Monitoring a VMware vCenter cluster with the Panopta OnSight


We have recently finished updating the Panopta OnSight so it can natively integrate with a vCenter cluster,  making monitoring a VMware vCenter cluster simple and easy. Now, by providing some basic information to the OnSight, Panopta can discover all the hosts, clusters, datastores, and virtual machines you have running in that environment and immediately begin pulling default metrics for those instances. This also allows for quick and easy onboarding, making it ideal for teams who need to pull additional, relevant metrics about the health of their hosts and virtual machines.

Monitoring a VMware vCenter Cluster with the Panopta OnSight

 To start with this integration, you’ll need to provide the Panopta OnSight with some basic log-in information so vCenter can authenticate the OnSight, giving it read-only access to your environment. This will include a username, password, IP address, and a few others to verify that you have securely given the OnSight access. 

Once the OnSight has access, it can begin making API calls to your vCenter cluster, pulling all of your instances running on that vCenter cluster into Panopta. After initial onboarding, the OnSight can begin to collect metrics on the health of your host, virtual machines, and datastores running within the cluster. 

For more information on how to set up this integration, contact support@panopta.com or check out the Panopta Knowledge Hub.

How can this help your team monitor more effectively?

In addition to the easy setup and streamlined onboarding for instances running on a vCenter cluster, this can help your team better identify the relationships and dependencies between the virtual machines running in your environment. By drawing these lines, and understanding the relationships between your deployments, teams can find correlations between incidents and the way they relate to different parts of a team’s infrastructure. 

This native integration also provides a lot of opportunities for Panopta to create more valuable features that teams can use to find a higher level of correlation. As we continue to expand our toolset, this is just one of the steps towards a more robust monitoring service. 

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