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

Compliance as Code

Approach to maintaining regulatory compliance by defining compliance requirements as code, enabling automation and consistency.
DevOps

Complicated-subsystem Team

Team responsible for a specific complex component within a larger system, requiring specialized knowledge.
DevOps

ConDep

Open-source tool for automating continuous deployment and server provisioning, simplifying infrastructure management.
DevOps

Configuration Drift

Inconsistencies between the desired configuration state and the actual state of a system.
DevOps

Configuration Management

Process of maintaining systems, such as computer servers, in a desired, consistent state across time.
DevOps

Configuration as Code (CaC)

Managing and provisioning computing infrastructure through machine-readable definition files.
DevOps

Constraint

Limitation or restriction in a system that affects its performance or capacity, often a focus in optimization efforts.
DevOps

Consul

Service networking platform to connect and secure services across any runtime platform and cloud.
DevOps

Container Image

Lightweight, standalone, executable package of software that includes everything needed to run an application.
DevOps

Container Registry

Centralized repository for storing, managing, and distributing container images, crucial for container-based development and deployment.
DevOps

Containerization

Encapsulating an application and its environment to ensure consistent operation across different computing environments.
DevOps

Containers

Lightweight, standalone executable packages of software that include everything needed to run an application.
DevOps

Containers-as-a-Service (CaaS)

Model where container engines, orchestration and underlying compute resources are provided on-demand.
DevOps

Content Delivery Network (CDN)

Geographically distributed network of proxy servers to provide high availability and performance.
DevOps

Continuous Compliance

Ongoing process of adhering to regulatory and security standards throughout the development lifecycle.
DevOps

Continuous Delivery (CD)

Approach where teams produce software in short cycles, ensuring it can be reliably released at any time.
DevOps

Continuous Delivery Pipeline

Automated implementation of an application's build, deploy, test, and release process.
DevOps

Continuous Deployment (CD)

Practice of automatically deploying every change that passes all stages of the production pipeline.
DevOps

Continuous Feedback

Constant flow of information about a product or process to facilitate continuous improvement.
DevOps

Continuous Governance

Ongoing process of implementing and monitoring policies and controls in software development.
DevOps

Continuous Improvement

Ongoing effort to enhance products, services, or processes, central to many management philosophies including Lean and Six Sigma.
DevOps

Continuous Integration (CI)

Development practice where code changes are automatically built, tested, and prepared for a release.
DevOps

Continuous Integration and Deployment (CI/CD)

Combined practices of Continuous Integration and either Continuous Delivery or Continuous Deployment.
DevOps

Continuous Intelligence

Real-time analytics embedded into business operations, processing current and historical data.
DevOps

Continuous Learning Culture

Organizational approach that encourages ongoing skill development and knowledge sharing.
DevOps

Continuous Monitoring

Automated process of identifying compliance and security risks in an IT infrastructure.
DevOps

Continuous Quality

Ongoing process of building quality assurance into every step of the development lifecycle.
DevOps

Continuous Quality Improvement (CQI)

Systematic approach to enhancing processes and products to achieve better performance.
DevOps

Continuous Reliability

Practice of building and maintaining reliable systems through constant monitoring and improvement.
DevOps

Continuous Security

Integrating security practices throughout the entire software development and deployment lifecycle.
DevOps

Continuous Testing

Process of executing automated tests as part of the software delivery pipeline to obtain feedback on business risks.
DevOps

Contract Testing

Testing method that verifies interactions at the boundary of an external service meet expectations.
DevOps

Cordova

Mobile application development framework that allows developers to build mobile apps using web technologies like HTML, CSS, and JavaScript.
DevOps

CoreOS

Lightweight Linux operating system designed for providing infrastructure to clustered deployments, now part of Red Hat.
DevOps

Coupon Scraping

Automated collection of online coupon codes, often to exploit promotional offers.
DevOps

Create Test for Every Bug

Practice of writing a test that reproduces a bug before fixing the issue, ensuring the bug doesn't recur.
DevOps

Credential Abuse

Unauthorized use of valid credentials to gain access to systems or data, often resulting from poor password practices or stolen credentials.
DevOps

Credential Stuffing

Cyberattack method where stolen account credentials are used to gain unauthorized access to user accounts through large-scale automated login requests.
DevOps

Credmgr

Credential manager tool for securely storing and managing passwords and other secrets.
DevOps

Cron Job

Time-based job scheduler in Unix-like operating systems, used to automate system maintenance or administration tasks.
DevOps

Cross Platform

Ability of software or hardware to work across different types of platforms or operating systems.
DevOps

Cross-Functional Team

Group of people with different functional expertise working toward a common goal.
DevOps

Cross-Site Scripting (XSS)

Security vulnerability allowing attackers to inject client-side scripts into web pages viewed by others.
DevOps

CruiseControl

Java-based framework for creating a custom continuous integration and deployment environment, popular in early CI/CD implementations.
DevOps

Cryptomining Malware

Malicious software that uses system resources to mine cryptocurrency without user consent.
DevOps

Culture

Shared values, beliefs, and practices that characterize an organization, crucial in shaping DevOps and Agile transformations.
DevOps

Cumulative Layout Shift (CLS)

Web performance metric measuring visual stability, quantifying how much page content unexpectedly shifts during loading.
DevOps

Cybersecurity

Practice of protecting systems, networks, and programs from digital attacks, crucial in today's interconnected world.
DevOps

DAST

Dynamic Application Security Testing; analyzes running applications to find vulnerabilities.
DevOps

DDoS

Distributed Denial of Service; cyberattack that floods a system with traffic to make it unavailable.
DevOps

DNS Lookup Time

Time taken to query the Domain Name System to translate a domain name into an IP address.
DevOps

DORA Metrics

Four key metrics (deployment frequency, lead time for changes, time to restore service, change failure rate) used to measure software delivery performance.
DevOps

Dark Launch

Technique of releasing features to production that are invisible to users until activated, allowing for testing in real environments.
DevOps

Dark Launching

Deploying code or feature flags to production without making them visible to users.
DevOps

Dark Release

Releasing new features to production that are invisible to users until activated.
DevOps

Dashboards

Visual displays of key performance indicators and metrics, providing at-a-glance views of business performance or system status.
DevOps

Data Breach

Incident where sensitive, protected or confidential data is copied, transmitted, viewed, stolen or used by unauthorized individuals.
DevOps

Data Leakage

Unauthorized transmission of data from within an organization to an external destination or recipient.
DevOps

Data Loss Prevention (DLP)

Set of tools and processes to ensure sensitive data is not lost, misused, or accessed by unauthorized users.
DevOps

Data Security

Protective measures applied to prevent unauthorized access to databases, websites, and computers.
DevOps

Database Management

Process of storing, organizing, and managing data in databases, ensuring data integrity, security, and accessibility.
DevOps

Database Versioning

Practice of keeping different versions of database schemas, often in conjunction with application versioning.
DevOps

Datadog

Monitoring and analytics platform for cloud-scale applications, providing full-stack observability for IT infrastructure and application performance.
DevOps

Dead Code

Source code that's never executed or has no effect on program output, often a target for removal to improve maintainability and performance.
DevOps

Declarative Infrastructure

Defining infrastructure using a descriptive model, focusing on what should be deployed rather than how.
DevOps

Dedicated Environment

Computing resources exclusively allocated to a single user, project, or organization.
DevOps

Defense-in-Depth (DiD)

Cybersecurity strategy that employs multiple layers of security controls to protect assets and data from various types of threats.
DevOps

Definition of Done

Agreed-upon set of items that must be completed before a project or user story can be considered complete.
DevOps

Deis

Open-source Platform-as-a-Service (PaaS) that makes it easy to deploy and manage applications.
DevOps

Denial of Service (DoS)

Cyberattack aimed at making a machine or network resource unavailable to its intended users.
DevOps

Deploykit

Tool designed to simplify and automate the process of deploying software applications across different environments and platforms.
DevOps

Deployment

Process of making software available and ready for use in a specific environment.
DevOps

Deployment Frequency

Rate at which new code or features are deployed to production, often used as a key metric in DevOps practices.
DevOps

Deployment Pattern

Standardized approach to rolling out software updates or changes, ensuring consistency and reliability in the deployment process.
DevOps

Deployment Pipeline

Automated manifestation of the process for getting software from version control to users.
DevOps

Deployment Target

Specific environment or infrastructure where software is deployed, such as development, staging, or production environments.
DevOps

Design Patterns

Reusable solutions to commonly occurring problems in software design, providing tested, proven development paradigms.
DevOps

Dev (from DevOps)

Represents the development aspects in the DevOps methodology, focusing on software creation and testing processes.
DevOps

DevOps

Set of practices combining software development (Dev) and IT operations (Ops) to shorten the development lifecycle.
DevOps

DevOps Assembly Line

Series of automated steps for building, testing, and deploying software in a DevOps environment.
DevOps

DevOps Culture

Organizational culture that bridges the gap between development and operation teams.
DevOps

DevOps Engineer

Professional combining software development and IT operations skills to improve collaboration and productivity.
DevOps

DevOps Lifecycle

Continuous cycle of development, testing, deployment, and monitoring in DevOps practices.
DevOps

DevOps Model

Conceptual framework for integrating development and operations teams and practices.
DevOps

DevOps Pipeline

Automated processes and tools used to move code from development to production in DevOps.
DevOps

DevOps Team

Cross-functional team responsible for the entire software delivery process in a DevOps environment.
DevOps

DevOps-as-a-Service

Outsourcing of DevOps functions to a third-party provider, offering expertise and tools to improve software delivery processes.
DevOps

DevSecOps

Approach integrating security practices within the DevOps process, ensuring security is considered throughout the software development lifecycle.
DevOps

DevSecOps Pipeline

Automated workflow that integrates security at every phase of the software development lifecycle.
DevOps

DevXOps

Extension of DevOps principles to include all teams involved in delivering software.
DevOps

Developer Experience

Overall experience developers have when using tools, platforms, or processes in their work.
DevOps

Device Fingerprinting

Technique of collecting information about a device for identification purposes, used in security and fraud prevention.
DevOps

Diamond

Ruby-based system monitoring tool that collects metrics and allows configuring custom collectors.
DevOps

Digital Customer Experience

Overall experience a customer has with a brand through digital channels and touchpoints.
DevOps

Directory Traversal

Security vulnerability allowing attackers to access unauthorized directories, potentially exposing sensitive files.
DevOps

Distributed Tracing

Method of tracking application requests as they flow through distributed systems.
DevOps

Distributed Version Control System (DVCS)

Version control system where the complete codebase, including its full history, is mirrored on every developer's computer.
DevOps

Django Framework

High-level Python web framework that encourages rapid development and clean, pragmatic design.
DevOps

Djangy

Platform-as-a-Service specifically designed for hosting and scaling Django web applications, simplifying deployment and management.
DevOps

Docker

Platform for developing, shipping, and running applications in containers, enabling consistent deployment across different environments.
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.

DaemonSet Pattern

Design pattern using DaemonSets to run system daemons or agents on every node in a cluster.

Data Backup and Recovery

Processes and tools for preserving and restoring data in containerized environments, ensuring data durability.

Data Consistency in Distributed Systems

Techniques ensuring data integrity across distributed container-based applications, maintaining reliability.

Data Fabric in Containerized Environments

Distributed data management architecture providing consistent data access across containerized applications.

Data Lakehouse Architecture

Unified data architecture combining data lake and data warehouse features in containerized environments.

Data Migration Between Containers

Process of moving data between containers or from traditional systems to containerized applications.

Data Persistence Strategies

Techniques for maintaining data across container lifecycles, including volume mounts and persistent volumes.

Data Plane

Network layer responsible for forwarding container traffic based on control plane decisions.

Data Replication in Containers

Techniques for creating and maintaining copies of data across multiple containerized instances.

Data Sharding in Containerized Databases

Partitioning data across multiple database containers for improved scalability and performance.

Database Containerization

Process of running database systems within containers for improved portability and resource utilization.

Database-per-Service Pattern

Microservices design pattern where each service has its own dedicated database, ensuring data isolation.

Datadog Container Monitoring

Platform for observability and monitoring of containerized environments and microservices.

Dead Letter Queue Pattern

Design pattern for handling failed message processing in containerized message-driven systems.

Declarative Deployments

Approach to deploying containers by specifying desired state rather than imperative commands.

Deployment Strategies

Techniques for rolling out container updates, including rolling updates, blue-green, and canary deployments.

Descheduler

Kubernetes component that evicts pods from nodes based on specific policies to optimize cluster resource usage.

DevSpace for Cloud-native Development

Standardized format defining the structure and metadata of Docker container images, ensuring portability.

Device Plugins

Kubernetes feature allowing nodes to advertise system hardware resources to the cluster, enabling specialized hardware use.

Direct Server Return (DSR)

Network optimization technique in container load balancing for improved performance by bypassing the load balancer for responses.

Distributed Tracing Integration

Implementation of tracing in containerized microservices for end-to-end request visibility.

Distributed Tracing with Jaeger

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

Distributed Tracing with OpenTelemetry

Implementation of OpenTelemetry for standardized observability in containerized environments.

Distroless Images

Minimal container images containing only the application and its runtime dependencies, reducing attack surface.

Docker Attach

Command to attach local standard input, output, and error streams to a running container for interaction and debugging.

Docker Build Context

Set of files located in the specified PATH or URL, used during the docker build process to create images.

Docker Buildx

Docker CLI plugin for extended build capabilities, including multi-platform builds and enhanced build options.

Docker CRI Shim

Component enabling Docker to be used as a container runtime in Kubernetes via the Container Runtime Interface.

Docker Client

Command-line tool for interacting with Docker daemon and managing containers, images, and other Docker objects.

Docker Commit

Command creating a new image from a container's changes, useful for saving modifications made to a running container.

Docker Compose

Tool for defining and running multi-container Docker applications, simplifying the process of managing complex application stacks.

Docker Container Inspection

Process of viewing detailed information about a container's configuration and state, aiding in troubleshooting.

Docker Content Trust

Feature providing digital signing and verification of Docker images, ensuring image authenticity and integrity.

Docker Content Trust Signature Verification

Process of validating the authenticity and integrity of signed Docker images before use.

Docker Contexts

Feature allowing management of multiple Docker endpoints from a single Docker client, simplifying multi-environment management.

Docker Daemon

Background service managing Docker objects like images, containers, networks, and volumes.

Docker Exec

Command allowing users to run a new process inside a running container, useful for debugging and maintenance tasks.

Docker Export/Import

Commands for exporting a container's filesystem as a tarball and importing it as an image.

Docker Hub

Cloud-based repository service for finding and sharing container images, central to the Docker ecosystem.

Docker Image History

Command showing the history of an image's layers, providing insight into how the image was built and modified.

Docker Image Inspection

Process of examining Docker image metadata, including layers, environment variables, and exposed ports.

Docker Image Specification

Standardized format defining the structure and metadata of Docker container images, ensuring portability.

Docker Network

Virtualized network providing connectivity between Docker containers, isolating container traffic from the host network.

Docker Network Driver Types (bridge, host, overlay, macvlan)

Different networking modes in Docker, including bridge, host, overlay, and macvlan, offering varied connectivity options.

Docker Prune

Command for removing unused Docker objects like containers, networks, images, and volumes.

Docker Save/Load

Commands for exporting Docker images to tar archives and importing them back, useful for image transfer and backup.

Docker Scan

Command-line tool for scanning Docker images for vulnerabilities, providing detailed reports on potential security issues.

Docker Shim

Deprecated component that provided CRI compatibility for Docker in Kubernetes, bridging Docker and CRI.

Docker Socket

Unix socket or named pipe used for communication between Docker client and daemon, enabling Docker API access.

Docker Stats

Command displaying a live stream of container resource usage statistics, including CPU, memory, and network I/O.

Docker Swarm

Native clustering and orchestration solution for Docker, allowing you to create and manage a swarm of Docker nodes as a single virtual system.

Docker System Events

Real-time stream of Docker daemon events, providing insights into container, image, volume, and network activities.

Docker Top

Command displaying the running processes of a container, similar to the Unix top command but container-specific.

Docker Volume

Persistent data storage mechanism for containers, independent of container lifecycle, enabling data persistence.

Docker Volume Driver Types

Different storage backends for Docker volumes, including local, NFS, and cloud-specific drivers.

Dockerfile

Text document containing all the commands a user could call on the command line to assemble a Docker image.

Dockerfile ARG

Instruction defining build-time variables that users can pass at build-time to the builder.

Dockerfile Best Practices

Guidelines for creating efficient, secure, and maintainable Dockerfiles, optimizing image builds and runtime performance.

Dockerfile HEALTHCHECK

Instruction telling Docker how to test a container to check its health status, improving reliability.

Dockerfile Instructions (ADD, COPY, RUN, CMD, ENTRYPOINT, etc.)

Set of commands used in Dockerfiles to build images, including ADD, COPY, RUN, CMD, and ENTRYPOINT.

Dockerfile ONBUILD

Set of commands used in Dockerfiles to build images, including ADD, COPY, RUN, CMD, and ENTRYPOINT.

Dockerfile STOPSIGNAL

Instruction setting the system call signal that will be sent to the container to exit, customizing shutdown behavior.

Dockerignore

File specifying which files and directories should be excluded when building a Docker image.

Domain-Driven Design (DDD) in Microservices

Approach to software design focusing on the core domain in containerized microservices architectures.

Dragonfly for P2P Image Distribution

P2P-based image and file distribution system to improve efficiency of image downloads in container environments.

Drain

Process of cordoning a node and evicting its pods in preparation for maintenance or decommissioning.

Dual-stack Networking

Networking configuration supporting both IPv4 and IPv6 in container environments, enabling broader connectivity options.

Dynamic Admission Control

Kubernetes feature allowing custom logic to be applied to object creation or modification requests.

Dynamic Auditing

Kubernetes feature enabling runtime configuration of audit policies without API server restart.

Dynamic Provisioning

Automatic creation of storage when persistent volume claims are made in Kubernetes, simplifying storage management.

Dynatrace OneAgent

Monitoring solution for containerized environments, providing deep visibility into application performance.

ELK Stack (Elasticsearch, Logstash, Kibana)

Combination of Elasticsearch, Logstash, and Kibana for logging and monitoring containerized environments.

East-West Traffic

Network communication between containers or services within the same cluster or data center.

Edge AI/ML

Deployment of artificial intelligence and machine learning models on edge devices using containers.

Edge Analytics

Processing and analyzing data at the network edge using containerized analytics applications.

Edge Device Management

Tools and practices for managing containerized workloads on edge devices, ensuring consistent deployment and updates.

Edge Orchestration

Management and coordination of containerized applications across distributed edge locations.

Edge Security

Security measures and practices specific to containerized edge computing environments, protecting distributed workloads.

Edge Workload Scheduling

Techniques for efficiently distributing containerized workloads across edge devices, optimizing resource usage.

Edge-Cloud Syncing

Synchronization of data and state between edge containers and cloud-based systems, ensuring consistency.

Egress Gateway

Component controlling outbound traffic from a container cluster to external services, enhancing security and traffic management.

Egress Gateways

Service mesh components managing outbound traffic from the mesh to external services, providing fine-grained control.

Egress Traffic Control

Management and policies for outbound network traffic from containers, ensuring security and compliance.

Elastic APM

Application Performance Monitoring tool for containerized applications in the Elastic Stack.

Encrypted Secrets

Sensitive data stored in an encrypted form in container orchestration platforms, enhancing security.

End-to-End Testing

Comprehensive testing of containerized applications from start to finish, validating entire system functionality.

EndpointSlices

Kubernetes API resource providing a more scalable alternative to Endpoints for service discovery.

Environment Variables in Containers

Key-value pairs passed to containers at runtime, used for configuration and runtime behavior control.

Envoy Proxy

High-performance proxy often used in service mesh implementations for containerized environments.

Ephemeral Containers

Temporary containers used for troubleshooting or debugging in Kubernetes pods, without affecting the main containers.

Ephemeral Volumes

Short-lived storage volumes in Kubernetes that share the lifecycle of a pod, useful for temporary data storage.

Equal-Cost Multi-Path (ECMP)

Routing strategy for load balancing network traffic across multiple paths in container networks.

Etcd

Distributed key-value store that provides a reliable way to store data across a cluster of machines.

Event Sinks

Destinations for cluster-level events in container orchestration platforms, used for monitoring and alerting.

Event Sources

Components or services generating events in containerized environments, often used in event-driven architectures.

Event Sourcing

Pattern of storing changes to application state as a sequence of events, often used in microservices architectures.

Event Sourcing Pattern

Design pattern capturing all changes to application state as a sequence of events, useful in distributed systems.

Event Sourcing in Containers

Implementation of event sourcing pattern in containerized microservices architectures, ensuring data consistency.

Event-driven Architectures

Design approach where containerized services produce, detect, and react to events, enabling loose coupling and scalability.

Eviction Policies

Rules determining which pods to terminate when a node is under resource pressure in Kubernetes clusters.