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.

Machine learning models deployed and executed on edge devices, often with cloud-based training or updates.

Techniques for reducing the size of AI models to run efficiently on resource-constrained edge devices.

Performing text analysis and language understanding tasks on edge devices with cloud support.

Managing and coordinating distributed edge computing resources and their interaction with the cloud.

Using AI on edge devices to forecast equipment failures, with cloud-based model updates and analysis.

Training AI agents on edge devices through interaction with the environment, supported by cloud resources.

Measures to protect data, devices, and applications at the network edge in cloud-connected systems.

Distributed network layer for managing service-to-service communication in edge computing environments.

Data storage systems designed for edge devices with intermittent connectivity to cloud backends.

Applying knowledge from pre-trained cloud models to new tasks on edge devices with limited data.

Creating applications specifically designed to run on edge devices with cloud integration capabilities.

Software development paradigms optimized for creating applications that run on edge devices.

Seamless integration of edge computing resources with centralized cloud infrastructure and services.

Cloud networking component allowing outbound internet communication while blocking inbound traffic.

Fully managed service for deploying and scaling web applications and services on AWS infrastructure.

Static public IP address that can be dynamically assigned to cloud resources, providing consistent access points for applications.

Virtual network interface that can be attached to instances in a VPC, providing flexible networking capabilities.

Virtual network cards that can be attached, detached, and moved between cloud instances.

Integration of analytical capabilities directly into cloud-based applications and workflows.

Cloud-based platforms for analyzing and responding to human emotions in various applications.

Cloud services using AI to detect and respond to user emotions for enhanced interactions.

Protecting data by encoding it both when stored and while moving between cloud systems.

Techniques for securing data both when stored in cloud systems and while being transmitted.

Cloud resource scaling that considers energy consumption alongside performance metrics.

Allocating cloud resources to tasks with consideration for energy consumption and efficiency.

Computing methods designed to minimize energy consumption in cloud environments.

Allocating cloud resources to optimize energy efficiency while meeting performance requirements.

Documenting cloud providers' sustainability and ethical practices for stakeholder transparency.

Open-source edge and service proxy designed for cloud-native applications, providing features like load balancing and observability.

Adherence to principles ensuring fair and responsible use of AI in cloud environments.

Fully managed event routing service for building event-driven applications in Azure.

Storing the state of a system as a sequence of events in cloud-based applications.

Real-time analysis of data streams in cloud environments for immediate insights.

System design where actions are triggered by events in cloud environments, enabling responsive and scalable applications.

Connecting cloud services and applications based on event occurrences, enabling real-time data flow and processing.

APIs that trigger or respond to events in cloud-native applications, enabling real-time data processing and integration.

Developing cloud applications that respond to and generate events, enabling reactive and scalable architectures.

Serverless event bus for building event-driven applications in AWS, facilitating communication between various services.

Data consistency model where all replicas eventually reach a consistent state in distributed cloud systems.

Cloud systems capable of at least one exaFLOPS, or a billion billion calculations per second.

The runtime context in which cloud functions or applications operate, including libraries, dependencies, and configurations.

Monitoring and recording parameters and results of machine learning experiments in cloud environments.

Cloud services for making AI decision-making processes more transparent and interpretable.

Tools for developing AI models with transparent decision-making processes in cloud environments.

Cloud services offering tools to make AI models' decision-making processes more understandable.

Service for creating private connections between Azure datacenters and on-premises infrastructure.

Data integration process where transformation occurs after loading data into the cloud target system.

Process of extracting data from sources, transforming it to fit operational needs, and loading into a target database in the cloud.

Extending cloud capabilities to devices at the extreme edge of the network, like IoT sensors.

Tools for dynamically enabling or disabling features in cloud applications without code deployments.

Centralized repository for storing, managing, and serving machine learning features in cloud environments.

Analyzing data across multiple cloud or edge locations without centralizing the raw data.

System allowing integrated data access across multiple autonomous database management systems in the cloud.

Machine learning technique that trains algorithms across decentralized devices or servers holding local data samples.

Coordinating federated learning processes across multiple edge devices or cloud nodes.

Cloud-based systems for implementing and managing federated learning across distributed datasets.

Applying federated learning techniques to train models on edge devices connected to cloud systems.

Tools for executing queries across multiple distributed databases or data sources in cloud environments.

Cloud service for storing and accessing file data through shared file systems, providing scalable and manageable data storage.

Cloud services providing scalable file storage accessible from multiple compute instances.

Tools and processes for automating financial operations and optimization in cloud environments.

Framework for managing and optimizing cloud costs across an organization, aligning financial and operational goals.

AI-driven tools for continuously optimizing cloud spend and resource allocation.

Security system that monitors and controls incoming and outgoing network traffic in cloud environments.

Open-source, Kubernetes-native serverless framework for building microservices in the cloud, simplifying application deployment.

Extending cloud computing to the edge of the network, bringing processing closer to data sources.

Using historical data and algorithms to predict future trends or values in cloud-based analytics.

Cloud-based encryption allowing computations on encrypted data without decryption.

Tools for building complex serverless applications by combining multiple cloud functions.

Cloud computing model where developers run and manage application functionalities without complex infrastructure.

Adhering to EU data protection regulations in cloud-based data processing and storage.

Cloud compute instances equipped with Graphics Processing Units for parallel processing tasks.

Cloud-based services for creating AI models that can generate new content or data.

Cloud-based systems for analyzing large volumes of location-based data efficiently.

User interfaces that interpret hand or body movements to interact with cloud services.

Methodology using Git repositories as the source of truth for declarative infrastructure and applications in the cloud.

Service that improves availability and performance of applications by optimizing traffic routing across cloud regions.

Database systems that replicate and distribute data across multiple geographic locations in the cloud.

Rules and constraints applied to resources within a Google Cloud organization, enforcing governance and compliance.

Cloud services for analyzing and visualizing complex relationships in large datasets using graph structures.

NoSQL databases designed to store and query data with complex relationships in cloud environments.

Practices and technologies aimed at reducing the environmental impact of cloud data centers and operations.

Practices for developing cloud software that minimizes energy consumption and environmental impact.

Techniques for developing cloud applications that optimize resource usage and reduce environmental impact.

Adhering to US healthcare data protection regulations in cloud-based systems and applications.

Transmitting touch and motion sensations through cloud-connected devices for immersive experiences.

Automated tests to verify the availability and proper functioning of cloud resources and services.

Utilizing excess heat generated by cloud data centers for other purposes, improving energy efficiency.

Packages of pre-configured Kubernetes resources for deploying applications in cloud environments.

Systems managing data across diverse database types and locations in cloud environments.

Using cloud resources for solving complex computational problems requiring significant processing power.

Advanced 3D visualization interfaces for interacting with cloud services and data.

Conceptual cloud data centers using holographic technology for data storage and processing.

Experimental technology using holograms to store data in cloud environments, potentially offering high density.

Experimental data storage technique using holograms in cloud systems for high-density, long-term preservation.

Cloud-based offerings that enable computations on encrypted data without decryption.

Cloud-based service offering encryption that allows computations on encrypted data.

Encryption technique allowing computations on encrypted data without decryption in cloud environments.

Adding more machines to a cloud system to distribute load and increase capacity.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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