Engineering Glossary

A single set of stashed changes in Git, which can be reapplied later to the working directory.

Automated tests or processes that run when changes are proposed in a Git repository, ensuring code quality and compatibility.

Notifications or updates a user receives about activity in Git repositories they're interested in or contributing to.

The main Git repository that contains submodules, managing references to specific versions of nested repositories.

A symbolic reference in Git that points to another reference, most commonly used for HEAD pointing to the current branch.

A Git object containing metadata about a tag, including the tagger, date, and optional message.

A group of users on a Git platform with shared access permissions to repositories within an organization.

A user with administrative privileges for managing a team's membership and access rights in a Git organization.

A chronological display of events and activities in a Git repository or user profile on hosting platforms.

A short-lived Git branch created to develop a specific feature or fix a particular issue.

Keywords or categories assigned to Git repositories to help users discover related projects on hosting platforms.

A visual representation of visitor activity and clone statistics for a Git repository on hosting platforms.

The process of moving Git objects between repositories during push, fetch, or clone operations.

A Git object representing a directory structure, containing references to blobs (files) and other trees (subdirectories).

A Git object that stores the hierarchy of files and directories in a repository at a specific point in time.

A Git term referring to an object that resolves to a tree, such as a commit, tag, or tree.

A state of a Git branch that has no commits yet, typically seen when initializing a new repository.

The state of the Git index containing conflicting changes from different branches during a merge operation.

A Git object not accessible from any reference, potentially subject to garbage collection if not recovered.

The remote branch that a local branch is set to track, used as a reference for pull and push operations.

An individual account on a Git platform, associated with personal repositories and contributions.

An authenticated request from a Git client to a server, typically for operations like push or fetch.

The unique identifier for a user account on Git platforms, used for authentication and mention notifications.

A team in a Git organization that is visible to all members of the organization, as opposed to secret teams.

A feature allowing users to receive notifications about activity in Git repositories they're interested in.

Alerts received for all notable events in a watched Git repository, including issues, pull requests, and releases.

Alerts displayed on Git platforms' web interfaces, notifying users of relevant activity or mentions.

The directory on your local machine where you modify files before staging and committing them in Git.

The set of files and directories in your project that are currently checked out and available for editing.

A Git feature allowing multiple working directories to be associated with a single repository.

Permission to make changes to a Git repository, including pushing commits and modifying branches.

Systems integrating blockchain technology with traditional cloud services for enhanced security and transparency.

Tools and practices for managing resources across public and private cloud environments.

Tracking performance and health of resources spanning both public and private cloud environments.

Coordinating and automating workflows across multiple cloud environments and on-premises infrastructure.

Data storage solutions that span both on-premises and cloud environments, offering flexible and scalable data management.

Network solutions that connect on-premises infrastructure with cloud services, enabling seamless integration and data flow.

Managing user identities and access across both on-premises systems and cloud services.

Tools for connecting applications, data, and processes across on-premises and cloud environments.

Computational methods combining quantum and classical processing in cloud environments.

Using both quantum and classical computing resources in tandem for cloud-based problem-solving.

Database systems supporting both real-time transactions and analytics in cloud environments.

Integrated compute, storage, and networking in a single cloud-managed system, simplifying data center architecture.

Process of optimizing machine learning model parameters in cloud-based environments.

Software layer that manages virtual machines in cloud computing environments, enabling efficient resource utilization and isolation.

Defined permissions and access controls for users and services in cloud environments.

International standard for information security management in cloud environments.

Security tools that verify user identity before granting access to cloud applications.

Automated process of examining container images for vulnerabilities in cloud environments.

Security approach based on replacing rather than modifying cloud infrastructure components.

Cloud storage that prevents data modification after writing, ensuring data integrity and compliance.

Database system that primarily uses main memory for data storage in cloud environments.

Distributed computing using the collective memory of networked computers in the cloud.

Processing data within network devices to reduce latency and bandwidth use in cloud architectures.

Systems for efficiently updating computation results when input data changes in cloud environments.

Process of organizing data to optimize query performance in cloud databases, enhancing search and retrieval efficiency.

Automated tools for identifying security issues in infrastructure definition files.

Validating infrastructure definitions before deployment in cloud environments, ensuring reliability and consistency.

Cloud-based provision of virtualized computing resources over the internet, including servers, storage, and networking.

Generating cloud infrastructure configurations directly from application code, streamlining development and deployment processes.

Predefined virtual server configurations optimized for different use cases in cloud environments.

Visual tool for creating and managing data integration processes in cloud environments.

Tools for tracking and analyzing the performance of integrated cloud systems and processes.

Automated data storage class selection based on access patterns in cloud environments.

Automatic movement of data between storage tiers based on usage patterns in the cloud.

Network management approach using AI to automate configuration based on business intent.

Network node that connects cloud VPCs to the internet, enabling communication with external resources.

Decentralized storage system for distributing and accessing files in the cloud, enhancing data availability and resilience.

Security tool that monitors network traffic for suspicious activity in cloud environments.

Security system that not only detects but also blocks potential threats in cloud networks.

Processing and analyzing data from Internet of Things devices in cloud environments.

Identifying unusual patterns in data from IoT devices using cloud-based analytics.

Fully managed IoT application platform in the Azure cloud for connecting, monitoring, and managing IoT devices at scale.

Process of collecting and importing data from IoT devices into cloud systems for storage, analysis, and processing.

Centralized repository in the cloud for storing large volumes of IoT device data.

Cloud-based systems for monitoring, updating, and controlling IoT devices, ensuring efficient operation and security at scale.

Process of setting up and configuring IoT devices for secure cloud connectivity.

Software development kit for building applications that connect IoT devices to cloud services.

Deploying cloud intelligence directly to IoT devices for local processing and analytics.

Processing data from IoT devices locally before sending to the cloud, reducing latency and bandwidth usage.

AWS service for running local compute, messaging, and data caching for connected IoT devices.

Central message hub for bi-directional communication between IoT applications and devices.

Tools for connecting and managing diverse IoT devices and data streams in cloud environments.

Cloud-based tools for managing IoT devices from deployment through retirement, ensuring efficient device administration.

Remote software updates for IoT devices managed through cloud platforms, ensuring device security and functionality.

Cloud-based platform for developing, managing, and integrating IoT applications and devices.

Lightweight communication protocols designed for IoT devices in cloud environments.

Cloud service for processing and acting on data from IoT devices based on predefined conditions.

Measures to protect IoT devices, data, and infrastructure in cloud-connected environments.

Real-time processing and analysis of data streams from IoT devices in the cloud.

Cloud service for creating and managing cryptographic keys for data encryption, ensuring secure data protection.

Kubernetes-based platform for building, deploying, and managing serverless workloads.

Kubernetes-native serverless framework enabling function deployment without managing underlying infrastructure.

Rules for controlling network traffic between pods in Kubernetes clusters, enhancing security in cloud-native environments.

Tools for assessing and improving security configurations in Kubernetes environments.

Managed Kubernetes platforms offered by major cloud providers for container orchestration.

Kubernetes native configuration management tool for customizing application configurations.

AWS service for running Lambda functions at edge locations to customize content delivery.

Template for EC2 instance settings used in Auto Scaling groups, defining instance type, AMI, and other parameters.

Security concept of granting only the minimum permissions necessary in cloud environments.

Managing software licenses efficiently to reduce costs in cloud environments, ensuring compliance and cost-effectiveness.

Migration strategy of moving applications to the cloud without significant modifications.

Minimalist virtual machines designed for fast startup and low resource usage in cloud environments.

Lightweight service mesh for Kubernetes, providing observability, reliability, and security for microservices.

Using liquid to dissipate heat in densely packed cloud data centers for improved efficiency.

Service that distributes incoming network traffic across multiple servers to ensure no single server becomes overwhelmed.

Process of collecting, analyzing, and visualizing log data from cloud resources for insights and troubleshooting.

AI-driven analysis of log data to identify patterns, anomalies, and insights in cloud environments.

Tools for building application integrations with minimal hand-coding in cloud environments.

Cloud-based tools for creating applications with little to no traditional programming.

Cloud services enabling app development with minimal coding, using visual interfaces and pre-built components.

Lightweight messaging protocol designed for IoT devices and low-bandwidth networks in cloud ecosystems.

Cloud-based services for building, training, and deploying machine learning models at scale.

Centralized management of critical business data entities in cloud environments.

Tools for developing AI models that can learn how to learn, improving adaptability in cloud environments.

Cloud tools for organizing, integrating, and governing metadata across various data sources.

Advanced antenna designs using engineered materials to enhance cloud network performance.

Gathering and storing quantitative data about cloud resource performance and usage.

Architectural style where frontend apps are composed from independently deployable components in the cloud.

Automating the process of dividing cloud networks into secure zones for enhanced protection.

Connecting and coordinating interactions between independent microservices in cloud architectures.

Strategic process of preparing and scheduling the move of applications and data to cloud environments.

Cloud-based platforms for developing and deploying mixed reality applications, combining virtual and physical environments.

Bringing cloud computing capabilities closer to mobile users to reduce latency and improve performance.

Extending cloud computing capabilities to the edge of mobile networks for lower latency.

Process of making machine learning models available for use in cloud production environments.

Techniques for understanding and interpreting decisions made by AI models in cloud environments.

Tracking the performance and behavior of deployed machine learning models in cloud environments.

Centralized repository for storing and managing machine learning models in cloud environments.

Process of making trained machine learning models available for real-time predictions in cloud environments.

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

Integration of 5G mobile edge computing with container platforms for low-latency applications and services at network edges.

Application of AI and machine learning for automated operations, monitoring, and management of containerized environments.

Guidelines for phasing out older API versions in Kubernetes, ensuring smooth transitions for users.

Mechanisms to extend the Kubernetes API with custom resources and functionalities, enhancing platform capabilities.

Containerized service that acts as a single entry point for all client requests to a microservices architecture.

Core component of Kubernetes that exposes the cluster's API and handles all administrative operations.

Kubernetes feature allowing the API server to be extended with additional APIs without modifying core Kubernetes code.

Approach prioritizing API design before implementation, crucial for developing scalable containerized microservices.

Serverless compute engine for containers, allowing you to run containers without managing the underlying infrastructure.

Design pattern in containerized microservices that wraps a service's interface to make it compatible with other services.

Plugins that intercept requests to the Kubernetes API server before object persistence, enforcing policies or modifying objects.

Admission controllers specifically focused on enforcing security policies and validating security-related configurations.

HTTP callbacks that receive admission requests and can modify or validate objects before they are persisted.

Use of admission webhooks within Kubernetes operators to enforce custom policies or modify resources.

Kubernetes feature providing detailed logging of all requests processed by the API server for security and compliance.

Extension of the Kubernetes API server to include custom resources and functionalities without modifying core Kubernetes.

Combination of multiple ClusterRoles into a single role, simplifying RBAC management in Kubernetes.

Container registries isolated from public networks, used in secure or restricted environments.

Open-source project for exposing heterogeneous leaf devices as resources in Kubernetes clusters.

Setup and management of Prometheus Alertmanager for handling alerts from monitoring systems.

Fully managed Docker container registry provided by AWS for storing, managing, and deploying container images.

Microservices design pattern where a dedicated service acts as an API gateway for other services.

Service mesh implementation that doesn't require sidecars, reducing resource overhead and simplifying deployment.

Open-source tool for deep inspection of container images, including vulnerability scanning and policy enforcement.

Kubernetes operators implemented using Ansible for automating application lifecycle management.

Network policies specific to the Antrea CNI plugin, offering fine-grained control over pod-to-pod communication.

Kubernetes networking solution using Open vSwitch for improved performance and advanced networking features.

Open-source serverless platform that executes functions in response to events or direct invocations.

Security profiles for Linux that restrict program capabilities, enhancing container isolation and security.

Logging implemented within applications, providing detailed insights into application behavior and performance.

Platform providing security and compliance for container-based and cloud-native applications throughout their lifecycle.

Comprehensive security solution for containerized and cloud-native environments, offering vulnerability management and runtime protection.

GitOps continuous delivery tool for Kubernetes, automating application deployment and lifecycle management.

Kubernetes controller for advanced deployment strategies like canary and blue-green deployments.

Declarative GitOps tool for Kubernetes, automating application deployment and synchronization with Git repositories.

Process of storing, organizing, and managing container images and related artifacts in container registries.

Open-source platform for fine-grained access control and authentication in distributed systems.

Access control paradigm where authorization decisions are based on attributes of users, resources, and environment.

Additional metadata added to Kubernetes audit events for enhanced context and analysis, improving audit trails.

Components responsible for processing and storing Kubernetes audit logs, supporting various storage and analysis options.

Records of requests and activities within a Kubernetes cluster, used for security monitoring and compliance.

Configurable detail levels for Kubernetes audit logs, ranging from metadata-only to full request and response details.

Process of recording API server requests and responses for security, troubleshooting, and compliance purposes.

Detailed records of activities and operations within a Kubernetes cluster, used for security and compliance monitoring.

Configuration defining which events should be recorded in Kubernetes audit logs and at what level of detail.

Predefined set of audit policy rules for common use cases in Kubernetes, simplifying audit configuration.

Different phases of request processing where audit events can be generated in Kubernetes, providing comprehensive auditing.

Setup for sending Kubernetes audit events to external webhook endpoints for processing or analysis.

Process of systematically recording and examining activities within a Kubernetes cluster for security and compliance purposes.

Intermediary service that handles authentication before forwarding requests to the Kubernetes API server.

Pluggable components in container orchestration platforms for verifying user identities using various methods.

Rules defining access permissions for users and services in container orchestration platforms.

Serverless container hosting service in Azure, offering rapid deployment of containers without cluster management.

Managed Docker registry service for storing and managing container images in Azure cloud environments.

Implementation of Border Gateway Protocol within containerized network environments for advanced routing.

In container networks, BGP (Border Gateway Protocol) manages routing information between containers and external networks for efficient traffic routing.

Microservices design pattern where a dedicated service acts as an API gateway for specific frontend needs.

Processes for preserving and recovering container data and configurations in orchestration platforms.

Foundation Docker image upon which other images are built, containing core OS and runtime components.

Process of choosing appropriate foundation images for container builds, balancing size, security, and functionality.

Kubernetes quality of service class for pods with no resource guarantees, scheduled when resources are available.

Deployment strategy using two identical environments to minimize downtime and risk during updates.

Temporary tokens used for secure cluster initialization and node joining in Kubernetes, simplifying cluster setup.

Minimalist Linux-based operating system optimized for running containers in cloud environments.

Advanced container image building toolkit offering improved performance and caching capabilities.

Use of BuildKit for efficient, concurrent, and cache-optimized container image creation, improving build performance.

Isolation technique in microservices to contain failures and prevent system-wide cascading failures.

The Bulkhead Pattern in microservices isolates failures by dividing services into separate compartments, preventing issues in one from affecting others.

Kubernetes quality of service class for pods that can use more resources than requested when available.

Security configuration guidelines for deploying containers securely in various environments.

Technique of using multiple Container Network Interface plugins together for advanced networking capabilities.

Kubernetes feature for fine-grained CPU resource management and allocation to containers, optimizing performance.

Technique to limit CPU usage of containers to prevent resource monopolization and ensure fair allocation.

Architectural pattern separating read and write operations in distributed systems, often used in microservices.

Architectural pattern separating read and write operations in distributed systems, often used in microservices.

Standard interface between container runtimes and Kubernetes, allowing pluggable runtime implementations.

Functionality within CRI for pulling, inspecting, and removing container images, standardizing image operations.

Standardized logging interface for container runtimes implementing the Container Runtime Interface.

Performance and resource usage data exposed by container runtimes adhering to the CRI specification.

Kubernetes feature allowing selection of different runtime configurations for containers, enabling specialized runtimes.

Unix domain socket used for communication between Kubelet and the CRI-compatible container runtime.

Process of verifying that a container runtime correctly implements the CRI specification, ensuring compatibility.

Lightweight container runtime specifically designed for Kubernetes, implementing the CRI specification.

Core components and architecture of the CRI-O container runtime, including its interaction with Kubernetes.

Use of CRI-O, a lightweight container runtime, as the primary runtime in a Kubernetes cluster.

Component of CSI responsible for volume provisioning and attachment operations in container orchestration systems.

Plugins implementing the Container Storage Interface for various storage systems in Kubernetes.

Short-lived volumes in Kubernetes, created and deleted alongside a pod using CSI drivers, for temporary storage.

Process of transitioning from in-tree volume plugins to CSI drivers in Kubernetes, improving storage extensibility.

Component of CSI responsible for mounting volumes and making them available to containers.

Feature allowing storage provisioning based on topology constraints in Kubernetes, optimizing data locality.

Caching strategy where the application checks the cache before retrieving data from the main data store.

Techniques for implementing and managing caches in containerized applications for improved performance.

Open-source networking and network security solution for containers, providing a rich set of security policies.

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

Technique of releasing new versions to a subset of users or servers to minimize risk and gather feedback.

Fine-grained privileges that can be assigned to containers, enhancing security by limiting root-level access.

Mechanisms for managing and restricting Linux capabilities assigned to containers for improved security.

Groupings or classifications of container-related resources or components for easier management and discovery.

Ceph's block storage system, often used for persistent volumes in container orchestration platforms.