Engineering Glossary

Lorem ipsum dolor sit amet, consectetur adipiscing elit. Suspendisse varius enim in eros elementum tristique.

DevOps
Git
Cloud Computing
Containerization & Orchestration

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

Log Management Process

Systematic approach to collecting, storing, analyzing, and disposing of log data.
DevOps

Log Rotation

Process of archiving filled log files and starting new ones to prevent excessive disk space usage.
DevOps

Log.io

Real-time log monitoring tool that allows users to view and search logs from multiple sources in a single web-based interface.
DevOps

LogShell Vulnerability

Critical security flaw in the Log4j library, allowing remote code execution and posing significant security risks.
DevOps

Loggly

Cloud-based log management and analytics service that helps organizations collect, analyze, and act on machine-generated data from various sources.
DevOps

Logstash

Open-source data processing pipeline that ingests data from multiple sources simultaneously.
DevOps

Logster

Utility for reading log files and generating metrics for monitoring systems like Graphite and Ganglia.
DevOps

Loom

Project aimed at adding lightweight concurrency and new programming models to Java.
DevOps

Low-code

Software development approach requiring little to no coding to build applications and processes.
DevOps

M Silicon

Apple's custom-designed ARM-based processors for Mac computers, offering improved performance and energy efficiency.
DevOps

MITRE ATT&CK

Globally-accessible knowledge base of adversary tactics and techniques based on real-world observations.
DevOps

MLOps

Set of practices that aims to deploy and maintain machine learning models in production reliably and efficiently.
DevOps

MTTI

Mean Time to Identify; average time between the start of an incident and its discovery.
DevOps

MTTR (Mean Time To Recovery)

Average time required to repair a failed system and restore it to normal operation, a key metric for measuring system reliability.
DevOps

Machine Data

Digital information created by the activity of computers, mobile phones, embedded systems and other networked devices.
DevOps

Machine Learning (ML)

Field of study giving computers the ability to learn without being explicitly programmed.
DevOps

Magecart

Group of threat actors that specialize in stealing credit card data from online stores.
DevOps

Managed Detection and Response

Cybersecurity service that combines technology and human expertise to rapidly identify and respond to threats.
DevOps

Managed SIEM

Security Information and Event Management offered as a managed service, providing expert monitoring and threat detection.
DevOps

Managing Secrets

Process of securely storing and handling sensitive information like passwords and API keys.
DevOps

Mass Assignment

Vulnerability where an active record pattern in a web application is abused to modify data items that the user should not be allowed to access.
DevOps

Maturity Model

Structured representation of improvement across multiple dimensions of an organization or service.
DevOps

Mcollective

Framework for building server orchestration or parallel job execution systems, facilitating large-scale system management.
DevOps

Mean Time Between Failures (MTBF)

Average time between system failures, used to measure reliability and predict future failure occurrences.
DevOps

Mean Time to Recovery (MTTR)

Average time required to repair a failed system and restore it to normal operation.
DevOps

Mean Time to Resolution

Average time between the detection of an incident and its full resolution, a key metric in IT service management.
DevOps

Measure everything

Practice of collecting metrics on all aspects of software development and operations to enable data-driven decisions.
DevOps

Memcached

Distributed memory caching system designed to speed up dynamic web applications.
DevOps

Memory Bottleneck

Situation where system performance is limited by the amount or speed of available memory.
DevOps

Mezmo

Cloud-native observability platform for log management and analysis, helping organizations gain insights from their machine data.
DevOps

Micro Frontend

Architectural style where a frontend app is decomposed into individual, loosely coupled components.
DevOps

Microsegmentation

Security technique that creates secure zones in data centers and cloud deployments to isolate workloads from one another.
DevOps

Microservice-Architektur

Architectural style structuring an application as a collection of loosely coupled services.
DevOps

Microservice-Infrastruktur

Infrastructure designed to support the deployment and operation of microservices.
DevOps

Microservices

Software development technique that structures an application as a collection of loosely coupled services.
DevOps

Microservices Architecture

Architectural style that structures an application as a collection of small autonomous services.
DevOps

Microsoft Azure

Cloud computing service created by Microsoft for building, testing, deploying, and managing applications and services.
DevOps

Mina

Network application framework which helps users develop high performance and high scalability network applications easily.
DevOps

Mobile Analytics

Tools and processes for measuring and analyzing mobile app usage and user behavior.
DevOps

Mobile App Automation

Tools and processes for measuring and analyzing mobile app usage and user behavior.
DevOps

Mobile App Testing

Process of testing mobile applications for functionality, usability, and consistency.
DevOps

Mobile Applications Security Testing (MAST)

Process of testing mobile applications for security vulnerabilities, ensuring protection of user data and app integrity.
DevOps

Mobile Artifacts

Data or files generated during mobile app development and testing, including binaries, logs, and test results.
DevOps

Mobile Testing

Process of testing mobile devices and applications to ensure proper functionality and user experience.
DevOps

Model-Based Testing (MBT)

Software testing technique in which test cases are derived from a model that describes the system under test.
DevOps

MongoDB

Popular open-source document-oriented database program classified as a NoSQL database, known for its flexibility and scalability.
DevOps

Monitoring

Continuous observation and checking of a system's performance, health, and security to ensure optimal operation and detect issues.
DevOps

Monitoring as Code (MaC)

Practice of defining and managing monitoring configurations using code and version control systems.
DevOps

Monolithic Architecture

Software design where all components of an application are interconnected and interdependent.
DevOps

Monorepo

Development approach where code for many projects is stored in the same repository.
DevOps

Muda

Japanese term for waste in lean methodologies, referring to any activity that doesn't add value to the final product or service.
DevOps

Multi-Cloud Strategy

Use of multiple cloud computing and storage services in a single heterogeneous architecture.
DevOps

Mura

Japanese term in lean methodologies referring to unevenness or irregularity in processes, which can lead to inefficiencies.
DevOps

Muri

Japanese term in lean methodologies referring to overburden or unreasonableness, which can lead to stress and inefficiencies.
DevOps

Mutable Infrastructure

Infrastructure that can be updated or modified after it is deployed, contrasting with immutable infrastructure approaches.
DevOps

NFRs

Non-Functional Requirements; requirements that specify criteria for judging the operation of a system, rather than specific behaviors.
DevOps

NIST SIEM Requirements and Standards

Guidelines set by the National Institute of Standards and Technology for Security Information and Event Management systems.
DevOps

NPM

Node Package Manager, the default package manager for Node.js, used for installing and managing JavaScript packages and dependencies.
DevOps

Nagios

Open source monitoring system for computer systems, networks and infrastructure.
DevOps

NestJS

Progressive Node.js framework for building efficient and scalable server-side applications.
DevOps

Network Bottleneck

Point in a network where bandwidth is limited, causing slowdowns in data transfer.
DevOps

Network as a Service (NaaS)

Cloud model where network services are delivered over the internet, offering flexibility and scalability.
DevOps

New Relic

Cloud-based observability platform that helps developers monitor, debug, and optimize their entire stack.
DevOps

Next Generation WAF (Web Application Firewall)

Advanced WAF that uses machine learning and behavioral analytics to protect web applications.
DevOps

Nexus

Repository manager that organizes, stores, and distributes software components, facilitating dependency management in development.
DevOps

Nexus Repository

Software repository manager for storing and distributing build artifacts, supporting various package formats and integrations.
DevOps

Nginx

Web server that can also be used as a reverse proxy, load balancer, mail proxy and HTTP cache.
DevOps

NoOps

Concept where an IT environment becomes so automated that there's no need for a dedicated team to manage software in-house.
DevOps

NoSQLi

NoSQL Injection; security exploit targeting databases that use non-SQL query languages.
DevOps

Node Logging

Process of recording events and data from individual nodes in a distributed system.
DevOps

Node Pool

Group of nodes within a cluster, typically with the same configuration, used in container orchestration platforms like Kubernetes.
DevOps

Node.js

JavaScript runtime built on Chrome's V8 JavaScript engine for building scalable network applications.
DevOps

Nomad

Flexible workload orchestrator to deploy and manage containers and non-containerized applications.
DevOps

Non-Functional Testing

Testing of non-functional aspects of software like performance, usability, and reliability.
DevOps

OSV

Open Source Vulnerabilities; database of vulnerabilities affecting open source software.
DevOps

OWASP

Open Web Application Security Project; nonprofit foundation working to improve software security.
DevOps

OWASP API Top 10

List of the ten most critical API security risks, providing awareness and guidance for developers and security professionals.
DevOps

OWASP Top 10

Standard awareness document for developers about the most critical security risks to web applications.
DevOps

Observability

Measure of how well internal states of a system can be inferred from knowledge of its external outputs.
DevOps

Observability vs Monitoring

Observability provides insights into system behavior, while monitoring tracks predefined metrics.
DevOps

On Premise Infrastructure

Computing infrastructure physically located within an organization's facilities.
DevOps

One-Stop Shop

Single location or service providing multiple resources or capabilities, often used in IT service management.
DevOps

Open Authorization (OAuth)

Open standard for access delegation, commonly used for secure authorization in web applications.
DevOps

Open Integration Framework (OIF)

Set of standards and practices for integrating different software systems, promoting interoperability and flexibility.
DevOps

Open Source

Software with source code that anyone can inspect, modify, and enhance, promoting collaboration and transparency.
DevOps

Open Source Applications

Software applications whose source code is openly available for modification and distribution.
DevOps

OpenShift

Container application platform by Red Hat that brings Docker and Kubernetes to the enterprise.
DevOps

OpenStack

Free, open-standard cloud computing platform, primarily deployed as infrastructure-as-a-service.
DevOps

OpenTelemetry

Collection of tools, APIs, and SDKs used to instrument, generate, collect, and export telemetry data.
DevOps

Operational Intelligence

Real-time dynamic business analytics that delivers visibility and insight into data, streaming events, and business operations.
DevOps

Operations Engineering (Ops)

Discipline of designing and managing systems for maximum efficiency and reliability.
DevOps

Ops (from DevOps)

Operational aspect of DevOps, focusing on system administration, infrastructure management, and deployment.
DevOps

OpsGenie

Incident management and alert notification tool designed to help teams handle critical issues quickly and efficiently.
DevOps

Opsbot

Chatbot designed to assist with operational tasks and incident management, streamlining IT operations and support.
DevOps

Opskeleton

Basic structure or framework for operations in a software project, providing a starting point for implementing DevOps practices.
DevOps

Orchestration

Automated configuration, coordination, and management of computer systems and software.
DevOps

Otto

Holistic, single command developer tool for managing development environments across multiple platforms and languages.
DevOps
special ref

special ref

A Git reference with a specific meaning or function, such as HEAD or FETCH_HEAD.
staging instance

staging instance

A deployment environment used for testing changes before releasing to production in Git-based workflows.
star

star

A feature on Git hosting platforms allowing users to bookmark repositories of interest.
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.

Fluentd vs Fluent Bit

Comparison of two popular log processors for containerized environments, with Fluent Bit being more lightweight.

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.