Vmware Vsphere
Ship your Vmware Vsphere Metrics via Telegraf to your Logit.io Stack
Follow the steps below to send your observability data to Logit.io
Metrics
Configure Telegraf to ship Vmware Vsphere metrics to your Logit.io stacks via Logstash.
Install Integration
Install Telegraf
This integration allows you to configure a Telegraf agent to send your metrics, in multiple formats, to Logit.io.
Choose the installation method for your operating system:
When you paste the command below into Powershell it will download the Telegraf zip file.
Once that is complete, press Enter again and the zip file will be extracted into C:\Program Files\InfluxData\telegraf\telegraf-1.31.2
.
wget https://dl.influxdata.com/telegraf/releases/telegraf-1.31.2_windows_amd64.zip -UseBasicParsing -OutFile telegraf-1.31.2_windows_amd64.zip
Expand-Archive .\telegraf-1.31.2_windows_amd64.zip -DestinationPath 'C:\Program Files\InfluxData\telegraf'
Configure the Telegraf input plugin
The configuration file below is pre-configured to scrape the system metrics from your hosts, add the following code to the configuration file /etc/telegraf/telegraf.conf
from the previous step.
# Read metrics from one or many vCenters
[[inputs.vsphere]]
## List of vCenter URLs to be monitored. These three lines must be uncommented
## and edited for the plugin to work.
vcenters = [ "https://vcenter.local/sdk" ]
username = "[email protected]"
password = "secret"
## VMs
## Typical VM metrics (if omitted or empty, all metrics are collected)
# vm_include = [ "/*/vm/**"] # Inventory path to VMs to collect (by default all are collected)
# vm_exclude = [] # Inventory paths to exclude
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",
]
# vm_metric_exclude = [] ## Nothing is excluded by default
# vm_instances = true ## true by default
## Hosts
## Typical host metrics (if omitted or empty, all metrics are collected)
# host_include = [ "/*/host/**"] # Inventory path to hosts to collect (by default all are collected)
# host_exclude [] # Inventory paths to exclude
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",
]
## Collect IP addresses? Valid values are "ipv4" and "ipv6"
# ip_addresses = ["ipv6", "ipv4" ]
# host_metric_exclude = [] ## Nothing excluded by default
# host_instances = true ## true by default
## Clusters
# cluster_include = [ "/*/host/**"] # Inventory path to clusters to collect (by default all are collected)
# cluster_exclude = [] # Inventory paths to exclude
# cluster_metric_include = [] ## if omitted or empty, all metrics are collected
# cluster_metric_exclude = [] ## Nothing excluded by default
# cluster_instances = false ## false by default
## Resource Pools
# resource_pool_include = [ "/*/host/**"] # Inventory path to resource pools to collect (by default all are collected)
# resource_pool_exclude = [] # Inventory paths to exclude
# resource_pool_metric_include = [] ## if omitted or empty, all metrics are collected
# resource_pool_metric_exclude = [] ## Nothing excluded by default
# resource_pool_instances = false ## false by default
## Datastores
# datastore_include = [ "/*/datastore/**"] # Inventory path to datastores to collect (by default all are collected)
# datastore_exclude = [] # Inventory paths to exclude
# datastore_metric_include = [] ## if omitted or empty, all metrics are collected
# datastore_metric_exclude = [] ## Nothing excluded by default
# datastore_instances = false ## false by default
## Datacenters
# datacenter_include = [ "/*/host/**"] # Inventory path to clusters to collect (by default all are collected)
# datacenter_exclude = [] # Inventory paths to exclude
datacenter_metric_include = [] ## if omitted or empty, all metrics are collected
datacenter_metric_exclude = [ "*" ] ## Datacenters are not collected by default.
# datacenter_instances = false ## false by default
## VSAN
# vsan_metric_include = [] ## if omitted or empty, all metrics are collected
# vsan_metric_exclude = [ "*" ] ## vSAN are not collected by default.
## Whether to skip verifying vSAN metrics against the ones from GetSupportedEntityTypes API.
# vsan_metric_skip_verify = false ## false by default.
## Plugin Settings
## separator character to use for measurement and field names (default: "_")
# separator = "_"
## number of objects to retrieve per query for realtime resources (vms and hosts)
## set to 64 for vCenter 5.5 and 6.0 (default: 256)
# max_query_objects = 256
## number of metrics to retrieve per query for non-realtime resources (clusters and datastores)
## set to 64 for vCenter 5.5 and 6.0 (default: 256)
# max_query_metrics = 256
## number of go routines to use for collection and discovery of objects and metrics
# collect_concurrency = 1
# discover_concurrency = 1
## the interval before (re)discovering objects subject to metrics collection (default: 300s)
# object_discovery_interval = "300s"
## timeout applies to any of the api request made to vcenter
# timeout = "60s"
## When set to true, all samples are sent as integers. This makes the output
## data types backwards compatible with Telegraf 1.9 or lower. Normally all
## samples from vCenter, with the exception of percentages, are integer
## values, but under some conditions, some averaging takes place internally in
## the plugin. Setting this flag to "false" will send values as floats to
## preserve the full precision when averaging takes place.
# use_int_samples = true
## Custom attributes from vCenter can be very useful for queries in order to slice the
## metrics along different dimension and for forming ad-hoc relationships. They are disabled
## by default, since they can add a considerable amount of tags to the resulting metrics. To
## enable, simply set custom_attribute_exclude to [] (empty set) and use custom_attribute_include
## to select the attributes you want to include.
## By default, since they can add a considerable amount of tags to the resulting metrics. To
## enable, simply set custom_attribute_exclude to [] (empty set) and use custom_attribute_include
## to select the attributes you want to include.
# custom_attribute_include = []
# custom_attribute_exclude = ["*"]
## The number of vSphere 5 minute metric collection cycles to look back for non-realtime metrics. In
## some versions (6.7, 7.0 and possible more), certain metrics, such as cluster metrics, may be reported
## with a significant delay (>30min). If this happens, try increasing this number. Please note that increasing
## it too much may cause performance issues.
# metric_lookback = 3
## Optional SSL Config
# ssl_ca = "/path/to/cafile"
# ssl_cert = "/path/to/certfile"
# ssl_key = "/path/to/keyfile"
## Use SSL but skip chain & host verification
# insecure_skip_verify = false
## The Historical Interval value must match EXACTLY the interval in the daily
# "Interval Duration" found on the VCenter server under Configure > General > Statistics > Statistic intervals
# historical_interval = "5m"
## Specifies plugin behavior regarding disconnected servers
## Available choices :
## - error: telegraf will return an error on startup if one the servers is unreachable
## - ignore: telegraf will ignore unreachable servers on both startup and gather
# disconnected_servers_behavior = "error"
Read more about how to configure data scraping and configuration options for Vmware Vsphere (opens in a new tab)
Configure the output plugin
Once you have generated the configuration file, you need to set up the output plug-in to allow Telegraf to transmit your data to Logit.io in Prometheus format. This can be accomplished by incorporating the following code into your configuration file:
[[outputs.http]]
url = "https://@metricsUsername:@metricsPassword@@metrics_id-vm.logit.io:@vmAgentPort/api/v1/write"
data_format = "prometheusremotewrite"
[outputs.http.headers]
Content-Type = "application/x-protobuf"
Content-Encoding = "snappy"
Start Telegraf
From the location where Telegraf was installed (C:\Program Files\InfluxData\telegraf\telegraf-1.31.2
) run the program
providing the chosen configuration file as a parameter:
.\telegraf.exe --config telegraf-demo.conf
Once Telegraf is running you should see output similar to the following, which confirms the inputs, output and basic configuration the application has been started with:
View your metrics
Data should now have been sent to your Stack.
View My DataIf you don't see take a look at How to diagnose no data in Stack below for how to diagnose common issues.
How to diagnose no data in Stack
If you don't see data appearing in your stack after following this integration, take a look at the troubleshooting guide for steps to diagnose and resolve the problem or contact our support team and we'll be happy to assist.
Telegraf Vmware Vsphere Overview
To efficiently monitor and analyze VMware vSphere metrics across multiple systems, it's crucial to implement a robust and effective metrics management solution. Telegraf, an open-source server agent used for collecting and sending telemetry data, is ideally suited for this task. It can gather vSphere metrics from a wide variety of sources, such as operational vSphere environments, databases, and other relevant applications.
Telegraf provides a comprehensive range of input plugins, enabling users to collect metrics from different sources like CPU usage, memory utilization, network traffic, and more, all of which are vital for understanding vSphere performance. To store and analyze these collected metrics, organizations can utilize Prometheus, an open-source monitoring and alerting tool celebrated for its flexible querying language and strong data visualization capabilities.
To transfer vSphere metrics from Telegraf to Prometheus, organizations need to configure Telegraf to output metrics in the Prometheus format, and then set up Prometheus to scrape these metrics from the Telegraf server. This process involves configuring Telegraf to collect vSphere metrics, outputting them in the Prometheus format, setting up Prometheus to retrieve these metrics from the Telegraf server, and then interpreting the data visually using Prometheus's robust querying and graphical visualization tools.
After the successful integration of the metrics into Prometheus, further analysis and visualization can be carried out using Grafana. Grafana, a top-tier open-source platform known for its monitoring and observability capabilities, is fully compatible with Prometheus. It allows users to design dynamic, interactive dashboards for an in-depth exploration of the metrics data, delivering a comprehensive understanding of performance trends and potential hardware issues in the vSphere environment.
If you need any further assistance with shipping your log data to Logit.io we're here to help you get started. Feel free to get in contact with our support team by sending us a message via live chat & we'll be happy to assist.