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.

Cloud-hosted version of ROS, providing robotics middleware and tools as a service.

Platforms for simulating and testing robotic systems using cloud computing resources.

Services for processing and rendering 3D audio experiences using cloud computing resources.

Factory automation systems leveraging cloud resources for data processing, analytics, and remote management.

Systems using cloud computing to enhance navigation capabilities of autonomous vehicles or robots.

Systems using cloud computing to enhance navigation capabilities of autonomous vehicles or robots.

Implementations of ACID properties for database transactions in distributed cloud environments.

Integrated security solutions designed to protect cloud-native applications throughout their lifecycle.

Specialized software for identifying and resolving issues in cloud-native applications and microservices.

Frameworks and services optimized for training and deploying deep learning models in cloud environments.

Specialized hardware accelerators optimized for cloud-native workloads and accessible as cloud services.

Network security tools designed specifically for protecting cloud-native applications and infrastructure.

Cloud-based services providing hardware-level encryption key management and cryptographic operations.

Integrated development environments optimized for building and deploying cloud-native applications.

Interactive computing environments for data analysis and machine learning, designed for cloud deployment.

Traffic distribution services designed specifically for cloud-native applications and microservices architectures.

Virtualized network services designed to run in containerized environments, optimized for cloud infrastructure.

Network services built as microservices, optimized for deployment in cloud-native environments.

Scalable platforms for training AI agents using reinforcement learning algorithms in cloud environments.

SIEM solutions designed for collecting and analyzing security data from cloud-native applications.

Automated coordination of security tools and processes in cloud-native environments.

Process of redesigning applications and infrastructure to fully leverage cloud-native technologies and practices.

BCI systems that use cloud computing for data processing and AI-driven interpretation of brain signals.

Design approach for building applications that can run on multiple cloud platforms without significant modifications.

Technology enabling virtual access to specialized AI hardware accelerators in the cloud.

Services for processing and delivering AR experiences using cloud computing resources.

Frameworks for building AI systems that mimic human cognitive processes using cloud resources.

Using cloud computing resources to perform complex calculations required for mining digital currencies.

Managed services for connecting, monitoring, and controlling Internet of Things devices using cloud infrastructure.

Services for automating repetitive tasks and workflows using software robots hosted in the cloud.

Platforms offering drag-and-drop interfaces for creating applications without traditional coding, hosted in the cloud.

Practices and tools for building, training, and deploying AI models optimized for cloud environments.

Techniques and tools for leveraging cloud-based GPUs to accelerate computational tasks in cloud-native applications.

Process of moving applications and data from one cloud provider to another, optimizing for cost, performance, or features.

Unified computing paradigm combining cloud, edge, and fog computing for optimal data processing and latency.

Infrastructure-as-Code service for defining and provisioning AWS infrastructure using declarative templates.

Visual tool for creating, viewing, and modifying AWS CloudFormation templates, simplifying infrastructure-as-code development.

Small-scale cloud data centers located at the edge of the network to support low-latency applications.

Lightweight application layer protocol designed for constrained devices in Internet of Things (IoT) environments.

Delay in executing serverless functions when they haven't been used recently and need to be initialized.

Multiple robots working together, leveraging cloud resources for coordination and shared learning.

Cloud-based tools enabling teams to jointly design and refine data models for applications.

Cloud platforms supporting team-based data analysis, model development, and knowledge sharing.

Cloud-based recommendation systems processing large datasets to suggest items based on user preferences.

Database storage format optimized for analytical queries in cloud data warehouses.

Architectural pattern separating read and write operations in cloud-based applications.

Real-time analysis of data streams to identify and respond to specific patterns or events in cloud environments.

Standardized guidelines for ensuring cloud systems meet regulatory requirements (e.g., GDPR, HIPAA, PCI DSS).

Regulatory standards guiding data protection and security practices in cloud computing.

Continuous assessment of cloud systems and practices to ensure adherence to regulatory standards.

Cloud service allowing dynamic assembly of virtualized compute, storage, and networking resources.

Storage devices with built-in processing capabilities, enabling data processing within the storage subsystem.

Storage hardware with integrated computing resources for in-situ data processing in cloud environments.

AI technology that enables machines to interpret and understand visual information from images or videos.

Cloud services offering pre-built models and tools for image and video analysis tasks.

Simultaneous execution of multiple computations or processes in cloud environments.

Technology protecting data in use by performing computation in a hardware-based trusted execution environment.

Isolated environments in cloud infrastructure for secure processing of sensitive data.

Monitoring and identifying unintended changes in cloud resource configurations over time.

Permissioned blockchain network operated by a group of organizations in a cloud environment.

Serverless compute platforms for running containers without managing the underlying infrastructure.

Optimizing container resource allocations to improve efficiency and reduce costs in cloud environments.

Technologies and practices for managing network connectivity between containerized applications in the cloud.

Tools and practices for protecting containerized applications during execution in cloud environments.

Measures and tools for protecting containerized applications and their data in cloud environments.

User interfaces that adapt based on user context, device capabilities, and environmental factors.

Dynamic approach to security that continuously analyzes and adapts to changing risks in cloud environments.

Ongoing process of assessing and improving security risks in cloud infrastructure configurations.

Automated, real-time tracking and reporting of compliance status for cloud resources and applications.

Ongoing validation of data quality, integrity, and consistency in cloud-based data pipelines and storage systems.

Automated process of releasing code changes to production environments in cloud infrastructure.

Automated pipeline for building, testing, and deploying applications in cloud environments.

Ongoing process of improving cloud resource utilization, performance, and cost-efficiency.

Constant monitoring and analysis of application performance in cloud environments to identify bottlenecks.

Ongoing process of adjusting cloud resource allocations to match actual usage and demand.

Automated process of regularly updating machine learning models with new data in cloud environments.

Ongoing process of validating cloud infrastructure and applications against defined policies and configurations.

Process of distributing cloud expenses across different departments, projects, or cost centers within an organization.

Automated identification of unusual or unexpected patterns in cloud spending, helping optimize resource allocation and budgeting.

Associating cloud expenses with specific resources, services, or business units for accurate accounting.

Tool for visualizing and analyzing cloud spending patterns and trends, helping optimize resource allocation and budgeting.

Automated suggestions for reducing cloud expenses while maintaining performance and reliability.

Intelligent scaling of cloud resources considering both performance requirements and cost implications.

Ensuring cloud data transfers comply with international data protection regulations.

Synchronizing data across multiple cloud providers for redundancy and disaster recovery.

Blockchain-based agreements executable across different cloud platforms, enabling multi-cloud decentralized applications.

Execution environments for cloud-native applications that work across multiple cloud providers.

Services for securely generating, storing, and rotating encryption keys in cloud environments.

Services defending against Distributed Denial of Service attacks on cloud-based applications and infrastructure.

Experimental technology using DNA molecules to store digital data, potentially leveraging cloud for processing.

Experimental technique using DNA molecules to store digital data, potentially integrated with cloud for processing and retrieval.

Managed Domain Name System services provided by cloud platforms for translating domain names to IP addresses.

Portable runtime for building microservices-based applications across cloud and edge environments.

Tools for creating interactive, visual representations of cloud data and metrics.

Centralized repository for metadata about an organization's data assets in the cloud.

Tools for organizing, indexing, and searching data assets across cloud environments.

Categorizing data based on sensitivity and importance for appropriate handling in cloud storage.

Monitoring changes in data distributions that may affect machine learning model performance in cloud environments.

Integrated architecture for managing and accessing data across diverse cloud and on-premises environments.

Unified data management framework spanning multiple cloud and on-premises environments.

System for collecting, processing, and storing performance metrics from containerized applications and infrastructure.

Kubernetes add-on that collects resource metrics from kubelets for use in autoscaling and monitoring.

Techniques for improving the performance and efficiency of the Kubernetes Metrics Server for better monitoring.

Lightweight, CNCF-certified Kubernetes distribution designed for developer workstations, IoT devices, and CI/CD.

Reusable base structure for building microservices, providing common functionalities like logging and monitoring.

High-performance, S3-compatible object storage system, often used for persistent storage in container environments.

Feature allowing containers to share mounted volumes, enabling advanced storage scenarios in Kubernetes.

Design patterns for deploying multiple containers within a single pod, such as sidecar, ambassador, or adapter patterns.

Container images supporting multiple CPU architectures, enabling deployment flexibility across diverse hardware.

Tools and practices for administering and orchestrating multiple Kubernetes clusters as a unified system.

Technologies and configurations enabling network connectivity and service discovery across multiple Kubernetes clusters.

Coordinated management and deployment of containerized applications across multiple Kubernetes clusters.

Mechanisms for locating and accessing services deployed across multiple Kubernetes clusters.

Implementation of service mesh functionalities spanning multiple Kubernetes clusters for unified traffic management.

Dockerfile technique using multiple stages to create optimized, smaller container images by separating build and runtime environments.

Performance and isolation tests for evaluating the effectiveness of multi-tenant Kubernetes cluster configurations.

CNI plugin enabling attachment of multiple network interfaces to pods in Kubernetes, supporting advanced networking scenarios.

Container Network Interface plugin allowing multiple CNI plugins to be used simultaneously, enabling multi-network support for pods.

Use of Multus to attach pods to multiple networks, enabling complex networking scenarios in Kubernetes.

Admission controller webhooks that can modify resource requests before they are persisted, enabling dynamic resource manipulation.

Security protocol ensuring both client and server authenticate each other, commonly used in service mesh implementations.

Observability platform offering performance monitoring and analytics for containerized applications and infrastructure.

Cloud-native approach to solving L2/L3 use cases and service chain provisioning in Kubernetes.

Kubernetes feature considering Non-Uniform Memory Access topology for optimal pod placement.

Kubernetes abstraction for creating multiple virtual clusters within a physical cluster, providing a scope for names and resources.

Kubernetes feature for partitioning clusters into virtual sub-clusters, enabling resource isolation and access control.

Process of modifying network address information in packet headers for routing in container networks.

Concept of replacing dedicated network appliances with virtualized functions, often containerized.

Security technique dividing networks into isolated zones, enhancing container and microservices security.

Kubernetes resources specifying how groups of pods are allowed to communicate with each other and other network endpoints.

Specification of how groups of pods are allowed to communicate with each other and other network endpoints.

Feature enabling logging of allowed and denied network connections based on Kubernetes Network Policies.

Practice of dividing a network into smaller segments or subnets, improving security and performance in container environments.

Cloud-native solution providing layer 2/3 network services to Kubernetes workloads, enhancing networking capabilities.

Kubernetes resource defining rules for pod-to-pod and pod-to-external communication, implementing network segmentation.

Security platform providing real-time container firewall, vulnerability management, and compliance for Kubernetes.

Observability platform offering performance monitoring and analytics for containerized applications and infrastructure.

Basic unit of a distributed application in many systems, often referring to individual machines or processes.

Kubernetes feature allowing pods to be scheduled on nodes with specific characteristics based on labels.

Kubernetes authorization mode controlling kubelet access to the API server, enhancing cluster security.

Feature automatically adjusting the number of nodes in a Kubernetes cluster based on workload demands.

Prometheus exporter for hardware and OS metrics exposed by *NIX kernels, used for node-level monitoring in Kubernetes.

Kubernetes add-on detecting hardware features and system configuration, facilitating hardware-aware scheduling.

Unique identifier for a node in a Kubernetes cluster, used in various operations and configurations.

Process of removing pods from a node when it experiences resource pressure, ensuring stability.

Kubernetes add-on monitoring and reporting node health issues, enhancing cluster reliability.

Kubernetes plugin limiting node and pod modifications to increase security and prevent privilege escalation.

Kubernetes feature for constraining pods to nodes with specific labels, enabling basic scheduling control.

Procedure for updating the software stack on Kubernetes nodes while minimizing disruption to running workloads.

Capture and management of system and container logs at the node level in a Kubernetes cluster.

Kubernetes controller managing the lifecycle of nodes, handling node registration and decommissioning.

Kubernetes add-on running a dns caching agent on cluster nodes to improve DNS performance.

Kubernetes service type exposing the service on each node's IP at a static port, enabling external access.

Kubernetes services that expose applications on a static port on each node, facilitating external access.

Security practice of running containers with non-privileged users to reduce potential attack surface.

Network communication between external clients and services within a Kubernetes cluster, typically through ingress.

Open-source project providing secure content distribution and verification for container registries.

Implementation of Notary to ensure the integrity and authenticity of container images, enhancing supply chain security.

Open Container Initiative specification defining an API protocol for distributing container images.

Open Container Initiative specification defining the format of container images, ensuring interoperability.

Detailed standard for container image format, ensuring interoperability between different container technologies.

Standard defining the configuration, execution environment, and lifecycle of containers, ensuring compatibility.

Linux kernel mechanism for terminating processes when the system runs out of memory, affecting container reliability.

Integration of Open Virtual Network with Kubernetes for advanced software-defined networking.

Open-source developer-centric web interface for visualizing Kubernetes cluster state and workloads.

Industry standard for container runtime implementations, ensuring compatibility across platforms.

General-purpose policy engine for cloud-native environments, often used for Kubernetes admission control.

OPA-based system for declaring, managing, and enforcing policies in Kubernetes environments.

Container-attached storage solution providing persistent storage for stateful workloads in Kubernetes.

OpenEBS feature for provisioning local persistent volumes, optimizing performance for I/O intensive workloads.

Framework for building serverless functions with Docker and Kubernetes, simplifying the deployment of event-driven workloads.

JSON Web Tokens used for authentication in Kubernetes, often integrated with external identity providers.

Vendor-agnostic way to receive, process, and export telemetry data in various formats for observability.

Vendor-neutral API for distributed tracing, facilitating the instrumentation of microservices for observability.

Kubernetes extension designed for edge computing scenarios, enabling efficient management of edge nodes.

Kubernetes extension that oversees installation, upgrades, and management of Operators in a cluster.

Feature for usage reporting and billing in Kubernetes clusters, often used with Operators.

Performance and health indicators exposed by Kubernetes Operators for monitoring and alerting.

Kubernetes extension pattern for automating application-specific operational knowledge and tasks.

Framework for building Kubernetes Operators, simplifying the development process with high-level APIs.

Tool for validating Operators against best practices and providing suggestions for improvements.

Public registry for finding and sharing Kubernetes Operators, facilitating discovery and distribution.

Kubernetes plugins developed and maintained outside the main Kubernetes repository, enabling extensibility.

Design pattern ensuring consistency between database and message broker in distributed systems.

Process of identifying abnormal behavior in containerized applications or infrastructure for troubleshooting.

Additional resource consumption introduced by container runtimes and orchestration systems.

Layered filesystem used by container runtimes to efficiently manage image layers and container writes.

Virtual networks created on top of existing networks, enabling container-to-container communication across hosts.

Base container image upon which other images are built, providing foundational layers for child images.

Service mesh feature ensuring mutual authentication between services using mTLS, enhancing security.

Kubernetes resource representing a request for storage by a user, abstracting storage implementation details.

Kubernetes abstraction for a piece of storage in the cluster, managed independently of individual pods.

Kubernetes resource representing a piece of storage in the cluster that has been provisioned by an administrator.

Kubernetes resource representing a request for storage by a user, abstracting the details of the underlying storage implementation.

Practice of defining CI/CD pipelines using code, often stored alongside application code for version control and review.

Open-source observability tool for Kubernetes, providing automatic data collection and real-time debugging capabilities.

Use of Pixie to gain deep insights into Kubernetes cluster performance and application behavior without code changes.

Smallest deployable unit in Kubernetes, consisting of one or more containers sharing storage and network resources.

Kubernetes scheduling constraint that allows pods to be co-located with other pods based on labels.

Kubernetes features for influencing pod scheduling based on the topology of the cluster and other pods.