在云原生技术栈中，Prometheus作为监控告警的事实标准，是保障分布式系统稳定性的核心组件。但多数技术人员仅停留在配置使用层面，难以应对大规模集群下的定制化需求。几米课堂特邀资深云原生CTO打造《prometheus源码讲解和二次开发专题课》，从架构设计到源码实现，从扩展机制到性能优化，带你深入Prometheus内核，掌握企业级监控系统的定制开发能力，成为云原生监控领域的技术专家。
* 01 prometheus全组件配置调优实战/
* prometheus实战课所需软件包.tar.gz (662.39 MB)
* prometheus实战课程/
* 01_全组件实战搭建调优篇/
* 01_环境准备.md (0.00 MB)
* 001_部署node_exporter和prometheus，prometheus基础概念讲解.md (0.01 MB)
* 002_自动化部署node_exporter它的使用、部署grafana导入大盘.md (0.01 MB)
* 003_黑盒探针blackbox_exporter、进程监控process_exporter、各种中间件mysqld、redis、consul exporter使用.md (0.02 MB)
* 004_pushgateway使用和高可用.md (0.00 MB)
* 004_pushgateway打点问题及高可用实战.md (0.00 MB)
* 005_alertmanager实战.md (0.01 MB)
* pic/
* alertm_arch.png (0.06 MB)
* alertm_arch.svg (0.04 MB)
* alertm_gossip.png (0.12 MB)
* at.png (0.06 MB)
* atop.png (0.09 MB)
* blackbox探测.png (0.13 MB)
* c_hash_01.png (0.04 MB)
* c_hash_02.png (0.13 MB)
* c_hash_03.png (0.12 MB)
* c_hash_04.png (0.15 MB)
* c_hash_05.png (0.17 MB)
* c_hash_06.png (0.16 MB)
* c_hash_07.png (0.11 MB)
* ch_01.png (0.28 MB)
* ch_02.png (0.11 MB)
* consul_sd_pushgateway.png (0.09 MB)
* consul_service.png (0.06 MB)
* falcon_alert.png (0.05 MB)
* file_sd.png (0.28 MB)
* gossip02.png (0.20 MB)
* gossip.png (0.16 MB)
* grafana_dashboard商城.png (0.15 MB)
* grafana_node_exporter大盘.png (0.15 MB)
* grafana新增dashboard.png (0.02 MB)
* grafana查看网卡数据.png (0.14 MB)
* grafana添加数据源.png (0.07 MB)
* grafana表格和变量.png (0.06 MB)
* group1.png (0.08 MB)
* group2.png (0.17 MB)
* happen.png (0.02 MB)
* im_dingding.png (0.12 MB)
* inhibite02.png (0.21 MB)
* inhibite.png (0.09 MB)
* k8s服务发现.png (0.09 MB)
* m1.png (0.15 MB)
* node_exporter默认关闭的采集项.png (0.05 MB)
* node_exporter默认开启的采集项.png (0.07 MB)
* pb.png (0.18 MB)
* process_exporter.png (0.24 MB)
* prometheus_targets.png (0.02 MB)
* pull_vs_push.png (0.06 MB)
* redis_exporter.png (0.13 MB)
* s01.png (0.03 MB)
* s02.png (0.03 MB)
* s03.png (0.04 MB)
* sample.png (0.02 MB)
* target成功率.png (0.21 MB)
* transfer一致性哈希算法01.png (0.13 MB)
* transfer一致性哈希算法02.png (0.18 MB)
* 企业微信02.png (0.07 MB)
* 企业微信.png (0.06 MB)
* 动态分片.png (0.14 MB)
* 升级.png (0.01 MB)
* 即时向量.png (0.03 MB)
* 告警聚合01.png (0.21 MB)
* 回调.png (0.01 MB)
* 快速屏蔽.png (0.14 MB)
* 服务发现原理1.png (0.14 MB)
* 服务发现对比.png (0.03 MB)
* 标签.png (0.00 MB)
* 生效时间.png (0.00 MB)
* 范围向量.png (0.07 MB)
* 触发参数.png (0.01 MB)
* 触发条件.png (0.00 MB)
* 通道_im.png (0.11 MB)
* 采集端HA.png (0.17 MB)
* scripts/
* 004_pushgateway.py (0.00 MB)
* 005_alert_receive.py (0.00 MB)
* 005_alert_silence.py (0.00 MB)
* 005_alertm_send.py (0.00 MB)
* service/
* 01alertmanager.yml (0.00 MB)
* 02alertmanager.yml (0.00 MB)
* 03alertmanager.yml (0.00 MB)
* 04alertmanager.yml (0.00 MB)
* alertmanager.service (0.00 MB)
* blackbox_exporter.service (0.00 MB)
* consul.service (0.00 MB)
* dbus-org.freedesktop.nm-dispatcher.service (0.00 MB)
* init_syslog_logrotate.yaml (0.00 MB)
* logrotate.conf (0.00 MB)
* loki.service (0.00 MB)
* mysqld_exporter.service (0.00 MB)
* node_exporter.service (0.00 MB)
* process-exporter.service (0.00 MB)
* prometheus.service (0.00 MB)
* prometheus.yml (0.00 MB)
* promtail.service (0.00 MB)
* pushgateway.service (0.00 MB)
* redis_6379.service (0.00 MB)
* redis_6479.service (0.00 MB)
* redis_exporter.service (0.00 MB)
* rule.yml (0.00 MB)
* rule_01.yml (0.00 MB)
* rule_02.yml (0.00 MB)
* rule_for_wechat.yml (0.00 MB)
* service_deploy.yaml (0.00 MB)
* syslog_server.conf (0.00 MB)
* wechat.tmpl (0.00 MB)
* 02_k8s监控实战和原理/
* 01_kubeadmin安装k8s1.20.md (0.00 MB)
* 02_k8s中prometheus、grafana搭建、导入大盘.md (0.00 MB)
* 03_prometheus适配k8s采集.md (0.01 MB)
* 03_采集分析.md (0.01 MB)
* 04_k8s监控指标讲解.md (0.01 MB)
* pic/
* ha_arch.png (0.09 MB)
* k8s.png (0.14 MB)
* k8s_node.png (0.03 MB)
* k8s_obj.png (0.06 MB)
* k8s_server.png (0.03 MB)
* mo01.png (0.13 MB)
* mo02.png (0.08 MB)
* mo03.png (0.11 MB)
* mo04.png (0.04 MB)
* mo05.png (0.22 MB)
* multi_remote_read.jpg (0.11 MB)
* p_target.png (0.06 MB)
* prome_remote01.png (0.02 MB)
* service/
* grafana/
* README.md (0.00 MB)
* grafana_k8s.yaml (0.00 MB)
* m3db/
* m3db_single_install.sh (0.00 MB)
* m3dbnode.service (0.00 MB)
* m3dbnode_single.yaml (0.01 MB)
* m_query.service (0.00 MB)
* m_query.yml (0.00 MB)
* prometheus.yml (0.00 MB)
* prome_k8s_all_pod/
* README.md (0.00 MB)
* control_plane_service.yaml (0.00 MB)
* kube-stats-metrics/
* cluster-role-binding.yaml (0.00 MB)
* cluster-role.yaml (0.00 MB)
* deployment.yaml (0.00 MB)
* service-account.yaml (0.00 MB)
* service.yaml (0.00 MB)
* prometheus_config.yaml (0.01 MB)
* prometheus_storageclass.yaml (0.00 MB)
* pv.yaml (0.00 MB)
* rbac.yaml (0.00 MB)
* statsfulset.yaml (0.00 MB)
* prometheus_in_k8s.yml (0.01 MB)
* 03_高可用采集模块实战/
* 01_服务发现和运维平台对接.md (0.01 MB)
* 02_dynamic-sharding： 解决pushgateway HA问题.md (0.00 MB)
* 03_hashmod静态分片和采集端高可用.md (0.00 MB)
* pic/
* c_hash_01.png (0.04 MB)
* c_hash_02.png (0.13 MB)
* c_hash_03.png (0.12 MB)
* c_hash_04.png (0.15 MB)
* c_hash_05.png (0.17 MB)
* c_hash_06.png (0.16 MB)
* c_hash_07.png (0.11 MB)
* ch_01.png (0.28 MB)
* ch_02.png (0.11 MB)
* consul_sd_pushgateway.png (0.09 MB)
* consul_service.png (0.06 MB)
* file_sd.png (0.28 MB)
* k8s服务发现.png (0.09 MB)
* m1.png (0.15 MB)
* transfer一致性哈希算法01.png (0.13 MB)
* transfer一致性哈希算法02.png (0.18 MB)
* 服务发现原理1.png (0.14 MB)
* 服务发现对比.png (0.03 MB)
* 采集端HA.png (0.17 MB)
* scripts/
* 001阻塞请求.py (0.00 MB)
* 002轮询key.py (0.00 MB)
* 003注册service.py (0.00 MB)
* 004注销服务.py (0.00 MB)
* 005watch服务.py (0.01 MB)
* prome_shard/
* README.md (0.00 MB)
* __init__.py
* ansi_new.py (0.01 MB)
* config.yaml (0.00 MB)
* consistent_hash_ring.py (0.00 MB)
* consul_work.py (0.00 MB)
* copy_file_and_reload_prome.yaml (0.00 MB)
* get_targets.py (0.01 MB)
* images/
* golang_consul_watch.png (0.05 MB)
* prome_shard_mon.png (0.17 MB)
* 采集端动态分片高可用实战.jpg (0.41 MB)
* metrics.py (0.00 MB)
* prome_shard.py (0.01 MB)
* prometheus.yml (0.00 MB)
* requirements.txt (0.00 MB)
* 多进程共享map.py (0.00 MB)
* 简化模型01.py (0.00 MB)
* prome_shard.zip (0.62 MB)
* 04_高可用存储模块实战/
* 01_tsdb底层原理/
* 001_什么是tsdb.md (0.01 MB)
* 002_lsm数据结构.md (0.01 MB)
* 002_tsdb存储模型.md (0.00 MB)
* 003_facebook_gorilla压缩算法.md (0.00 MB)
* 004_mmap原理及应用.md (0.00 MB)
* 004_prometheus本地存储解析.md (0.01 MB)
* 004_倒排索引原理.md (0.01 MB)
* 004_布隆过滤器.md (0.00 MB)
* pic/
* boolm_01.png (0.06 MB)
* boolm_02.png (0.20 MB)
* boolm_03.png (0.21 MB)
* boolm_04.png (0.13 MB)
* db_engine_tsdb_ranking.png (0.15 MB)
* gorilla_01.jpg (0.06 MB)
* gorilla_02.jpg (0.05 MB)
* gorilla_03.jpg (0.22 MB)
* gorilla_04.jpg (0.12 MB)
* gorilla_05.jpg (0.04 MB)
* index_02.png (0.01 MB)
* index_分布.png (0.03 MB)
* lsm_compact_01.png (0.19 MB)
* lsm_compact_02.png (0.22 MB)
* lsm_compact_03.png (0.21 MB)
* lsm_compact_04.png (0.29 MB)
* lsm_level_compact.jpg (0.15 MB)
* lsm_size_tried.png (0.24 MB)
* lsm_sstable.png (0.05 MB)
* lsm_sstable全局有序.png (0.23 MB)
* lsm核心.png (0.30 MB)
* m3db_01.png (0.05 MB)
* m3db_02.png (0.06 MB)
* m3db_arch01.png (0.08 MB)
* m3db_arch02.png (0.05 MB)
* m3dbz01.png (0.11 MB)
* m3dbz02.png (0.09 MB)
* mmap_01.png (0.28 MB)
* mmap_02.png (0.29 MB)
* mmap_03.png (0.28 MB)
* mmap_04.png (0.30 MB)
* mo01.png (0.13 MB)
* mo02.png (0.08 MB)
* mo03.png (0.11 MB)
* mo04.png (0.04 MB)
* mo05.png (0.22 MB)
* mu01.png (0.13 MB)
* prome_index_01.jpg (0.11 MB)
* prome_mem_01.png (0.07 MB)
* prome_remote01.png (0.02 MB)
* prome_tsdb_01.jpg (0.03 MB)
* prome_tsdb_disk_01.png (0.06 MB)
* prome_tsdb_disk_02.png (0.08 MB)
* prome_tsdb_disk_sample.png (0.02 MB)
* prome_tsdb_disk_series.png (0.01 MB)
* prome_tsdb_disk_tombstone.png (0.03 MB)
* r01.jpg (0.05 MB)
* ranking_method.png (0.21 MB)
* tsdb_ranking_2.png (0.16 MB)
* 时序mysql.png (0.23 MB)
* 02_集群tsdb-m3db原理/
* 006_远端存储.md (0.00 MB)
* 007_m3db简介.md (0.00 MB)
* 008_m3db上手搭建.md (0.01 MB)
* 009_m3db_oom.md (0.00 MB)
* 010_m3db_总结.md (0.01 MB)
* pic/
* boolm_01.png (0.06 MB)
* boolm_02.png (0.20 MB)
* boolm_03.png (0.21 MB)
* boolm_04.png (0.13 MB)
* db_engine_tsdb_ranking.png (0.15 MB)
* gorilla_01.jpg (0.06 MB)
* gorilla_02.jpg (0.05 MB)
* gorilla_03.jpg (0.22 MB)
* gorilla_04.jpg (0.12 MB)
* gorilla_05.jpg (0.04 MB)
* index_02.png (0.01 MB)
* index_分布.png (0.03 MB)
* lsm_compact_01.png (0.19 MB)
* lsm_compact_02.png (0.22 MB)
* lsm_compact_03.png (0.21 MB)
* lsm_compact_04.png (0.29 MB)
* lsm_level_compact.jpg (0.15 MB)
* lsm_size_tried.png (0.24 MB)
* lsm_sstable.png (0.05 MB)
* lsm_sstable全局有序.png (0.23 MB)
* lsm核心.png (0.30 MB)
* m3db_01.png (0.05 MB)
* m3db_02.png (0.06 MB)
* m3db_arch01.png (0.08 MB)
* m3db_arch02.png (0.05 MB)
* m3dbz01.png (0.11 MB)
* m3dbz02.png (0.09 MB)
* mmap_01.png (0.28 MB)
* mmap_02.png (0.29 MB)
* mmap_03.png (0.28 MB)
* mmap_04.png (0.30 MB)
* mo01.png (0.13 MB)
* mo02.png (0.08 MB)
* mo03.png (0.11 MB)
* mo04.png (0.04 MB)
* mo05.png (0.22 MB)
* mu01.png (0.13 MB)
* prome_index_01.jpg (0.11 MB)
* prome_mem_01.png (0.07 MB)
* prome_remote01.png (0.02 MB)
* prome_tsdb_01.jpg (0.03 MB)
* prome_tsdb_disk_01.png (0.06 MB)
* prome_tsdb_disk_02.png (0.08 MB)
* prome_tsdb_disk_sample.png (0.02 MB)
* prome_tsdb_disk_series.png (0.01 MB)
* prome_tsdb_disk_tombstone.png (0.03 MB)
* r01.jpg (0.05 MB)
* ranking_method.png (0.21 MB)
* tsdb_ranking_2.png (0.16 MB)
* 时序mysql.png (0.23 MB)
* service/
* bloom_filter.py (0.00 MB)
* m3db_single_install.sh (0.00 MB)
* m3dbnode.service (0.00 MB)
* m3dbnode_single.yaml (0.01 MB)
* m_query.service (0.00 MB)
* m_query.yml (0.00 MB)
* prometheus.yml (0.00 MB)
* service.zip (0.01 MB)
* 03_低成本高可用存储方案/
* 04_低成本multi_remote_read方案.md (0.00 MB)
* pic/
* ha_arch.png (0.09 MB)
* k8s.png (0.14 MB)
* k8s_node.png (0.03 MB)
* k8s_obj.png (0.06 MB)
* k8s_server.png (0.03 MB)
* mo01.png (0.13 MB)
* mo02.png (0.08 MB)
* mo03.png (0.11 MB)
* mo04.png (0.04 MB)
* mo05.png (0.22 MB)
* multi_remote_read.jpg (0.11 MB)
* p_target.png (0.06 MB)
* prome_remote01.png (0.02 MB)
* pic/
* boolm_01.png (0.06 MB)
* boolm_02.png (0.20 MB)
* boolm_03.png (0.21 MB)
* boolm_04.png (0.13 MB)
* db_engine_tsdb_ranking.png (0.15 MB)
* gorilla_01.jpg (0.06 MB)
* gorilla_02.jpg (0.05 MB)
* gorilla_03.jpg (0.22 MB)
* gorilla_04.jpg (0.12 MB)
* gorilla_05.jpg (0.04 MB)
* index_02.png (0.01 MB)
* index_分布.png (0.03 MB)
* lsm_compact_01.png (0.19 MB)
* lsm_compact_02.png (0.22 MB)
* lsm_compact_03.png (0.21 MB)
* lsm_compact_04.png (0.29 MB)
* lsm_level_compact.jpg (0.15 MB)
* lsm_size_tried.png (0.24 MB)
* lsm_sstable.png (0.05 MB)
* lsm_sstable全局有序.png (0.23 MB)
* lsm核心.png (0.30 MB)
* m3db_01.png (0.05 MB)
* m3db_02.png (0.06 MB)
* m3db_arch01.png (0.08 MB)
* m3db_arch02.png (0.05 MB)
* m3dbz01.png (0.11 MB)
* m3dbz02.png (0.09 MB)
* mmap_01.png (0.28 MB)
* mmap_02.png (0.29 MB)
* mmap_03.png (0.28 MB)
* mmap_04.png (0.30 MB)
* mo01.png (0.13 MB)
* mo02.png (0.08 MB)
* mo03.png (0.11 MB)
* mo04.png (0.04 MB)
* mo05.png (0.22 MB)
* mu01.png (0.13 MB)
* prome_index_01.jpg (0.11 MB)
* prome_mem_01.png (0.07 MB)
* prome_remote01.png (0.02 MB)
* prome_tsdb_01.jpg (0.03 MB)
* prome_tsdb_disk_01.png (0.06 MB)
* prome_tsdb_disk_02.png (0.08 MB)
* prome_tsdb_disk_sample.png (0.02 MB)
* prome_tsdb_disk_series.png (0.01 MB)
* prome_tsdb_disk_tombstone.png (0.03 MB)
* r01.jpg (0.05 MB)
* ranking_method.png (0.21 MB)
* tsdb_ranking_2.png (0.16 MB)
* 时序mysql.png (0.23 MB)
* 05_高可用查询模块实战/
* 01_query_log和range_query原理.md (0.01 MB)
* 02_prometheus预聚合.md (0.01 MB)
* 03_判定高基数的依据.md (0.00 MB)
* 03_查询提速项目pre_query/
* README.md (0.01 MB)
* __init__.py
* all_prome_query
* confd/
* conf.d/
* records.yml.toml (0.00 MB)
* templates/
* records.yml.tmpl (0.00 MB)
* config.yaml (0.00 MB)
* consul_delete.py (0.00 MB)
* get_high_can.py (0.00 MB)
* images/
* arch.jpg (1.87 MB)
* heavy_query_diff.png (0.12 MB)
* init.sh (0.00 MB)
* libs.py (0.00 MB)
* nginx.conf (0.00 MB)
* ngx_prome_redirect.conf (0.00 MB)
* parse_prome_query_log.py (0.02 MB)
* prome_heavy_expr_parse.yaml (0.00 MB)
* prome_redirect.lua (0.00 MB)
* recovery_by_local_yaml.py (0.00 MB)
* recovery_heavy_metrics.sh (0.00 MB)
* requirements.txt (0.00 MB)
* to_del_record_key_file (0.00 MB)
* pic/
* g_ha.png (0.18 MB)
* get_h01.png (0.09 MB)
* h_zhi.png (0.10 MB)
* high01.png (0.08 MB)
* high02.png (0.07 MB)
* high03.png (0.07 MB)
* high04.png (0.05 MB)
* high05.png (0.02 MB)
* label_names.png (0.10 MB)
* new_query.png (0.11 MB)
* push01.png (0.16 MB)
* push02.png (0.04 MB)
* push_arch.png (0.13 MB)
* push_config.png (0.06 MB)
* push_fenxi.png (0.08 MB)
* query_range_time.png (0.09 MB)
* range01.png (0.08 MB)
* record01.png (0.03 MB)
* reload.png (0.06 MB)
* series01.png (0.05 MB)
* span_timer.png (0.17 MB)
* 06_loki介绍和优势分析/
* loki.md (0.01 MB)
* loki.png (0.15 MB)
* 目录.md (0.00 MB)
* 第1节 学习收益：冲击一线大厂offer/
* 第1节 学习收益：冲击一线大厂offer (187.86 MB), 13:00
* 第2节 全组件实战搭建调优篇/
* 01 prometheus部署和基本概念介绍 (277.25 MB), 36:02
* 02 ansible自动化部署node_exporter的使用 (549.81 MB), 37:11
* 03 黑盒探针、进程监控、中间件监控实战 (764.99 MB), 50:56
* 04 sdk打点4中数据结构和pushgateway使用 (305.25 MB), 19:56
* 05 告警实战：企业微信配置分组、抑制、静默等 (784.94 MB), 52:54
* 第3节 k8s监控实战和prometheus采集k8s原理/
* 01 10分钟使用kubeadmin安装k8s集群1.21版本 (171.25 MB), 11:11
* 02 k8s中prometheus和grafana一键部署导入大盘 (482.54 MB), 32:39
* 03 prome采集k8s底层原理和4大适配工作 (582.78 MB), 39:30
* 04 k8s监控指标讲解，到底怎么写promql监控k8s (393.67 MB), 24:45
* 第4节 高可用实战进阶：采集模块/
* 01 和运维平台-cmdb对接,服务发现和consul使用 (387.31 MB), 26:25
* 02 动手实现pushgateway 高可用 (249.34 MB), 16:04
* 03 hashmod和动态分片解决大内存和单节点问题 (387.55 MB), 25:36
* 第5节 高可用实战进阶：存储模块/
* 01 tsdb底层原理：倒排索引、压缩算法、mmap (447.69 MB), 30:20
* 02 集群tsdb实战：m3db搭建使用及问题总结 (403.64 MB), 27:15
* 03 低成本高可用存储实战：multi_remote_read (281.75 MB), 19:00
* 第6节 高可用实战进阶：查询模块/
* 01 查询提速知识：预聚合，query_log，高基数 (410.89 MB), 28:02
* 02 查询提速实战项目：提升查询速度30-100倍 (283.01 MB), 18:54
* 第7节 额外赠送篇：loki介绍/
* loki安装、原理介绍、和alertmanger整合 (452.78 MB), 30:36
* 02 prometheus源码讲解和二次开发/
* prometheus二开和源码解读文档和代码/
* 代码/
* log2metrics/
* common/
* const.go (0.00 MB)
* config/
* config.go (0.00 MB)
* consumer/
* consumer.go (0.00 MB)
* group.go (0.00 MB)
* counter/
* counter.go (0.00 MB)
* go.mod (0.00 MB)
* go.sum (0.05 MB)
* log2metrics.yml (0.00 MB)
* logjob/
* manager.go (0.00 MB)
* perjob.go (0.00 MB)
* main.go (0.00 MB)
* metrics/
* metrics.go (0.00 MB)
* reader/
* reader.go (0.00 MB)
* strategy/
* log.go (0.00 MB)
* prome_remote_read_write/
* config/
* config.go (0.00 MB)
* datasource/
* prome.go (0.00 MB)
* read.go (0.00 MB)
* write.go (0.01 MB)
* go.mod (0.00 MB)
* go.sum (0.12 MB)
* main.go (0.00 MB)
* prome_remote_read_write.yml (0.00 MB)
* 文档/
* 1.1 node_exporter主流程源码解读.md (0.01 MB)
* 1.2 node_exporter二开日志采集模块.md (0.01 MB)
* 2.1 blackbox探测源码解读.md (0.00 MB)
* 2.2 普罗采集标签替换源码解读.md (0.01 MB)
* 3.1 二次开发之改造成一对多探测探针型.md (0.01 MB)
* 4.1 监控kafka和zookeeper的jvm.md (0.00 MB)
* 4.2 导入grafana大盘和指标讲解.md (0.01 MB)
* 7.1 kube-state-metrics源码讲解.md (0.02 MB)
* 7.2 k8s-apiserver监控源码解读.md (0.02 MB)
* 7.3 prometheus中k8s服务发现源码解读.md (0.01 MB)
* 8.1 k8s监控中标签relabel的应用和原理.md (0.01 MB)
* 8.2 prometheus为k8s做的4大适配工作.md (0.00 MB)
* 11.1 prometheus-exporter管理.md (0.00 MB)
* 11.2 prometheus target管理.md (0.01 MB)
* 11.3 基于文件的服务发现模式.md (0.01 MB)
* 11.4 基于consul服务发现模式.md (0.01 MB)
* 11.5 基于http服务发现模式.md (0.01 MB)
* 11.6 监控系统在采集侧对接运维平台.md (0.00 MB)
* 12.1 降低采集资源消耗的收益和无用监控指标的判定依据.md (0.01 MB)
* 12.2 采集端高基数的现象和原因.md (0.00 MB)
* 12.3 使用relabel中的drop将对应的无用指标丢弃.md (0.00 MB)
* 13.1 分位值summary和histogram对比.md (0.01 MB)
* 13.2 histogram线性插值法源码解读.md (0.00 MB)
* 13.3 summary源码解读.md (0.01 MB)
* 14.1 时序监控和日志监控的对比，分析日志监控的核心诉求.md (0.00 MB)
* 14.2 golang实战项目log2metrics架构说明.md (0.00 MB)
* 14.3 准备工作，编写配置文件，解析配置，校验正则，设置log.md (0.01 MB)
* 14.4 日志任务增量更新管理器和具体的日志job对象.md (0.01 MB)
* 14.5 日志消费组和日志正则处理对象AnalysPoint.md (0.01 MB)
* 14.6 时序统计的结构体对象和metrics结果打点方法.md (0.01 MB)
* 14.7 编译运行，读取日志配置看图.md (0.00 MB)
* 15.1 时序数据压缩的必要和facebook-gorilla压缩算法简介.md (0.00 MB)
* 15.2 DOD压缩和相关的prometheus源码解读.md (0.01 MB)
* 15.3 XOR压缩和相关的prometheus源码解读.md (0.00 MB)
* 16.1 prometheus联邦功能源码解读和它的问题.md (0.01 MB)
* 16.2 为什么remote_read查询series比直接查询要慢很多和源码解读.md (0.01 MB)
* 16.3 prometheus5大数据查询接口.md (0.02 MB)
* 16.4 range_query和querylog源码解读.md (0.01 MB)
* 17.1 remote实战项目之设计prometheus数据源的结构.md (0.01 MB)
* 17.2 read的代码，查询series方法和QueryEngine的RangeQuery方法.md (0.05 MB)
* 17.3 write的代码编写和测试.md (0.01 MB)
* 18.1 用最近1天的内存平均使用率等出业务资源利用率报表.md (0.01 MB)
* 目录.md (0.00 MB)
* 第1节 课程简介/
* 普罗源码和二开 (202.27 MB), 12:46
* 第2节 node_exporter源码解读和二次开发/
* 1.1 node_exporter采集原理简介 (212.03 MB), 13:56
* 1.2 node_exporter二开新增自定义模块 (203.45 MB), 13:30
* 第3节 黑盒探针blackbox_exporter和普罗relabel源码解读/
* 2.1 blackbox框架源码和http探测源码解读 (277.75 MB), 19:05
* 2.2 普罗relabel address替换源码解析 (263.35 MB), 17:41
* 第4节 mysqld_exporter二次开发之改造成探针型/
* 3.1 二次开发之改造成一对多探测探针型 (345.64 MB), 23:45
* 第5节 java应用监控jvm实例/
* 4.1 监控kafka和zookeeper的jvm (240.02 MB), 15:50
* 4.2 导入grafana大盘和指标讲解 (203.69 MB), 12:27
* 第6节 prometheus监控k8s源码解读/
* 7.1 kube-state-metrics源码讲解 (346.44 MB), 22:47
* 7.2 k8s-apiserver监控源码解读 (222.61 MB), 14:18
* 7.3 普罗中k8s服务发现源码解读 (149.02 MB), 09:45
* 第7节 k8s监控中relabel应用和k8s监控总结/
* 8.1 k8s监控中标签relabel应用和原理 (277.72 MB), 18:46
* 8.2 prometheus为k8s做的4大适配工作 (22.37 MB), 05:30
* 第9节 如何降低采集资源消耗/
* 12.1 过滤采集指标依据和降低资源消耗 (308.72 MB), 17:42
* 12.2 什么是高基数 (56.14 MB), 13:05
* 12.3 标签relabel应用之drop (80.67 MB), 05:58
* 第10节 分位值作用和原理/
* 13.1 分位值summary和histogram对比 (203.63 MB), 13:21
* 13.2 histogram线性插值法源码解读 (234.33 MB), 15:48
* 13.3 summary源码解读 (170.71 MB), 11:38
* 第11节 如何使用非侵入式形式如日志接入prometheus/
* 14.1 时序监控和日志监控的对比 (137.05 MB), 10:49
* 14.2 golang实战项目log2metrics架构说明 (159.79 MB), 11:24
* 14.3 准备工作，解析配置，校验正则 (216.13 MB), 13:40
* 14.4 日志任务增量更新管理器 (245.12 MB), 16:43
* 14.5 日志消费组和正则处理对象AnalysPoint (263.50 MB), 17:43
* 14.6 时序统计的结构体对象和结果打点方法 (229.85 MB), 14:51
* 14.7 编译运行，读取日志配置看图 (271.48 MB), 17:03
* 第12节 facebook-gorilla压缩算法原理/
* 15.1 facebook-gorilla压缩算法简介 (108.35 MB), 07:24
* 15.2 DOD压缩源码解读 (206.66 MB), 13:11
* 15.3 XOR压缩源码解读 (109.08 MB), 06:51
* 第13节 prometheus核心接口源码解析/
* 16.1 联邦功能源码解读和它的问题 (150.24 MB), 10:31
* 16.2 为什么remote查询series比要慢很多 (185.05 MB), 12:51
* 16.3 prometheus5大数据查询接口 (443.83 MB), 29:51
* 16.4 range_query和querylog源码解读 (464.14 MB), 32:22
* 第14节 prometheus 适配remote实战项目/
* 17.1 remote实战项目之设计据源的结构 (152.47 MB), 10:02
* 17.2 read的代码，查询QueryEngine (293.09 MB), 19:16
* 17.3 write的代码编写和测试 (253.34 MB), 17:05
* 第15节 prometheus接口开发实战/
* 18.1 业务资源利用率报表 (253.34 MB), 17:05
* 03 kube-prometheus和prometheus-operator实战和原理介绍/
* ink8s-pod代码/
* ink8s-pod-metrics/
* Dockerfile (0.00 MB)
* deployment.yaml (0.00 MB)
* get_k8s_objs.go (0.00 MB)
* go.mod (0.00 MB)
* go.sum (0.05 MB)
* rbac.yaml (0.00 MB)
* readme.md (0.00 MB)
* serviceMonitor/
* myPod_rule.yaml (0.00 MB)
* myPod_serviceMonitor.yaml (0.00 MB)
* myPod_svc.yaml (0.00 MB)
* kube-prometheus/
* 19.1 使用k8s的sdk编写一个项目获取pod和node信息.md (0.01 MB)
* 19.2 编写dockerfile和k8s yaml.md (0.01 MB)
* 19.3 打镜像部署到k8s中，prometheus配置采集并在grafana看图.md (0.01 MB)
* 36.1 kube-prometheus项目讲解和安装部署.md (0.04 MB)
* 36.2 内置的k8s采集任务分析.md (0.02 MB)
* 36.3 grafana-dashboard看图分析.md (0.01 MB)
* 36.4 prometheus告警和预聚合分析.md (0.01 MB)
* 36.5 自定义指标接入prometheus-operator.md (0.01 MB)
* 第1节 kube-prometheus项目讲解和安装部署/
* kube-prometheus项目讲解和安装部署 (746.38 MB), 51:00
* 第2节 kube-prometheus内置的k8s采集任务分析/
* kube-prometheus内置的k8s采集任务分析 (480.71 MB), 32:24
* 第3节 kube-prometheus内置的grafana-dashboard看图分析/
* kube-prometheus内置的grafana-dashboard看图分析 (198.16 MB), 13:23
* 第4节 内置的告警和预聚合分析，6层预聚合slo原理/
* 内置的告警和预聚合分析，6层预聚合slo原理 (224.90 MB), 15:09
* 第5节 用golang写项目，使用k8s的sdk编写/
* 01 用golang写项目，使用k8s的sdk编写 (260.54 MB), 17:13
* 02 编写dockerfile和k8s yaml (156.65 MB), 10:11
* 03 打镜像部署到k8s中，采集并在grafana看图 (278.55 MB), 18:35
* 第6节 自定义指标接入prometheus-operator/
* 自定义指标接入prometheus-operator (308.72 MB), 20:30
* 04 prometheus-thanos使用和源码解读/
* thanos文档/
* 35.1 thanos项目介绍和二进制部署.md (0.01 MB)
* 35.2 thanos-sidecar源码阅读.md (0.03 MB)
* 35.3 thanos-store 源码阅读.md (0.02 MB)
* 35.4 thanos-query 源码阅读.md (0.02 MB)
* 35.5 thanos-compactor 源码阅读.md (0.02 MB)
* 35.6 thanos-rule 源码阅读.md (0.01 MB)
* 第1节 thanos项目介绍和部署/
* thanos项目介绍和部署 (416.61 MB), 27:46
* 第2节 thanos-sidecar使用和源码解读/
* thanos-sidecar使用和源码解读 (305.55 MB), 20:39
* 第3节 thanos-store 使用和源码解读/
* hanos-store 使用和源码解读 (228.81 MB), 15:40
* 第4节 thanos-query 使用和源码解读/
* thanos-query 使用和源码解读 (228.81 MB), 15:40
* 第5节 thanos-compactor 使用和源码解读/
* thanos-compactor 使用和源码解读 (179.31 MB), 11:57
* 第6节 thanos-rule 使用和源码解读/
* thanos-rule 使用和源码解读 (159.73 MB), 12:28
* 更多资料/
* ink8s-pod代码/
* ink8s-pod-metrics/
* .idea/
* .gitignore (0.00 MB)
* ink8s-pod-metrics.iml (0.00 MB)
* misc.xml (0.00 MB)
* modules.xml (0.00 MB)
* workspace.xml (0.00 MB)
* Dockerfile (0.00 MB)
* deployment.yaml (0.00 MB)
* get_k8s_objs.go (0.00 MB)
* go.mod (0.00 MB)
* go.sum (0.05 MB)
* rbac.yaml (0.00 MB)
* readme.md (0.00 MB)
* serviceMonitor/
* myPod_rule.yaml (0.00 MB)
* myPod_serviceMonitor.yaml (0.00 MB)
* myPod_svc.yaml (0.00 MB)
* sy.jpg (0.24 MB)
* kube-prometheus/
* 19.1 使用k8s的sdk编写一个项目获取pod和node信息.md (0.01 MB)
* 19.2 编写dockerfile和k8s yaml.md (0.01 MB)
* 19.3 打镜像部署到k8s中，prometheus配置采集并在grafana看图.md (0.01 MB)
* 36.1 kube-prometheus项目讲解和安装部署.md (0.04 MB)
* 36.2 内置的k8s采集任务分析.md (0.02 MB)
* 36.3 grafana-dashboard看图分析.md (0.01 MB)
* 36.4 prometheus告警和预聚合分析.md (0.01 MB)
* 36.5 自定义指标接入prometheus-operator.md (0.01 MB)
* prometheus二开和源码解读文档和代码/
* 代码/
* log2metrics/
* .idea/
* .gitignore (0.00 MB)
* log2metrics.iml (0.00 MB)
* misc.xml (0.00 MB)
* modules.xml (0.00 MB)
* workspace.xml (0.01 MB)
* common/
* const.go (0.00 MB)
* config/
* config.go (0.00 MB)
* consumer/
* consumer.go (0.00 MB)
* group.go (0.00 MB)
* counter/
* counter.go (0.00 MB)
* go.mod (0.00 MB)
* go.sum (0.05 MB)
* log2metrics.yml (0.00 MB)
* logjob/
* manager.go (0.00 MB)
* perjob.go (0.00 MB)
* main.go (0.00 MB)
* metrics/
* metrics.go (0.00 MB)
* reader/
* reader.go (0.00 MB)
* strategy/
* log.go (0.00 MB)
* prome_remote_read_write/
* .idea/
* .gitignore (0.00 MB)
* misc.xml (0.00 MB)
* modules.xml (0.00 MB)
* prome_remote_read_write.iml (0.00 MB)
* workspace.xml (0.00 MB)
* config/
* config.go (0.00 MB)
* datasource/
* prome.go (0.00 MB)
* read.go (0.00 MB)
* write.go (0.01 MB)
* go.mod (0.00 MB)
* go.sum (0.12 MB)
* main.go (0.00 MB)
* prome_remote_read_write.yml (0.00 MB)
* 文档/
* 1.1 node_exporter主流程源码解读.md (0.01 MB)
* 1.2 node_exporter二开日志采集模块.md (0.01 MB)
* 2.1 blackbox探测源码解读.md (0.00 MB)
* 2.2 普罗采集标签替换源码解读.md (0.01 MB)
* 3.1 二次开发之改造成一对多探测探针型.md (0.01 MB)
* 4.1 监控kafka和zookeeper的jvm.md (0.00 MB)
* 4.2 导入grafana大盘和指标讲解.md (0.01 MB)
* 7.1 kube-state-metrics源码讲解.md (0.02 MB)
* 7.2 k8s-apiserver监控源码解读.md (0.02 MB)
* 7.3 prometheus中k8s服务发现源码解读.md (0.01 MB)
* 8.1 k8s监控中标签relabel的应用和原理.md (0.01 MB)
* 8.2 prometheus为k8s做的4大适配工作.md (0.00 MB)
* 11.1 prometheus-exporter管理.md (0.00 MB)
* 11.2 prometheus target管理.md (0.01 MB)
* 11.3 基于文件的服务发现模式.md (0.01 MB)
* 11.4 基于consul服务发现模式.md (0.01 MB)
* 11.5 基于http服务发现模式.md (0.01 MB)
* 11.6 监控系统在采集侧对接运维平台.md (0.00 MB)
* 12.1 降低采集资源消耗的收益和无用监控指标的判定依据.md (0.01 MB)
* 12.2 采集端高基数的现象和原因.md (0.00 MB)
* 12.3 使用relabel中的drop将对应的无用指标丢弃.md (0.00 MB)
* 13.1 分位值summary和histogram对比.md (0.01 MB)
* 13.2 histogram线性插值法源码解读.md (0.00 MB)
* 13.3 summary源码解读.md (0.01 MB)
* 14.1 时序监控和日志监控的对比，分析日志监控的核心诉求.md (0.00 MB)
* 14.2 golang实战项目log2metrics架构说明.md (0.00 MB)
* 14.3 准备工作，编写配置文件，解析配置，校验正则，设置log.md (0.01 MB)
* 14.4 日志任务增量更新管理器和具体的日志job对象.md (0.01 MB)
* 14.5 日志消费组和日志正则处理对象AnalysPoint.md (0.01 MB)
* 14.6 时序统计的结构体对象和metrics结果打点方法.md (0.01 MB)
* 14.7 编译运行，读取日志配置看图.md (0.00 MB)
* 15.1 时序数据压缩的必要和facebook-gorilla压缩算法简介.md (0.00 MB)
* 15.2 DOD压缩和相关的prometheus源码解读.md (0.01 MB)
* 15.3 XOR压缩和相关的prometheus源码解读.md (0.00 MB)
* 16.1 prometheus联邦功能源码解读和它的问题.md (0.01 MB)
* 16.2 为什么remote_read查询series比直接查询要慢很多和源码解读.md (0.01 MB)
* 16.3 prometheus5大数据查询接口.md (0.02 MB)
* 16.4 range_query和querylog源码解读.md (0.01 MB)
* 17.1 remote实战项目之设计prometheus数据源的结构.md (0.01 MB)
* 17.2 read的代码，查询series方法和QueryEngine的RangeQuery方法.md (0.05 MB)
* 17.3 write的代码编写和测试.md (0.01 MB)
* 18.1 用最近1天的内存平均使用率等出业务资源利用率报表.md (0.01 MB)
* .idea/
* .gitignore (0.00 MB)
* misc.xml (0.00 MB)
* modules.xml (0.00 MB)
* workspace.xml (0.00 MB)
* 文档.iml (0.00 MB)
* 目录.md (0.00 MB)
* prometheus实战课所需软件包.tar.gz (662.39 MB)
* prometheus实战课程/
* 01_全组件实战搭建调优篇/
* 01_环境准备.md (0.00 MB)
* 001_部署node_exporter和prometheus，prometheus基础概念讲解.md (0.01 MB)
* 002_自动化部署node_exporter它的使用、部署grafana导入大盘.md (0.01 MB)
* 003_黑盒探针blackbox_exporter、进程监控process_exporter、各种中间件mysqld、redis、consul exporter使用.md (0.02 MB)
* 004_pushgateway使用和高可用.md (0.00 MB)
* 004_pushgateway打点问题及高可用实战.md (0.00 MB)
* 005_alertmanager实战.md (0.01 MB)
* pic/
* alertm_arch.png (0.06 MB)
* alertm_arch.svg (0.04 MB)
* alertm_gossip.png (0.12 MB)
* at.png (0.06 MB)
* atop.png (0.09 MB)
* blackbox探测.png (0.13 MB)
* c_hash_01.png (0.04 MB)
* c_hash_02.png (0.13 MB)
* c_hash_03.png (0.12 MB)
* c_hash_04.png (0.15 MB)
* c_hash_05.png (0.17 MB)
* c_hash_06.png (0.16 MB)
* c_hash_07.png (0.11 MB)
* ch_01.png (0.28 MB)
* ch_02.png (0.11 MB)
* consul_sd_pushgateway.png (0.09 MB)
* consul_service.png (0.06 MB)
* falcon_alert.png (0.05 MB)
* file_sd.png (0.28 MB)
* gossip02.png (0.20 MB)
* gossip.png (0.16 MB)
* grafana_dashboard商城.png (0.15 MB)
* grafana_node_exporter大盘.png (0.15 MB)
* grafana新增dashboard.png (0.02 MB)
* grafana查看网卡数据.png (0.14 MB)
* grafana添加数据源.png (0.07 MB)
* grafana表格和变量.png (0.06 MB)
* group1.png (0.08 MB)
* group2.png (0.17 MB)
* happen.png (0.02 MB)
* im_dingding.png (0.12 MB)
* inhibite02.png (0.21 MB)
* inhibite.png (0.09 MB)
* k8s服务发现.png (0.09 MB)
* m1.png (0.15 MB)
* node_exporter默认关闭的采集项.png (0.05 MB)
* node_exporter默认开启的采集项.png (0.07 MB)
* pb.png (0.18 MB)
* process_exporter.png (0.24 MB)
* prometheus_targets.png (0.02 MB)
* pull_vs_push.png (0.06 MB)
* redis_exporter.png (0.13 MB)
* s01.png (0.03 MB)
* s02.png (0.03 MB)
* s03.png (0.04 MB)
* sample.png (0.02 MB)
* target成功率.png (0.21 MB)
* transfer一致性哈希算法01.png (0.13 MB)
* transfer一致性哈希算法02.png (0.18 MB)
* 企业微信02.png (0.07 MB)
* 企业微信.png (0.06 MB)
* 动态分片.png (0.14 MB)
* 升级.png (0.01 MB)
* 即时向量.png (0.03 MB)
* 告警聚合01.png (0.21 MB)
* 回调.png (0.01 MB)
* 快速屏蔽.png (0.14 MB)
* 服务发现原理1.png (0.14 MB)
* 服务发现对比.png (0.03 MB)
* 标签.png (0.00 MB)
* 生效时间.png (0.00 MB)
* 范围向量.png (0.07 MB)
* 触发参数.png (0.01 MB)
* 触发条件.png (0.00 MB)
* 通道_im.png (0.11 MB)
* 采集端HA.png (0.17 MB)
* scripts/
* 004_pushgateway.py (0.00 MB)
* 005_alert_receive.py (0.00 MB)
* 005_alert_silence.py (0.00 MB)
* 005_alertm_send.py (0.00 MB)
* service/
* 01alertmanager.yml (0.00 MB)
* 02alertmanager.yml (0.00 MB)
* 03alertmanager.yml (0.00 MB)
* 04alertmanager.yml (0.00 MB)
* alertmanager.service (0.00 MB)
* blackbox_exporter.service (0.00 MB)
* consul.service (0.00 MB)
* dbus-org.freedesktop.nm-dispatcher.service (0.00 MB)
* init_syslog_logrotate.yaml (0.00 MB)
* logrotate.conf (0.00 MB)
* loki.service (0.00 MB)
* mysqld_exporter.service (0.00 MB)
* node_exporter.service (0.00 MB)
* process-exporter.service (0.00 MB)
* prometheus.service (0.00 MB)
* prometheus.yml (0.00 MB)
* promtail.service (0.00 MB)
* pushgateway.service (0.00 MB)
* redis_6379.service (0.00 MB)
* redis_6479.service (0.00 MB)
* redis_exporter.service (0.00 MB)
* rule.yml (0.00 MB)
* rule_01.yml (0.00 MB)
* rule_02.yml (0.00 MB)
* rule_for_wechat.yml (0.00 MB)
* service_deploy.yaml (0.00 MB)
* syslog_server.conf (0.00 MB)
* wechat.tmpl (0.00 MB)
* 02_k8s监控实战和原理/
* 01_kubeadmin安装k8s1.20.md (0.00 MB)
* 02_k8s中prometheus、grafana搭建、导入大盘.md (0.00 MB)
* 03_prometheus适配k8s采集.md (0.01 MB)
* 03_采集分析.md (0.01 MB)
* 04_k8s监控指标讲解.md (0.01 MB)
* pic/
* ha_arch.png (0.09 MB)
* k8s.png (0.14 MB)
* k8s_node.png (0.03 MB)
* k8s_obj.png (0.06 MB)
* k8s_server.png (0.03 MB)
* mo01.png (0.13 MB)
* mo02.png (0.08 MB)
* mo03.png (0.11 MB)
* mo04.png (0.04 MB)
* mo05.png (0.22 MB)
* multi_remote_read.jpg (0.11 MB)
* p_target.png (0.06 MB)
* prome_remote01.png (0.02 MB)
* service/
* grafana/
* README.md (0.00 MB)
* grafana_k8s.yaml (0.00 MB)
* m3db/
* m3db_single_install.sh (0.00 MB)
* m3dbnode.service (0.00 MB)
* m3dbnode_single.yaml (0.01 MB)
* m_query.service (0.00 MB)
* m_query.yml (0.00 MB)
* prometheus.yml (0.00 MB)
* prome_k8s_all_pod/
* README.md (0.00 MB)
* control_plane_service.yaml (0.00 MB)
* kube-stats-metrics/
* cluster-role-binding.yaml (0.00 MB)
* cluster-role.yaml (0.00 MB)
* deployment.yaml (0.00 MB)
* service-account.yaml (0.00 MB)
* service.yaml (0.00 MB)
* prometheus_config.yaml (0.01 MB)
* prometheus_storageclass.yaml (0.00 MB)
* pv.yaml (0.00 MB)
* rbac.yaml (0.00 MB)
* statsfulset.yaml (0.00 MB)
* prometheus_in_k8s.yml (0.01 MB)
* 03_高可用采集模块实战/
* 01_服务发现和运维平台对接.md (0.01 MB)
* 02_dynamic-sharding： 解决pushgateway HA问题.md (0.00 MB)
* 03_hashmod静态分片和采集端高可用.md (0.00 MB)
* pic/
* c_hash_01.png (0.04 MB)
* c_hash_02.png (0.13 MB)
* c_hash_03.png (0.12 MB)
* c_hash_04.png (0.15 MB)
* c_hash_05.png (0.17 MB)
* c_hash_06.png (0.16 MB)
* c_hash_07.png (0.11 MB)
* ch_01.png (0.28 MB)
* ch_02.png (0.11 MB)
* consul_sd_pushgateway.png (0.09 MB)
* consul_service.png (0.06 MB)
* file_sd.png (0.28 MB)
* k8s服务发现.png (0.09 MB)
* m1.png (0.15 MB)
* transfer一致性哈希算法01.png (0.13 MB)
* transfer一致性哈希算法02.png (0.18 MB)
* 服务发现原理1.png (0.14 MB)
* 服务发现对比.png (0.03 MB)
* 采集端HA.png (0.17 MB)
* scripts/
* 001阻塞请求.py (0.00 MB)
* 002轮询key.py (0.00 MB)
* 003注册service.py (0.00 MB)
* 004注销服务.py (0.00 MB)
* 005watch服务.py (0.01 MB)
* prome_shard/
* .gitattributes (0.00 MB)
* .gitignore (0.00 MB)
* README.md (0.00 MB)
* __init__.py
* ansi_new.py (0.01 MB)
* config.yaml (0.00 MB)
* consistent_hash_ring.py (0.00 MB)
* consul_work.py (0.00 MB)
* copy_file_and_reload_prome.yaml (0.00 MB)
* get_targets.py (0.01 MB)
* images/
* golang_consul_watch.png (0.05 MB)
* prome_shard_mon.png (0.17 MB)
* 采集端动态分片高可用实战.jpg (0.41 MB)
* metrics.py (0.00 MB)
* prome_shard.py (0.01 MB)
* prometheus.yml (0.00 MB)
* requirements.txt (0.00 MB)
* 多进程共享map.py (0.00 MB)
* 简化模型01.py (0.00 MB)
* prome_shard.zip (0.62 MB)
* 04_高可用存储模块实战/
* 01_tsdb底层原理/
* 001_什么是tsdb.md (0.01 MB)
* 002_lsm数据结构.md (0.01 MB)
* 002_tsdb存储模型.md (0.00 MB)
* 003_facebook_gorilla压缩算法.md (0.00 MB)
* 004_mmap原理及应用.md (0.00 MB)
* 004_prometheus本地存储解析.md (0.01 MB)
* 004_倒排索引原理.md (0.01 MB)
* 004_布隆过滤器.md (0.00 MB)
* pic/
* boolm_01.png (0.06 MB)
* boolm_02.png (0.20 MB)
* boolm_03.png (0.21 MB)
* boolm_04.png (0.13 MB)
* db_engine_tsdb_ranking.png (0.15 MB)
* gorilla_01.jpg (0.06 MB)
* gorilla_02.jpg (0.05 MB)
* gorilla_03.jpg (0.22 MB)
* gorilla_04.jpg (0.12 MB)
* gorilla_05.jpg (0.04 MB)
* index_02.png (0.01 MB)
* index_分布.png (0.03 MB)
* lsm_compact_01.png (0.19 MB)
* lsm_compact_02.png (0.22 MB)
* lsm_compact_03.png (0.21 MB)
* lsm_compact_04.png (0.29 MB)
* lsm_level_compact.jpg (0.15 MB)
* lsm_size_tried.png (0.24 MB)
* lsm_sstable.png (0.05 MB)
* lsm_sstable全局有序.png (0.23 MB)
* lsm核心.png (0.30 MB)
* m3db_01.png (0.05 MB)
* m3db_02.png (0.06 MB)
* m3db_arch01.png (0.08 MB)
* m3db_arch02.png (0.05 MB)
* m3dbz01.png (0.11 MB)
* m3dbz02.png (0.09 MB)
* mmap_01.png (0.28 MB)
* mmap_02.png (0.29 MB)
* mmap_03.png (0.28 MB)
* mmap_04.png (0.30 MB)
* mo01.png (0.13 MB)
* mo02.png (0.08 MB)
* mo03.png (0.11 MB)
* mo04.png (0.04 MB)
* mo05.png (0.22 MB)
* mu01.png (0.13 MB)
* prome_index_01.jpg (0.11 MB)
* prome_mem_01.png (0.07 MB)
* prome_remote01.png (0.02 MB)
* prome_tsdb_01.jpg (0.03 MB)
* prome_tsdb_disk_01.png (0.06 MB)
* prome_tsdb_disk_02.png (0.08 MB)
* prome_tsdb_disk_sample.png (0.02 MB)
* prome_tsdb_disk_series.png (0.01 MB)
* prome_tsdb_disk_tombstone.png (0.03 MB)
* r01.jpg (0.05 MB)
* ranking_method.png (0.21 MB)
* tsdb_ranking_2.png (0.16 MB)
* 时序mysql.png (0.23 MB)
* 02_集群tsdb-m3db原理/
* 006_远端存储.md (0.00 MB)
* 007_m3db简介.md (0.00 MB)
* 008_m3db上手搭建.md (0.01 MB)
* 009_m3db_oom.md (0.00 MB)
* 010_m3db_总结.md (0.01 MB)
* pic/
* boolm_01.png (0.06 MB)
* boolm_02.png (0.20 MB)
* boolm_03.png (0.21 MB)
* boolm_04.png (0.13 MB)
* db_engine_tsdb_ranking.png (0.15 MB)
* gorilla_01.jpg (0.06 MB)
* gorilla_02.jpg (0.05 MB)
* gorilla_03.jpg (0.22 MB)
* gorilla_04.jpg (0.12 MB)
* gorilla_05.jpg (0.04 MB)
* index_02.png (0.01 MB)
* index_分布.png (0.03 MB)
* lsm_compact_01.png (0.19 MB)
* lsm_compact_02.png (0.22 MB)
* lsm_compact_03.png (0.21 MB)
* lsm_compact_04.png (0.29 MB)
* lsm_level_compact.jpg (0.15 MB)
* lsm_size_tried.png (0.24 MB)
* lsm_sstable.png (0.05 MB)
* lsm_sstable全局有序.png (0.23 MB)
* lsm核心.png (0.30 MB)
* m3db_01.png (0.05 MB)
* m3db_02.png (0.06 MB)
* m3db_arch01.png (0.08 MB)
* m3db_arch02.png (0.05 MB)
* m3dbz01.png (0.11 MB)
* m3dbz02.png (0.09 MB)
* mmap_01.png (0.28 MB)
* mmap_02.png (0.29 MB)
* mmap_03.png (0.28 MB)
* mmap_04.png (0.30 MB)
* mo01.png (0.13 MB)
* mo02.png (0.08 MB)
* mo03.png (0.11 MB)
* mo04.png (0.04 MB)
* mo05.png (0.22 MB)
* mu01.png (0.13 MB)
* prome_index_01.jpg (0.11 MB)
* prome_mem_01.png (0.07 MB)
* prome_remote01.png (0.02 MB)
* prome_tsdb_01.jpg (0.03 MB)
* prome_tsdb_disk_01.png (0.06 MB)
* prome_tsdb_disk_02.png (0.08 MB)
* prome_tsdb_disk_sample.png (0.02 MB)
* prome_tsdb_disk_series.png (0.01 MB)
* prome_tsdb_disk_tombstone.png (0.03 MB)
* r01.jpg (0.05 MB)
* ranking_method.png (0.21 MB)
* tsdb_ranking_2.png (0.16 MB)
* 时序mysql.png (0.23 MB)
* service/
* bloom_filter.py (0.00 MB)
* m3db_single_install.sh (0.00 MB)
* m3dbnode.service (0.00 MB)
* m3dbnode_single.yaml (0.01 MB)
* m_query.service (0.00 MB)
* m_query.yml (0.00 MB)
* prometheus.yml (0.00 MB)
* service.zip (0.01 MB)
* 03_低成本高可用存储方案/
* 04_低成本multi_remote_read方案.md (0.00 MB)
* pic/
* ha_arch.png (0.09 MB)
* k8s.png (0.14 MB)
* k8s_node.png (0.03 MB)
* k8s_obj.png (0.06 MB)
* k8s_server.png (0.03 MB)
* mo01.png (0.13 MB)
* mo02.png (0.08 MB)
* mo03.png (0.11 MB)
* mo04.png (0.04 MB)
* mo05.png (0.22 MB)
* multi_remote_read.jpg (0.11 MB)
* p_target.png (0.06 MB)
* prome_remote01.png (0.02 MB)
* pic/
* boolm_01.png (0.06 MB)
* boolm_02.png (0.20 MB)
* boolm_03.png (0.21 MB)
* boolm_04.png (0.13 MB)
* db_engine_tsdb_ranking.png (0.15 MB)
* gorilla_01.jpg (0.06 MB)
* gorilla_02.jpg (0.05 MB)
* gorilla_03.jpg (0.22 MB)
* gorilla_04.jpg (0.12 MB)
* gorilla_05.jpg (0.04 MB)
* index_02.png (0.01 MB)
* index_分布.png (0.03 MB)
* lsm_compact_01.png (0.19 MB)
* lsm_compact_02.png (0.22 MB)
* lsm_compact_03.png (0.21 MB)
* lsm_compact_04.png (0.29 MB)
* lsm_level_compact.jpg (0.15 MB)
* lsm_size_tried.png (0.24 MB)
* lsm_sstable.png (0.05 MB)
* lsm_sstable全局有序.png (0.23 MB)
* lsm核心.png (0.30 MB)
* m3db_01.png (0.05 MB)
* m3db_02.png (0.06 MB)
* m3db_arch01.png (0.08 MB)
* m3db_arch02.png (0.05 MB)
* m3dbz01.png (0.11 MB)
* m3dbz02.png (0.09 MB)
* mmap_01.png (0.28 MB)
* mmap_02.png (0.29 MB)
* mmap_03.png (0.28 MB)
* mmap_04.png (0.30 MB)
* mo01.png (0.13 MB)
* mo02.png (0.08 MB)
* mo03.png (0.11 MB)
* mo04.png (0.04 MB)
* mo05.png (0.22 MB)
* mu01.png (0.13 MB)
* prome_index_01.jpg (0.11 MB)
* prome_mem_01.png (0.07 MB)
* prome_remote01.png (0.02 MB)
* prome_tsdb_01.jpg (0.03 MB)
* prome_tsdb_disk_01.png (0.06 MB)
* prome_tsdb_disk_02.png (0.08 MB)
* prome_tsdb_disk_sample.png (0.02 MB)
* prome_tsdb_disk_series.png (0.01 MB)
* prome_tsdb_disk_tombstone.png (0.03 MB)
* r01.jpg (0.05 MB)
* ranking_method.png (0.21 MB)
* tsdb_ranking_2.png (0.16 MB)
* 时序mysql.png (0.23 MB)
* 05_高可用查询模块实战/
* 01_query_log和range_query原理.md (0.01 MB)
* 02_prometheus预聚合.md (0.01 MB)
* 03_判定高基数的依据.md (0.00 MB)
* 03_查询提速项目pre_query/
* .gitattributes (0.00 MB)
* .gitignore (0.00 MB)
* README.md (0.01 MB)
* __init__.py
* all_prome_query
* confd/
* conf.d/
* records.yml.toml (0.00 MB)
* templates/
* records.yml.tmpl (0.00 MB)
* config.yaml (0.00 MB)
* consul_delete.py (0.00 MB)
* get_high_can.py (0.00 MB)
* images/
* arch.jpg (1.87 MB)
* heavy_query_diff.png (0.12 MB)
* init.sh (0.00 MB)
* libs.py (0.00 MB)
* nginx.conf (0.00 MB)
* ngx_prome_redirect.conf (0.00 MB)
* parse_prome_query_log.py (0.02 MB)
* prome_heavy_expr_parse.yaml (0.00 MB)
* prome_redirect.lua (0.00 MB)
* recovery_by_local_yaml.py (0.00 MB)
* recovery_heavy_metrics.sh (0.00 MB)
* requirements.txt (0.00 MB)
* to_del_record_key_file (0.00 MB)
* pic/
* g_ha.png (0.18 MB)
* get_h01.png (0.09 MB)
* h_zhi.png (0.10 MB)
* high01.png (0.08 MB)
* high02.png (0.07 MB)
* high03.png (0.07 MB)
* high04.png (0.05 MB)
* high05.png (0.02 MB)
* label_names.png (0.10 MB)
* new_query.png (0.11 MB)
* push01.png (0.16 MB)
* push02.png (0.04 MB)
* push_arch.png (0.13 MB)
* push_config.png (0.06 MB)
* push_fenxi.png (0.08 MB)
* query_range_time.png (0.09 MB)
* range01.png (0.08 MB)
* record01.png (0.03 MB)
* reload.png (0.06 MB)
* series01.png (0.05 MB)
* span_timer.png (0.17 MB)
* 06_loki介绍和优势分析/
* loki.md (0.01 MB)
* loki.png (0.15 MB)
* .idea/
* 299课程.iml (0.00 MB)
* .gitignore (0.00 MB)
* inspectionProfiles/
* profiles_settings.xml (0.00 MB)
* misc.xml (0.00 MB)
* modules.xml (0.00 MB)
* workspace.xml (0.01 MB)
* 目录.md (0.00 MB)
* thanos文档/
* 35.1 thanos项目介绍和二进制部署.md (0.01 MB)
* 35.2 thanos-sidecar源码阅读.md (0.03 MB)
* 35.3 thanos-store 源码阅读.md (0.02 MB)
* 35.4 thanos-query 源码阅读.md (0.02 MB)
* 35.5 thanos-compactor 源码阅读.md (0.02 MB)
* 35.6 thanos-rule 源码阅读.md (0.01 MB)
* sy.jpg (0.24 MB)
![[衡天云]爆款云服务器 低至12元/月](/hty.png)