Engineering Glossary

A variation of Git pull that fetches remote changes and rebases local commits on top of them instead of merging.

A safer alternative to force push, which only updates the branch if it hasn't been modified since your last fetch.

A command that compares the changes between two commit ranges, useful for reviewing rebased branches.

A low-level command that reads tree objects into the index, used in complex merging scenarios.

A log of all reference updates in a repository, useful for recovering lost commits or branches.

Same as Git Reflog, logs that record when the tips of branches and other references were updated in the repository.

The system Git uses to store references (like branches and tags) as files in the .git directory.

A string that specifies the mapping between remote and local references when fetching or pushing.

Adds a new remote repository to your local Git configuration, associating a name with a URL.

A command that removes remote-tracking branches that no longer exist on the remote repository.

Removes a remote repository from your local Git configuration, deleting its associated references.

A feature allowing one Git object to be transparently used in place of another, useful for history rewriting.

A feature that remembers how you resolved merge conflicts and automatically reapplies the resolution.

A command used to undo changes by moving the current branch head to a specific commit.

A Git reset option that updates the working directory and staging area to match the specified commit.

A Git reset option that moves the HEAD to a specified commit without changing the working directory or staging area.

A command that lists commit objects in reverse chronological order, often used as a basis for other commands.

A command used to parse Git revision syntax and return the corresponding object name.

A command that creates a new commit that undoes the changes made by a previous commit.

A comparison of two Git commands used to undo changes, with revert creating new commits and reset modifying history.

A command to remove files from both the working directory and the Git repository.

A clone that only fetches a limited number of commits, reducing download size and time for large repositories.

A command that summarizes git log output, typically used to create release announcements.

Commits that are cryptographically signed to verify the identity of the committer and ensure integrity.

Tags that are cryptographically signed to verify the identity of the tagger and ensure the tag's integrity.

The process of combining multiple commits into a single commit, often used to simplify history before merging.

A command that applies a stored stash to the working directory without removing it from the stash list.

A command that applies a stored stash to the working directory and removes it from the stash list.

A command that displays the state of the working directory and the staging area.

A repository embedded within another repository, allowing you to keep a Git repository as a subdirectory of another Git repository.

A command that executes a specified shell command for each initialized submodule in a Git repository.

A comparison of two Git features used to include external repositories in a project, each with different use cases.

A feature for managing nested repositories as subdirectories of a parent repository, an alternative to submodules.

A low-level Git command that manipulates the staging area, updating file information and preparing changes for commit.

The communication protocol used between Git clients and servers for efficient data transfer.

A feature allowing multiple working trees to be attached to the same repository, useful for working on different branches simultaneously.

Creates a new working tree associated with the repository, allowing work on multiple branches simultaneously.

A command to list details of each working tree associated with the repository, showing paths and branch information.

A low-level Git command that creates a tree object from the current index, representing a directory structure.

A Git command used to create an archive (zip or tar) of files from a specified commit, useful for creating release packages.

Agreed-upon patterns for naming branches to improve organization and clarity in collaborative projects.

A command to examine the contents and type of Git objects, useful for inspecting repository internals.

A command to resume the cherry-pick process after resolving conflicts in a paused cherry-pick operation.

Levels at which Git configuration can be set: system (all users), global (user), and local (repository).

A command providing detailed statistics about the number and size of objects in a Git repository.

Mechanisms to securely store and retrieve credentials for Git operations, reducing manual authentication.

Custom scripts that determine how Git should generate diffs for specific file types.

A versatile tool for rewriting Git repository history, offering more power and flexibility than git filter-branch.

A more thorough garbage collection process in Git, optimizing repository storage and performance.

A low-level Git command that computes the object ID (SHA-1 hash) for a given file or string, used in Git's internal storage.

Scripts triggered by specific events in Git workflows, used to automate tasks or enforce policies.

The intermediate area in Git where changes are prepared before committing, also known as the staging area.

Individual, uncompressed Git objects stored separately in the object database before being packed.

A command to list the contents of a tree object in Git, showing files and subdirectories.

Custom scripts defining how Git should handle merges for specific file types or patterns.

A low-level Git command that creates a tree object from a specific index or tree listing.

The four fundamental object types used by Git to store repository data and history.

A command to pack references into a single file for improved performance in repositories with many references.

Compressed files containing multiple Git objects, optimizing storage and transfer efficiency in repositories.

Server-side scripts that run after commits have been accepted, often used for notifications or deployments.

Server-side scripts that run before pushed commits are accepted, used to enforce policies or checks.

An improved version of the Git transfer protocol, offering better performance and feature negotiation.

A command to move a series of commits to a new base commit, useful for changing the parent of a branch.

A command to remove old entries from the reflog, useful for cleaning up Git history and freeing space.

A command to combine all loose objects in a repository into packfiles, improving storage efficiency.

Commands to undo changes in Git, with varying impacts on the working directory and staging area.

Techniques and tools for securely storing and accessing sensitive information in Git repositories.

A command that lists references in a Git repository along with their associated commit hashes.

A feature allowing users to check out only a subset of files from a repository, saving space and time.

A command to validate the contents of Git pack files, ensuring data integrity in the object database.

An application that can be installed directly on organizations and user accounts to extend GitHub's functionality.

A version of Markdown with additional features specifically supported on GitHub.

A tool for importing repositories to GitHub from other version control systems or source code hosts.

A feature in GitHub for tracking tasks, enhancements, and bugs for a project.

A platform for posting and finding software development jobs, integrated with GitHub profiles, that was discontinued in 2021.

A platform for developers to sell and buy integrations for GitHub, enhancing workflow and productivity.

A static site hosting service that takes files directly from a GitHub repository to publish websites.

A collaborative documentation feature in GitHub repositories, allowing easy creation and editing of project documentation.

A lightweight, branch-based workflow that supports teams and projects where deployments are made regularly.

A version control workflow that combines feature-driven development and feature branches with issue tracking.

Branching model for Git that defines a strict branching model designed around project releases.

A graphical interface for viewing Git repositories, providing a visual representation of commit history.

Query language for APIs and a runtime for executing those queries with existing data.

A pointer in Git that refers to the latest commit in the current checked-out branch.

A simple program often used as an introduction to a new programming language or environment, including Git tutorials.

A method for quickly patching production releases by branching directly from the main branch or a tag.

Also known as the staging area, where changes are prepared before committing in Git.

Predefined structures for creating new issues in Git repositories, ensuring consistent and complete information.

A static site generator often used with GitHub Pages to create websites from Markdown files in a Git repository.

A tool in GitHub Pages that allows users to easily select and apply pre-designed themes to their Jekyll sites.

Git Large File Storage, an extension for versioning large files in Git repositories.

A library used by GitHub to detect the programming languages used in repositories.

A lightweight markup language commonly used for documentation in Git repositories.

Formerly the default name for the primary branch in Git repositories, now often replaced by 'main'.

The process of combining changes from different branches into a single branch, integrating multiple lines of development.

An application that uses the OAuth protocol to access Git platform APIs on behalf of users.

A secure string used for authentication in Git operations, allowing access to resources without sharing passwords.

The default name for the remote repository from which a local repository was cloned.

A file describing changes between versions, used to share and apply modifications across different Git repositories.

A Git command that fetches changes from a remote repository and merges them into the current branch.

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.

Design pattern using specialized containers that run before app containers in a pod, used for setup or dependency management.

Specialized containers that run to completion before other containers in a Kubernetes pod, used for initialization tasks.

Specification of CPU and memory limits for initialization containers in Kubernetes pods, ensuring efficient resource utilization.

Deprecated Kubernetes feature for dynamically modifying resource configurations before they become visible to the system.

Methods and patterns for containers within a pod to exchange data and signals, utilizing shared volumes or localhost networking.

Architectural designs for deploying and managing containerized applications on edge devices in Internet of Things scenarios.

Open-source service mesh providing traffic management, security, and observability for cloud-native applications.

Core services of the Istio service mesh responsible for configuring proxies and implementing policies.

Istio traffic management resource defining policies that apply to traffic intended for a service after routing has occurred.

Istio resources managing inbound and outbound traffic for the service mesh, providing fine-grained control over traffic flow.

Istio design that removes the Mixer component, improving performance and scalability of the service mesh.

Istio resources allowing the addition of entries to the service registry, enabling traffic to external dependencies.

Istio traffic management resources defining a set of traffic routing rules to apply when a host is addressed.

Istio feature providing a sidecar-less service mesh implementation, reducing resource overhead and simplifying deployment.

Open-source, end-to-end distributed tracing system for monitoring and troubleshooting microservices-based distributed systems.

Kubernetes operator for automated deployment and management of Jaeger tracing infrastructure in container environments.

Implementation of distributed tracing using Jaeger to monitor and optimize performance in microservices architectures.

Cloud-native CI/CD solution for Kubernetes, automating the entire software development lifecycle for containerized applications.

Tool for building optimized Docker and OCI images for Java applications without the need for a Docker daemon.

Kubernetes resource that creates one or more pods to perform a specific task and ensures they successfully complete, ideal for batch processes.

Lightweight Kubernetes distribution designed for edge, IoT, and resource-constrained environments, simplifying cluster deployment.

Terminal-based UI for managing and monitoring Kubernetes clusters, providing an intuitive interface for cluster operations.

Kubernetes-based Event Driven Autoscaling, enabling fine-grained autoscaling for event-driven workloads based on event sources.

Kubernetes Universal Declarative Operator, a toolkit for writing operators using a declarative spec, simplifying complex application management.

Tool for building container images from a Dockerfile inside a container or Kubernetes cluster, without requiring a Docker daemon.

Framework for application-level data management in Kubernetes, ensuring consistent backups of stateful apps.

Open-source project for multi-cluster application management in Kubernetes, facilitating resource distribution across clusters.

Lightweight virtual machines that feel and perform like containers, but provide the workload isolation and security of VMs.

Major update to Kata Containers, introducing improved performance, reduced footprint, and enhanced security features.

Cloud-native application lifecycle orchestration tool, automating deployment, testing, and remediation for containerized apps.

Technique allowing network packets to bypass the kernel, improving performance in container networking scenarios.

Linux feature providing isolation for system resources, fundamental to container implementation and resource separation.

CNI plugin using WireGuard to create a mesh overlay network for Kubernetes, enhancing security and simplicity.

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

Knative component providing tools for routing events between publishers and subscribers in cloud-native applications.

Knative component for deploying and managing serverless workloads, handling scaling and routing of containerized applications.

Tool allowing WebAssembly modules to run in Kubernetes clusters, enabling language-agnostic workloads.

Network virtualization solution for Kubernetes integrating the Open vSwitch software switch to provide advanced networking features.

Implementation of Kube-OVN to leverage Open vSwitch for flexible, high-performance container networking.

Tool for checking whether Kubernetes deployments adhere to Center for Internet Security (CIS) best practices.

Use of kube-bench to perform automated security audits of Kubernetes clusters against established benchmarks.

Kubernetes networking solution providing direct container-to-container networking with BGP-based routing.

Tool for static code analysis of Kubernetes object definitions, identifying misconfigurations and potential issues.

Service that listens to the Kubernetes API server and generates metrics about the state of Kubernetes objects.

Open-source system extending native containerized application orchestration capabilities to hosts at Edge.

Tool for bootstrapping a minimum viable Kubernetes cluster, simplifying the process of setting up a production-grade cluster.

Open-source tool for auditing Kubernetes clusters and workloads for potential security issues and best practice violations.

Framework for building Kubernetes APIs using custom resource definitions (CRDs), simplifying the creation of operators and controllers.

Tool providing real-time cost visibility and insights for running applications on Kubernetes, optimizing resource allocation.

Kubernetes Cluster Federation, enabling resource management across multiple Kubernetes clusters from a single control plane.

Kubernetes-native serverless framework, allowing deployment of small bits of code (functions) without managing underlying infrastructure.

System for evolving the Kubernetes API over time, allowing for backwards compatibility and gradual feature deprecation.

Plugins intercepting requests to the Kubernetes API server before object persistence, enforcing policies.

Feature allowing the Kubernetes API to be extended with additional APIs, enabling custom resources and controllers.

Key-value pairs for attaching non-identifying metadata to objects, used for tooling and client retrieval.

Mechanisms (HPA, VPA, Cluster Autoscaler) for automatically adjusting resources based on demand and metrics.

CNCF initiative ensuring consistency and portability across Kubernetes distributions and installations.

API objects automatically created when other objects change state, providing a cluster activity audit trail.

Mechanism for coordinating multiple Kubernetes clusters, enabling multi-cluster application deployment and management.

Field on resources preventing accidental deletion, ensuring proper cleanup of related resources or external dependencies.

Process of automatically deleting objects that no longer have owners, preventing resource leaks.

Evolved ingress and service networking, providing a more expressive, extensible way to configure traffic routing.

Key-value pairs attached to objects for identification and selection, crucial for organizing and selecting object subsets.

Cluster-wide aggregator of resource usage data, providing CPU and memory metrics for Horizontal Pod Autoscaler.

Software extensions to Kubernetes that use custom resources to manage applications and their components.

Relationship between API objects where one object owns another, used for cascading deletion and orphan handling.

Label query over a set of resources, used for identifying and grouping API objects based on their labels.

Policies and timelines for Kubernetes version releases, support, and deprecation, guiding upgrade planning.

Fully functional Kubernetes clusters running on top of other Kubernetes clusters, enabling multi-tenancy.

Web-based tool for security risk analysis of Kubernetes resource manifests, identifying vulnerabilities.

Kubernetes native configuration management tool that allows customization of YAML manifests without templating.

Technique in Kustomize for creating variations of a common base of Kubernetes resources, enabling environment-specific configs.

Method in Kustomize for modifying existing Kubernetes resources without directly editing the original YAML files.

Cloud security platform providing compliance monitoring and threat detection for containerized environments.

Unit of a container image representing a set of files or changes, crucial for image building and optimization.

Storage mechanism used by container runtimes, allowing efficient storage and quick updates of container images.

Design pattern ensuring only one instance of a distributed application component is active at a time.

Process where multiple instances of an operator elect a leader to prevent conflicts in resource management.

Security concept of giving a user or process only the minimum levels of access necessary to perform its function.

User-friendly, open-source IDE for managing Kubernetes clusters, providing a unified interface for multiple clusters.

Observability platform providing insights into the behavior of highly distributed software systems and microservices.

Kubernetes policy for constraining resource allocations (CPU and memory) for pods or containers in a namespace.

Kubernetes object defining the min, max, and default compute resources for pods and containers in a namespace.

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

Component of Linkerd responsible for proxying traffic between services, implementing service mesh functionality.

Linkerd resource providing service-specific traffic metrics and control, enhancing observability and management.

High-performance, minimal-footprint proxy used in Linkerd's data plane for efficient service mesh operations.

Framework allowing various security models to be plugged into the Linux kernel, enhancing container isolation.

Process of connecting external load balancers with Kubernetes services for distributing incoming traffic.

Methods used by load balancers to distribute traffic across multiple container instances or pods.

Kubernetes service type that provisions an external load balancer in cloud environments for routing external traffic to services.

Kubernetes volume type for locally attached storage, providing high-performance storage options for stateful workloads.

Technique for routing traffic to geographically or topologically closer endpoints in distributed container deployments.

Techniques for collecting, processing, and storing logs from distributed containerized applications for centralized analysis.

Design of systems for capturing, storing, and analyzing logs from containers and orchestration platforms.

Horizontally-scalable, multi-tenant log aggregation system designed for use with Prometheus and Kubernetes.

Cloud-native distributed block storage system for Kubernetes, providing persistent storage for stateful workloads.

Implementation of Longhorn for providing resilient, replicated block storage in Kubernetes clusters.

Comparison of container runtimes operating at different abstraction levels, balancing performance and features.

Technique for precomputing and storing query results, improving performance in microservices architectures.