DRS Lens provides an alternative UI for a DRS enabled cluster. It gives a simple, yet powerful interface to monitor the cluster real time and provide useful analyses to the users. The UI is comprised of different dashboards in the form of tabs for each cluster being monitored.
Dashboard showing the variations in the cluster balance metric plotted over time with DRS runs. This shows how DRS reacts to and tries to clear cluster imbalance every time it runs.
This dashboard shows VM happiness for the first time in a UI. This chart shows the summary of total VMs in the cluster that are happy and those that are unhappy based on the user defined thresholds. Users can then select individual VMs to view performance metrics related to its happiness, like CPU ready time and memory swapIn rate.
This dashboard provides a summary of vMotions that happened in the cluster over time. For each DRS run period, there will be a breakdown of vMotions as DRS-initiated and user-initiated. This helps users see how actively DRS has been working to resolve cluster imbalance. It also helps to see if there are vMotions outside of DRS control, which may be affecting cluster balance.
This dashboard tracks different operations (tasks, in vCenter Server) that happened in the cluster, over time. Users can correlate information about tasks from this dashboard against DRS load balancing and its effects from the other dashboards.
Users can download DRS Lens from VMware flings website.
At the VMworld 2016 Barcelona keynote, CTO Ray O’Farrell proudly presented the performance improvements in vCenter 6.5. He showed the following slide:
Slide from Ray O’Farrell’s keynote at VMworld 2016 Barcelona, showing 2x improvement in scale from 6.0 to 6.5 and 6x improvement in throughput from 5.5 to 6.5.
As a senior performance engineer who focuses on vCenter, and as one of the presenters of VMworld Session INF8108 (listed in the top-right corner of the slide above), I have received a number of questions regarding the “6x” and “2x scale” labels in the slide above. This blog is an attempt to explain these numbers by describing (at a high level) the performance improvements for vCenter in 6.5. I will focus specifically on the vCenter Appliance in this post.
Better performance, lower latency, and streamlined statistics are just some of the new features you can expect to find in the vCenter Server in version 5.1. The VMware performance team has published a paper about vCenter Server 5.1 database performance in large environments. The paper shows that statistics collection creates the biggest performance impact on the vCenter Server database. In vSphere 5.1, several aspects of statistics collection have been changed to improve the overall performance of the database. There were three sources of I/O to the statistics tables in vCenter Server—inserting statistics, rolling up statistics between different intervals, and deleting statistics when they expire. These activities have been improved by changing the way the relevant data is persisted to the tables, by partitioning the tables instead of using staging tables. In addition, by removing the staging tables, statistics collection is more robust, resolving the issues described in KB 2011523 and KB 1003878. Scalability is also improved by allowing larger inventories to be supported because they don’t take so long to read/write data from the old staging tables. The paper also includes best practices to take advantage of these changes in environments where vCenter Server has a large inventory. For more details, see vCenter Server 5.1 Database Performance in Large-Scale Environments.
Here are the URLs for the paper, “VMware vCenter Server 5.1 Database Performance Improvements and Best Practices for Large-Scale Environments”:
The hugely popular Performance Troubleshooting for VMware vSphere 4 guide is now updated for vSphere 4.1 . This document provides step-by-step approaches for troubleshooting most common performance problems in vSphere-based virtual environments. The steps discussed in the document use performance data and charts readily available in the vSphere Client and esxtop to aid the troubleshooting flows. Each performance troubleshooting flow has two parts:
How to identify the problem using specific performance counters.
Possible causes of the problem and solutions to solve it.
New sections that were added to the document include troubleshooting performance problems in resource pools on standalone hosts and DRS clusters, additional troubleshooting steps for environments experiencing memory pressure (hosts with compressed and swapped memory), high CPU ready time in hosts that are not CPU saturated, environments sharing resources such as storage and network, and environments using snapshots.
The Troubleshooting guide can be found here. Readers are encouraged to provide their feedback and comments in the performance community site at this link.
Do you want to know how many VMware vCloud Director server instances are needed for your deployment? Do you know how to load balance the VC Listener across multiple vCloud Director instances? Are you curious about how OVF File Upload behaves on a WAN environment? What is the most efficient way to import LDAP users? This white paper, VMware vCloud Director 1.0 Performance and Best Practices, provides insight to help you answer all the above questions.
In this paper, we discuss VMware vCloud Director 1.0 architecture, server instance sizing, LDAP sync, OVF file upload, vApp clones across vCenter Server instances, inventory sync, and adjusting thread pool and cache limits. The following performance tips are provided:
Ensure the inventory cache size is big enough to hold all inventory objects.
Ensure JVM heap size is big enough to satisfy the memory requirement for the inventory cache and memory burst so the vCloud Director server does not run out of memory.
Import LDAP users by groups instead of importing individual users one by one.
Ensure the system is not running LDAP sync too frequently because the vCloud database is updated at regular intervals.
In order to help load balance disk I/O, separate the storage location for OVF uploads from the location of the vCloud Director server logs.
Have a central datastore to hold the most popular vApp templates and media files and have this datastore mounted to at least one ESX host per cluster.
Be aware that the latency to deploy a vApp in fence mode has a static cost and does not increase proportionately with the number of VMs in the vApp.
Deploy multiple vApps concurrently to achieve high throughput.
For load balancing purposes, it is possible to move a VC Listener to another vCloud Director instance by reconnecting the vCenter Server through the vCloud Director user interface.
Please read the white paper for more performance tips with more details. You can download the full white paper from here.
vSphere is an industry-leading virtualization platform that enables customers to build private clouds for running enterprise applications such as SQL server databases. Customers can expect near-native performance from their virtualized SQL databases when running in a vSphere environment. VMware vCenter Server, the management component of vSphere, uses a database to store and organize information related to vSphere-based virtual environments. This database can be implemented using SQL server. Based on the previous VMware performance studies involving SQL databases, it is reasonable to expect the performance of a virtualized SQL Server-based vCenter database to be similar to that in native.
A study was conducted in the VMware performance engineering lab to validate the assumption. The results of the study show that:
The most resource-intensive operations of a virtualized SQL Server-based vCenter database perform at a level comparable to that in native environment.
A SQL Server-based vCenter database managing a vSphere virtual environment of any scale can be virtualized on vSphere.
SQL databases, in general, perform at a near-native level when virtualized on vSphere 4.1.
Complete details of the experiments and their results can be found in this technical document.