实时报告

实时报告可以让你了解你的应用如何使用 Supabase Realtime，包括连接情况、广播和变更事件、执行时间以及延迟。

🌐 Realtime reports give insights into how your application uses Supabase Realtime, including connections, broadcast and change events, execution times, and lag.

这些报告可以帮你：

🌐 These reports help you:

• 监控连接数和消息量是否超出你的计划配额
• 找出 RLS 策略或数据库复制中的性能瓶颈
• 排查错误和连接问题
• 根据使用趋势规划容量升级

实时报告概览 #

🌐 Realtime reports overview

已连接的客户端 #

🌐 Connected Clients

“已连接客户端”报告可以帮助你随时监控项目的实时客户端总连接数。这个指标对于了解应用的连接使用模式以及识别何时接近计划的连接限制非常重要。

🌐 The Connected Clients report helps you monitor the total number of concurrent Realtime client connections to your project over time. This metric is essential for understanding your application's connection usage patterns and identifying when you're approaching your plan's connection limits.

该报告显示了连接的实时客户端总数，展示在所选时间段内连接数量的波动情况。每个客户端连接都代表了与你的实时服务的一个活跃 WebSocket 连接，该连接可以订阅多个通道以接收实时更新。

🌐 The report displays the total number of connected Realtime clients, showing how connection counts fluctuate throughout the selected time period. Each client connection represents an active WebSocket connection to your Realtime service, which can subscribe to multiple channels for receiving real-time updates.

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广播活动 #

🌐 Broadcast Events

广播事件报告可以帮助你监控通过实时通道发送的广播消息数量随时间的变化。这个指标对于了解你应用的实时消息模式以及识别什么时候接近你的计划消息吞吐量上限非常重要。

🌐 The Broadcast Events report helps you monitor the volume of broadcast messages sent through your Realtime channels over time. This metric is essential for understanding your application's real-time messaging patterns and identifying when you're approaching your plan's message throughput limits.

该报告显示了客户端发送的广播事件总数，展示了所选时间段内的消息量。广播事件是使用 Realtime 的发布/订阅模式在用户之间发送的低延迟消息，可以通过客户端库、REST API 或直接从数据库发送。每个事件都表示向特定通道主题的订阅者广播的一条消息。

🌐 The report displays the total number of broadcast events sent by clients, showing message volume throughout the selected time period. Broadcast events are low-latency messages sent between users using Realtime's pub/sub pattern, which can be sent from client libraries, REST APIs, or directly from your database. Each event represents a message broadcast to subscribers of a specific channel topic.

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出席活动 #

🌐 Presence Events

Presence Events 报告可以帮助你监控通过你的实时通道发送的状态更新数量随时间的变化。这个指标对于理解你的应用如何跟踪和同步用户之间的共享状态非常重要，比如在线状态、用户活动或自定义状态信息。

🌐 The Presence Events report helps you monitor the volume of presence state updates sent through your Realtime channels over time. This metric is essential for understanding how your application tracks and synchronizes shared state between users, such as online status, user activity, or custom state information.

报告显示了客户端发送的总在线事件数，展示了所选时间段内的状态同步活动。当客户端 track、update 或 untrack 在通道中更新它们的在线状态时，就会触发 sync、join 或 leave 事件。与广播消息不同，在线状态会保存在通道中，因此新加入的用户可以立即收到当前状态，而不必等其他用户发送更新。

🌐 The report displays the total number of presence events sent by clients, showing state synchronization activity throughout the selected time period. Presence events occur when clients track, update, or untrack their presence state in a channel, triggering sync, join, or leave events. Unlike broadcast messages, presence state is persisted in the channel so new joiners immediately receive the current state without waiting for other users to send updates.

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Postgres 变更事件 #

🌐 Postgres Changes Events

Postgres 变更事件报告可以帮助你监控随时间发送给实时客户端的数据库变更事件（INSERT、UPDATE、DELETE）的数量。这个指标对于了解你的应用如何处理数据库变更，以及识别潜在的性能瓶颈或扩展问题，非常重要。

🌐 The Postgres Changes Events report helps you monitor the volume of database change events (INSERT, UPDATE, DELETE) sent to your Realtime clients over time. This metric is essential for understanding how your application processes database changes and identifying potential performance bottlenecks or scaling issues.

该报告显示客户端接收到的 Postgres 变更事件总数，展示了所选时间段内的数据库变更活动。Postgres 变更使用逻辑复制，将数据库中的变更从预写日志（WAL）传输给订阅的客户端。每个事件代表一个已广播给订阅了相关 schema 和表的客户端的数据库变更。需要注意的是，Postgres 变更在单线程上处理变更以保持顺序，所以在大规模情况下相比 Broadcast 可能会产生瓶颈。

🌐 The report displays the total number of Postgres change events received by clients, showing database change activity throughout the selected time period. Postgres Changes use logical replication to stream database changes from the Write-Ahead Log (WAL) to subscribed clients. Each event represents a database change that has been broadcast to clients subscribed to the relevant schema and table. Note that Postgres Changes process changes on a single thread to maintain order, which can create bottlenecks at scale compared to Broadcast.

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通道加入率 #

🌐 Rate of Channel Joins

通道加入速率报告可以帮你监控客户加入实时通道的速度。这个指标对于了解你应用的通道订阅模式非常重要，也能帮助你发现什么时候接近你的计划通道加入速率的上限。

🌐 The Rate of Channel Joins report helps you monitor how fast clients are joining Realtime channels over time. This metric is essential for understanding your application's channel subscription patterns and identifying when you're approaching your plan's channel join rate limits.

该报告显示了每秒通道加入的速率，展示了在所选时间段内客户端订阅通道的频率。每当客户端订阅一个通道主题以接收实时更新时，就会发生一次通道加入。每个客户端连接可以加入多个通道（大多数计划每个连接最多可加入 100 个通道），加入速率就是衡量整个项目中每秒发生多少此类订阅。

🌐 The report displays the rate of channel joins per second, showing how frequently clients subscribe to channels throughout the selected time period. A channel join occurs whenever a client subscribes to a channel topic to receive real-time updates. Each client connection can join multiple channels (up to 100 per connection for most plans), and the join rate measures how many of these subscriptions happen per second across your entire project.

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消息负载大小 #

🌐 Message Payload Size

消息负载大小报告可以帮助你监控通过你的实时通道发送的消息负载的中位大小随时间的变化。这个指标对于理解消息大小如何影响实时应用的性能、延迟和带宽使用非常重要。

🌐 The Message Payload Size report helps you monitor the median size of message payloads sent through your Realtime channels over time. This metric is essential for understanding how message size impacts performance, latency, and bandwidth usage in your real-time application.

该报告显示了有效载荷大小的中位数（以字节为单位），展示了在所选时间段内消息大小的波动情况。有效载荷大小会直接影响消息吞吐量和延迟——较大的有效载荷需要更多的带宽和处理时间，这可能增加延迟并减少系统每秒可以处理的消息数量。监控这一指标可以帮助你优化消息结构，并发现减少有效载荷大小以提升性能的机会。

🌐 The report displays the median payload size in bytes, showing how message sizes fluctuate throughout the selected time period. Payload size directly affects message throughput and latency—larger payloads require more bandwidth and processing time, which can increase latency and reduce the number of messages your system can handle per second. Monitoring this metric helps you optimize your message structure and identify opportunities to reduce payload sizes for better performance.

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来自数据库复制延迟的广播 #

🌐 Broadcast From Database Replication Lag

《数据库复制延迟广播》报告可以帮助你监控消息从写入数据库到广播给实时客户端的中位时间。这一指标对于了解使用数据库广播时数据库复制过程带来的延迟非常重要。

🌐 The Broadcast from Database Replication Lag report helps you monitor the median time between when a message is committed to your database and when it's broadcast to Realtime clients. This metric is essential for understanding the latency introduced by the database replication process when using broadcast from database.

报告显示了中位复制延迟（以毫秒为单位），展示了从数据库提交到广播在所选时间段内的延迟。当你使用数据库广播（通过向 realtime.messages 插入消息）时，实时功能会通过逻辑复制从预写日志（WAL）读取更改。延迟表示这些更改处理并广播给订阅客户端所需的时间。延迟值越高，说明复制流程越慢，这可能会影响你应用的实时响应性。

🌐 The report displays the median replication lag in milliseconds, showing the delay between database commit and broadcast throughout the selected time period. When you use broadcast from database (by inserting messages into realtime.messages), Realtime reads changes from the Write-Ahead Log (WAL) using logical replication. The lag represents the time it takes for these changes to be processed and broadcast to subscribed clients. Higher lag values indicate delays in the replication pipeline, which can impact the real-time responsiveness of your application.

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(阅读) 私有通道订阅 RLS 执行时间 #

🌐 (Read) Private Channel Subscription RLS Execution Time

(读取)私有通道订阅 RLS 执行时间报告帮助你监控用户订阅私有通道时执行行级安全 (RLS) 策略的中位时间。这个指标对于了解 RLS 策略的复杂性如何影响通道加入延迟和整体连接性能非常重要。

🌐 The (Read) Private Channel Subscription RLS Execution Time report helps you monitor the median time it takes to execute Row Level Security (RLS) policies when users subscribe to private channels. This metric is essential for understanding how RLS policy complexity impacts channel join latency and overall connection performance.

该报告显示了 RLS 执行时间的中位数（以毫秒为单位），展示了在选定时间段内订阅私有通道时验证用户权限所需的时间。当用户加入私有通道时，Realtime 会检查 realtime.messages 表上的 RLS 策略，以确定用户是否有读取权限。每个通道订阅只会进行一次该授权检查，并且结果会在连接期间缓存。然而，如果 RLS 策略包含复杂的连接、函数调用或缺少索引，可能会显著增加初始连接时间。

🌐 The report displays the median RLS execution time in milliseconds, showing how long it takes to validate user permissions when subscribing to private channels throughout the selected time period. When a user joins a private channel, Realtime checks RLS policies on the realtime.messages table to determine if the user has read access. This authorization check happens once per channel subscription and the result is cached for the duration of the connection. However, complex RLS policies with joins, function calls, or missing indexes can significantly increase this initial connection time.

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(写)私有通道订阅RLS执行时间 #

🌐 (Write) Private Channel Subscription RLS Execution Time

（写）私有通道订阅 RLS 执行时间报告帮助你监控用户向私有通道发布消息时执行行级安全（RLS）策略所需的中位时间。这个指标对于了解 RLS 策略的复杂性如何影响消息发布延迟和整体广播性能非常重要。

🌐 The (Write)Private Channel Subscription RLS Execution Time report helps you monitor the median time it takes to execute Row Level Security (RLS) policies when users publish messages to private channels. This metric is essential for understanding how RLS policy complexity impacts message publishing latency and overall broadcast performance.

该报告显示了 RLS 执行时间的中位数（以毫秒为单位），说明在所选时间段内向私有通道发布内容时验证用户权限所需的时间。当用户向私有通道发送广播消息时，Realtime 会检查 realtime.messages 表上的 RLS 策略，以确定用户是否有写入（INSERT）权限。这个授权检查只在发送第一条消息时进行，然后会被缓存。带有连接、函数调用或缺少索引的复杂 RLS 策略会显著增加第一条消息发布的延迟。

🌐 The report displays the median RLS execution time in milliseconds, showing how long it takes to validate user permissions when publishing to private channels throughout the selected time period. When a user sends a broadcast message to a private channel, Realtime checks RLS policies on the realtime.messages table to determine if the user has write (INSERT) access. This authorization check happens for the first message sent and then it's cached. Complex RLS policies with joins, function calls, or missing indexes can significantly increase first message publishing latency.

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总请求数 #

🌐 Total Requests

总请求数报告可以帮助你随时监控 Realtime 的 HTTP 请求总量。这个指标对于了解你的应用使用情况以及发现流量趋势或 API 请求处理潜在问题非常重要。

🌐 The Total Requests report helps you monitor the overall volume of HTTP requests for Realtime over time. This metric is essential for understanding your application's usage patterns and identifying traffic trends or potential issues with API request handling.

该报告显示了对实时服务发出的 HTTP 请求总数，其中包括 WebSocket 升级请求和 REST API 请求。

🌐 The report displays the total number of HTTP requests made to the Realtime service which include the WebSocket upgrade requests and the REST API requests.

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响应错误 #

🌐 Response Errors

响应错误报告可以帮助你监控一段时间内对实时服务的失败 HTTP 请求数量。这个指标对于识别 API 请求问题、WebSocket 升级失败、认证问题以及其他可能影响你应用实时功能的错误情况非常重要。

🌐 The Response Errors report helps you monitor the number of failed HTTP requests to the Realtime service over time. This metric is essential for identifying issues with API requests, WebSocket upgrade failures, authentication problems, and other error conditions that may impact your application's real-time functionality.

报告显示了 Realtime API 的总响应错误数，展示了选定时间段内的错误频率。这些错误包括 REST API 请求的 HTTP 错误状态码（4xx 客户端错误和 5xx 服务器错误）、WebSocket 升级请求失败、授权失败以及其他错误响应。将错误率和总请求量一起监控，可以帮助你发现规律，将错误与特定事件关联起来，并排查影响 Realtime 服务可用性的问题。

🌐 The report displays the total number of response errors from the Realtime API, showing error frequency throughout the selected time period. These errors include HTTP error status codes (4xx client errors and 5xx server errors) from REST API requests, failed WebSocket upgrade requests, authorization failures, and other error responses. Monitoring error rates alongside total requests helps you identify patterns, correlate errors with specific events, and troubleshoot issues affecting your Realtime service availability.

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响应速度 #

🌐 Response Speed

响应速度报告可以帮助你监控实时服务的 HTTP 请求的平均响应时间。这个指标对于了解 API 性能、发现延迟问题，以及确保你的实时功能达到性能预期非常重要。

🌐 The Response Speed report helps you monitor the average response time for HTTP requests to the Realtime service over time. This metric is essential for understanding API performance, identifying latency issues, and ensuring your real-time features meet performance expectations.

该报告显示了平均响应时间（以毫秒为单位），展示了实时服务在所选时间段内响应 HTTP 请求的速度。这包括 REST API 请求的响应时间，比如广播消息、WebSocket 升级请求以及其他基于 HTTP 的交互。较高的响应时间可能表明存在性能瓶颈、数据库负载问题或网络问题，可能会影响应用的实时响应性能。

🌐 The report displays the average response time in milliseconds, showing how fast the Realtime service responds to HTTP requests throughout the selected time period. This includes response times for REST API requests such as broadcast messages, WebSocket upgrade requests, and other HTTP-based interactions. Higher response times can indicate performance bottlenecks, database load issues, or network problems that may impact the real-time responsiveness of your application.

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