Engineering Glossary

A variation of Git pull that fetches remote changes and rebases local commits on top of them instead of merging.

A safer alternative to force push, which only updates the branch if it hasn't been modified since your last fetch.

A command that compares the changes between two commit ranges, useful for reviewing rebased branches.

A low-level command that reads tree objects into the index, used in complex merging scenarios.

A log of all reference updates in a repository, useful for recovering lost commits or branches.

Same as Git Reflog, logs that record when the tips of branches and other references were updated in the repository.

The system Git uses to store references (like branches and tags) as files in the .git directory.

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

Adds a new remote repository to your local Git configuration, associating a name with a URL.

A command that removes remote-tracking branches that no longer exist on the remote repository.

Removes a remote repository from your local Git configuration, deleting its associated references.

A feature allowing one Git object to be transparently used in place of another, useful for history rewriting.

A feature that remembers how you resolved merge conflicts and automatically reapplies the resolution.

A command used to undo changes by moving the current branch head to a specific commit.

A Git reset option that updates the working directory and staging area to match the specified commit.

A Git reset option that moves the HEAD to a specified commit without changing the working directory or staging area.

A command that lists commit objects in reverse chronological order, often used as a basis for other commands.

A command used to parse Git revision syntax and return the corresponding object name.

A command that creates a new commit that undoes the changes made by a previous commit.

A command to remove files from both the working directory and the Git repository.

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

A command that summarizes git log output, typically used to create release announcements.

Commits that are cryptographically signed to verify the identity of the committer and ensure integrity.

Tags that are cryptographically signed to verify the identity of the tagger and ensure the tag's integrity.

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

A command that applies a stored stash to the working directory without removing it from the stash list.

A command that applies a stored stash to the working directory and removes it from the stash list.

A command that displays the state of the working directory and the staging area.

A repository embedded within another repository, allowing you to keep a Git repository as a subdirectory of another Git repository.

A command that executes a specified shell command for each initialized submodule in a Git repository.

A feature for managing nested repositories as subdirectories of a parent repository, an alternative to submodules.

A low-level Git command that manipulates the staging area, updating file information and preparing changes for commit.

The communication protocol used between Git clients and servers for efficient data transfer.

A feature allowing multiple working trees to be attached to the same repository, useful for working on different branches simultaneously.

Creates a new working tree associated with the repository, allowing work on multiple branches simultaneously.

A command to list details of each working tree associated with the repository, showing paths and branch information.

A low-level Git command that creates a tree object from the current index, representing a directory structure.

A Git command used to create an archive (zip or tar) of files from a specified commit, useful for creating release packages.

Agreed-upon patterns for naming branches to improve organization and clarity in collaborative projects.

A command to examine the contents and type of Git objects, useful for inspecting repository internals.

A command to resume the cherry-pick process after resolving conflicts in a paused cherry-pick operation.

Levels at which Git configuration can be set: system (all users), global (user), and local (repository).

A command providing detailed statistics about the number and size of objects in a Git repository.

Mechanisms to securely store and retrieve credentials for Git operations, reducing manual authentication.

Custom scripts that determine how Git should generate diffs for specific file types.

A versatile tool for rewriting Git repository history, offering more power and flexibility than git filter-branch.

A more thorough garbage collection process in Git, optimizing repository storage and performance.

A low-level Git command that computes the object ID (SHA-1 hash) for a given file or string, used in Git's internal storage.

Scripts triggered by specific events in Git workflows, used to automate tasks or enforce policies.

The intermediate area in Git where changes are prepared before committing, also known as the staging area.

Individual, uncompressed Git objects stored separately in the object database before being packed.

A command to list the contents of a tree object in Git, showing files and subdirectories.

Custom scripts defining how Git should handle merges for specific file types or patterns.

A low-level Git command that creates a tree object from a specific index or tree listing.

The four fundamental object types used by Git to store repository data and history.

A command to pack references into a single file for improved performance in repositories with many references.

Compressed files containing multiple Git objects, optimizing storage and transfer efficiency in repositories.

Server-side scripts that run after commits have been accepted, often used for notifications or deployments.

Server-side scripts that run before pushed commits are accepted, used to enforce policies or checks.

An improved version of the Git transfer protocol, offering better performance and feature negotiation.

A command to move a series of commits to a new base commit, useful for changing the parent of a branch.

A command to remove old entries from the reflog, useful for cleaning up Git history and freeing space.

A command to combine all loose objects in a repository into packfiles, improving storage efficiency.

Commands to undo changes in Git, with varying impacts on the working directory and staging area.

Techniques and tools for securely storing and accessing sensitive information in Git repositories.

A command that lists references in a Git repository along with their associated commit hashes.

A feature allowing users to check out only a subset of files from a repository, saving space and time.

A command to validate the contents of Git pack files, ensuring data integrity in the object database.

An application that can be installed directly on organizations and user accounts to extend GitHub's functionality.

A version of Markdown with additional features specifically supported on GitHub.

A tool for importing repositories to GitHub from other version control systems or source code hosts.

A feature in GitHub for tracking tasks, enhancements, and bugs for a project.

A platform for posting and finding software development jobs, integrated with GitHub profiles, that was discontinued in 2021.

A platform for developers to sell and buy integrations for GitHub, enhancing workflow and productivity.

A static site hosting service that takes files directly from a GitHub repository to publish websites.

A collaborative documentation feature in GitHub repositories, allowing easy creation and editing of project documentation.

A lightweight, branch-based workflow that supports teams and projects where deployments are made regularly.

A version control workflow that combines feature-driven development and feature branches with issue tracking.

Branching model for Git that defines a strict branching model designed around project releases.

A graphical interface for viewing Git repositories, providing a visual representation of commit history.

Query language for APIs and a runtime for executing those queries with existing data.

A pointer in Git that refers to the latest commit in the current checked-out branch.

A simple program often used as an introduction to a new programming language or environment, including Git tutorials.

A method for quickly patching production releases by branching directly from the main branch or a tag.

Also known as the staging area, where changes are prepared before committing in Git.

Predefined structures for creating new issues in Git repositories, ensuring consistent and complete information.

A static site generator often used with GitHub Pages to create websites from Markdown files in a Git repository.

A tool in GitHub Pages that allows users to easily select and apply pre-designed themes to their Jekyll sites.

Git Large File Storage, an extension for versioning large files in Git repositories.

A library used by GitHub to detect the programming languages used in repositories.

A lightweight markup language commonly used for documentation in Git repositories.

Formerly the default name for the primary branch in Git repositories, now often replaced by 'main'.

The process of combining changes from different branches into a single branch, integrating multiple lines of development.

An application that uses the OAuth protocol to access Git platform APIs on behalf of users.

A secure string used for authentication in Git operations, allowing access to resources without sharing passwords.

The default name for the remote repository from which a local repository was cloned.

A file describing changes between versions, used to share and apply modifications across different Git repositories.

A Git command that fetches changes from a remote repository and merges them into the current branch.

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.

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.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Kubernetes operators implemented using Ansible for automating application lifecycle management.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Security configuration guidelines for deploying containers securely in various environments.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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