VMware vSphere and Nebius Cloud Monitoring Integration

Input and output integration overview

The VMware vSphere Telegraf plugin provides a means to collect metrics from VMware vCenter servers, allowing for comprehensive monitoring and management of virtual resources in a vSphere environment.

This plugin allows users to effortlessly send aggregated metrics to Nebius Cloud Monitoring, leveraging the cloud’s monitoring solutions.

Integration details

VMware vSphere

This plugin connects to VMware vSphere servers to gather a variety of metrics from virtual environments, enabling efficient monitoring and management of virtual resources. It interfaces with the vSphere API to collect statistics regarding clusters, hosts, resource pools, VMs, datastores, and vSAN entities, presenting them in a format suitable for analysis and visualization. The plugin is particularly valuable for administrators who manage VMware-based infrastructures, as it helps to track system performance, resource usage, and operational issues in real-time. By aggregating data from multiple sources, the plugin empowers users with insights that facilitate informed decision-making regarding resource allocation, troubleshooting, and ensuring optimal system performance. Additionally, the support for secret-store integration allows secure handling of sensitive credentials, promoting best practices in security and compliance assessments.

Nebius Cloud Monitoring

The Nebius Cloud Monitoring plugin serves as an intermediary to send custom metrics to the Nebius Cloud Monitoring service. It is designed specifically to facilitate the monitoring of applications and services running within the Nebius ecosystem. This plugin is especially useful for users of the Nebius Cloud Platform who need to leverage cloud-based monitoring capabilities without significant configuration overhead. The plugin’s integration relies on Google Cloud metadata, allowing it to automatically fetch the necessary authentication credentials from the Compute instance it operates within. Key technical considerations include the management of reserved labels to ensure metrics are recorded correctly without conflicts.

Configuration

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 = ""

Nebius Cloud Monitoring

[[outputs.nebius_cloud_monitoring]]
  ## Timeout for HTTP writes.
  # timeout = "20s"

  ## Nebius.Cloud monitoring API endpoint. Normally should not be changed
  # endpoint = "https://monitoring.api.il.nebius.cloud/monitoring/v2/data/write"

Input and output integration examples

VMware vSphere

1. Dynamic Resource Allocation: Utilize this plugin to monitor resource usage across a fleet of VMs and automatically adjust resource allocations based on performance metrics. This scenario could involve triggering scaling actions in real time based on CPU and memory usage metrics collected from the vSphere API, ensuring optimal performance and cost-efficiency.

2. Capacity Planning and Forecasting: Leverage the historical metrics gathered from vSphere to conduct capacity planning. Analyzing the trends of CPU, memory, and storage usage over time helps administrators anticipate when additional resources will be needed, avoiding outages and ensuring that the virtual infrastructure can handle growth.

3. Automated Alerting and Incident Response: Integrate this plugin with alerting tools to set up automated notifications based on the metrics gathered. For example, if the CPU usage on a host exceeds a specified threshold, it could trigger alerts and automatically initiate predefined remediation steps, such as migrating VMs to less utilized hosts.

4. Performance Benchmarking Across Clusters: Use the metrics collected to compare the performance of clusters in different vCenters. This benchmarking provides insights into which cluster configurations yield the best resource efficiency and can guide future infrastructure enhancements.

Nebius Cloud Monitoring

1. Dynamic Application Monitoring: Integrate this plugin with your application to continuously send metrics related to resource usage, such as CPU and memory utilization, to Nebius Cloud Monitoring. By doing so, you can gain insights into the performance of your application, allowing for adjustments in real-time based on the metrics received.

2. Incident Response Automation: Use the Nebius Cloud Monitoring plugin to automatically send alerts and metrics when certain thresholds are reached. For instance, if a particular service’s uptime drops below a certain percentage, the plugin can be configured to report this directly to the monitoring service, enabling quicker incident response and resolution.

3. Comparative Service Analysis: Set up the plugin to send metrics from multiple cloud instances running different versions of the same application to Nebius Cloud Monitoring. This approach allows for a comparative analysis of resource usage and performance, helping teams determine which version performs best under similar workloads.

4. Aggregated Metrics Dashboard: Use this plugin to create a centralized dashboard displaying metrics from various services across your cloud instances. By aggregating different application metrics into one interface, stakeholders can assess the overall health and performance of their cloud environment easily.

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