目录
输入和输出集成概述
VMware vSphere Telegraf 插件提供了一种从 VMware vCenter 服务器收集指标的方法,从而可以对 vSphere 环境中的虚拟资源进行全面监控和管理。
MongoDB Telegraf 插件使用户能够将指标发送到 MongoDB 数据库,自动管理时序集合。
集成详情
VMware vSphere
此插件连接到 VMware vSphere 服务器以收集来自虚拟环境的各种指标,从而实现对虚拟资源的高效监控和管理。它与 vSphere API 接口,以收集关于集群、主机、资源池、虚拟机、数据存储和 vSAN 实体的统计信息,并以适合分析和可视化的格式呈现它们。该插件对于管理基于 VMware 的基础设施的管理员尤其有价值,因为它有助于实时跟踪系统性能、资源使用情况和操作问题。通过聚合来自多个来源的数据,该插件使用户能够获得洞察力,从而有助于就资源分配、故障排除和确保最佳系统性能做出明智的决策。此外,对密钥存储集成的支持允许安全处理敏感凭据,从而促进安全和合规性评估方面的最佳实践。
MongoDB
此插件将指标发送到 MongoDB,并与其时序功能无缝集成,从而允许在时序集合尚不存在时自动创建为时序集合。它需要 MongoDB 5.0 或更高版本才能使用时序集合功能,这对于高效存储和查询基于时间的数据至关重要。此插件通过确保所有相关指标都正确存储和组织在 MongoDB 中,从而增强了监控功能,为用户提供了利用 MongoDB 强大的查询和聚合功能进行时序分析的能力。
配置
VMware vSphere
[[inputs.vsphere]]
vcenters = [ "https://vcenter.local/sdk" ]
username = "[email protected]"
password = "secret"
vm_metric_include = [
"cpu.demand.average",
"cpu.idle.summation",
"cpu.latency.average",
"cpu.readiness.average",
"cpu.ready.summation",
"cpu.run.summation",
"cpu.usagemhz.average",
"cpu.used.summation",
"cpu.wait.summation",
"mem.active.average",
"mem.granted.average",
"mem.latency.average",
"mem.swapin.average",
"mem.swapinRate.average",
"mem.swapout.average",
"mem.swapoutRate.average",
"mem.usage.average",
"mem.vmmemctl.average",
"net.bytesRx.average",
"net.bytesTx.average",
"net.droppedRx.summation",
"net.droppedTx.summation",
"net.usage.average",
"power.power.average",
"virtualDisk.numberReadAveraged.average",
"virtualDisk.numberWriteAveraged.average",
"virtualDisk.read.average",
"virtualDisk.readOIO.latest",
"virtualDisk.throughput.usage.average",
"virtualDisk.totalReadLatency.average",
"virtualDisk.totalWriteLatency.average",
"virtualDisk.write.average",
"virtualDisk.writeOIO.latest",
"sys.uptime.latest",
]
host_metric_include = [
"cpu.coreUtilization.average",
"cpu.costop.summation",
"cpu.demand.average",
"cpu.idle.summation",
"cpu.latency.average",
"cpu.readiness.average",
"cpu.ready.summation",
"cpu.swapwait.summation",
"cpu.usage.average",
"cpu.usagemhz.average",
"cpu.used.summation",
"cpu.utilization.average",
"cpu.wait.summation",
"disk.deviceReadLatency.average",
"disk.deviceWriteLatency.average",
"disk.kernelReadLatency.average",
"disk.kernelWriteLatency.average",
"disk.numberReadAveraged.average",
"disk.numberWriteAveraged.average",
"disk.read.average",
"disk.totalReadLatency.average",
"disk.totalWriteLatency.average",
"disk.write.average",
"mem.active.average",
"mem.latency.average",
"mem.state.latest",
"mem.swapin.average",
"mem.swapinRate.average",
"mem.swapout.average",
"mem.swapoutRate.average",
"mem.totalCapacity.average",
"mem.usage.average",
"mem.vmmemctl.average",
"net.bytesRx.average",
"net.bytesTx.average",
"net.droppedRx.summation",
"net.droppedTx.summation",
"net.errorsRx.summation",
"net.errorsTx.summation",
"net.usage.average",
"power.power.average",
"storageAdapter.numberReadAveraged.average",
"storageAdapter.numberWriteAveraged.average",
"storageAdapter.read.average",
"storageAdapter.write.average",
"sys.uptime.latest",
]
datacenter_metric_include = [] ## if omitted or empty, all metrics are collected
datacenter_metric_exclude = [ "*" ] ## Datacenters are not collected by default.
vsan_metric_include = [] ## if omitted or empty, all metrics are collected
vsan_metric_exclude = [ "*" ] ## vSAN are not collected by default.
separator = "_"
max_query_objects = 256
max_query_metrics = 256
collect_concurrency = 1
discover_concurrency = 1
object_discovery_interval = "300s"
timeout = "60s"
use_int_samples = true
custom_attribute_include = []
custom_attribute_exclude = ["*"]
metric_lookback = 3
ssl_ca = "/path/to/cafile"
ssl_cert = "/path/to/certfile"
ssl_key = "/path/to/keyfile"
insecure_skip_verify = false
historical_interval = "5m"
disconnected_servers_behavior = "error"
use_system_proxy = true
http_proxy_url = ""
MongoDB
[[outputs.mongodb]]
# connection string examples for mongodb
dsn = "mongodb://localhost:27017"
# dsn = "mongodb://mongod1:27017,mongod2:27017,mongod3:27017/admin&replicaSet=myReplSet&w=1"
# overrides serverSelectionTimeoutMS in dsn if set
# timeout = "30s"
# default authentication, optional
# authentication = "NONE"
# for SCRAM-SHA-256 authentication
# authentication = "SCRAM"
# username = "root"
# password = "***"
# for x509 certificate authentication
# authentication = "X509"
# tls_ca = "ca.pem"
# tls_key = "client.pem"
# # tls_key_pwd = "changeme" # required for encrypted tls_key
# insecure_skip_verify = false
# database to store measurements and time series collections
# database = "telegraf"
# granularity can be seconds, minutes, or hours.
# configuring this value will be based on your input collection frequency.
# see https://docs.mongodb.com/manual/core/timeseries-collections/#create-a-time-series-collection
# granularity = "seconds"
# optionally set a TTL to automatically expire documents from the measurement collections.
# ttl = "360h"
输入和输出集成示例
VMware vSphere
-
动态资源分配:利用此插件监控虚拟机群的资源使用情况,并根据性能指标自动调整资源分配。此场景可能涉及根据从 vSphere API 收集的 CPU 和内存使用率指标实时触发扩展操作,从而确保最佳性能和成本效益。
-
容量规划和预测:利用从 vSphere 收集的历史指标进行容量规划。分析 CPU、内存和存储使用率随时间变化的趋势,有助于管理员预测何时需要额外资源,从而避免中断并确保虚拟基础设施能够应对增长。
-
自动化告警和事件响应:将此插件与告警工具集成,以根据收集的指标设置自动通知。例如,如果主机上的 CPU 使用率超过指定阈值,则可能会触发告警并自动启动预定义的补救步骤,例如将虚拟机迁移到利用率较低的主机。
-
跨集群性能基准测试:使用收集的指标比较不同 vCenter 中集群的性能。此基准测试提供了关于哪些集群配置产生最佳资源效率的见解,并可以指导未来的基础设施增强。
MongoDB
-
IoT 设备动态日志记录到 MongoDB:利用此插件实时收集和存储来自 IoT 设备群的指标。通过将设备日志直接发送到 MongoDB,您可以创建一个集中式数据库,该数据库允许轻松访问和查询健康指标和性能数据,从而能够基于历史趋势进行主动维护和故障排除。
-
Web 流量时序分析:使用 MongoDB Telegraf 插件收集和分析随时间变化的 Web 流量指标。此应用可以帮助您了解高峰使用时间、用户交互和行为模式,从而指导营销策略和基础设施扩展决策,以改善用户体验。
-
自动化监控和告警系统:将 MongoDB 插件集成到跟踪应用程序性能指标的自动化监控系统中。借助时序集合,您可以根据特定阈值设置告警,使您的团队能够在潜在问题影响用户之前做出响应。这种主动管理可以提高服务可靠性和整体性能。
-
指标存储中的数据保留和 TTL 管理:利用 MongoDB 集合中文档的 TTL 功能自动过期过时的指标。这对于仅相关最近性能数据的环境尤其有用,可以防止您的 MongoDB 数据库因旧指标而变得混乱,并确保高效的数据管理。
反馈
感谢您成为我们社区的一份子!如果您有任何一般性反馈或在这些页面上发现任何错误,我们欢迎并鼓励您提出意见。请在 InfluxDB 社区 Slack 中提交您的反馈。