# Agent Config #### 介绍 Agent Config 是用来决定 Agent 行为的配置，一般会保存在 `/etc/eru/agent.yaml` 也可以通过 `agent --config` 来指定。一个标准的 agent 配置如下： ``` pid: /tmp/agent.pid pid path store: grpc optional store 的类型，默认为 grpc，即 eru-core 的 grpc 服务 runtime: docker optional runtime 类型，默认为 docker kv: etcd optional kv 类型，默认为 ETCD core: Core 的 API 地址 - 127.0.0.1:5001 可以配置多个地址 healthcheck: Health Check 配置 interval: 120 optional Health Check 间隔 timeout: 10 optional Health Check 超时判定 cache_ttl: 300 optional 本地缓存的过期时间，仅当 enable_selfmon 为 true 时生效 enable_selfmon: false optional 集群里是否启动了 selfmon auth: optional Core API Basic auth username: username password: password docker: Docker 配置 endpoint: unix:///var/run/docker.sock Docker url，支持 unix socket file 地址和 tcp 地址的形式 yavirt: Yavirt 配置 endpoint: grpc://127.0.0.1:9697 Yavirt url，支持 grpc 地址和 http 地址 skip_guest_report_regexps: ID 符合任意正则表达式的 VM 将不会被检查 - .+002 metrics: Metrics 配置 step: 30 发送间隔 transfers: optional 默认支持 prometheus，也可以开启 statsd - 127.0.0.1:8125 可以配置多个 statsd 后端 api: optional profile API 配置 addr: 127.0.0.1:12345 profile API 地址 log: 日志选项 forwards: - tcp://127.0.0.1:5144 optional 日志远端, 支持 tcp、udp、journal 和特殊的 __discard__ stdout: False 是否把容器日志打到 agent 自身日志流里面 ha_keepalive_interval: 16s optional selfmon 发送心跳的时间间隔 etcd: ETCD 配置，仅当此 agent 以 selfmon 模式运行时生效 machines: ETCD 服务器地址 - 127.0.0.1:2379 prefix: /agent-selfmon Key的前缀 ``` Agent 在监听到隶属 Eru 的容器启动后，会把 stdout/stderr 的日志 forward 到配置的远端，同时开始监听 metrics。 对于日志，格式如下： ``` {"id":"{CONTAINER_ID}","name":"{APP_NAME}","type":"{stderr || stdout}","entrypoint":"{APP_ENTRYPOINT}","ident":"{APP_IDENT}","data":"{LOG_MSG}","datetime":"2018-06-27 07:19:25.507018","extra":{CONTAINER_LABELS}} ``` 在测试的时候甚至可以用 `netcat` 来模拟日志接收，使用 ``` nc -l {PORT} -k ``` 需要注意的是，log 参数支持 tcp 和 udp 2种形式，udp 对于单条日志大小限制为了1024K，因此对于线上系统而言，建议使用 TCP 模式。 对于 Metrics，Agent 会发一组数据到配置的远端 statsd 中： ``` eru.{APPNAME}.{TAG}.{ENTRYPOINT}.{HOST}.{CONTAINER_ID}.cpu_usage:0.06814310051085702|g eru.{APPNAME}.{TAG}.{ENTRYPOINT}.{HOST}.{CONTAINER_ID}.cpu_user_usage:0|g eru.{APPNAME}.{TAG}.{ENTRYPOINT}.{HOST}.{CONTAINER_ID}.cpu_sys_usage:40.00000000003638|g eru.{APPNAME}.{TAG}.{ENTRYPOINT}.{HOST}.{CONTAINER_ID}.mem_rss:6184960|g eru.{APPNAME}.{TAG}.{ENTRYPOINT}.{HOST}.{CONTAINER_ID}.mem_usage:2088960|g eru.{APPNAME}.{TAG}.{ENTRYPOINT}.{HOST}.{CONTAINER_ID}.mem_max_usage:2215936|g eru.{APPNAME}.{TAG}.{ENTRYPOINT}.{HOST}.{CONTAINER_ID}.mem_usage_percent:0|g eru.{APPNAME}.{TAG}.{ENTRYPOINT}.{HOST}.{CONTAINER_ID}.lo.drop.in:0|g eru.{APPNAME}.{TAG}.{ENTRYPOINT}.{HOST}.{CONTAINER_ID}.lo.drop.out:0|g eru.{APPNAME}.{TAG}.{ENTRYPOINT}.{HOST}.{CONTAINER_ID}.lo.err.in:0|g eru.{APPNAME}.{TAG}.{ENTRYPOINT}.{HOST}.{CONTAINER_ID}.lo.err.out:0|g eru.{APPNAME}.{TAG}.{ENTRYPOINT}.{HOST}.{CONTAINER_ID}.lo.bytes.recv:10445.6|g eru.{APPNAME}.{TAG}.{ENTRYPOINT}.{HOST}.{CONTAINER_ID}.lo.bytes.sent:0|g eru.{APPNAME}.{TAG}.{ENTRYPOINT}.{HOST}.{CONTAINER_ID}.lo.packets.recv:0|g eru.{APPNAME}.{TAG}.{ENTRYPOINT}.{HOST}.{CONTAINER_ID}.lo.packets.sent:0|g eru.{APPNAME}.{TAG}.{ENTRYPOINT}.{HOST}.{CONTAINER_ID}.cali0.drop.in:0|g eru.{APPNAME}.{TAG}.{ENTRYPOINT}.{HOST}.{CONTAINER_ID}.cali0.drop.out:0|g eru.{APPNAME}.{TAG}.{ENTRYPOINT}.{HOST}.{CONTAINER_ID}.cali0.err.in:0|g eru.{APPNAME}.{TAG}.{ENTRYPOINT}.{HOST}.{CONTAINER_ID}.cali0.err.out:0|g eru.{APPNAME}.{TAG}.{ENTRYPOINT}.{HOST}.{CONTAINER_ID}.cali0.bytes.recv:5191.333333333333|g eru.{APPNAME}.{TAG}.{ENTRYPOINT}.{HOST}.{CONTAINER_ID}.cali0.bytes.sent:0|g eru.{APPNAME}.{TAG}.{ENTRYPOINT}.{HOST}.{CONTAINER_ID}.cali0.packets.recv:0|g eru.{APPNAME}.{TAG}.{ENTRYPOINT}.{HOST}.{CONTAINER_ID}.cali0.packets.sent:0|g ``` 通过这个数据我们就可以从容器外面监控容器行为。 如果没有开启 statsd，也可以通过 `API_HOST:PORT/metrics` 拿到 prometheus 规格的 metrics。 --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://book.eru.dev/specs/agent.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.