"We receive all key indicators at a glance and no longer have to gather the information in various systems" states one of our customer’s after using Performance Analyzer for more than a year to monitor his VMware environment.

As Performance Analyzer comes packed with dozens of dashboards for different purposes and can be enhanced to hundreds of different dashboards, it is important to classify these.

  • Status dashboards: Show my up and running VMs and Services. Are some down?
  • Statistical dashboards: How many systems have been deployed lately? What pCPU/vCPU ratio do we have?
  • Planning dashboards: When to purchase new hardware, deploy new VMs? How many VMs can still be deployed without risking performance bottlenecks?
  • Redundancy dashboards: Are my systems utilized in an optimal way, but I can still lose 50% of the hosts?
  • Performance dashboards: What is the current utilization of my systems? Any bottleneck visible based on real-time data?

All of these can visualize different components in your datacenter, starting from the physical hardware to the actual service within the guest OS.

Depending on the type of dashboard and the type of data, you may want to group and rotate between them. 

Maybe you want to put them on a big screen in your support department?

Btw. you can test the software without any risk. 30 day free trial:

Download Performance Analyzer

Think about a multi-tenant setup of Performance Analyzer and you want to rotate between different customers (tenants) and their environments.

pulse of your virtual machines

In any case, we got you covered.

We chose the fantastic Open Source project Grafana for the visualization of our collected metrics. That choice has many positive benefits for you as a customer:

  1. very powerful visualization and high level of customization
  2. you learn to customize and use Grafana, you can also use Performance Analyzer in a heartbeat
  3. last but not least, there is a cost benefit we share with you!

No worries, as Performance Analyzer comes as a virtual appliance, we handle all in one. So you don’t need to code, install or update anything. We deliver a product that comes with

  • a highly efficient data collector
  • dashboards to see your most important metrics, preset with best practice thresholds
  • features for capacity planning, bottleneck detection, reporting and correlating events with performance
  • a nice admin interface to configure VMware vCenter, NetApp aso.
  • full multi-tenant capability
  • infrastructure aware time series database

Coming back to Grafana and the original topic of this blog post. There is a feature called Playlist that is of great use to create a collection of existing dashboards and automatically rotate them. That feature is great to cover a certain task, like troubleshooting or VM performance, as well as showing status dashboard on a big screen.

Creating a Playlist in Performance Analyzer

To create a playlist, you should first think about the task you want to cover. Let’s assume its about the MS SQL databases in your virtual environment. In the end you want to keep your finger on the pulse of your virtual machines.

Create a Playlist

That means you typically want to get an overall overview of your environment and if something looks weird or slow.

The following dashboards a good mix in my case as I want to see the common vital signs of my hosts and vms as well as the application itself:

  • Highlights: Virtual Machines

pulse of your virtual machines

  • VMware vSphere Health Status
  • VMware Performance: VM Cluster
  • SQL Server Monitoring

MS SQL Virtual Machine Performance

The dashboards should rotate every minute, therefore we set the interval to 1m.

Playlist Link

After saving the playlist, you can either use the Start url or the Play button to start the rotation through the selected dashboards. Don’t forget to bookmark the link!

Playlist controls

While the playlist is active, you can see the control buttons next to the dashboard name. Go Back, Skip the current dashboard or pause the dashboard rotation.

You can watch the video below to see how to create the playlist step by step. 

Don’t miss to run Performance Analyzer in your own environment if you haven’t done so yet. I promise you’ll like it!

Download Performance Analyzer

Video – how to create a daily routing playlist using Performance Analyzer

Opvizor Performance Analyzer – Use Playlists to optimize your daily routine from opvizor on Vimeo.

Metrics and Logs

(formerly, Opvizor Performance Analyzer)

VMware vSphere & Cloud

Monitor and Analyze Performance and Log files:
Performance monitoring for your systems and applications with log analysis (tamperproof using immudb) and license compliance (RedHat, Oracle, SAP and more) in one virtual appliance!

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Use Case - Tamper-resistant Clinical Trials


Blockchain PoCs were unsuccessful due to complexity and lack of developers.

Still the goal of data immutability as well as client verification is a crucial. Furthermore, the system needs to be easy to use and operate (allowing backup, maintenance windows aso.).


immudb is running in different datacenters across the globe. All clinical trial information is stored in immudb either as transactions or the pdf documents as a whole.

Having that single source of truth with versioned, timestamped, and cryptographically verifiable records, enables a whole new way of transparency and trust.

Use Case - Finance


Store the source data, the decision and the rule base for financial support from governments timestamped, verifiable.

A very important functionality is the ability to compare the historic decision (based on the past rulebase) with the rulebase at a different date. Fully cryptographic verifiable Time Travel queries are required to be able to achieve that comparison.


While the source data, rulebase and the documented decision are stored in verifiable Blobs in immudb, the transaction is stored using the relational layer of immudb.

That allows the use of immudb’s time travel capabilities to retrieve verified historic data and recalculate with the most recent rulebase.

Use Case - eCommerce and NFT marketplace


No matter if it’s an eCommerce platform or NFT marketplace, the goals are similar:

  • High amount of transactions (potentially millions a second)
  • Ability to read and write multiple records within one transaction
  • prevent overwrite or updates on transactions
  • comply with regulations (PCI, GDPR, …)


immudb is typically scaled out using Hyperscaler (i. e. AWS, Google Cloud, Microsoft Azure) distributed across the Globe. Auditors are also distributed to track the verification proof over time. Additionally, the shop or marketplace applications store immudb cryptographic state information. That high level of integrity and tamper-evidence while maintaining a very high transaction speed is key for companies to chose immudb.

Use Case - IoT Sensor Data


IoT sensor data received by devices collecting environment data needs to be stored locally in a cryptographically verifiable manner until the data is transferred to a central datacenter. The data integrity needs to be verifiable at any given point in time and while in transit.


immudb runs embedded on the IoT device itself and is consistently audited by external probes. The data transfer to audit is minimal and works even with minimum bandwidth and unreliable connections.

Whenever the IoT devices are connected to a high bandwidth, the data transfer happens to a data center (large immudb deployment) and the source and destination date integrity is fully verified.

Use Case - DevOps Evidence


CI/CD and application build logs need to be stored auditable and tamper-evident.
A very high Performance is required as the system should not slow down any build process.
Scalability is key as billions of artifacts are expected within the next years.
Next to a possibility of integrity validation, data needs to be retrievable by pipeline job id or digital asset checksum.


As part of the CI/CD audit functionality, data is stored within immudb using the Key/Value functionality. Key is either the CI/CD job id (i. e. Jenkins or GitLab) or the checksum of the resulting build or container image.

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