new-starter-dashboard-for-vmware-vsphere-troubleshooting

The issue with troubleshooting is, that it is simply not preventive. You can only search for issues and fix them, when you are aware of them. Of  course there is a lot of hype around predictive analysis, but we are not there yet, that you can really predict bad performance problems. It is more about filling up partitions or patterns that didn´t happen for some time range (anomalies). Keeping up with best practices and knowledge base articles also has its limits. No doubt, you lower the changes of having trouble because of simple misconfigurations. 

But you don´t know what´s going on inside of the virtual machines, the applications or of course if it happens in a lower layer like (hardware or software failures in your network or storage network. 

So you need to watch your environment consistently. That´s part of being predictive. Issue is, the larger the environment, the harder to monitor it. And when something is ringing an alert, you need to dig deeper, go back in time and compare situations, change a configuration and compare performance metrics, and so on. That´s the troubleshooting part.

That´s one of many reasons why we created Performance Analyzer – to collect and correlate data for monitoring, analytics and troubleshooting into dashboards that are easy to understand.

VMware VM troubleshooting

Now we went a step further and created 2 starter dashboards, one for ESXi hosts and one for virtual machines, that display all important metrics to monitor.

VMware ESX troubleshooting

Lets go into more details…

Starter Virtual Machines Troubleshooting Dashboard

VMware vSphere Troubleshooting Virtual Machines

Download Performance Analyzer

The dashboard can be downloaded here: Download Starter Virtual Machine Troubleshooting Dashboard

What virtual machine metrics are covered in the dashboard:

  • CPU Usage
  • CPU Ready %
  • CPU Co-Stopping
  • Memory Usage
  • Memory Ballooning
  • Memory Swapping
  • Disk Read Latency
  • Disk Write Latency
  • Network dropped incoming (RX) packets
  • Network dropped outgoing (TX) packets
  • VM Storage Read Throughput
  • VM Storage Write Throughput
  • Read IOps
  • Write IOps
  • Network vNIC throughput incoming (RX)
  • Network vNIC throughput outgoing (RX)
  • current, average and maximum values for the chosen timeframe
  • go back up to months, years (depends on configuration)

The metrics and charts are combined in sections (rows) for better and easier visibility. Sections are based on typical slowdown indicators for cpu, memory, network and disk access. 

All patches and new dashboards can always be found in our online manual, Change Log, Patch – manual.opvizor.com

If you don´t know where to import the dashboard in Performance Analyzer (btw. we proudly use Grafana!):

Import Dashboard

Starter ESXi Host Troubleshooting Dashboard

VMware vSphere Troubleshooting - VMware ESXi

Download Performance Analyzer

The dashboard can be downloaded here: Download Starter ESXi Host Troubleshooting Dashboard

What VMware ESXi host metrics are covered in the dashboard:

  • VMs powered on
  • CPU usage
  • VM CPU usage on Host
  • VM CPU ready on Host
  • VM CPU co-stopping on Host
  • Memory Usage
  • Memory Swap Usage
  • Memory Ballooning Usage
  • VM memory usage on Host
  • VM memory swapping on Host
  • VM memory ballooning on Host
  • Network throughput incoming (RX)
  • Network throughput outgoing (TX)
  • Network packets incoming (RX)
  • Network packets outgoing (TX)
  • Network packets incoming dropped (RX)
  • Network packets outgoing dropped (TX)
  • VM network throughput incoming (RX) on Host
  • VM network throughput outgoing (TX) on Host
  • VM network packets incoming (RX) on Host
  • VM network packets outgoing (TX) on Host
  • VM network packets incoming dropped (RX) on Host
  • VM network packets outgoing dropped (TX) on Host
  • ESXi VMHBA read latency
  • ESXi VMHBA write latency
  • ESXi device latency
  • ESXi queue latency
  • ESXi kernel latency
  • Total VM read latency on Host
  • Total VM write latency on Host
  • current, average and maximum metrics for the chosen timeframe
  • go back up to months, years depending on configuration

The end to end visibility inside the cluster between ESXi host and the running virtual machines provides a great way to pinpoint and troubleshoot storage or network performance issues. Of course cpu and memory congestions are much better to notice and to alert on.

VMware vSphere troubleshooting should be simple. But don´t take just our word – test Performance Analyzer yourself.

All patches and new dashboards can always be found in our online manual, Change Log, Patch – manual.opvizor.com

If you don´t know where to import the dashboard in Performance Analyzer (btw. we proudly use Grafana!):

Import Dashboard

CNIL
Metrics and Logs

(formerly, Opvizor Performance Analyzer)

VMware vSphere & Cloud
PERFORMANCE MONITORING, LOG ANALYSIS, LICENSE COMPLIANCE!

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

Goal:

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.).

Implementation:

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

Goal:

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.

Implementation:

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

Goal:

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, …)


Implementation:

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

Goal:

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.

Implementation:

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

Goal:

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.

Implementation:

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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