Save energy without reducing VM performance in your VMware vSphere cluster

Over the last couple of decades energy consumption went up massively in every data center and while the costs were always high, they were manageable. For some time you can see more and more companies that started “Green Initiatives” to reduce energy waste and the sudden energy crisis accelerates the need for change,

One of the most common energy-saving practices is to turn off servers and other devices when they are not in use. However, turning off these devices can often lead to performance degradation and even data loss.

A VMware vSphere cluster is a group of physical or virtualized servers that work together as if they were one. When you’re running a VMware vSphere cluster, it’s important to ensure that your ESXi host has been configured properly for energy savings without sacrificing performance.

Small optimization in a larger setup can already save real money within a week:

You should consider looking into:

  • Power management settings on ESXi hosts
  • Storage power management

We are going to focus on the Power management of the ESXi hosts in this blog.

VMware vSphere has a feature called DPM (Distributed Power Management) that allows migrating virtual machines to a fewer amount of ESXi hosts in a cluster with the goal of freeing up some ESXi hosts completely. These hosts that run no VM anymore can be switched to standby mode reducing the power consumption massively. Whenever the resources within the cluster are not sufficient anymore, the standby hosts are automatically powered on again using wake on LAN or the KVM functionality of the server.

The standby hosts must be configured in such a way that they can take over the role of the host that just went off-line. If a host goes down during migration and is not capable to take over, DPM will halt the migration process.

You can find out more about the DPM configuration here: https://docs.vmware.com/en/VMware-vSphere/7.0/com.vmware.vsphere.resmgmt.doc/GUID-051ED894-10C3-4D80-AE52-A518FB973875.html

or the whole tech paper: https://www.vmware.com/content/dam/digitalmarketing/vmware/en/pdf/techpaper/performance/hpm-vsphere7-perf.pdf

To have a good understanding what power consumption can be reduced without annoying users with slowed-down application response times, Opvizor Metrics & Logs supports you with several dashboards. That can help you find the best ways to optimize energy use and your performance.

most important dashboards to use while reducing power consumption

The dashboard dedicated to showing the achieved reduction in power consumption is called VMware DPM Host Power Consumption. You can define the price per kWh and the reference period to see the detailed changes in your ESXi energy use.

Hint: longer reference periods can only be used when Metrics & Logs is already collecting data for that time range

To monitor the overall performance over time, Opvizor Metrics & Logs has many more dashboards to offer.

Starter Dashboards

and dedicated Performance Dashboards:

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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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