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.

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.