[[["易于理解","easyToUnderstand","thumb-up"],["解决了我的问题","solvedMyProblem","thumb-up"],["其他","otherUp","thumb-up"]],[["很难理解","hardToUnderstand","thumb-down"],["信息或示例代码不正确","incorrectInformationOrSampleCode","thumb-down"],["没有我需要的信息/示例","missingTheInformationSamplesINeed","thumb-down"],["翻译问题","translationIssue","thumb-down"],["其他","otherDown","thumb-down"]],["最后更新时间 (UTC)：2025-08-26。"],[[["\u003cp\u003eOperations Anomalies identifies unusual API data patterns, distinguishing them from random fluctuations based on recent data.\u003c/p\u003e\n"],["\u003cp\u003eThis feature, available in the Apigee UI in Cloud console, detects increases in specific HTTP errors and latency levels.\u003c/p\u003e\n"],["\u003cp\u003eUsing Operations Anomalies requires the AAPI Ops add-on to be enabled, along with the appropriate user roles and logging access.\u003c/p\u003e\n"],["\u003cp\u003eApigee automatically trains models from the previous six hours of API data to detect anomalies, and a minimum of six hours of API data is needed to train a model.\u003c/p\u003e\n"],["\u003cp\u003eDetected anomalies are displayed on the Operations Anomalies dashboard, providing details such as the time, summary, environment, region, and severity of the anomaly.\u003c/p\u003e\n"]]],[],null,["*This page\napplies to **Apigee** and **Apigee hybrid**.*\n\n\n*View [Apigee Edge](https://docs.apigee.com/api-platform/get-started/what-apigee-edge) documentation.*\n\n| **Important:** This page describes how to use Operations Anomalies, which is comparable to the [Advanced API Operations Anomaly Detection](/apigee/docs/aapi-ops) functionality in the Classic Apigee UI. Operations Anomalies is only available in the [Apigee UI in Cloud console](https://console.cloud.google.com/apigee) while Anomaly Detection is only available when using the classic [Apigee UI](https://apigee.google.com). Both are available at this time.\n\nOperations Anomalies overview\n\nOperations Anomalies identifies unusual or unexpected API data patterns on your APIs,\nbased on recent data patterns. For example,\nin this graph of API error rate, the error rate suddenly jumps up at around 7 AM. Compared\nto the data leading up to that time, this increase is unusual enough to be classified as an anomaly.\n\nNot all variations in API data represent anomalies: most\nare random fluctuations. For example, you can see some minor variations in\nerror rate leading up to the anomaly, but these are not significant enough to be categorized as an\nanomaly.\n\nOperations Anomalies continually monitors API data and performs statistical analysis to distinguish true\nanomalies from random fluctuations in the data.\n\nOperations Anomalies automatically detects these anomaly types:\n\n- Increase in HTTP 503 errors at the organization, environment, and region level\n- Increase in HTTP 504 errors at the organization, environment, and region level\n- Increase in all HTTP 4xx or 5xx errors at the organization, environment, and region level\n- Increase in the total response latency for the 90th percentile (p90) at the organization, environment, and region level\n\nA detected anomaly includes this information:\n\n- The metric that caused the anomaly, such as proxy latency or an HTTP error code.\n- The severity of the anomaly. The severity can be slight, moderate, or severe, based on its confidence level in the model. A low confidence level indicates that the severity is slight, while a high confidence level indicates that it is severe.\n\nPrerequisites for using Operations Anomalies\n\nTo use Operations Anomalies:\n\n- The AAPI Ops add-on must be enabled for your organization. See [Enable AAPI Ops in an organization](/apigee/docs/aapi-ops#enable).\n- Users of Operations Anomalies must have the [required roles for AAPI Ops](/apigee/docs/aapi-ops#required-roles-for-aapi-ops).\n- Users who [investigate anomalies in the dashboard](/apigee/docs/api-platform/analytics/investigate-anomalies) also need the `roles/logging.viewer` role.\n\n\u003cbr /\u003e\n\nView detected Operations Anomalies\n\nWhen Operations Anomalies detects an anomaly, it displays the anomaly details in the\nOperations Anomalies dashboard.\nYou can investigate the anomaly in the API Monitoring dashboards and\ntake appropriate action if necessary. You can also\ncreate an alert to notify you if similar events occur in future.\n\nThe Operations Anomalies dashboard in the Apigee UI is your primary source of information about\ndetected Operations Anomalies. The dashboard displays a list of recent anomalies.\n\nTo open the Operations Anomalies dashboard:\n\n1. Sign in to [Apigee UI in Cloud console](https://console.cloud.google.com/apigee).\n2. [Switch to the organization](/apigee/docs/api-platform/get-started/switch-org) that you want to monitor.\n3. In the left menu, select **Analytics \\\u003e Operations Anomalies**.\n\nThis displays the Operations Anomalies dashboard.\n\nBy default, the dashboard shows anomalies that have occurred during the previous hour.\nIf no anomalies have been detected during that time period, no rows are\ndisplayed in the dashboard. You can select a larger time range from\nthe time range menu in the top right of the dashboard.\n\nEach row in the table corresponds to a detected anomaly,\nand displays the following information:\n\n- The date and time of the anomaly.\n- A brief summary of the anomaly, including the proxy in which it occurred and the fault code that triggered it.\n- The environment in which the anomaly occurred.\n- The region where the anomaly occurred.\n- The severity of the anomaly event: slight, moderate, or severe. Severity is based on a statistical measure (p-value) of how unlikely it would be for the event to occur by chance (the more unlikely the event, the greater its severity).\n\nYou can also\n[investigate an anomaly](/apigee/docs/api-platform/analytics/investigate-anomalies)\nin the API Monitoring dashboards, which shows various graphs of recent API traffic\ndata.\n\nHow anomaly detection works\n\nAnomaly detection involves the following stages:\n\n- [Train models](#train-models)\n- [Log anomaly events](#log-anomaly-events)\n\nTrain models\n\nOperations Anomalies works by training a model of the behavior of your API proxies from historical\ntime-series data. There is no action required on your part to train the model. Apigee automatically\ncreates and trains models for you from the previous six hours of API data.\nTherefore, Apigee requires a minimum of six hours of data on an API proxy to train the model before\nit can log an anomaly.\n\nThe goal of training is to improve the accuracy of the model, which can then be tested\non historical data. The simplest\nway to test a model's accuracy is to calculate its *error rate*---the\nsum of false positives and false negatives, divided by the total number of predicted events.\n\nLog anomaly events\n\nAt runtime, Operations Anomalies compares the current behavior of your API proxies with the behavior\npredicted by the model. Operations Anomalies can then determine, with a specific confidence level,\nwhen an operational metric is exceeding the predicted value. For example, when the rate of 5xx errors\nexceeds the rate predicted by the model.\n\nWhen Apigee detects an anomaly, it automatically logs the event in the\n[Operations Anomalies\ndashboard](#view-detected-operations-anomalies). The list of events displayed in the dashboard includes all\ndetected anomalies, as well as triggered alerts."]]
