Engineering Glossary

A feature in Git platforms that allows users to notify specific team members or reference issues by using the @ symbol followed by a username.

A feature allowing developers to test and provide feedback on new Git API functionality before it's officially released.

A Git repository containing version control information without a working directory, typically used as a central repository for collaboration.

A Git command used to perform a binary search through a repository's history to identify the commit that introduced a bug or issue.

An integrated CI/CD service in Bitbucket for automating builds, tests, and deployments.

A Git feature that shows which user last modified each line of a file, helping developers trace changes and understand code history.

A collaborative process of analyzing Git blame information to identify the source of bugs or issues in a codebase.

A parallel version of a repository, allowing developers to work on different features or experiments without affecting the main codebase.

Rules enforced on Git branches to ensure code quality, require reviews, or restrict certain actions before merging.

A premium subscription tier offered by Git hosting services, providing advanced features and support for enterprise users.

A digital certificate issued by a Certificate Authority, used in Git to establish secure HTTPS connections and verify server identities.

A temporary storage area that holds frequently accessed data for quick retrieval, improving system performance.

A Git command used to switch between different branches or restore files from a specific commit in a repository's history.

A Git operation that applies the changes from a specific commit to the current branch, useful for selective code integration.

The practice of selecting and applying specific commits from one branch to another in Git, often used for targeted bug fixes.

The process of creating a local copy of a remote Git repository, allowing developers to work on the codebase independently.

A file specifying individuals or teams responsible for code in different parts of a repository.

Operation in version control systems that saves changes to the local repository, creating a new revision with a unique identifier.

A situation in Git where incompatible changes have been made to the same part of a file, requiring manual resolution before merging.

Practice of merging all developer working copies to a shared mainline several times a day.

Directed Acyclic Graph, the underlying data structure used by Git to represent the commit history and relationships between commits.

A Git operation that moves the HEAD pointer to a specific commit, allowing for temporary exploration of historical states.

A Git command or operation that shows the differences between two commits, branches, files, or other Git objects.

Refers to the direction of change propagation in Git, typically from a parent branch to its child branches or forks.

A feature in Git platforms for browsing repository contents, viewing files, and navigating through different branches.

A Git pattern where each new feature is developed in a dedicated branch, then merged back to the main branch.

A Git command that retrieves changes from a remote repository without automatically merging them into the local branch.

A Git push operation that overwrites the remote branch's history with the local branch, potentially causing data loss if used carelessly.

A personal copy of another user's repository on a Git hosting platform, allowing independent development without affecting the original project.

A no-cost tier offered by Git hosting services, typically with limited features and storage for individual users or small projects.

An encryption software used with Git for signing commits and tags, enhancing security and verification.

A simple way to share code snippets, notes, or small files using Git, often integrated into Git platforms.

Distributed version control system for tracking changes in source code during software development.

A custom shortcut command defined by users to simplify complex or frequently used Git operations.

A mechanism in Git allowing a repository to borrow objects from another repository, useful for saving disk space in large projects.

A Git command that shows the author and commit information for each line in a file, similar to the "blame" feature.

A Git feature that tells the system to temporarily ignore changes to a tracked file, useful for local configuration files.

A mechanism in Git for defining attributes on a per-path basis, controlling how Git handles certain files or directories.

A Git command used to perform a binary search through the commit history to find the commit that introduced a bug.

An automated version of Git Bisect that uses a script to determine if each checked-out commit is "good" or "bad".

An enhanced version of Git Blame that detects lines moved or copied from other files, providing better change tracking.

A Git command that creates a single file containing all the data needed to recreate a repository's branch or history.

Commands to create and verify Git bundles, useful for transferring repository data without using a network.

A quick reference guide summarizing common Git commands and their usage, helpful for both beginners and experienced users.

A Git command used to find commits that haven't been merged upstream, useful for identifying changes to be applied to another branch.

A command to remove untracked files from the working directory, helping to maintain a clean repository state.

A command that allows you to modify the most recent commit, adding new changes or updating the commit message.

A command that allows you to modify the most recent commit, changing its message or contents, and update it without creating a new commit.

Scripts that run automatically before or after a commit, allowing you to enforce rules, format code, or perform checks on changes.

Predefined structures for commit messages, helping maintain consistency and include necessary information in commits.

Metadata added to the end of commit messages, often used for things like issue references or sign-offs.

A file format used to store commit graph structure, improving performance for operations that traverse commit history.

A command to check the integrity and validity of the commit-graph file in a Git repository.

A low-level Git command used to create a new commit object from an existing tree object.

A command and system for setting configuration options for Git on a global, local, or repository level.

A diagnostic command that provides statistics about the number and size of objects in a Git repository.

A system that securely stores and retrieves credentials for Git operations, reducing the need for manual authentication.

A lightweight server for the Git protocol, allowing anonymous read access to Git repositories.

Objects in Git that are not reachable from any reference, often created during rebasing or other history-altering operations.

A command that generates a human-readable name for a commit based on the most recent tag and additional commit information.

A command that shows changes between commits, branches, files, or the working directory and the index.

Various methods used by Git to compute differences between versions of files, optimizing for different scenarios.

An external program or interface used to visualize differences between files or commits in a more user-friendly manner.

A command that fetches updates from all remote repositories configured in a Git project.

A powerful tool for rewriting Git history, allowing for large-scale changes across many commits.

A branching model for Git that defines a strict branching structure designed to support multiple parallel developments.

The process of creating a personal copy of someone else's project, allowing for independent development without affecting the original.

A command that verifies the connectivity and validity of objects in the Git database.

Verifies the integrity of objects in the Git database, checking for corruption and inconsistencies.

A security feature in Git that uses GPG to sign and verify commits and tags, ensuring authenticity.

A process that optimizes the Git repository by removing unnecessary files and compressing objects.

Short for Git Garbage Collection, a command to clean up unnecessary files and optimize the repository.

A command for searching files in a Git repository using regular expressions or simple string matching.

A script that Git automatically runs before or after specific events, like commits or merges, to customize workflows and enforce rules.

Same as Git Hook, scripts triggered by various Git actions to automate tasks or enforce policies.

A mechanism to specify intentionally untracked files that Git should ignore, typically defined in a .gitignore file.

The internal format used by Git to store the staging area information, representing the next commit to be made.

A command used to initialize a new Git repository, creating the necessary directory structure for version control.

A feature allowing users to modify commits in their branch history, useful for cleaning up before merging.

The underlying data structures and mechanisms Git uses to store and manage version control information.

A command to parse and manipulate the trailer lines typically found at the end of commit messages.

A system that manages large files by storing them outside the main repository, replacing them with lightweight pointers to improve performance and efficiency.

An extension that replaces large files with text pointers in Git, while storing the file contents on a remote server.

A command to display the commit history of a repository, showing details like author, date, and commit message.

A set of tasks performed to keep a Git repository in good condition, including garbage collection and optimization.

Different algorithms used by Git to combine separate development histories when merging branches.

External programs or interfaces used to resolve merge conflicts in a more visual and user-friendly manner.

A command that finds the best common ancestor between two commits, useful for determining the point where branches diverged.

A feature that improves performance for repositories with many pack files by creating an index across multiple packs.

A feature allowing multiple references (like branches or tags) with the same name to coexist by separating them into different namespaces.

A way to add or inspect object notes, allowing additional information to be attached to Git objects without changing their SHA-1 hash.

The system Git uses to store all the versions of files, commits, and other objects in a content-addressable filesystem.

Compressed files containing Git objects, used to efficiently store and transfer repository data.

The internal format used by Git to store multiple objects efficiently in a single file, reducing disk usage and improving performance.

A feature allowing users to clone a repository without downloading all of its objects, saving bandwidth and storage.

A file format representing changes between versions, used for sharing and applying modifications across different repositories.

Low-level Git commands that expose the internal workings of Git, primarily used for scripting and advanced operations.

User-friendly commands for everyday tasks, like git status and git commit, designed for ease of use and clear output.

The native network protocol used by Git for efficient data transfer between repositories.

A command that removes objects that are no longer reachable from any references in the repository.

Network architectures allowing customization of data packet processing in cloud infrastructure.

Technique for gradually rolling out new features to subsets of users in cloud applications.

Asynchronous communication pattern for decoupled microservices in cloud architectures.

Infrastructure-as-Code tool for deploying and managing cloud resources using programming languages.

Quantum computing technique for solving optimization problems in cloud environments.

Cloud-based emulation of quantum circuits for algorithm development and testing.

Interface for accessing and controlling quantum computing resources in the cloud.

Cloud-based platforms offering access to quantum computing resources and algorithms.

Experimental database systems leveraging quantum principles for enhanced performance in the cloud.

Techniques for mitigating errors in quantum computations performed in cloud environments.

Experimental cloud services utilizing quantum communication for enhanced security and speed.

Secure communication method using quantum mechanics principles in cloud environments.

Infrastructure for ultra-secure data transmission using quantum principles in cloud systems.

Systems for ultra-secure data transmission using quantum mechanics in cloud environments.

Applying quantum computing techniques to machine learning tasks in cloud environments.

Cloud-based platforms offering quantum-enhanced machine learning algorithms and resources.

Using quantum computing to solve complex optimization problems in cloud environments.

Tools and libraries for developing quantum algorithms in cloud computing environments.

Assessing quantum computational requirements for algorithms in cloud environments.

Tools for creating and testing quantum algorithms in cloud computing platforms, enabling quantum application development.

Demonstrating quantum computers' ability to outperform classical computers in specific tasks.

Metric for measuring the capability and performance of quantum computing systems in the cloud.

Cloud-based access to quantum computing resources and algorithms, enabling exploration of quantum applications.

Algorithms combining quantum and classical computing techniques for enhanced problem-solving in the cloud.

Classical algorithms that emulate quantum computing concepts to solve problems efficiently in the cloud.

Optimization technique inspired by quantum annealing, used for complex problems in cloud computing.

Algorithms based on quantum concepts for identifying unusual patterns in cloud data.

Encryption methods inspired by quantum principles, designed for use in classical cloud systems.

Techniques for data representation inspired by quantum states, used in classical cloud computing.

Optimization methods combining evolutionary principles with quantum concepts in cloud environments.

Data transformation techniques based on quantum principles for machine learning in the cloud.

Applying quantum-like algorithms to financial analysis and prediction in cloud environments.

AI models for data generation based on quantum computing principles, used in classical cloud systems.

Classical ML algorithms incorporating quantum computing concepts for improved performance in the cloud.

NLP techniques leveraging quantum computing principles in classical cloud environments.

AI models mimicking both neural and quantum systems for enhanced learning in cloud computing.

Classical algorithms using quantum-like approaches for solving complex optimization problems in the cloud.

RL techniques incorporating quantum principles for improved decision-making in cloud environments.

Data sampling methods based on quantum principles, used in classical cloud computing tasks.

Data structures and algorithms inspired by quantum tensor networks, used in classical cloud computing.

Encryption methods designed to withstand attacks from future quantum computers in cloud systems.

Database systems designed to maintain security against potential quantum computer attacks in the cloud.

Cloud-based HSMs designed to resist attacks from both classical and quantum computers, ensuring long-term data protection.

Encryption techniques designed to be secure against both quantum and classical attacks in cloud environments.

Classical algorithms mimicking quantum principles to improve AI performance in cloud environments.

Techniques for improving the efficiency and speed of database queries in cloud environments.

Metrics for assessing the usage and financial impact of Reserved Instances in cloud environments.

Process of moving applications to a new cloud platform, often involving some code modifications.

Development paradigm for building responsive, resilient applications in cloud environments.

Copy of a database that allows read-only queries, improving performance and scalability in cloud environments.

Multiple copies of a database for distributing read operations, enhancing performance in cloud systems.

Instantaneous processing and analysis of data as it's generated in cloud environments.

Systems for continuous data processing and analysis in cloud environments with minimal latency.

Process of standardizing diverse data formats in real-time within cloud environments.

Ensuring immediate consistency of data across multiple cloud systems or locations.

Continuous tracking and analysis of business processes in cloud-based systems, enabling rapid decision-making.

Combining data from multiple sources instantly in cloud-based systems, enabling up-to-date analytics and decision-making.

Instantaneous generation and submission of compliance reports in cloud environments.

AI-driven tools suggesting items or actions to users based on data analysis in the cloud.

Generation and submission of compliance-related reports using cloud-based tools and data.

Cloud-based solutions for managing regulatory compliance and reporting, streamlining governance processes.

AI technique where agents learn optimal behaviors through trial and error in cloud environments.

Simulated or real-world scenarios for training AI agents in cloud-based systems.

Managed cloud service for deploying, operating, and scaling relational databases.

Certificates representing clean energy used to power cloud data centers, promoting sustainable cloud operations.

Tracking and optimizing the use of clean energy certificates in cloud operations.

Cloud-based environments ensuring scientific experiments can be replicated precisely.

Optimizing the use of pre-purchased cloud resources to maximize cost savings and ensure resource availability.

Administering pre-purchased cloud instances to optimize costs and resource allocation.

Strategizing the purchase of discounted cloud instances for long-term use to reduce costs.

Pre-purchased cloud compute capacity offered at a discount for a committed term.

Visual representation of cloud resources and their relationships for better management and insight.

Structuring and categorizing cloud resources for efficient management and access control.

Restrictions on the amount or type of cloud resources that can be consumed by a user or account.

Assigning metadata to cloud resources for better organization, management, and cost allocation.

Using metadata tags to track and allocate cloud costs across different projects or departments.

Rules determining how long data is kept in cloud storage before being deleted or archived.

Data privacy principle allowing individuals to request deletion of their personal data from cloud systems.

Adjusting cloud resource allocations to match actual usage, optimizing performance and cost.

Cloud-based systems for coordinating and monitoring multiple robots in industrial or commercial settings.

Cloud-based platform for remotely operating and managing robotic systems, enabling scalable robotics applications.

Using cloud-based software robots to automate repetitive tasks and workflows, improving efficiency and accuracy.

Controlling robots remotely using cloud infrastructure for communication and processing.

AI-driven tools for identifying the source of issues in cloud systems, speeding up troubleshooting and resolution.

Configuration defining network traffic paths between subnets and gateways in cloud environments.

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

Adherence to security and privacy standards for cloud service providers handling customer data.

Digital certificates ensuring secure, encrypted connections to cloud services and applications.

Flexible pricing model offering lower prices on cloud compute usage in exchange for a commitment.

Tools for securely storing, accessing, and managing sensitive information in cloud environments.

Cloud services enabling collaborative computation while keeping individual inputs private.

Proactively testing cloud system resilience by simulating security incidents and failures.

Virtual firewall for controlling inbound and outbound traffic to cloud resources.

Virtual firewalls controlling inbound and outbound traffic for cloud instances within defined security rules.

Platforms integrating security tools and automating incident response in the cloud.

Cloud databases using AI to automate administration, optimization, and security tasks.

Tools allowing non-technical users to perform data analysis in cloud environments without IT assistance.

Standards enabling meaningful data exchange between different cloud systems and services.

AI services that automatically scale and manage underlying infrastructure in cloud environments.

Framework for building and deploying serverless applications in cloud environments.

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.