Engineering Glossary

From fundamental principles to cutting-edge practices, this glossary covers the full spectrum of software engineering terminology.

DevOps
Cloud Computing
Git
Containerization & Orchestration

I/O Throughput

Measure of the amount of data processed by a system's input/output operations in a given amount of time.
DevOps

IAST

Interactive Application Security Testing; security testing methodology that analyzes code for security vulnerabilities while the app is run.
DevOps

IDE

Integrated Development Environment; software application that provides comprehensive facilities to computer programmers for software development.
DevOps

IIS Log Viewer

Tool for analyzing and troubleshooting logs from Microsoft Internet Information Services.
DevOps

IIS Server

Microsoft's web server for hosting websites, web applications, and services on Windows operating systems, offering various features and security options.
DevOps

IOPS (Input/Output Operations per Second)

Performance measurement for storage devices, indicating how many read/write operations can be performed in one second.
DevOps

IT Infrastructure

Composite hardware, software, network resources, and services required for the existence, operation, and management of an enterprise IT environment.
DevOps

IT Operations

Daily work of managing the IT infrastructure and systems that support an organization's business operations.
DevOps

IT Operations Management (ITOM)

Practices and processes for operating, administering, and maintaining IT infrastructure and services.
DevOps

ITSI

IT Service Intelligence; uses machine learning for monitoring, anomaly detection, and service health.
DevOps

IaC (Infrastructure as Code)

Infrastructure as Code; managing and provisioning infrastructure through code instead of manual processes.
DevOps

IaaS (Infrastructure-as-a-Service)

Infrastructure as a Service; cloud-computing service in which compute, storage, and networking resources are provided on-demand.
DevOps

Icinga

Open source monitoring system checking availability and performance of network resources.
DevOps

Identity and Access Management (IAM)

Framework of policies and technologies for ensuring that the right users have the appropriate access to resources.
DevOps

Improper Assets Management

Security issue where an organization fails to properly inventory, update, and manage its IT assets.
DevOps

Incident

Any unplanned interruption or reduction in quality of a service, requiring prompt response and resolution to minimize impact.
DevOps

Incident Management

Structured approach to responding to and resolving IT service disruptions, minimizing their impact on business operations.
DevOps

Incident Prozess

The Incident Prozess involves identifying, managing, and resolving unexpected disruptions to restore normal service, minimizing impact and preventing recurrence.
DevOps

Incident Response

Organized approach to addressing and managing the aftermath of a security breach or attack.
DevOps

Indicators of Compromise (IoC)

Pieces of forensic data that identify potentially malicious activity on a network or system.
DevOps

InfluxDB

Open-source time series database designed to handle high write and query loads, often used for monitoring and metrics.
DevOps

Information Security Management

Set of policies and procedures for systematically managing an organization's sensitive data.
DevOps

Infrastructure

Composite of all DevOps components that make up an organization's environment, including hardware, software, and networking.
DevOps

Infrastructure Drift

Unplanned changes to infrastructure over time, deviating from the desired state.
DevOps

Infrastructure Management (IM)

Process of managing essential operation components, such as policies, processes, equipment, data, human resources, and external contacts.
DevOps

Infrastructure Metrics

Measurements used to assess the performance, health, and efficiency of IT infrastructure components.
DevOps

Infrastructure Monitoring

Process of collecting and analyzing data from infrastructure to ensure optimal performance.
DevOps

Infrastructure Resilience

Ability of IT infrastructure to withstand and recover from disruptions and disasters.
DevOps

Infrastructure as Code (IaC)

Managing and provisioning infrastructure through code instead of manual processes. Enables version control, automation, and consistent environments.
DevOps

Infrastructure as Code (IaC) Framework

Set of tools and practices for managing infrastructure through machine-readable definition files.
DevOps

Infrastructure as Data

Approach to infrastructure management where the desired state is described as data, not procedural code.
DevOps

Infrastructure as Software

Treating infrastructure configuration and management as a software development problem.
DevOps

Infrastructure on Demand

Ability to provision and de-provision infrastructure resources as needed, often in cloud environments.
DevOps

Infrastructure-as-a-Service (IaaS)

Cloud computing model providing virtualized computing resources over the internet. Users can rent servers, storage, networks, and operating systems.
DevOps

Ingress Controller

Kubernetes resource managing external access to services in a cluster, typically HTTP.
DevOps

Injection

Security vulnerability where untrusted data is sent to an interpreter as part of a command or query.
DevOps

Insecure Deserialization

Security vulnerability occurring when untrusted data is used to abuse the logic of an application.
DevOps

Insecure Direct Object Reference (IDOR)

Security flaw allowing attackers to bypass authorization and access resources directly by modifying the value of a parameter.
DevOps

Instance

Single copy of a running computer program, often referring to a virtual server in cloud computing.
DevOps

Insufficient Logging & Monitoring

Security weakness where systems lack adequate logging and real-time monitoring, hindering threat detection and forensics.
DevOps

Integration Testing

Phase in software testing where individual modules are combined and tested as a group.
DevOps

Intelligent Automation

Use of AI and machine learning to automate complex business processes and decisions.
DevOps

Interactive Application Security Testing (IAST)

Security testing tool that combines static and dynamic testing methods to detect vulnerabilities in running applications.
DevOps

Internal Developer Platform (IDP)

Set of tools and practices that improve developer experience and productivity within an organization.
DevOps

Internal Threat Intelligence

Process of gathering, analyzing, and disseminating information about potential internal security threats.
DevOps

Inventory Hoarding

Excessive accumulation of IT resources, often in cloud environments, leading to waste and inefficiency.
DevOps

Ionic

Open-source SDK for developing hybrid mobile applications using web technologies.
DevOps

Issue Tracking

Process of recording and following the progress of problems or tasks in a project.
DevOps

Iterations

Fixed time periods in Agile development during which a team completes a set amount of work.
DevOps

JVM Heap

Portion of memory where the Java Virtual Machine stores objects, crucial for application performance and garbage collection processes.
DevOps

JVM Threads

Lightweight processes within the Java Virtual Machine that allow concurrent execution of tasks in Java applications.
DevOps

Jamstack

Web development architecture based on client-side JavaScript, reusable APIs, and prebuilt Markup.
DevOps

Jcloud

Java library providing a multi-cloud abstraction layer, simplifying cloud platform interactions.
DevOps

Jenkins

Open-source automation server that enables developers to build, test, and deploy their software reliably.
DevOps

Jenkins Job

Runnable task configured in Jenkins, defining a series of related steps to be executed.
DevOps

Jenkins Pipeline

Suite of plugins supporting implementation and integration of continuous delivery pipelines into Jenkins.
DevOps

Jest

JavaScript testing framework designed to ensure correctness of any JavaScript codebase.
DevOps

Jetpack Compose

Modern toolkit for building native Android UI, using a declarative and composable approach.
DevOps

Jira

Project management tool used for issue tracking, bug tracking, and agile project management.
DevOps

Juju

Open-source application modeling tool for deploying, configuring, scaling, and operating software.
DevOps

KISS (Keep it simple, stupid)

Design principle stating that systems perform best when kept simple rather than made complicated.
DevOps

Kafka

Distributed event streaming platform capable of handling trillions of events a day.
DevOps

Kaizen

Japanese business philosophy of continuous improvement of working practices and personal efficiency.
DevOps

Kanban

Visual system for managing work as it moves through a process, emphasizing continuous delivery.
DevOps

Kanban Board

Visual representation of work items as they progress through different stages of a process.
DevOps

Kata

Programming exercise aimed at honing coding skills through practice and repetition, often used in coding dojos and training sessions.
DevOps

Keystroke Loggers

Software or hardware that records keyboard inputs, often used maliciously to capture sensitive information.
DevOps

Kibana

Data visualization and exploration tool for Elasticsearch, allowing users to create interactive dashboards and analyze large volumes of data.
DevOps

Kickstart

Method of performing automatic installation and configuration of operating systems, particularly in Linux.
DevOps

Kubernetes

Open-source system for automating deployment, scaling, and management of containerized applications.
DevOps

Kubernetes (K8s)

Alternative abbreviation for Kubernetes, where 8 replaces the eight letters between K and s.
DevOps

Kubernetes (Ks)

Alternate abbreviation for Kubernetes, the open-source container orchestration platform for automating application deployment and scaling.
DevOps

Kubernetes Cronjobs

Kubernetes object for creating recurring scheduled tasks, allowing automated execution of jobs at specified intervals.
DevOps

Kubernetes Monitoring

Observing and tracking the health, performance, and resource usage of Kubernetes clusters and applications.
DevOps

Kubernetes Operator

Method of packaging, deploying, and managing a Kubernetes application using custom resources and controllers.
DevOps

Kubernetes Pod

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

Kubernetes QoS

Quality of Service classes in Kubernetes that determine how pods are scheduled and evicted based on resource requirements.
DevOps

Kubernetes Replica

Identical copy of a pod, used to ensure specified number of pod instances are running at any given time.
DevOps

Kubernetes Workloads

Objects in Kubernetes that manage a set of pods, such as Deployments, StatefulSets, and DaemonSets.
DevOps

Lack of Resources

Insufficient tools, infrastructure, skills, or personnel needed to implement and maintain efficient CI/CD pipelines and automation processes.
DevOps

Largest Contentful Paint (LCP)

Metric measuring the render time of the largest image or text block visible within the viewport.
DevOps

Lead Time

Time between the initiation and completion of a process, often used in software development to measure efficiency.
DevOps

Lead Time for Changes

Metric measuring the time it takes for a commit to be deployed to production, indicating the efficiency of the development process.
DevOps

Leaking API

API that unintentionally exposes sensitive data or functionality, potentially leading to security vulnerabilities and data breaches.
DevOps

Lean

Methodology aimed at maximizing customer value while minimizing waste, applicable to various industries including software development.
DevOps

Lean IT

Application of lean manufacturing principles to IT operations, focusing on eliminating waste and improving efficiency in IT processes.
DevOps

Legacy Application

Outdated computer system, programming language or application software that is still in use.
DevOps

Linux

Open-source, Unix-like operating system kernel that forms the basis of many popular distributions, known for its stability and flexibility.
DevOps

Linux Out of Memory Killer (OOM Killer)

Linux kernel process that terminates applications in low memory situations to prevent system crashes.
DevOps

Load Balancer

Device that distributes network or application traffic across multiple servers to ensure no single server bears too much demand.
DevOps

Load Balancing

Process of distributing network traffic across multiple servers to ensure no single server bears too much demand.
DevOps

Local File Inclusion (LFI)

Vulnerability allowing an attacker to include files on a server through the web browser.
DevOps

Log Aggregation

Process of collecting and centralizing log data from multiple sources into a single, searchable repository for analysis and monitoring.
DevOps

Log Analysis

Process of examining log files to identify events, patterns, or anomalies, crucial for troubleshooting and security monitoring.
DevOps

Log Drain

Process of forwarding log data from its origin to a centralized log management system.
DevOps

Log Every Change

Practice of recording all modifications made to a system or application, crucial for auditing and troubleshooting.
DevOps

Log File

Record of events occurring within an organization's systems and networks, crucial for troubleshooting and security analysis.
DevOps

Log Levels

Categories used to distinguish the importance and nature of logged messages, aiding in log analysis and troubleshooting.
DevOps

Log Management

Process of collecting, storing, analyzing, and disposing of log data generated by various IT systems and applications.
DevOps

Log Management Policy

Set of guidelines and procedures governing the collection, storage, analysis, and retention of log data within an organization.
DevOps
stash entry

stash entry

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

status checks

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

subscription

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

superproject

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

symref

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

tag object

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

team

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

team maintainer

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

timeline

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

topic branch

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

topics

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

traffic graph

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

transfer

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

tree

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

tree object

A Git object that stores the hierarchy of files and directories in a repository at a specific point in time.
tree-ish (also treeish)

tree-ish (also treeish)

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

unborn

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

unmerged index

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

unreachable object

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

upstream branch

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

user

An individual account on a Git platform, associated with personal repositories and contributions.
user-to-server request

user-to-server request

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

username

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

visible team

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

watch

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

watching notifications

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

web notifications

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

working area

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

working tree

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

worktree

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

write access

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

3D Stacked Memory for Cloud Servers

High-density memory architecture using vertically stacked chips, enhancing performance and capacity in cloud server hardware.

5G Cloud

Cloud infrastructure optimized for 5G networks, supporting high-speed, low-latency services and applications.

5G Network Slicing

Technique to create multiple virtual networks on a shared physical 5G infrastructure, each optimized for specific use cases.

5G and Edge Computing

Integration of 5G networks with edge computing to enable low-latency, high-bandwidth applications closer to end-users.

6G Cloud Integration

Future convergence of 6G networks with cloud computing, promising ultra-high speeds and advanced capabilities.

ACID Compliance

Database transaction properties (Atomicity, Consistency, Isolation, Durability) ensuring data integrity in cloud environments.

AI Ethics Compliance Tools

Software ensuring AI systems adhere to ethical guidelines and regulations in cloud deployments.

AI Ethics and Bias Detection Tools

Software for identifying and mitigating ethical issues and biases in AI models deployed in cloud environments.

AI Ethics and Governance Tools

Solutions for managing ethical considerations and regulatory compliance in cloud-based AI systems.

AI Governance Frameworks

Structured approaches for managing AI development, deployment, and use in cloud environments.

AI Model Governance Platforms

Comprehensive solutions for managing, monitoring, and controlling AI models in cloud-based systems.

AI Model Interpretability Services

Cloud-based tools for explaining and understanding the decision-making processes of AI models.

AI Model Interpretability Tools

Software for analyzing and explaining AI model decisions, crucial for transparency in cloud AI services.

AI Model Marketplaces

Cloud platforms for discovering, sharing, and monetizing pre-trained AI models and algorithms.

AI Model Monitoring and Drift Detection

Tools for tracking AI model performance and identifying deviations from expected behavior in cloud environments.

AI Model Versioning and Governance

Systems for managing different versions of AI models and enforcing governance policies in cloud deployments.

AI-Assisted Coding Platforms

Cloud-based development environments that use AI to assist programmers in writing and optimizing code.

AI-Augmented Analytics

Integration of AI capabilities into data analytics processes in cloud environments for enhanced insights.

AI-Driven Capacity Planning

Use of AI algorithms to predict and optimize resource allocation in cloud infrastructures.

AI-Driven Cloud Optimization

Application of AI techniques to improve efficiency, performance, and cost-effectiveness of cloud resources.

AI-Driven Cloud Resource Allocation

Automated distribution of cloud resources using AI to optimize performance and cost-efficiency.

AI-Driven Cloud Service Composition

AI-based automation of cloud service selection and integration for complex workflows.

AI-Driven Code Generation

Automated creation of source code using AI models, often integrated into cloud development platforms.

AI-Driven Data Classification

Automated categorization and labeling of data using AI algorithms in cloud storage and processing systems.

AI-Driven Network Optimization

Use of AI to improve network performance, efficiency, and security in cloud environments.

AI-Driven Resource Allocation

Intelligent distribution of computing resources in cloud environments using AI algorithms.

AI-Driven Security Information and Event Management (SIEM)

Enhanced SIEM systems using AI for improved threat detection and response in cloud environments.

AI-Driven Threat Detection

Use of AI algorithms to identify and analyze potential security threats in cloud systems.

AI-Driven Threat Hunting

Proactive search for hidden threats in cloud environments using AI-powered analytics and automation.

AI-Optimized Cloud Hardware

Cloud infrastructure components designed or configured to enhance AI workload performance.

AI-Optimized Databases

Database systems tailored for AI workloads, often featuring in-memory processing and distributed architectures.

AI-Powered Anomaly Detection

Use of AI algorithms to identify unusual patterns or behaviors in cloud systems and data.

AI-Powered Integration

Intelligent automation of data and application integration processes in cloud environments using AI.

AI-as-a-Service

Cloud-based offering of AI capabilities, allowing businesses to leverage AI without extensive in-house expertise.

AI-as-a-Service (AIaaS)

Cloud-based AI capabilities offered as a service, enabling easy integration of AI into applications.

AIOps

Application of AI for automating and enhancing IT operations management in cloud environments.

AIOps Platforms

Integrated solutions leveraging AI for automated monitoring, analysis, and management of cloud IT operations.

AIOps for Predictive Maintenance

Use of AI-driven analytics to forecast and prevent system failures in cloud infrastructure.

API Security Gateway

Service that protects APIs in cloud environments by managing access, monitoring traffic, and preventing attacks.

API Security Gateways

Dedicated services for securing and managing APIs in cloud environments, including access control and threat protection.

API-First Development

Design approach prioritizing API creation before implementation, common in cloud-native application development.

API-Led Connectivity

Integration strategy using purpose-built APIs to connect data, devices, and applications in cloud ecosystems.

AR Cloud

Persistent 3D digital content overlaid on the physical world, accessible via cloud infrastructure for augmented reality applications.

AR/VR Analytics

Cloud-based tools for analyzing user behavior and performance in augmented and virtual reality environments.

AR/VR Collaboration Platforms

Cloud-hosted services enabling multi-user interaction in shared augmented or virtual reality spaces.

AR/VR Content Delivery Network

Specialized CDN optimized for delivering AR/VR content with low latency and high bandwidth.

AR/VR Development Platforms

Cloud-based tools and services for creating, testing, and deploying augmented and virtual reality applications.

ARM Templates (Azure)

JSON-based files defining infrastructure and configuration for Azure resource deployment.

Adaptive User Interfaces for Cloud Services

Dynamic UIs that adjust based on user behavior, device capabilities, and context in cloud applications.

Adversarial Machine Learning Detection

Techniques to identify and mitigate attacks on ML models in cloud-based AI systems.

Alerting and Notification

Systems for informing administrators or users about important events or issues in cloud environments.

Algorithmic Auditing

Process of examining AI algorithms for bias, errors, or unintended consequences in cloud-based systems.

Ambient Computing Interfaces for Cloud

Seamless, context-aware interaction methods for accessing cloud services in IoT environments.

Anomaly Detection Systems

Tools for identifying unusual patterns or behaviors in cloud systems, often using machine learning techniques.

Application-Aware Networking

Network management approach that optimizes performance based on specific application requirements in cloud environments.

Approximate Query Processing

Technique for quickly estimating query results in large-scale cloud databases, trading accuracy for speed.

Archive Storage (e.g., Amazon Glacier, Azure Archive Storage)

Low-cost cloud storage for infrequently accessed data with longer retrieval times, e.g., Amazon Glacier, Azure Archive Storage.

Artifact Repository

Cloud-based storage for software build outputs, dependencies, and related metadata.

Artificial General Intelligence (AGI) as a Service

Hypothetical cloud offering of human-level AI capabilities across various domains.

Artificial General Intelligence Research Platforms

Cloud-based environments for developing and testing advanced AI systems approaching human-level intelligence.

Audit Logging

Systematic recording of actions and events in cloud systems for security and compliance purposes.

Audit Trails

Chronological records of system activities for reconstructing and examining the sequence of events in cloud environments.

Augmented Analytics

Integration of machine learning and natural language processing in cloud-based data analytics workflows.

Augmented Reality (AR) Cloud

Shared, persistent digital content overlaid on the physical world, accessible via cloud infrastructure.

Augmented Reality Cloud Interfaces

Cloud-based systems for managing and delivering AR content and experiences, enabling scalable AR applications.

Augmented Reality Cloud Rendering

Cloud-powered generation of AR graphics and content, offloading processing from end-user devices.

Auto Scaling Groups

Collections of EC2 instances that automatically adjust capacity based on defined conditions.

Auto-scaling

Automatic adjustment of cloud resources to match workload demands, ensuring optimal performance and cost-efficiency.

AutoML

Automated machine learning processes for model selection, hyperparameter tuning, and feature engineering in cloud environments.

AutoML in the Cloud

Cloud-based services automating the machine learning pipeline from data preparation to model deployment and monitoring.

Automated AI Pipeline Optimization

AI-driven tools for improving efficiency and performance of machine learning workflows in the cloud.

Automated Cloud Governance Enforcement

Systems that automatically implement and maintain cloud resource policies and compliance.

Automated Compliance Monitoring

Continuous, AI-driven assessment of cloud systems against regulatory and security standards.

Automated Data Discovery

AI-powered tools for identifying, categorizing, and mapping data assets in cloud environments.

Automated Data Governance

AI-driven systems for managing data quality, security, and compliance in cloud environments.

Automated Data Wrangling Services

Cloud-based tools using AI to clean, transform, and prepare data for analysis, streamlining data preparation processes.

Automated Feature Engineering

AI-powered generation and selection of features for machine learning models in cloud environments.

Automated Incident Response Orchestration

AI-driven coordination of security incident detection and resolution in cloud systems, automating response workflows.

Automated Machine Learning (AutoML)

Cloud services that automate the process of creating and optimizing machine learning models, from data prep to deployment.

Automated Machine Learning (AutoML) Platforms

Cloud-based systems that automate the end-to-end machine learning model development process, including feature engineering and model selection.

Automated Penetration Testing

AI-driven tools for simulating cyberattacks to identify vulnerabilities in cloud systems and applications.

Automated Threat Modeling

AI-powered analysis of cloud architectures to identify potential security risks and attack vectors.

Autonomous Systems in the Cloud

Self-managing, self-healing cloud services requiring minimal human intervention, leveraging AI for operations.

Azure Edge Zones

Ultra-low latency edge computing extensions of Azure for 5G networks, bringing cloud resources closer to users.

Azure Policy

Service for creating, assigning, and managing policies to control Azure resources and ensure compliance.

B2B Integration Platforms

Cloud-based services facilitating data exchange and process integration between business partners.

Backend for Frontend (BFF) Pattern

Architectural approach creating backend services tailored to specific frontend application needs in cloud environments.

Bare Metal Server

Physical server dedicated to a single tenant, offering direct hardware access in cloud environments.

Bare Metal Servers

Dedicated physical servers without virtualization, offered as a cloud service for high-performance workloads.

Batch Processing (e.g., AWS Batch, Azure Batch)

Execution of series of jobs without user interaction, often for large-scale data processing in the cloud (e.g., AWS Batch, Azure Batch).

Big Data Clusters

Distributed computing environments for processing and analyzing massive datasets in the cloud.

Billing Dashboard

Interface for monitoring and managing cloud service usage and costs, providing detailed breakdowns and forecasts.

Biocomputing in the Cloud

Use of cloud resources for computational biology and genomics research, enabling large-scale analysis and modeling.

Biodiversity Impact Assessment for Cloud Facilities

Evaluation of cloud data center effects on local ecosystems and wildlife to ensure sustainable operations.

Block Storage

Cloud storage that provides fixed-size raw storage volumes, typically used for databases or file systems.

Block Storage (e.g., Amazon EBS, Azure Disk Storage)

Cloud services providing persistent block-level storage volumes for use with compute instances.

Blockchain Analytics

Cloud-based tools for analyzing and visualizing blockchain data and transactions, offering insights into network activity.

Blockchain Databases

Distributed databases using blockchain technology for enhanced security and immutability in cloud environments.

Blockchain Governance Tools

Software for managing and enforcing rules, permissions, and consensus mechanisms in blockchain networks deployed on cloud platforms.

Blockchain Integration Services

Cloud-based solutions for connecting blockchain networks with existing enterprise systems and applications.

Extended Resources

Custom, cluster-level resources in Kubernetes that can be allocated to containers, such as GPUs or FPGAs.

Extender

Kubernetes component allowing custom logic to be added to the scheduling process for advanced pod placement strategies.

External Admission Webhooks

HTTP callbacks that receive admission requests and can modify or reject objects before persistence in Kubernetes.

External Secrets Management Integration

Incorporation of external secret management systems like HashiCorp Vault with container platforms.

ExternalName

Kubernetes service type that maps a service to a DNS name, useful for representing external services within a cluster.

ExternalName Services

Kubernetes services that reference external resources by DNS name, facilitating access to external dependencies.

FPGA Scheduling

Allocation and management of Field-Programmable Gate Arrays as resources in container orchestration platforms.

FaaS on Kubernetes

Implementation of Function-as-a-Service platforms on Kubernetes, enabling serverless architectures in container environments.

Falco

Open-source cloud-native runtime security project, providing real-time threat detection for containerized environments.

Falco for Runtime Security

Use of Falco to monitor and alert on unexpected behavior in running containers and Kubernetes clusters.

Fault Injection

Technique of intentionally introducing failures in containerized systems to test resilience and error handling capabilities.

Feature Gates

Flags in Kubernetes used to enable or disable specific features, allowing for fine-grained control over cluster functionality.

Federated Service Mesh

Implementation of service mesh across multiple Kubernetes clusters, enabling cross-cluster service communication.

Federation

Technique for managing multiple Kubernetes clusters from a single control plane, useful for multi-cloud or hybrid deployments.

Finalizers

Kubernetes feature allowing controllers to implement asynchronous pre-delete hooks, ensuring proper resource cleanup.

Finalizers in Operators

Use of finalizers in Kubernetes operators to perform cleanup operations before custom resource deletion.

Firecracker

Lightweight virtualization technology used for creating and managing secure, multi-tenant container environments.

Firecracker MicroVMs

Minimal virtual machines used by Firecracker to provide strong isolation for containers or functions.

Fission

Open-source, Kubernetes-native serverless framework for running functions, supporting multiple languages and event triggers.

Flagger

Progressive delivery tool for Kubernetes, automating canary releases and A/B testing of containerized applications.

Flannel

Network fabric for containers designed to give a consistent, easily configured layer 3 network across multiple hosts for Kubernetes.

Flannel for Simple Overlay Networking

CNI plugin providing a simple overlay network for container communication across hosts, enabling basic networking.

FlexVolume

Out-of-tree plugin mechanism in Kubernetes for interfacing with third-party storage systems, predating CSI.

FluentD

Open-source data collector for unified logging layer, enabling efficient data collection and consumption for better use of data.

Fluentd DaemonSet

Kubernetes deployment ensuring Fluentd log collectors run on every node for comprehensive log aggregation.

Fluentd Input Plugins

Modular components in Fluentd for ingesting logs from various sources in containerized environments.

Fluentd Output Plugins

Modular components in Fluentd for sending processed logs to various destinations from containerized environments.

Flux CD

GitOps toolkit for deploying applications to Kubernetes, automating the deployment pipeline from Git repositories.

Flux v2

Next generation of Flux, providing a set of continuous delivery solutions for Kubernetes with improved modularity and features.

Function Autoscaling

Automatic adjustment of function instances based on demand in serverless container environments.

Function Buildpacks

Standardized way of building function containers, abstracting away infrastructure concerns for developers.

GPU Scheduling in Kubernetes

Process of allocating and managing GPU resources for containers running machine learning workloads.

Garden.io for Remote Kubernetes Development

Tool facilitating development and testing of Kubernetes applications in remote clusters.

Generic Ephemeral Volumes

Kubernetes feature allowing for dynamic provisioning of short-lived volumes for containers.

Geneve Overlay Networks

Network virtualization technology used in some container networking solutions for multi-tenant environments.

GitLab CI/CD

Integrated CI/CD platform with native container and Kubernetes support for building, testing, and deploying applications.

GitOps Toolkit

Set of composable APIs and specialized tools for building continuous delivery systems on top of Kubernetes.

GitOps Workflow

Operational model where the desired state of a Kubernetes cluster is version controlled and automated from a Git repository.

GlusterFS

Distributed file system that can be used for providing persistent storage to containerized applications in Kubernetes.

Go-based Operators

Kubernetes operators written in Go, leveraging the client-go library for interacting with the Kubernetes API.

Goldilocks for Resource Recommendation

Tool that provides recommendations for resource requests and limits for Kubernetes deployments.

Google Cloud Run

Managed compute platform for deploying containerized applications in a serverless environment.

Google Container Registry (GCR)

Managed Docker registry service by Google for storing, managing, and securing container images.

Grafana Dashboards

Customizable visualization panels for monitoring containerized environments and applications.

Grafana Data Sources

Configurable backends in Grafana for retrieving metrics and logs from various container monitoring systems.

Grafana Loki

Horizontally-scalable, multi-tenant log aggregation system designed for use in containerized environments.

Grafana Provisioning

Automated setup and configuration of Grafana dashboards and data sources in container deployments.

GraphQL in Containerized Environments

Implementation of GraphQL APIs in microservices architectures for flexible data querying and manipulation.

Guaranteed QoS

Kubernetes Quality of Service class ensuring pods receive the exact amount of requested resources, ideal for critical workloads.

Harbor

Open-source container registry providing content trust, vulnerability scanning, and RBAC for storing and distributing container images.

Harness CD

Continuous Delivery platform supporting various deployment strategies for containerized applications in Kubernetes environments.

Headless Services

Kubernetes services that don't allocate a cluster IP, used for direct pod-to-pod communication in stateful applications.

Helm

Package manager for Kubernetes that helps you define, install, and upgrade even the most complex Kubernetes applications.

Helm Charts

Packages of pre-configured Kubernetes resources, facilitating the deployment and management of complex applications.

Helm Hooks

Helm feature allowing custom actions to be performed at specific points in a release's lifecycle, enhancing deployment flexibility.

Helm Operator

Kubernetes operator that manages Helm releases, automating the deployment and lifecycle of Helm-based applications.

Helm Repositories

Storage locations for packaged Helm charts, enabling version control and distribution of containerized application configurations.

Helm Values

Mechanism in Helm for parameterizing chart templates, allowing for customization of deployments across different environments.

Helm-based Operators

Kubernetes operators leveraging Helm charts for managing the lifecycle of complex, stateful applications.

Hierarchical Namespaces

Kubernetes feature allowing nested namespaces, providing finer-grained resource isolation and multi-tenancy capabilities.

Horizontal Pod Autoscaler

Kubernetes controller that automatically adjusts the number of pods in a deployment based on observed metrics.

Horizontal Pod Autoscaler Metrics

Metrics used by HPA to determine when to scale containerized applications, including CPU, memory, and custom metrics.

Horizontal Pod Autoscaler with Custom Metrics

Extended HPA functionality allowing scaling decisions based on application-specific or external metrics.

HorizontalPodAutoscaler

Kubernetes resource defining the behavior for automatically scaling the number of pods in a replication controller or deployment.

Host Networking

Container networking mode where pods use the host's network namespace, bypassing virtual networks for improved performance.

HugePages

Linux kernel feature for managing large memory pages, improving performance for memory-intensive containerized applications.

IPVS

IP Virtual Server, a transport-layer load balancing technology used in Kubernetes for efficient service proxying and load distribution.

IPsec for Container Networks

Implementation of IPsec protocols to secure container-to-container communications across hosts and clusters.

IPv4/IPv6 Dual-Stack

Kubernetes feature enabling pods and services to be assigned both IPv4 and IPv6 addresses, facilitating transition to IPv6.

IPv6 in Kubernetes

Support and configuration for using IPv6 addressing in Kubernetes clusters, enabling large-scale container deployments.

Idempotent API Design

Approach to designing APIs that can be called multiple times without changing the result, crucial for reliable microservices.

Image

Lightweight, standalone, executable package that includes everything needed to run a piece of software.

Image Digests

Unique identifiers for container images, ensuring consistency and integrity across different environments and registries.

Image Index (Fat Manifest)

OCI specification for multi-architecture container images, allowing a single image to support multiple platforms.

Image Layer Caching

Technique for reusing unchanged layers when building or pulling container images, improving build and deployment speed.

Image Layer Optimization

Strategies for reducing the size and number of layers in container images, improving storage efficiency and pull times.

Image Manifest

Metadata file describing the contents and configuration of a container image, crucial for image distribution and deployment.

Image Manifest V2 Schema 2

Standardized format for container image manifests, supporting multi-architecture images and content-addressable layers.

Image Promotion

Process of moving container images through different environments (e.g., dev, staging, production) in a controlled manner.

Image Pulling

Process of downloading container images from a registry to a local environment or container runtime.

Image Pushing

Process of uploading locally built container images to a remote registry for distribution and deployment.

Image Retention Policies

Rules defining how long container images are kept in a registry, balancing storage costs with availability needs.

Image Scanning

Automated process of analyzing container images for vulnerabilities, misconfigurations, and compliance issues.

Image Signing

Cryptographic process of digitally signing container images to ensure their integrity and authenticity during distribution.

Image Signing and Verification

End-to-end process of cryptographically signing container images and verifying their authenticity before deployment.

Image Squashing

Technique of combining multiple layers of a container image into a single layer, potentially reducing image size and complexity.

Image Tagging

Process of assigning human-readable labels to container images, facilitating version management and deployment workflows.

Image Vulnerability Scanning

Automated security analysis of container images to identify known vulnerabilities in installed packages and dependencies.

ImageService

Component in container runtimes responsible for managing image-related operations like pulling, pushing, and local storage.

Immutable Infrastructure

Practice of replacing entire container instances instead of modifying existing ones, enhancing consistency and reliability.

Imperative Deployments

Approach to deploying containerized applications by directly specifying the desired actions, as opposed to declarative methods.

In-Memory Data Grids

Distributed data management systems optimized for high-performance data processing in containerized environments.

In-Place Upgrades

Technique for updating containerized applications or infrastructure components without full redeployment, minimizing downtime.

In-Tree Plugins

Built-in plugins in Kubernetes for various functionalities, as opposed to out-of-tree or external plugins.

Incremental Image Transfer (eStargz)

Technique for optimizing container image distribution by allowing partial and on-demand loading of image layers.

Infrastructure as Code (IaC) Testing

Automated testing of infrastructure definitions, ensuring consistency and reliability in container deployments.

Ingress

Kubernetes API object managing external access to services in a cluster, typically HTTP, providing load balancing and SSL termination.

Ingress Controllers

Components implementing the Ingress resource in Kubernetes, managing the routing of external traffic to internal services.

Ingress Gateway

Entry point for external traffic in service mesh architectures, providing routing, security, and observability for incoming requests.

Init Container Pattern

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