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 component allowing plugins to customize the scheduling process without changing the core scheduler code.

Modular components in Kubernetes scheduler implementing specific scheduling behaviors and policies.

Configurations defining sets of scheduling plugins to be used for different scheduling scenarios in Kubernetes.

Use of Berkeley Packet Filter programs to define fine-grained seccomp profiles for container security.

Security profiles defining allowed system calls for containers, enhancing isolation and reducing attack surface.

Kubernetes object for storing and managing sensitive information such as passwords, tokens, or keys.

Process of securely storing, distributing, and rotating sensitive data in containerized environments.

Linux kernel feature limiting the system calls a process can make, often used to secure containers.

Practices ensuring the integrity and security of container images and their dependencies throughout the development lifecycle.

OpenShift object defining a set of conditions that a pod must run with to be accepted into the system.

OpenShift feature for fine-grained control over the actions containers can perform and the resources they can access.

Integration of vulnerability and compliance scans into the continuous integration process for container images.

Tools and platforms for building and deploying serverless applications on container orchestration systems.

Techniques and tools for monitoring, tracing, and debugging serverless functions and applications.

Architectural patterns for designing and implementing serverless applications in containerized environments.

Practices and tools for securing serverless functions and applications in container-based infrastructures.

Orchestration of multiple serverless functions to create complex, event-driven applications.

Kubernetes abstraction defining a logical set of pods and a policy by which to access them.

Kubernetes feature for securely delivering service account tokens to pods, enhancing security.

Credentials automatically generated for pods to authenticate with the Kubernetes API server.

Technique allowing services to locate and communicate with each other dynamically in containerized environments.

Component of a service mesh responsible for managing and configuring the data plane proxies.

Component of a service mesh consisting of proxies that intercept and control service-to-service communication.

Specification defining a set of common APIs for service meshes on Kubernetes, promoting interoperability.

Architectural pattern providing a dedicated infrastructure layer for handling service-to-service communication.

Standard for measuring and characterizing the performance of service mesh deployments, aiding in optimization.

Custom resources in Prometheus Operator for declaratively defining how services should be monitored.

Mechanisms and configurations for enabling network communication between services in container orchestration platforms.

Kubernetes feature allowing services to route traffic based on node topology for improved performance.

Process of verifying the identity of services communicating with each other in a containerized environment.

Kubernetes object providing an identity for processes running in a pod, used for authentication and authorization.

Technique of dividing data across multiple database instances in containerized environments.

Additional containers in a pod that enhance or extend the functionality of the main container.

Design pattern where a sidecar container is deployed alongside the main application container to provide supporting features.

Proxy container deployed alongside application containers to handle network traffic and implement service mesh functionality.

Use of sidecar proxies to implement service mesh features like traffic management and security in Kubernetes.

Open-source application performance monitoring and observability platform for microservices and Kubernetes environments.

Tool facilitating continuous development for Kubernetes applications, handling building, pushing, and deploying application code.

Use of Skaffold to streamline the development workflow for Kubernetes applications in local environments.

Platform providing vulnerability scanning and security management for container images and Kubernetes deployments.

Approach to network management enabling dynamic, programmatically efficient network configuration in container environments.

Tool and workflow for building reproducible container images from source code, simplifying the build process.

Open-source, multi-cloud continuous delivery platform for releasing software changes with high velocity and confidence.

Integration of Splunk's data platform with containerized environments for logging, monitoring, and analysis.

Security platform providing vulnerability management, compliance, and runtime protection for Kubernetes.

Containerized applications that maintain data or state, requiring special considerations for persistence and scaling.

Kubernetes workload API object used to manage stateful applications, providing unique network identities and stable storage.

Design patterns for deploying and managing stateful applications in Kubernetes using StatefulSets.

Pods managed directly by the kubelet on a specific node, without the API server observing them.

Process of pre-creating storage resources in Kubernetes before they are claimed by persistent volume claims.

File-based method for providing authentication tokens to the Kubernetes API server, useful for bootstrap authentication.

Kubernetes API feature allowing updates to an object's status without modifying its spec, enabling more granular updates.

Kubernetes feature for making scheduling decisions based on the available storage capacity of nodes.

Kubernetes objects defining different classes of storage with varying performance characteristics or policies.

Kubernetes object describing the "classes" of storage offered by the administrator, used for dynamic provisioning.

Software-defined storage for cloud-native applications, providing persistent storage for containers.

Incremental approach to modernizing legacy applications by gradually replacing components with microservices.

Network protocols optimized for real-time data transmission in containerized environments.

Kubernetes volume feature allowing mounting a specific directory of a volume instead of its root.

Open-source project enabling direct networking between pods and services across Kubernetes clusters.

Kubernetes API feature representing sub-components of a resource, allowing more granular access control and operations.

Open-source container management system for edge computing, extending Kubernetes to manage edge nodes efficiently.

Security platform providing real-time threat detection and response for containerized environments.

Specification for securing software update systems, applicable to container image distribution.

Kubernetes node attributes that repel certain pods from scheduling unless they have matching tolerations.

Kubernetes mechanism for controlling which pods can be scheduled on specific nodes, enabling node specialization.

Cloud-native CI/CD framework for Kubernetes, providing custom resources for defining pipelines and tasks.

Kubernetes-native CI/CD solution using custom resources to define pipelines as a series of tasks.

Tool allowing developers to run a single service locally while connecting to a remote Kubernetes cluster.

Platform providing vulnerability management and compliance monitoring for container images and registries.

Techniques for separating and securing resources belonging to different users or groups in multi-tenant Kubernetes clusters.

Open-source tool for static code analysis of Infrastructure as Code, including Kubernetes manifests.

Open-source project extending Prometheus for long-term storage and global query view in large-scale deployments.

Use of Thanos to provide durable storage and global query capability for Prometheus metrics.

Technique for limiting the rate at which a containerized service processes requests to prevent overload.

Development environment as code for teams building Kubernetes microservices, streamlining local development.

Settings controlling the maximum duration for various operations in containerized applications and infrastructure.

Kubernetes pod specifications that allow (but do not require) pods to be scheduled on nodes with matching taints.

Kubernetes feature coordinating resource allocation decisions to provide topology-aligned resource allocations.

Technique of duplicating live traffic to a separate service instance for testing or debugging purposes.

Gradual redirection of traffic from one version of a service to another, often used in canary deployments.

Distribution of incoming requests across multiple versions of a service, enabling advanced deployment strategies.

Open-source security scanner for containers and other artifacts, finding vulnerabilities and misconfigurations.

Set of best practices for building software-as-a-service apps that can be easily deployed to the cloud.

Container security platform providing vulnerability management, compliance, and runtime protection (now part of Prisma Cloud).

Comprehensive cloud-native security platform for containers, serverless, and cloud environments.

Physical network infrastructure upon which overlay networks for container communication are built.

Specialized, single-purpose machine images offering potential advantages in size and security over containers.

Filesystem service for Linux allowing files and directories of separate filesystems to be overlaid, forming a single coherent filesystem.

Kubernetes feature allowing a user to act as another user, useful for debugging and testing access controls.

Linux kernel feature providing per-process isolated instances of user and group ID number spaces.

Network virtualization technology used in container networking for creating overlay networks.

Virtual networks using VXLAN encapsulation to enable container communication across hosts.

Design pattern for providing clients with restricted direct access to a specific resource or service.

Admission controller webhooks in Kubernetes that validate resource requests without modifying them.

Kubernetes admission control mechanism for validating API requests against custom logic before persistence.

Open-source tool for backing up and restoring Kubernetes cluster resources and persistent volumes.

Guidelines defining supported version differences between Kubernetes components to ensure compatibility.

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.