pods that can be down simultaneously for a given application.

Isolation boundary for one or more containers in a pod, providing shared kernel namespaces and cgroups.

Deprecated cluster-level resource controlling security-sensitive aspects of pod specification.

Tool for managing containers and images without a container daemon, compatible with Docker CLI.

Open-source tool for checking Kubernetes resources against configurable best practices, enhancing reliability.

Use of multiple data storage technologies in microservices architectures to best fit varying data storage needs.

Network address translation technique used in container networking for mapping ports, enabling external access.

Process of forwarding a network port from the host to a container, enabling external access to containerized services.

Web-based management UI for Docker environments, simplifying container operations and monitoring.

Cloud-native storage platform providing persistent storage for containerized applications in multi-cloud environments.

Software-defined storage solution by Portworx for containerized stateful applications in Kubernetes.

Kubernetes scheduling policies that filter out nodes that cannot run a pod, based on resource requirements and constraints.

Kubernetes process of evicting lower-priority pods to schedule higher-priority pods when resources are constrained.

CustomResourceDefinition feature for defining custom columns in kubectl output for custom resources.

Kubernetes scheduling policies that rank nodes that have passed the predicate phase, determining the best placement for a pod.

Kubernetes objects defining the relative importance of pods, used in scheduling and preemption decisions.

Kubernetes feature allowing pods to be assigned different priorities, influencing scheduling and eviction decisions.

Containers running with elevated permissions, potentially accessing host resources and devices.

Deployment strategy gradually rolling out changes to a subset of users or servers, monitoring for issues.

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

Kubernetes volume type that maps several existing volume sources into the same directory, combining multiple configs.

Open-source systems monitoring and alerting toolkit, widely used for Kubernetes and container monitoring.

Component of Prometheus handling alerts, including silencing, inhibition, aggregation, and notifications.

Kubernetes operator that makes it easy to deploy and manage Prometheus instances, simplifying monitoring setup.

Component allowing ephemeral and batch jobs to expose their metrics to Prometheus, enhancing monitoring coverage.

Feature allowing Prometheus to send samples to compatible remote storage systems, enabling long-term storage.

Definitions for recording rules and alerting rules in Prometheus, allowing for complex queries and alert conditions.

Process of choosing the appropriate network protocol for container communication based on requirements.

Kubernetes classifications (Guaranteed, Burstable, BestEffort) for pods based on resource requirements and limits.

Platform providing vulnerability management, policy compliance, and runtime defense for containers.

Container registry by Red Hat offering advanced features like vulnerability scanning and fine-grained access controls.

Kubernetes authorization mechanism for fine-grained control over the actions users can perform.

Guidelines for implementing secure and manageable role-based access control in Kubernetes environments.

Use of role-based access control to implement isolation and access management in multi-tenant Kubernetes clusters.

Integration of Remote Direct Memory Access for high-performance, low-latency container networking.

Platform for managing multiple Kubernetes clusters across different cloud providers and on-premises.

Technique to control the rate of requests or traffic in distributed systems, often implemented in API gateways.

Kubernetes volume type providing direct access to a block device for applications requiring this capability.

Architectural approach emphasizing responsiveness, resilience, elasticity, and message-driven communication in distributed systems.

Security practice of mounting a container's root filesystem as read-only to prevent runtime modifications.

Kubernetes volumes mounted with read-only access, enhancing security by preventing modifications.

Service for storing and distributing container images, crucial for managing and deploying containerized applications.

HTTP API provided by container registries for image management, authentication, and metadata retrieval.

Process of verifying the identity of clients making requests to containerized services or APIs.

Technique of locally caching container images to improve pull times and reduce network usage.

Process of replicating container images across multiple registries for improved availability and reduced latency.

Mechanism for registries to send notifications about events such as image pushes, pulls, or deletions.

Scheduled, periodic releases of software components, often used in microservices architectures for coordinated updates.

Kubernetes controller ensuring a specified number of pod replicas are running at any given time.

Process of verifying the identity of clients making requests to containerized services or APIs.

Technique of duplicating incoming requests to a separate service instance for testing or debugging purposes.

Scheduling strategy aiming to consolidate workloads onto a minimal number of nodes for efficient resource utilization.

Constraints set on the amount of compute resources (CPU, memory) a container can consume, preventing resource hogging.

Kubernetes objects for limiting aggregate resource consumption per namespace, ensuring fair resource allocation.

Specifications of the minimum amount of compute resources required by a container, aiding in scheduling decisions.

Process of optimizing resource allocations for containers to balance performance and efficiency.

Kubernetes object providing constraints that limit aggregate resource consumption per namespace.

Limits on the number of retry attempts for failed operations in distributed systems to prevent cascading failures.

Implementation of automatic reattempts for failed operations in microservices to improve system resilience.

Design pattern for handling transient failures in distributed systems by automatically repeating failed operations.

Kubernetes RBAC object defining a set of permissions within a particular namespace, controlling access to resources.

Kubernetes RBAC object that binds a role to a set of users or service accounts within a namespace.

Kubernetes objects associating Roles and ClusterRoles with users, groups, or service accounts.

Kubernetes RBAC objects defining sets of permissions at namespace or cluster level respectively.

Process of reverting a deployment to a previous version in case of issues with the current version.

Deployment strategy where new versions of an application are gradually rolled out by replacing instances incrementally.

Networking solution for Kubernetes providing native Layer 3 networking without overlays for improved performance.

Open-source cloud-native storage orchestrator for Kubernetes, providing the platform, framework, and support for storage solutions.

Kubernetes operator for file, block, and object storage systems, automating deployment and management of storage services.

Containers running without root privileges, enhancing security by reducing the potential impact of container breakouts.

Lightweight, portable container runtime adhering to the OCI specification, used as a low-level runtime by container engines.

Inner workings and components of the RunC container runtime, including its interaction with Linux kernel features.

Security technology that detects and prevents real-time attacks on containerized applications.

Measures and tools for protecting containerized applications during execution, including threat detection and prevention.

Process of identifying and alerting on security threats to running containers and orchestration platforms.

CRI component responsible for managing the entire lifecycle of a container, including creation, execution, and deletion.

Security policies enforcing mandatory access controls on containers and pods in Linux-based systems.

Monitoring approach focusing on Service Level Objectives to ensure application performance and reliability.

Standard specification for service meshes on Kubernetes, providing a common interface for various implementations.

Standards and implementation for securely identifying and authenticating workloads in dynamic environments.

Use of Single Root I/O Virtualization to provide high-performance networking for containers.

Design pattern for managing data consistency across microservices in distributed transactions.

Implementation of the Saga pattern to maintain data consistency in microservices architectures.

Container runtimes providing additional isolation between the container and the host system for enhanced security.

Techniques for isolating running containers from the host system and each other to enhance security.

Kubernetes API for directly managing the number of replicas of a workload without modifying the entire object.

Kubernetes component responsible for assigning pods to nodes based on resource requirements, policies, and constraints.

External process allowing custom logic to be added to the Kubernetes scheduling decisions.

Methods used by Kubernetes scheduler to determine the best node placement for pods based on various factors.