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 comparison of two Git commands used to undo changes, with revert creating new commits and reset modifying history.

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 comparison of two Git features used to include external repositories in a project, each with different use cases.

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.

Process of teaching machine learning algorithms to make predictions using data in cloud environments.

Managing different iterations of machine learning models in cloud-based development pipelines.

Repository for storing and managing reusable software components in cloud development environments.

Experimental technique using molecules to store digital data, potentially integrated with cloud systems.

Tools and practices for managing multiple cloud accounts within an organization.

Using services from multiple cloud providers in a single architecture, optimizing for cost, performance, and redundancy.

Centralized platforms for managing data and application integrations across multiple cloud providers.

Distributing workloads across multiple cloud providers to optimize performance and reliability.

Tools and practices for administering resources and applications across multiple cloud providers.

Technologies enabling seamless networking across multiple cloud provider environments.

Coordinating microservices communication and security across multiple cloud environments.

Security system requiring two or more verification methods to access cloud resources.

Database systems supporting multiple data models (e.g., document, graph, relational) in a single backend.

Copying data across multiple geographic regions in cloud environments for redundancy and disaster recovery.

Bringing cloud capabilities closer to the network edge for improved performance and reduced latency.

Tools and strategies for monitoring and optimizing expenses across multiple cloud providers.

Strategies to minimize expenses and maximize efficiency when using multiple cloud providers.

Implementing backup and failover systems across multiple cloud providers for enhanced resilience.

Connecting and managing network resources across multiple cloud provider environments.

Strategies and tools for protecting data and applications across multiple cloud provider environments.

Tools for managing and orchestrating data across multiple cloud provider environments.

Unified network architecture spanning multiple cloud providers for seamless connectivity.

Cloud services supporting AI models that can process and integrate multiple types of data (e.g., text, image, audio).

User interfaces that combine multiple input/output methods (e.g., voice, touch, gesture) for cloud service interaction.

Cloud services for integrating and analyzing data from various sources and formats.

Service that enables private subnet instances to connect to the internet or other AWS services.

Isolated environment within a cluster to organize and manage resources in cloud platforms.

Systems allowing users to interact with cloud services using conversational language.

AI technology for understanding, interpreting, and generating human language in cloud environments.

Cloud-based platforms offering pre-built NLP models and APIs for text analysis and generation.

Smaller data centers located closer to end-users for reduced latency in cloud service delivery.

UI design approach mimicking physical objects for intuitive cloud service interaction.

Rules controlling inbound and outbound traffic for subnets in cloud virtual networks.

Stateless firewall for controlling traffic in and out of cloud subnets, enhancing network security.

Process of modifying network address information to route traffic between private and public networks.

Virtualizing network services traditionally run on proprietary hardware in cloud environments.

Tools for monitoring, analyzing, and troubleshooting cloud network performance and behavior.

Tools and practices for measuring and optimizing network performance in cloud environments.

Technology for managing and securing service-to-service communication in cloud-native environments.

Collecting and analyzing network data for visibility and troubleshooting in cloud environments.

Techniques for improving the efficiency and performance of data flow in cloud networks.

Defining and managing network infrastructure using code in cloud environments, enabling automated and version-controlled networking.

Cloud-based automated design of optimal neural network architectures for specific AI tasks.

Cloud platforms combining neural networks with symbolic reasoning for more robust AI systems.

Cloud-based AI integrating neural networks and symbolic AI for enhanced reasoning capabilities.

Cloud services using brain-inspired computing architectures for improved efficiency in AI tasks.

Cloud platforms providing access to brain-inspired computing architectures for AI applications.

Cloud-based offerings of brain-inspired computing architectures for specialized AI workloads.

Cloud-based AI processing using brain-inspired chip designs for improved efficiency and performance.

Cloud databases combining the scalability of NoSQL with the ACID guarantees of traditional relational databases.

Non-relational databases designed for flexible, scalable data storage and retrieval in cloud environments.

High-performance storage protocol for accessing SSDs over network fabrics in cloud environments.

Technology for quickly analyzing multidimensional data from multiple perspectives in cloud databases.

Cloud storage for unstructured data, accessed via APIs and organized as objects rather than files.

Scalable cloud storage services for unstructured data, accessible via APIs, ideal for large-scale data storage and retrieval.

Devices or software providing local access to cloud-based object storage systems.

Centralized repositories for storing and analyzing large volumes of observability data in cloud environments.

Systems for collecting, processing, and routing observability data in cloud environments.

Software development approach prioritizing built-in monitoring and debugging in cloud applications.

Analyzing and interpreting scent-related data using cloud computing resources, enabling digital olfactory applications.

Running ML models on edge devices, reducing reliance on cloud processing for certain tasks.

Technology for rapid analysis of multidimensional data in cloud-based data warehouses.

Open-source framework for building serverless functions with Docker and Kubernetes in cloud environments.

Kubernetes extension for automating application management tasks in cloud-native environments.

Using light-based processing for high-speed, energy-efficient computation in cloud data centers.

Remote software updates for devices connected to cloud services, often used for IoT.

Adhering to Payment Card Industry Data Security Standard requirements in cloud environments.

Dividing large datasets or databases into smaller, more manageable parts in cloud storage systems.

Pricing structure where users only pay for the cloud resources they actually use.

Billing model where customers are charged based on their actual usage of cloud resources.

Pricing scheme where users are billed only when their serverless functions are invoked.

Direct network link between two virtual private clouds, often in different accounts or regions.

Simulated cyberattacks to evaluate the security of cloud-based systems and applications.

Non-volatile memory that combines speed of DRAM with data persistence, used in cloud storage systems.

Storage resources in cloud environments that exist independently of any specific pod or container.

Light-based chips for high-speed data processing in cloud infrastructure, improving energy efficiency.

Defining and managing continuous integration/deployment workflows using code in cloud environments.

Ability to restore cloud-based data to a specific moment in the past, enabling granular data recovery options.

Implementing and maintaining security and compliance rules across cloud resources.

Creating, updating, and enforcing rules governing cloud resource usage and security.

Serverless platform supporting multiple programming languages for cloud function development.

Using multiple data storage technologies to handle varied data storage needs in cloud applications.

Creating serverless applications using multiple programming languages in cloud environments.

Refining and improving cloud-based systems after initial migration from on-premises.

Deploying encryption methods resistant to quantum computer attacks in cloud systems.

Metric for measuring energy efficiency of cloud data centers, comparing total power consumption to IT equipment power usage.

Using AI to anticipate resource needs and adjust cloud capacity automatically, optimizing performance and cost-efficiency.

Using data analytics and machine learning to forecast future cloud resource requirements and optimize infrastructure.

Using data analytics to anticipate and prevent equipment failures in cloud infrastructure.

Advanced analytics providing recommendations for actions in cloud-based decision making.

Tool for estimating costs of cloud services based on expected usage, helping in budgeting and resource planning.

Techniques for processing sensitive data while preserving privacy in cloud environments.

Tools and methods for protecting personal data privacy in cloud computing, ensuring compliance and user trust.

Techniques for analyzing data in the cloud while maintaining individual privacy.

Extracting useful information from large datasets without compromising individual privacy in the cloud.

Performing data analysis in the cloud while protecting sensitive information, balancing insights with data privacy.

Dedicated 5G networks deployed for specific enterprise use, often integrated with cloud services.

Service enabling private connectivity between VPCs, AWS services, and on-premises applications.

Tools for securing, controlling, and monitoring access to critical cloud resources and data.

Memory-efficient data structures for approximate data analysis 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.