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.

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

Managing different iterations of machine learning models in cloud-based development pipelines.

Repository for storing and managing reusable software components in cloud development environments.

Experimental technique using molecules to store digital data, potentially integrated with cloud systems.

Tools and practices for managing multiple cloud accounts within an organization.

Using services from multiple cloud providers in a single architecture, optimizing for cost, performance, and redundancy.

Centralized platforms for managing data and application integrations across multiple cloud providers.

Distributing workloads across multiple cloud providers to optimize performance and reliability.

Tools and practices for administering resources and applications across multiple cloud providers.

Technologies enabling seamless networking across multiple cloud provider environments.

Coordinating microservices communication and security across multiple cloud environments.

Security system requiring two or more verification methods to access cloud resources.

Database systems supporting multiple data models (e.g., document, graph, relational) in a single backend.

Copying data across multiple geographic regions in cloud environments for redundancy and disaster recovery.

Bringing cloud capabilities closer to the network edge for improved performance and reduced latency.

Tools and strategies for monitoring and optimizing expenses across multiple cloud providers.

Strategies to minimize expenses and maximize efficiency when using multiple cloud providers.

Implementing backup and failover systems across multiple cloud providers for enhanced resilience.

Connecting and managing network resources across multiple cloud provider environments.

Strategies and tools for protecting data and applications across multiple cloud provider environments.

Tools for managing and orchestrating data across multiple cloud provider environments.

Unified network architecture spanning multiple cloud providers for seamless connectivity.

Cloud services supporting AI models that can process and integrate multiple types of data (e.g., text, image, audio).

User interfaces that combine multiple input/output methods (e.g., voice, touch, gesture) for cloud service interaction.

Cloud services for integrating and analyzing data from various sources and formats.

Service that enables private subnet instances to connect to the internet or other AWS services.

Isolated environment within a cluster to organize and manage resources in cloud platforms.

Systems allowing users to interact with cloud services using conversational language.

AI technology for understanding, interpreting, and generating human language in cloud environments.

Cloud-based platforms offering pre-built NLP models and APIs for text analysis and generation.

Smaller data centers located closer to end-users for reduced latency in cloud service delivery.

UI design approach mimicking physical objects for intuitive cloud service interaction.

Rules controlling inbound and outbound traffic for subnets in cloud virtual networks.

Stateless firewall for controlling traffic in and out of cloud subnets, enhancing network security.

Process of modifying network address information to route traffic between private and public networks.

Virtualizing network services traditionally run on proprietary hardware in cloud environments.

Tools for monitoring, analyzing, and troubleshooting cloud network performance and behavior.

Tools and practices for measuring and optimizing network performance in cloud environments.

Technology for managing and securing service-to-service communication in cloud-native environments.

Collecting and analyzing network data for visibility and troubleshooting in cloud environments.

Techniques for improving the efficiency and performance of data flow in cloud networks.

Defining and managing network infrastructure using code in cloud environments, enabling automated and version-controlled networking.

Cloud-based automated design of optimal neural network architectures for specific AI tasks.

Cloud platforms combining neural networks with symbolic reasoning for more robust AI systems.

Cloud-based AI integrating neural networks and symbolic AI for enhanced reasoning capabilities.

Cloud services using brain-inspired computing architectures for improved efficiency in AI tasks.

Cloud platforms providing access to brain-inspired computing architectures for AI applications.

Cloud-based offerings of brain-inspired computing architectures for specialized AI workloads.

Cloud-based AI processing using brain-inspired chip designs for improved efficiency and performance.

Cloud databases combining the scalability of NoSQL with the ACID guarantees of traditional relational databases.

Non-relational databases designed for flexible, scalable data storage and retrieval in cloud environments.

High-performance storage protocol for accessing SSDs over network fabrics in cloud environments.

Technology for quickly analyzing multidimensional data from multiple perspectives in cloud databases.

Cloud storage for unstructured data, accessed via APIs and organized as objects rather than files.

Scalable cloud storage services for unstructured data, accessible via APIs, ideal for large-scale data storage and retrieval.

Devices or software providing local access to cloud-based object storage systems.

Centralized repositories for storing and analyzing large volumes of observability data in cloud environments.

Systems for collecting, processing, and routing observability data in cloud environments.

Software development approach prioritizing built-in monitoring and debugging in cloud applications.

Analyzing and interpreting scent-related data using cloud computing resources, enabling digital olfactory applications.

Running ML models on edge devices, reducing reliance on cloud processing for certain tasks.

Technology for rapid analysis of multidimensional data in cloud-based data warehouses.

Open-source framework for building serverless functions with Docker and Kubernetes in cloud environments.

Kubernetes extension for automating application management tasks in cloud-native environments.

Using light-based processing for high-speed, energy-efficient computation in cloud data centers.

Remote software updates for devices connected to cloud services, often used for IoT.

Adhering to Payment Card Industry Data Security Standard requirements in cloud environments.

Dividing large datasets or databases into smaller, more manageable parts in cloud storage systems.

Pricing structure where users only pay for the cloud resources they actually use.

Billing model where customers are charged based on their actual usage of cloud resources.

Pricing scheme where users are billed only when their serverless functions are invoked.

Direct network link between two virtual private clouds, often in different accounts or regions.

Simulated cyberattacks to evaluate the security of cloud-based systems and applications.

Non-volatile memory that combines speed of DRAM with data persistence, used in cloud storage systems.

Storage resources in cloud environments that exist independently of any specific pod or container.

Light-based chips for high-speed data processing in cloud infrastructure, improving energy efficiency.

Defining and managing continuous integration/deployment workflows using code in cloud environments.

Ability to restore cloud-based data to a specific moment in the past, enabling granular data recovery options.

Implementing and maintaining security and compliance rules across cloud resources.

Creating, updating, and enforcing rules governing cloud resource usage and security.

Serverless platform supporting multiple programming languages for cloud function development.

Using multiple data storage technologies to handle varied data storage needs in cloud applications.

Creating serverless applications using multiple programming languages in cloud environments.

Refining and improving cloud-based systems after initial migration from on-premises.

Deploying encryption methods resistant to quantum computer attacks in cloud systems.

Metric for measuring energy efficiency of cloud data centers, comparing total power consumption to IT equipment power usage.

Using AI to anticipate resource needs and adjust cloud capacity automatically, optimizing performance and cost-efficiency.

Using data analytics and machine learning to forecast future cloud resource requirements and optimize infrastructure.

Using data analytics to anticipate and prevent equipment failures in cloud infrastructure.

Advanced analytics providing recommendations for actions in cloud-based decision making.

Tool for estimating costs of cloud services based on expected usage, helping in budgeting and resource planning.

Techniques for processing sensitive data while preserving privacy in cloud environments.

Tools and methods for protecting personal data privacy in cloud computing, ensuring compliance and user trust.

Techniques for analyzing data in the cloud while maintaining individual privacy.

Extracting useful information from large datasets without compromising individual privacy in the cloud.

Performing data analysis in the cloud while protecting sensitive information, balancing insights with data privacy.

Dedicated 5G networks deployed for specific enterprise use, often integrated with cloud services.

Service enabling private connectivity between VPCs, AWS services, and on-premises applications.

Tools for securing, controlling, and monitoring access to critical cloud resources and data.

Memory-efficient data structures for approximate data analysis in cloud environments.

Condition where a node or container is running low on available memory, potentially triggering evictions or OOM kills.

Process of extending service mesh capabilities to workloads running outside the primary container orchestration platform.

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.