# 指标配置文件 # 算法成员可以在此添加自定义指标 # Redis 连接配置(也可通过环境变量覆盖) redis: host: ${REDIS_HOST:localhost} port: ${REDIS_PORT:6379} db: ${REDIS_METRICS_DB:0} password: ${REDIS_PASSWORD:} # 全局配置 global: prefix: "functional_scaffold" # 指标名称前缀 instance_label: true # 是否添加实例标签 # 内置指标(框架自动收集) builtin_metrics: http_requests: enabled: true name: "http_requests_total" type: counter description: "HTTP 请求总数" labels: [method, endpoint, status] http_latency: enabled: true name: "http_request_duration_seconds" type: histogram description: "HTTP 请求延迟" labels: [method, endpoint] buckets: [0.005, 0.01, 0.025, 0.05, 0.1, 0.25, 0.5, 1, 2.5, 5, 10] http_in_progress: enabled: true name: "http_requests_in_progress" type: gauge description: "当前进行中的 HTTP 请求数" labels: [] algorithm_executions: enabled: true name: "algorithm_executions_total" type: counter description: "算法执行总数" labels: [algorithm, status] algorithm_latency: enabled: true name: "algorithm_execution_duration_seconds" type: histogram description: "算法执行延迟" labels: [algorithm] buckets: [0.01, 0.05, 0.1, 0.5, 1, 5, 10, 30, 60] # 自定义指标(算法成员在此添加) custom_metrics: # 示例:质数判断结果统计 prime_check_results: name: "prime_check_results_total" type: counter description: "质数判断结果统计" labels: [is_prime] # 示例:输入数字大小分布 input_number_size: name: "input_number_size" type: histogram description: "输入数字大小分布" labels: [] buckets: [10, 100, 1000, 10000, 100000, 1000000] # 异步任务指标 jobs_created: name: "jobs_created_total" type: counter description: "创建的异步任务总数" labels: [algorithm] jobs_completed: name: "jobs_completed_total" type: counter description: "完成的异步任务总数" labels: [algorithm, status] job_execution_duration: name: "job_execution_duration_seconds" type: histogram description: "异步任务执行时间" labels: [algorithm] buckets: [0.1, 0.5, 1, 5, 10, 30, 60, 120, 300] webhook_deliveries: name: "webhook_deliveries_total" type: counter description: "Webhook 回调发送总数" labels: [status] prime_check_total: name: "prime_check" type: counter description: "出现问题的次数" labels: [status]