[[["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):2025-08-19。"],[],[],null,["# Monitor a deployed index\n\nVertex AI provides two metrics for monitoring the `IndexEndpoint` of a\ndeployed index:\n\n- `aiplatform.googleapis.com/matching_engine/current_shards`\n\n The number of shards of the `DeployedIndex`. As data is added and deleted,\n Vector Search automatically reshards the index to\n achieve optimal performance. This metric indicates the current number of\n shards of the deployed index.\n- `aiplatform.googleapis.com/matching_engine/current_replicas`\n\n The total number of active replica servers being used by the\n `DeployedIndex`. To match query volume,\n Vector Search automatically turns up\n or down replica servers based on the minimum and maximum replica settings\n specified when deploying the index.\n\n If the index has multiple shards, each shard can be served by using a\n different number of replica servers. This metric is the total number of\n replica servers across all shards of the given index.\n\n### What's next\n\n- Learn [how to query your indexes to find their\n nearest neighbors](/vertex-ai/docs/vector-search/query-index-public-endpoint).\n- Learn [how to select, query, and display these metrics in\n Metrics Explorer](/monitoring/charts/metrics-selector)."]]