> For the complete documentation index, see [llms.txt](https://developer.harness.io/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://developer.harness.io/university/readme/feature-management-experimentation.md).

# Feature Management & Experimentation

Learn Feature Management & Experimentation through Harness University

Helps you manage feature releases, monitor performance, and run experiments for data-driven development.

Go to [Harness University](/university/readme.md) for the full catalogue of courses and certifications.

## Self-Paced Training

Free self-paced courses that you can consume on your own time.

<table data-view="cards"><thead><tr><th></th><th></th><th data-hidden data-card-target data-type="content-ref"></th></tr></thead><tbody><tr><td><img src="https://2307127582-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2Feh03Q8VHpO02MFM5nUSL%2Fuploads%2Fgit-blob-8d9330b11e4adb2c19a6b64b4a75262530fb0ef8%2Fplatform.svg?alt=media" alt="" data-size="line"> <strong>Harness Platform Fundamentals</strong></td><td>Self-paced video course introducing the Harness Platform.<br><em>Product version: Free Plans of any module</em></td><td><a href="https://university-registration.harness.io/self-paced-training-platform-fundamentals">https://university-registration.harness.io/self-paced-training-platform-fundamentals</a></td></tr><tr><td><img src="https://2307127582-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2Feh03Q8VHpO02MFM5nUSL%2Fuploads%2Fgit-blob-8d9330b11e4adb2c19a6b64b4a75262530fb0ef8%2Fplatform.svg?alt=media" alt="" data-size="line"> <strong>Introduction to AI Agents</strong></td><td>Self-paced tidbit introducing the Custom AI Agents.<br><em>Product version: Paid Plans of any module</em></td><td><a href="https://university-registration.harness.io/self-paced-training-tidbit-custom-ai-agents">https://university-registration.harness.io/self-paced-training-tidbit-custom-ai-agents</a></td></tr><tr><td><img src="https://2307127582-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2Feh03Q8VHpO02MFM5nUSL%2Fuploads%2Fgit-blob-9f8fe5009878dffca59fec27834eafdfd785413b%2Ffeature.svg?alt=media" alt="" data-size="line"> <strong>Feature Management &#x26; Experimentation</strong></td><td>Self-paced courses introducing Feature Management &#x26; Experimentation.<br><em>Product version: FME Paid Plans</em></td><td><a href="https://university-registration.harness.io/page/fme">https://university-registration.harness.io/page/fme</a></td></tr></tbody></table>

## Instructor-Led Training

Intensive two-day courses are designed for engineers looking to deepen their understanding and expertise in Harness.

<table data-view="cards"><thead><tr><th></th><th></th><th data-hidden data-card-target data-type="content-ref"></th></tr></thead><tbody><tr><td><img src="https://2307127582-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2Feh03Q8VHpO02MFM5nUSL%2Fuploads%2Fgit-blob-8d9330b11e4adb2c19a6b64b4a75262530fb0ef8%2Fplatform.svg?alt=media" alt="" data-size="line"> <strong>Introduction to the Harness Platform</strong></td><td>Self-paced hands-on, prerequisite course to all module-specific ILT courses.<br><em>Product version: Paid Plans of any module</em></td><td><a href="https://university-registration.harness.io/introduction-to-the-harness-platform">https://university-registration.harness.io/introduction-to-the-harness-platform</a></td></tr><tr><td><img src="https://2307127582-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2Feh03Q8VHpO02MFM5nUSL%2Fuploads%2Fgit-blob-9f8fe5009878dffca59fec27834eafdfd785413b%2Ffeature.svg?alt=media" alt="" data-size="line"> <strong>Feature Management &#x26; Experimentation</strong></td><td>Deep dive into Feature Management &#x26; Experimentation use cases and concepts.<br><em>Product version: Harness Paid Plans</em></td><td><a href="https://university-registration.harness.io/ilt-feature-management-experimentation">https://university-registration.harness.io/ilt-feature-management-experimentation</a></td></tr></tbody></table>

## Certifications

Test and validate your knowledge of Harness by becoming a Harness Certified Expert.

{% tabs %}
{% tab title="For Developer" %}

### Feature Management & Experimentation - Developer

![Feature Management & Experimentation - Developer badge](https://2307127582-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2Feh03Q8VHpO02MFM5nUSL%2Fuploads%2Fgit-blob-744de914457ea07aa1b6ab81c54457628938e9b6%2Fcert-dev-fme-badge.svg?alt=media)

**Product version:** Harness FME Paid Plans

Assesses the fundamental skills to manage your applications with FME projects.

#### Review Study Guide

| Topic                                                    | Material                                                                                                                                                                                                 |
| -------------------------------------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| ***1. Release Monitoring & Impact Detection***           |                                                                                                                                                                                                          |
| Purpose of Release Monitoring in FME                     | [Release Monitoring Overview](https://developer.harness.io/docs/feature-management-experimentation/release-monitoring/overview)                                                                          |
| Percentage-based rollouts and statistical validity       | [Rollouts](https://developer.harness.io/docs/feature-management-experimentation/feature-management/setup/rollout-board/)                                                                                 |
| Configuration and monitoring impact on outcomes          | [Configure Release Monitoring](https://developer.harness.io/docs/feature-management-experimentation/release-monitoring/quickstart)                                                                       |
| ***2. Metrics, Impressions & Attribution***              |                                                                                                                                                                                                          |
| How impressions and events generate metrics              | [Impressions, Events, and Metrics](https://developer.harness.io/docs/feature-management-experimentation/feature-management/monitoring-analysis/impressions/)                                             |
| When impressions are generated                           | [Impression Tracking Behavior](https://developer.harness.io/docs/feature-management-experimentation/feature-management/monitoring-analysis/impressions/#tracking-impressions)                            |
| Issues caused by disabled impressions or SDK limitations | [SDK Limitations and Impression Tracking](https://developer.harness.io/docs/feature-management-experimentation/feature-management/monitoring-analysis/impressions/#toggle-impression-tracking-on-or-off) |
| ***3. Feature Flags, SDKs & Performance***               |                                                                                                                                                                                                          |
| Organizing feature flags for SDK performance             | [Harness FME SDKs and Customer-Deployed Components](https://developer.harness.io/docs/feature-management-experimentation/sdks-and-infrastructure)                                                        |
| Impression metadata and targeting rule labels            | [Impressions](https://developer.harness.io/docs/feature-management-experimentation/feature-management/monitoring-analysis/impressions/)                                                                  |
| Control, fallback, and evaluation failure behavior       | [Fallback Treatment](https://developer.harness.io/docs/feature-management-experimentation/feature-management/setup/fallback-treatment/)                                                                  |
| ***4. Experiment Design & Statistical Analysis***        |                                                                                                                                                                                                          |
| Experiment lifecycle and phases                          | [Manage the Feature Flag Lifecycle](https://developer.harness.io/docs/feature-management-experimentation/getting-started/overview/manage-the-feature-flag-lifecycle/)                                    |
| Hypothesis-driven experimentation                        | [Create an Expirement](https://developer.harness.io/docs/feature-management-experimentation/getting-started/overview/create-an-experiment)                                                               |
| Statistical tradeoffs in analysis                        | [Create an Expirement](https://developer.harness.io/docs/feature-management-experimentation/getting-started/overview/create-an-experiment)                                                               |
| ***5. Metrics Design & Measurement Strategy***           |                                                                                                                                                                                                          |
| Selecting metric types                                   | [Metrics](https://developer.harness.io/docs/feature-management-experimentation/release-monitoring/metrics/)                                                                                              |
| Configuring metrics correctly                            | [Create and Configure Metrics](https://developer.harness.io/docs/feature-management-experimentation/getting-started/overview/create-a-metric/)                                                           |
| Metrics for alerting and monitoring                      | [Metrics-Based Alerting](https://developer.harness.io/docs/feature-management-experimentation/getting-started/overview/create-a-metric/#create-an-alert-policy)                                          |
| ***6. Alerting & Troubleshooting***                      |                                                                                                                                                                                                          |
| Alert prerequisites                                      | [Alert Policy Requirements](https://developer.harness.io/docs/feature-management-experimentation/release-monitoring/metrics/setup/metric-alert-policy/)                                                  |
| Troubleshooting alerts not firing                        | [Troubleshoot Metric and Significance Alerts](https://developer.harness.io/docs/feature-management-experimentation/release-monitoring/alerts/troubleshooting)                                            |
| Alert lifecycle and auto-resolution                      | [Alert Lifecycle and Resolution](https://developer.harness.io/docs/feature-management-experimentation/release-monitoring/alerts/alert-policies/#overview)                                                |
| ***7. Attribution, Rule Changes & Exclusions***          |                                                                                                                                                                                                          |
| Event timing and attribution                             | [Event efficiency](https://developer.harness.io/docs/feature-management-experimentation/admin-best-practices/event-efficiency/)                                                                          |
| Attribution behavior when rules change                   | [Targeting Rule Changes and Attribution](https://developer.harness.io/docs/feature-management-experimentation/release-monitoring/attribution-and-exclusion/)                                             |
| User exclusion from metrics                              | [Metric Exclusions and Filtering](https://developer.harness.io/docs/feature-management-experimentation/release-monitoring/attribution-and-exclusion/#exclusions)                                         |
| ***8. Platform Navigation, Governance & RBAC***          |                                                                                                                                                                                                          |
| Core FME platform concepts                               | [Harness Feature Management Overview](https://developer.harness.io/docs/feature-management-experimentation/feature-management)                                                                           |
| Dashboards and customer-level data                       | [FME Dashboards](https://developer.harness.io/docs/feature-management-experimentation/feature-management/monitoring-analysis/customer-dashboard/)                                                        |
| Governance, users, and RBAC                              | [FME Governance and RBAC](https://developer.harness.io/docs/feature-management-experimentation/users)                                                                                                    |

[**Register for Exam**](https://university-registration.harness.io/certification-exam-harness-certified-fme-developer)

#### Exam Details

The Feature Management & Experimentation(FME) Developer exam tests your knowledge and skills of the Harness Feature Management & Experimentation module.

**Prerequisites**

* Basic terminal skills
* Basic understanding of on-premise or cloud architecture

**Exam Details**

| Exam Type          | Duration   |
| ------------------ | ---------- |
| **Knowledge Exam** | 90 minutes |

| Covered Domain                           | Coverage |
| ---------------------------------------- | -------- |
| Release Monitoring & Impact Detection    | 12%      |
| Metrics, Impressions & Attribution       | 15%      |
| Feature Flags, SDKs & Performance        | 13%      |
| Experiment Design & Statistical Analysis | 15%      |
| Metrics Design & Measurement Strategy    | 15%      |
| Alerting & Troubleshooting               | 15%      |
| Attribution, Rule Changes & Exclusions   | 8%       |
| Platform Navigation, Governance & RBAC   | 7%       |

**Exam Objectives**

<details>

<summary>List of Objectives</summary>

The following is a detailed list of exam objectives:

| #   | Objective                                                                                       |
| --- | ----------------------------------------------------------------------------------------------- |
| 1   | **Release Monitoring & Impact Detection**                                                       |
| 1.1 | Explain the purpose of Release Monitoring in Harness FME.                                       |
| 1.2 | Describe why percentage-based rollouts are required for statistically valid release monitoring. |
| 1.3 | Identify how configuration and monitoring choices affect release monitoring outcomes.           |
| 2   | **Metrics, Impressions & Attribution**                                                          |
| 2.1 | Explain how impressions and events work together to calculate metrics.                          |
| 2.2 | Determine when impressions are generated and how impression tracking affects metric visibility. |
| 2.3 | Diagnose issues caused by disabling impression tracking or unsupported SDK behavior.            |
| 3   | **Feature Flags, SDKs & Performance**                                                           |
| 3.1 | Apply best practices for organizing feature flags to optimize SDK performance.                  |
| 3.2 | Explain the role of impression metadata and targeting rule labels in debugging.                 |
| 3.3 | Differentiate control treatments, fallback treatments, and evaluation failure behavior.         |
| 4   | **Experiment Design & Statistical Analysis**                                                    |
| 4.1 | Identify the correct lifecycle and phases of experimentation.                                   |
| 4.2 | Explain the importance of hypothesis-driven experimentation and goal alignment.                 |
| 4.3 | Evaluate statistical tradeoffs in experiment analysis.                                          |
| 5   | **Metrics Design & Measurement Strategy**                                                       |
| 5.1 | Select appropriate metric types based on experiment goals.                                      |
| 5.2 | Configure metrics correctly to measure performance changes.                                     |
| 5.3 | Explain how key metrics enable alerting and monitoring.                                         |
| 6   | **Alerting & Troubleshooting**                                                                  |
| 6.1 | Identify prerequisites required for metric alert policies to fire.                              |
| 6.2 | Diagnose why metric or significance alerts fail to fire.                                        |
| 6.3 | Explain alert lifecycle behavior, including auto-resolution.                                    |
| 7   | **Attribution, Rule Changes & Exclusions**                                                      |
| 7.1 | Explain how event timing affects metric attribution.                                            |
| 7.2 | Analyze attribution behavior when targeting rules change.                                       |
| 7.3 | Identify when user data is excluded from metric calculations.                                   |
| 8   | **Platform Navigation, Governance & RBAC**                                                      |
| 8.1 | Describe core Harness FME platform concepts and structure.                                      |
| 8.2 | Navigate operational dashboards and customer-level data.                                        |
| 8.3 | Apply governance rules for users, groups, naming, and traffic types.                            |

</details>

**Next Steps**

The Feature Management & Experimentation Developer exam can start immediately after registering. Please allow up to 90 mins to complete the knowledge exam.

1. Create an account in Harness University
2. Review the Study Guide above.
3. Register for an exam.
4. Take the exam.

[**Register for Exam**](https://university-registration.harness.io/certification-exam-harness-certified-fme-developer)
{% endtab %}

{% tab title="For Administrator" %}

### Feature Management & Experimentation - Administrator (BETA COMING SOON)

![Feature Management & Experimentation - Administrator (BETA COMING SOON) badge](https://2307127582-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2Feh03Q8VHpO02MFM5nUSL%2Fuploads%2Fgit-blob-82642a8225dfe68d1bbbfe00d716912e91bd7590%2Fcert-adm-fme-badge.svg?alt=media)

**Product version:** Harness FME Paid Plans

{% hint style="info" %}
**Coming soon**

This certification is in beta and not yet open for registration.
{% endhint %}

Assesses the fundamental skills to deploy and maintain FME projects and the overall Harness Platform.
{% endtab %}

{% tab title="For Architect" %}

### Feature Management & Experimentation - Architect (BETA COMING SOON)

![Feature Management & Experimentation - Architect (BETA COMING SOON) badge](https://2307127582-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2Feh03Q8VHpO02MFM5nUSL%2Fuploads%2Fgit-blob-25fbc5fb009df016acbfa766a8881b68d3ce6df6%2Fcert-arc-fme-badge.svg?alt=media)

**Product version:** Harness FME Paid Plans

{% hint style="info" %}
**Coming soon**

This certification is in beta and not yet open for registration.
{% endhint %}

Assess key technical job functions and advanced skills in design, implementation and management of FME.
{% endtab %}
{% endtabs %}