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.

Policies and processes for ensuring data quality, security, and compliance in cloud environments.

Cloud-based tools for combining data from various sources into a unified view, enabling comprehensive data analysis.

Centralized repository storing structured and unstructured data at scale in its native format.

Large-scale storage repository for raw data in various formats in cloud environments.

Hybrid architecture combining data lake storage with data warehouse query capabilities in cloud environments.

Tracking the origin, movement, and transformations of data throughout its lifecycle in cloud systems.

Monitoring data origins, transformations, and usage across cloud environments for compliance and analysis.

Subset of a data warehouse focused on specific business functions or departments in cloud environments.

Techniques to protect sensitive information by obscuring or replacing identifiable data in cloud storage.

Decentralized approach to data management, treating data as a product owned by domain teams in cloud environments.

Tools supporting implementation of data mesh principles in cloud-based data architectures.

Process of transferring data between storage types, formats, or systems in cloud environments.

Automated process for extracting, transforming, and loading data between cloud systems or services.

Systematic analysis of how data processing activities affect privacy in cloud environments.

Cloud-based tools for assessing, improving, and maintaining the quality of data assets.

Specifying the physical location where cloud-stored data resides for compliance with regulations.

Controls for protecting intellectual property and sensitive information in cloud-based data sharing.

Platforms for sharing and monetizing data science models and algorithms in the cloud.

Tools for tracking changes and collaborating on data science projects in cloud environments.

Techniques for managing uneven data distribution in cloud-based parallel processing.

Concept that data is subject to the laws of the country in which it is stored in cloud environments.

Cloud-based tools for replacing sensitive data with non-sensitive equivalents for security purposes.

Capability to access and restore previous versions of data in cloud storage systems.

Technology that provides a unified view of data from multiple cloud and on-premises sources without moving it.

Tools and techniques for creating visual representations of data stored in cloud environments.

Centralized repository optimized for analytics and business intelligence in cloud environments.

Process of collecting, storing, and managing data from varied sources in a central cloud repository for analysis.

Monitoring and recording database activities in cloud environments for security and compliance purposes.

Process of creating copies of databases and recovering them in cloud environments for data protection.

Technique to store frequently accessed data in memory for faster retrieval in cloud databases.

Process of encoding data to protect sensitive information in cloud-based databases.

Automatic switching to a redundant database when the primary system fails in cloud environments.

Techniques ensuring continuous database operation in cloud environments, minimizing downtime.

Process of moving databases from on-premises or other cloud environments to a target cloud platform.

Managed service for migrating databases to cloud platforms with minimal downtime.

Optimizing database operations for improved speed and efficiency in cloud environments.

Intermediary service managing connections between applications and cloud databases for improved security and performance.

Adjusting database resources vertically (more powerful hardware) or horizontally (more instances) in cloud environments.

Distributing data across multiple database instances for improved performance and scalability in the cloud.

Process of updating database software to newer versions in cloud environments, improving performance and security.

Managed cloud service providing database functionality without the need for infrastructure management.

Storage for messages that can't be processed successfully in cloud-based message queuing systems.

Distributed cloud computing model leveraging blockchain technology for increased security and user control.

Blockchain-based platforms for trading compute resources across distributed cloud networks.

Self-sovereign identity management using blockchain technology in cloud environments.

Systems for user authentication and authorization using blockchain in cloud environments.

Distributed file storage systems using peer-to-peer networks in cloud computing environments.

Security approach using decoys to detect, deceive, and deflect attackers in cloud environments.

Contrasting approaches to defining cloud infrastructure, focusing on desired state vs. step-by-step instructions.

Subset of machine learning using neural networks with multiple layers for complex pattern recognition in cloud environments.

Tools and practices for automatically releasing and updating applications in cloud environments.

Service for declaratively managing and deploying cloud resources on Google Cloud Platform.

Automated, end-to-end pipelines for software delivery in cloud environments, streamlining development and deployment processes.

Collaborative approach integrating development and operations teams for efficient cloud-based software delivery.

Measurements for assessing the performance and efficiency of DevOps processes in cloud environments.

Integration of security practices into DevOps processes using automated tools in cloud environments.

Integrated tools for implementing security throughout the DevOps lifecycle in cloud environments.

Tools and practices for configuring, monitoring, and securing IoT devices connected to cloud platforms.

Process of setting up and configuring IoT devices for secure connection to cloud platforms.

Cloud-based tools for adding noise to data to protect individual privacy while maintaining overall accuracy.

Tools for tracking and optimizing user interactions with cloud-based applications and services.

Virtual representations of physical objects or systems, often leveraging cloud resources for simulation and analysis.

Virtual models of physical assets or processes, often using cloud computing for data processing and simulation.

Cloud-based virtual representations of physical entities for monitoring, simulation, and optimization.

Dedicated network connection between on-premises infrastructure and cloud service providers.

Cloud infrastructure designs separating compute, storage, and networking for flexible resource allocation.

Cloud storage architecture separating storage management functions from physical storage devices.

Strategies and tools for recovering data and systems after a catastrophic event in cloud environments.

Process of training machine learning models across multiple cloud nodes for improved speed and efficiency.

Cloud services distributed across multiple physical locations but managed centrally.

Techniques for solving complex problems across multiple cloud nodes while satisfying various constraints.

Cloud-based systems for running data analysis and machine learning tasks across multiple nodes.

Cloud-based security systems deploying decoys across multiple points to detect and mislead attackers.

Process of training AI models across multiple edge devices and cloud resources, enabling decentralized learning at scale.

Technique for tuning machine learning models across multiple cloud nodes for improved performance.

Managing and coordinating blockchain networks across multiple cloud environments.

Tracking and analyzing requests as they flow through cloud-based microservices architectures.

Specialized programming languages designed for efficient cloud resource management and deployment.

Monitoring and identifying unauthorized or unintended changes in cloud infrastructure configurations.

Extension of Azure Functions that enables stateful operations in serverless compute environments.

Adaptive security measures that adjust permissions based on context in cloud environments.

Responsible disposal and recycling of outdated or decommissioned cloud hardware.

Strategies for sustainably disposing of and recycling obsolete cloud computing hardware.

Process of moving data from source systems into a data warehouse in cloud environments.

Approaches to moving to the cloud that minimize environmental impact and energy consumption.

Artificial intelligence algorithms running on devices at the network edge, often integrated with cloud backends.

Methods for reducing the size of AI models to run efficiently on edge devices with cloud support.

Managing and updating AI model versions across distributed edge devices and cloud systems.

Measures to protect AI models and data on edge devices connected to cloud networks.

Artificial intelligence and machine learning capabilities deployed on edge devices, often with cloud integration.

Processing and analyzing data near its source on edge devices before sending insights to the cloud.

Software platforms for developing and deploying analytics applications on edge devices with cloud connectivity.

Identifying unusual patterns or behaviors in data at the network edge before sending alerts to the cloud.

Storing frequently accessed data on edge devices or servers to reduce latency and cloud bandwidth usage.

Network architectures optimized for connecting edge computing devices to cloud resources.

Processing and analyzing visual data on edge devices before sending results to the cloud.

Distributing and caching content on edge servers to reduce latency and cloud bandwidth consumption.

Database systems designed to run on edge devices with intermittent connectivity to cloud backends.

Creating AI-generated content on edge devices with potential cloud-based model updates and synchronization.

Techniques to improve AI model performance on edge devices, reducing latency and cloud dependence.

Kubernetes component that automatically adjusts the CPU and memory reservations for pods to optimize resource utilization.

Resource utilization data used by VPA to make decisions on adjusting pod resource allocations.

Extended VPA functionality allowing scaling decisions based on application-specific metrics.

Kubernetes resource defining the behavior for automatically adjusting pod resource requests and limits.

Isolated environments within a physical Kubernetes cluster, providing multi-tenancy and resource isolation.

Single IP address representing a service, used for load balancing in container networking.

Kubernetes kubelet implementation that masquerades as a node and schedules pods on non-Kubernetes platforms.

Kubernetes volume properties (ReadWriteOnce, ReadOnlyMany, ReadWriteMany) defining how a volume can be mounted.

Process of creating a new volume populated with the contents of an existing volume in Kubernetes.

Feature allowing the size of a persistent volume to be increased without recreating the volume.

Kubernetes feature for detecting and reporting issues with persistent volumes to ensure data integrity.

Kubernetes volume properties (Block, Filesystem) defining how the storage is presented to the container.

Process of making a storage volume accessible within a container's filesystem, enabling data persistence.

Specifications in Kubernetes pod definitions declaring how volumes should be mounted into containers.

Kubernetes components enabling integration with various storage systems for persistent storage.

Point-in-time copies of volumes in Kubernetes, used for backup, restoration, or cloning of persistent data.

Incorporation of security scanning tools into the container build and deployment pipeline.

Set of tools for implementing GitOps workflows in Kubernetes environments, automating deployment and management.

Software-defined networking solution for containerized applications, providing a virtual network across hosts.

Use of Weave Net to create a virtual network connecting Docker containers across multiple hosts.

Use of WebAssembly runtimes in containers for portable, secure, and high-performance applications.

Integration of WebAssembly modules in service mesh proxies for customizable traffic management.

External services invoked during the Kubernetes admission process to validate or mutate API requests.

Kubernetes authorization mode delegating access decisions to an external REST service, enabling custom auth logic.

Kubernetes authentication method verifying bearer tokens against an external webhook service.

CNI IPAM plugin for dynamically allocating IP addresses across multiple nodes in Kubernetes.

Use of the Wireguard VPN protocol to secure container-to-container communication across hosts.

Digital certificates used for authenticating clients in Kubernetes API server communications.

Linux kernel technology for high-performance packet processing, useful in container networking scenarios.

Container advisor that collects, aggregates, and exports resource usage and performance data from running containers.

Second version of control groups, offering a unified hierarchy and improved resource management for containers.

Industry-standard container runtime used by many container and orchestration platforms, providing core container operations.

Core components and architecture of the containerd container runtime, including its image management and execution features.

Intermediary process between containerd and runc, managing container lifecycle and I/O, enhancing isolation.

Use of extended Berkeley Packet Filter for advanced container networking capabilities, enhancing performance and security.

Use of extended Berkeley Packet Filter for deep insights into container behavior and performance.

Integration of eBPF technology in service mesh implementations for improved performance and observability.

Use of eBPF for efficient and detailed monitoring of containerized applications and infrastructure.

Feature ensuring at-rest encryption of data stored in etcd, Kubernetes' distributed key-value store.

Optimization techniques for improving etcd performance in large-scale container orchestration.

Point-in-time copies of etcd's state, used for backup and recovery in Kubernetes clusters.

Process of updating the etcd cluster to a newer version in a Kubernetes environment, ensuring cluster data store reliability.

High-performance, open-source RPC framework used for efficient communication between containerized microservices.

Use of gRPC, a high-performance RPC framework, for communication between containerized microservices.

Container runtime sandbox that provides an additional layer of isolation between containerized applications and the host kernel.

Use of gVisor to enhance security in multi-tenant container environments by isolating containers from the host kernel.

Framework for securing software supply chains, applicable to container image build and distribution processes.

Open-source tool for discovering security weaknesses in Kubernetes clusters through simulated attacks.

Kubernetes network proxy maintaining network rules on nodes, implementing part of the Kubernetes Service concept.

Different implementations of kube-proxy for managing service networking, each with unique performance characteristics.

Kubernetes component responsible for assigning newly created pods to nodes based on resource requirements and constraints.

Primary node agent running on each node in a Kubernetes cluster, ensuring containers are running in a pod as expected.

Linux Containers, a userspace interface for the Linux kernel containment features, providing operating system-level virtualization.

Container runtime focusing on security and composability, offering an alternative to Docker (now deprecated).