Glossary
Welcome to the Harness Glossary! This page is a work in progress. If you have feedback or terms to define, click the Feedback button.
A
account
An account is the highest-level container where you define organizational structure, manage global settings, and establish shared security and governance rules that cascade down to all organizations and projects in the Harness platform.
platform
assignment source
A data source that defines how users are assigned to different variations in an experiment. In Warehouse Native, this data is typically stored in your data warehouse.
Feature Management & Experimentation
Related terms: cloud experimentation, data warehouse, experiment
B
binary files
Executable program files produced after compiling source code (for example, Go or Java). OpenTofu or Terraform uses these binaries to interact with your infrastructure.
Infrastructure as Code Management
Related terms: checksum file, custom provider, gpg key
C
checksum file
A file listing SHA-256 hashes for each binary you plan to publish. The registry uses this to verify file integrity.
Infrastructure as Code Management
Related terms: binary files, custom provider, gpg key
cloud experimentation
A method of running feature management experiments using a cloud-based service provided by Harness FME, which handles data collection, analysis, and reporting.
Feature Management & Experimentation
Related terms: assignment source, data warehouse, experiment
custom dashboard
A user-created dashboard built in Canvas and published to the Insights page for viewing and sharing. It can be tailored to display the most important data for your use case, providing insights and facilitating decision-making.
Software Engineering Insights
Related terms: custom variable, data source, query variable
custom provider
An OpenTofu or Terraform provider built and maintained by your organization, usually for internal APIs or services not available in the public registry.
Infrastructure as Code Management
Related terms: binary files, checksum file, gpg key
custom stage
A custom stage is a user-defined stage in a pipeline that allows you to run custom logic or actions as part of a pipeline. FME steps are only supported in Custom stages.
Feature Management & Experimentation
Related terms: pipeline, pipeline template, stage
custom variable
A custom variable is a user-defined parameter that can be used in Canvas to store and manipulate data. It can be used in queries, calculations, or as part of the dashboard configuration to create more complex and tailored visualizations.
Software Engineering Insights
Related terms: custom dashboard, data source, query variable
D
data source
A data source is a connection to an external system or database that provides data for use in Canvas. It allows you to pull in data from various sources to create visualizations and insights in your custom dashboards.
Software Engineering Insights
Related terms: custom dashboard, custom variable, query variable
data warehouse
A centralized repository for storing and managing large volumes of structured and semi-structured data. Examples include Snowflake, BigQuery, Redshift, and Databricks.
Feature Management & Experimentation
Related terms: assignment source, cloud experimentation, experiment
E
evaluation api
The Evaluation API is the main interface developers use to interact with feature flags. It enables applications to evaluate feature flags and adapt behavior based on the results, while supporting customization and integration with additional tools.
Feature Management & Experimentation
Related terms: evaluation context, events, feature flag
evaluation context
The Evaluation Context holds contextual information used during flag evaluation. It can include static data (like application or host identifiers) and dynamic data (such as a client IP address), which can be passed explicitly or propagated automatically. Static and dynamic values can be merged for richer, more targeted evaluations.
Feature Management & Experimentation
Related terms: evaluation api, events, feature flag
events
Events allow your application to respond to changes in provider state or flag configuration, such as readiness changes, errors, or updates to flag values.
Feature Management & Experimentation
Related terms: evaluation api, evaluation context, feature flag
experiment
A controlled test to evaluate the impact of different variations on user behavior or system performance. In Warehouse Native, experiments are defined in Harness FME.
Feature Management & Experimentation
Related terms: assignment source, cloud experimentation, data warehouse
F
feature flag
A feature flag is a conditional toggle in Harness FME that enables or disables specific functionality without deploying new code. It allows for controlled feature rollouts, A/B testing, and quick rollbacks if issues arise.
Feature Management & Experimentation
Related terms: evaluation api, evaluation context, events
G
gpg key
A cryptographic key used to verify the authenticity and integrity of files. In this case, it ensures provider binaries have not been tampered with.
Infrastructure as Code Management
Related terms: binary files, checksum file, custom provider
guardrail metric
A guardrail metric is a specific type of metric used to monitor for negative impacts during a feature rollout or experiment. It serves as a safety check to ensure that the new feature does not cause significant issues or degrade user experience. If a guardrail metric indicates a problem, it can trigger alerts or rollbacks to mitigate potential harm.
Feature Management & Experimentation
Related terms: key metric, metric, metric alert
H
hook
Hooks let you inject custom behavior at various points in the flag evaluation lifecycle. They can be used for validation, modifying the evaluation context, logging, telemetry, or custom functionality to extend the SDK.
Feature Management & Experimentation
Related terms: evaluation api, evaluation context, events
I
identity
A unique key representing a user, account, device, or other entity in Harness FME. Identities can store associated attribute data used for targeting workflows, search, and analysis.
Feature Management & Experimentation
init
OpenTofu/Terraform command used to initialize a configuration. It downloads and configures providers, modules, and other dependencies.
Infrastructure as Code Management
K
key metric
A key metric is a specific metric that is critical for evaluating the success of a feature flag or experiment. It is used to determine whether a feature rollout or experiment is achieving its intended goals and can influence decisions about further rollouts or adjustments.
Feature Management & Experimentation
Related terms: guardrail metric, metric, metric alert
M
metric
A metric measures events that are sent to Harness FME and can count the occurrence of events, measure event values, or measure event properties. Metrics are used to evaluate the impact of feature flags and experiments on user behavior and system performance.
Feature Management & Experimentation
Related terms: guardrail metric, key metric, metric alert
metric
A quantifiable measure used to track and assess the performance of a specific aspect of an experiment. In Warehouse Native, metrics are defined in Harness FME.
Feature Management & Experimentation
Related terms: assignment source, cloud experimentation, data warehouse
metric alert
A metric alert is a notification triggered when a specific metric reaches a predefined threshold. This can indicate potential issues or significant changes in user behavior, allowing teams to respond quickly to mitigate negative impacts or capitalize on positive trends.
Feature Management & Experimentation
Related terms: guardrail metric, key metric, metric
metric source
A data source that defines how metrics are collected and calculated for an experiment. In Warehouse Native, this data is typically stored in your data warehouse.
Feature Management & Experimentation
Related terms: assignment source, cloud experimentation, data warehouse
multiple platforms
Supported platforms include Darwin/macOS (arm64, amd64), Linux (amd64), and Windows (amd64).
Infrastructure as Code Management
Related terms: binary files, checksum file, custom provider
O
organization
An organization groups projects sharing common goals or business units, providing a structured way for managing teams, access, and shared resources in the Harness platform.
platform
P
pipeline
A pipeline is a sequence of stages that define how services are deployed to an environment. Pipelines can include approvals, barriers, notifications, and other execution logic.
Feature Management & Experimentation
Related terms: custom stage, pipeline template, stage
pipeline template
A reusable end-to-end workflow that discovers eligible feature flags, lets you select a cleanup candidate, and generates a pull request with the proposed code changes.
Feature Management & Experimentation
Related terms: custom stage, pipeline, stage
project
A project is a shared workspace within an organization where teams manage their users, pipelines, and resources needed to build, deploy, and operate their applications in the Harness platform.
platform
provider
An OpenFeature Provider wraps the Harness FME SDK, acting as a bridge between the OpenFeature SDK and the FME SDK. It translates OpenFeature function calls into operations handled by the FME SDK, which communicates with Harness services to evaluate flags and retrieve configuration updates.
Feature Management & Experimentation
Related terms: evaluation api, evaluation context, events
Q
query variable
A query variable is a dynamic parameter that can be used in Canvas HQL queries to filter or modify the data being retrieved. It allows you to create more flexible and interactive dashboards by enabling users to input values that affect the displayed data.
Software Engineering Insights
Related terms: custom dashboard, custom variable, data source
S
segment
Segments are groups of users defined by specific attributes or behaviors. They allow you to target feature flags and experiments to specific subsets of your user base.
Feature Management & Experimentation
signature file
A detached signature produced by signing the checksum file with your GPG private key. The public key is used to verify authenticity.
Infrastructure as Code Management
Related terms: binary files, checksum file, custom provider
significance alert
A significance alert is a notification triggered when the results of an experiment reach a predefined level of statistical significance. This indicates that the observed effects are unlikely to be due to chance, helping teams make informed decisions about feature rollouts or adjustments based on the experiment's outcomes.
Feature Management & Experimentation
Related terms: guardrail metric, key metric, metric
stage
A stage represents a discrete phase of a pipeline, such as testing, experimentation, or production rollout. You can add FME steps to any Custom stage, whether newly created or existing.
Feature Management & Experimentation
Related terms: custom stage, pipeline, pipeline template
stage template
A reusable cleanup stage that removes a specific feature flag and generates a pull request when the target flag and treatment are already known.
Feature Management & Experimentation
Related terms: custom stage, pipeline, pipeline template
statistical significance
Statistical significance is a measure of the likelihood that the observed results of an experiment are not due to random chance. It is typically determined by a p-value threshold (e.g., 0.05), indicating that there is a less than 5% probability that the results occurred by chance. Achieving statistical significance helps teams make informed decisions about feature rollouts or adjustments based on the experiment's outcomes.
Feature Management & Experimentation
Related terms: guardrail metric, key metric, metric
step
A step is an individual action within a stage. FME steps include operations such as creating or updating a feature flag, modifying rollout behavior, or killing a flag.
Feature Management & Experimentation
Related terms: custom stage, pipeline, pipeline template
T
targeting key
A unique identifier used to target specific users or entities when evaluating feature flags. It helps determine which variation of a flag should be served based on predefined rules and conditions.
Feature Management & Experimentation
Related terms: evaluation api, evaluation context, events
W
warehouse native
A method of running feature management experiments directly within your data warehouse, leveraging its processing power and existing data infrastructure.
Feature Management & Experimentation
Related terms: assignment source, cloud experimentation, data warehouse
widget
A widget is a visual component that displays specific data or information on a Canvas dashboard. Widgets can be customized to show different types of data, such as charts, tables, or metrics, and can be arranged to create a personalized dashboard layout.
Software Engineering Insights
Related terms: custom dashboard, custom variable, data source
workspace
A workspace is a one-to-one mapping of your infrastructure state. It is used to store and manage your infrastructure state in Harness IaCM.
Infrastructure as Code Management