Kubernetes 360 is part of Logz.io’s Open 360, a unified platform combining a true log analytics solution, the best Prometheus metrics monitoring, and the value of distributed tracing powered by Jaeger.

Kubernetes 360 lets R&D and engineering teams monitor and troubleshoot applications deployed in Kubernetes environments.

The platform utilizes Kubernetes’ numerous advantages for R&D and dev teams, allowing you to monitor application SLOs in a simple, efficient, and actionable manner. Kubernetes 360 offers flexibility and visibility while providing service discovery, balancing load, and allowing developer autonomy and business agility.

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To get started with Kubernetes 360, you can connect your Kubernetes data quickly and easily through Logz.io’s Telemetry Collector.

If you’ve already connected your Kubernetes data or prefer to send it manually, you’ll need an active Infrastructure Monitoring account, and ensure that your Kubernetes data is connected to Logz.io.

In addition, you’ll need to ship your cluster metrics from the following sources:

  • Node exporter (should be installed on every node).
  • CAdvisor.
  • Kube-state-metrics version 2.1 or higher.

And send the following metrics:

Metric name   Labels
*   p8s_logzio_name // Equivalent to a Cluster's name
kube_pod_status_phase   pod, uid, node, host_ip, phase, namespace
kube_pod_info   pod,namespace,p8s_logzio_name,region
container_cpu_usage_seconds_total   pod, region, topology_kubernetes_io_region, container
container_memory_working_set_bytes   pod, container, resource
kube_pod_container_resource_limits   pod
kube_pod_container_info   pod
container_network_transmit_bytes_total   pod
container_network_receive_bytes_total   pod
kube_pod_created   pod
kube_pod_owner   pod, owner_kind, owner_name
kube_pod_container_status_restarts_total   pod
kube_pod_status_reason   pod, reason
kube_pod_container_status_waiting_reason   pod, reason
node_cpu_seconds_total   instance, mode
node_memory_MemAvailable_bytes   instance
node_memory_MemTotal_bytes   instance
kube_node_role   node,role
kube_node_status_condition   node, status, condition
kube_node_created   node
node_filesystem_avail_bytes   instance
node_filesystem_size_bytes   instance
kube_node_status_allocatable   resource, resource
kube_node_labels   logzio_p8s_name
kube_replicaset_owner   owner_kind, owner_name,replicaset
kube_deployment_created   deployment
kube_deployment_status_condition   deployment,status

Once everything is up and running, you can view your data on the Kubernetes 360 application.

Kubernetes 360 application

Kubernetes 360 application provides a quick overview of your current deployments and nodes.

You can switch your view to focus on Deployments or Nodes using the buttons at the top right.

The deployments view includes cards representing the different deployments, a quick overview of the deployment’s average CPU and memory, and a rundown of the pods’ status. You can quickly identify whether pods are failing, if they’re consuming a high amount of CPU, memory, if they had multiple restarts, and the number of log error rates inside. The pods’ colors indicate their current status, when red dots indicate an issue with this pod.

deployments card

The node view includes a summary of each node’s physical CPU, memory, and disk. It also has a rundown of the inner pods’ status similar to the deployments view, including how many pods are failing, whether they’re using a high CPU or memory, the number of restarts, and the log error rate.

deployments card

Click on the cards or the elements inside them to get more information through the Quick view menu.

Customize your application

You can change and adjust Kubernetes 360 application to match your monitoring and troubleshooting needs. To help you get started, we’ll break down the different options, how you can access them, and how they can help you and your team.

Dashboard breakdown


Choose which cluster you want to review. The dropdown menu includes all clusters in your Kubernetes account, bundled under their respective accounts.


Environments with many users, teams, or projects use a namespace to bundle relevant clusters and nodes. This filter allows you to focus on all elements inside a specific namespace.

Auto refresh

Your Kubernetes 360 application is set to auto refresh every 60 seconds to provide you with the most recent data. Hover over the refresh button to see when the data was last updated.

Click on the button to stop the auto refresh. This allows you to investigate an issue or focus on your Kubernetes environment’s current state. Click on the button again to turn auto refresh on.

autorefresh button

Change your metrics view

By default, Kubernetes 360 provides an overview of your current environment. Use the bottom menu to focus on different metrics according to your monitoring needs:

  • Status - Understand which pods are running, failing, pending, or which pods succeeded.
  • CPU - View CPU consumtions by percentage: 0-50%, 50%-80%, 80%-100%, or over 100%.
  • Memory - Know how much memory each pod uses: 0-50%, 50%-80%, 80%-100%, or over 100%.
  • Restarts - Get a numeric overview of how many restarts occurred in each pod: 0, 1-10, 11-20, or over 20 restarts.
  • Log Error Rate - Analyze the percentage of log errors that occurred and how many pods were affected. How do we calculate the log error rate?

Quick view

Click on a deployment, node, or pod to open the quick view menu and get more information about each element. The menu allows you to investigate and understand what’s happening inside your Kubernetes environment by adding more helpful information.

Deployment quick view

A deployment quick view includes the following fields:

  • Name - The name of the deployment you’re focusing on.
  • Status - An indicator of the deployment’s status. It can be True, False, or Unknown.
  • Cluster - The cluster that this deployment is a part of.
  • Region- Your deployment’s region.
  • Namespace - The deployment’s unique namespace.
  • Uptime - The duration of how long this deployment has been running.
  • CPU - Amount of CPU used by this deployment. If the CPU is not capped, you’ll see an indicator stating there’s no limit.
  • Memory - An average calculation of how much memory this deployment uses.
  • Disk - The amount of disk space taken up by this node.

The deployment quick view menu includes the related pods, and you can see their status, the number of containers they’re in, and how much CPU and memory they’re using.

Quick menu Overview

Node quick view

A node quick view menu includes the following fields:

  • Name - The name of the node you’re focusing on.
  • Role - Master or worker.
  • Status - Indicates whether that condition is applicable, with possible values True, False, or Unknown.
  • Cluster - The cluster to which this node belongs.
  • Region - The node’s region.
  • Uptime - The number of hours this node has been running.
  • CPU - A percentile average of how much CPU has been used.
  • Memory - An average percentage of how much memory was consumed.
  • Disk - The amount of disk space taken up by this node, and how much is left.

The node quick view menu also includes a list of the pods related to it. The list indicates each pod’s status, the number of containers they’re in, and how much CPU and memory they use.

Node menu Overview

Pod quick view

Click on a pod to access its quick view menu and gain access to this additional information:

  • Name - The name of the pod you’re focusing on.
  • Status - Indicates whether that condition is applicable, with possible values True, False, or Unknown.
  • Node - The node that this pod is a part of.
  • Deployment - The deployment related to this pod.
  • Cluster - The cluster in which this pod resided.
  • Containers number - Number of containers inside the pod.
  • Region - This pod’s region.
  • Namespace - The pod’s unique namespace.
  • Uptime - The duration of how long this pod has been up and running.
  • Restarts - The number of restarts in this pod.
  • CPU - A percentile average of how much CPU has been used.
  • Memory - An average percentage of how much memory was consumed.

Pod menu Overview

Investigate through quick view

See Metrics

Whether you’re viewing a deployment, node, or pod, you can easily investigate the different issues you might encounter.

Each quick view menu contains the View Metrics button, allowing you to view the relevant information in a Grafana application. This can provide a focused overview of the chosen element, allowing you to pinpoint what happened and when it started quickly.

See Logs

Node and pod views include the See Logs button, which opens an OpenSearch Dashboard screen with the relevant query to display the log information.

If you’ve set up your Kubernetes account manually, you might get an empty query with no results. In this case, you can use a custom filter to view all related logs.

Click on Add filter at the top of the screen. The fields vary according to your chosen view; add kubernetes.host to the field to view Node related logs. To view Pod related logs, add kubernetes.pod_name to the field.

Next, choose the operator. For example, you can select exists to view all of the related logs.


To re-focus your view, click on the Locate button at the top of the quick view menu. This will scroll back to the specific deployment, node, or pod you’re investigating.

Locate button

Logs tab

Nodes and pods quick view menu has an additional Logs tab that contains a table with all of the logs related to the chosen node or pod. The table includes the total number of logs, the time they were ingested, the log level, and its message.

Logs inside nodes

You can sort the table by clicking on each header: Time, Log level, or Message. Click on the same header again to change your view to ascending/descending.

Additional information

Calculating Log error rate

To calculate percentage error, we take the percentage of errors in the last 15 minutes and the percentage of errors in the last 2 hours:

Errors in the last 15 minutes <= Amount of errors in the last 2 hours

For example, if in the last 15 minutes there were 10 log errors out of 200 total logs, it means that there’s a total of 5% errors:

10/200 * 100 = 5%

And if in the last 2 hours there were 15 log errors out of 800 total logs, the percentage of errors will be 1.8%:

15/800 * 100 = 1.8%

So the log error rate you’ll see will be 177.7%, based on the following formula:

(5/1.8 * 100) - 100 = 177.7%

Additional examples:

  • Last 15 minutes = 5 error logs out of 50 total logs = 5/50 * 100 = 10%
  • Last 2 hours = 6 error logs out of 800 total logs = 6/800 * 100 = 0.75%
  • Error rate = (10/0.75 * 100) - 100 = 1233.3%


  • Last 15 minutes = 2 error logs out of 100 total logs = 2/100 * 100 = 2%
  • Last 2 hours = 2 error logs out of 800 total logs = 2/800 * 100 = 0.25%
  • Error rate = (2/0.25 * 100) - 100 = 700%
Additional resources
  • Read more about Logz.io’s Kubernetes 360 platform.