--- title: OpenAI Codex description: >- Track Codex usage, code-review, and token metrics from the Codex Analytics API. breadcrumbs: Docs > Integrations > OpenAI Codex --- > For the complete documentation index, see [llms.txt](https://docs.datadoghq.com/llms.txt). # OpenAI Codex Supported OS Integration version1.0.0 {% callout %} # Important note for users on the following Datadog sites: us2.ddog-gov.com {% alert level="info" %} To find out if this integration is available in your organization, see your [Datadog Integrations](https://app.datadoghq.com/integrations) page or ask your organization administrator. To initiate an exception request to enable this integration for your organization, email [support@ddog-gov.com](mailto:support@ddog-gov.com). {% /alert %} {% /callout %} Track Codex usage, tokens, and code changes in the Overview Dashboard.See Codex's impact on delivery in the Delivery Performance Explorer. ## Overview{% #overview %} OpenAI Codex is OpenAI's enterprise AI coding agent. This integration collects per-user, per-day Codex activity from the Codex Analytics API, reports it to Datadog as standard metrics, and uses it to attribute AI-assisted pull requests in AI Impact. Engineering leaders can measure Codex adoption and correlate it with software delivery performance. ### What this integration collects{% #what-this-integration-collects %} The integration polls the Codex Analytics API once per day for each enterprise workspace and emits metrics under the `openai.codex.*` namespace: - **Usage totals**: Threads, turns, credits, and token counts for each engineer. - **Usage breakdowns**: Token counts by model, and thread and turn counts by client. - **Code attribution**: Lines of code added and removed that are attributable to Codex. - **Code reviews**: Reviews completed and review comments by priority, with the reactions and replies those comments receive. - **User engagement**: A daily per-engineer signal that AI Impact uses to attribute AI assistance. Spend and dollar amounts are not collected. Credits reflect consumed Codex credits, not a currency amount. ### Dashboards and monitors{% #dashboards-and-monitors %} - An **OpenAI Codex Overview** dashboard for usage, token consumption by model, client activity, code attribution, and code reviews. - A recommended monitor that alerts when usage metrics stop reporting. - [Delivery Performance Explorer](https://app.datadoghq.com/ci/dora/ai-impact), available when you enable AI Impact. ### Use cases{% #use-cases %} - Track Codex adoption, token consumption, and engagement across teams and models. - Measure how much code Codex contributes and how its reviews are received. - Segment deployment frequency, lead time, change failure rate, and mean time to restore by Codex engagement. ## Setup{% #setup %} ### Prerequisites{% #prerequisites %} - An active OpenAI enterprise subscription with Codex enabled. - Workspace admin access to the Codex enterprise admin portal. ### Get your Codex credentials{% #get-your-codex-credentials %} 1. Sign in to [admin.openai.com](https://admin.openai.com), then go to **Credentials** → **Admin keys**. 1. Create an API key and select the workspace you'd like to collect metrics for. Note your workspace ID. 1. Choose **Restricted** permissions and enable the **Codex Analytics read** scope (`codex.enterprise.analytics.read`). ### Configure the integration in Datadog{% #configure-the-integration-in-datadog %} 1. Enter a unique name to identify your account from within Datadog. Also enter your **Codex API Key** and **Codex Workspace ID**, both copied from OpenAI on the Integration tile. 1. To send engagement data to [AI Impact](https://docs.datadoghq.com/delivery_performance/ai_impact.md), select the **Use for attribution in AI Impact** toggle. 1. Click **Create Account**. The integration automatically collects usage, code-attribution, and code-review metrics after account configuration. Data is reported once per day, so it may take up to 24 hours for metrics to appear. You can view your data in the **OpenAI Codex Overview** dashboard or the [Metrics Explorer](https://app.datadoghq.com/metric/explorer) to confirm that usage metrics appear. If you enabled AI Impact, also check the [Delivery Performance Explorer](https://app.datadoghq.com/ci/dora/ai-impact). ## Data Collected{% #data-collected %} ### Metrics{% #metrics %} | | | | | **openai.codex.usage.threads**(count) | Codex threads (conversations) started by the user that day | | **openai.codex.usage.turns**(count) | User turns (messages) sent across Codex threads that day | | **openai.codex.usage.credits**(count) | Codex credits consumed by the user that day | | **openai.codex.usage.tokens.uncached_input**(count) | Uncached text input tokens processed by the user that day | | **openai.codex.usage.tokens.cached_input**(count) | Cached text input tokens processed by the user that day | | **openai.codex.usage.tokens.output**(count) | Text output tokens generated for the user that day | | **openai.codex.usage.tokens.total**(count) | Total text tokens (input and output) processed for the user that day | | **openai.codex.usage.by_model.tokens.uncached_input**(count) | Uncached text input tokens broken down by model | | **openai.codex.usage.by_model.tokens.cached_input**(count) | Cached text input tokens broken down by model | | **openai.codex.usage.by_model.tokens.output**(count) | Text output tokens broken down by model | | **openai.codex.usage.by_model.tokens.total**(count) | Total text tokens broken down by model | | **openai.codex.usage.by_client.threads**(count) | Codex threads started via this client (for example, cli, ide, or web) | | **openai.codex.usage.by_client.turns**(count) | User turns sent via this client (for example, cli, ide, or web) | | **openai.codex.usage.code_attribution.lines_added**(count) | Lines of code added attributable to Codex that day | | **openai.codex.usage.code_attribution.lines_removed**(count) | Lines of code removed attributable to Codex that day | | **openai.codex.code_reviews.completed**(count) | Pull request reviews completed by Codex | | **openai.codex.code_reviews.comments.total**(count) | Total review comments left by Codex | | **openai.codex.code_reviews.comments.p0**(count) | P0 (highest priority) review comments left by Codex | | **openai.codex.code_reviews.comments.p1**(count) | P1 review comments left by Codex | | **openai.codex.code_reviews.comments.p2**(count) | P2 review comments left by Codex | | **openai.codex.code_review_responses.reactions.upvotes**(count) | Upvote reactions received on Codex review comments | | **openai.codex.code_review_responses.reactions.downvotes**(count) | Downvote reactions received on Codex review comments | | **openai.codex.code_review_responses.reactions.other**(count) | Other reactions received on Codex review comments | | **openai.codex.code_review_responses.replies**(count) | Codex review comments that received a reply | | **openai.codex.code_review_responses.engaged**(count) | Codex review comments that were engaged with | ## Uninstallation{% #uninstallation %} To uninstall, remove all configured accounts from the **OpenAI Codex** tile in Datadog. Deleting the last account stops all data collection for this integration. ## Support{% #support %} Need help? Contact [Datadog Support](https://app.datadoghq.com/help). ## Further Reading{% #further-reading %} Additional helpful documentation, links, and articles: - [Measure the real impact of AI coding tools on software delivery with Datadog AI Impact](https://www.datadoghq.com/blog/ai-impact/) - [Measure AI Coding Tool Impact](https://www.datadoghq.com/product/software-delivery/ai-impact/)