Performance Management covers monitoring the physical infrastructure, the virtual infrastructure and applications for end-to-end performance and service levels. It covers Application Performance Management, Infrastructure Performance Management, Operations Management, Capacity Planning, and Capacity Management. (Read More)(Read Less)
Environments covered include Virtualization Performance Management, Software Defined Data Center Performance Management, and Cloud Performance Management. Key issues include ensuring the performance of virtualized and cloud based data centers, ensuring the performance of software defined data centers (SDDC performance management), ensuring virtualized application performance, cloud application performance, and SDDC application performance. Key vendors covered include VMware, AppDynamics, AppEnsure, AppFirst, AppNeta, Astute Networks, Aternity, BlueStripe, Boundary, Cirba, CloudPhysics, Correlsense, Compuware, Dell, Embotics, ExtraHop, GigaMon, Hotlink, HP, Intigua, ManageEngine, New Relic, Prelert, Puppet Labs, Riverbed, Splunk, Tintri, Virtual Instruments, Virtustream, VMTurbo, Xangati, and Zenoss.
VMware has published a fascinating white paper which goes through the resource requirements, performance requirements, suggested configurations, performance comparison between physical and virtual environments and whether or not there are licensing issues for various business critical applications.
The VMware Virtualizing Business Critical Apps White Paper
VMware has also published a list of worldwide partners who have specific domain expertise in virtualizing business critical applications. That matrix is below.
More information on virtualizing business critical applications can be found at Blogs.VMware/Apps/
Having successfully virtualized all of the low hanging fruit in its customer base, VMware has now put a serious focus upon virtualizing business critical and performance critical applications. That focus includes not just highlighting progress to date, but also working with partners who have specific domain expertise is specific applications.
VMware has announced financial results for the fourth quarter of 2012 and for the entire year of 2012. Fourth quarter revenue came in at $1.29B growing 22% over the fourth quarter of 2011. Full year revenue came in at $4.61B also growing 22% over 2011. The full results are detailed in the table below:
One of the great things about Splunk as both an Operations Management tool and as an Application Performance Management tool is the ease with which an astonishing variety of data sources can be fed into the Splunk data store. Splunk automatically indexes this data based upon time stamps, and stores it in a back end data store that scales out horizontally on commodity servers with commodity storage. This means that Splunk one of the very few management solutions that can scale out to accept the tsunami of management that is generated across the infrastructure and application stack in a modern dynamic or cloud based environment.
The Splunk Architecture
The wealth of data sources that can be collected an indexed by Splunk are shown in the left portion of the image below. The scaled out architecture that is how Splunk can keep up with the management data tsunami is shown in the rest of the diagram.
Now we come to the part about the good news and the bad news. The good news is that Splunk is able to be your management data store across your physical hardware, virtualization layer, operating system layer, application infrastructure layer (middleware) and the layer comprised of the applications themselves.
The bad news is that until today, if you wanted to pull all of the data together than pertained to a particular application, you had to be an expert in the topology of that application (where does it run), the virtual and physical infrastructure that supports that application (what is it dependent on) and on how to tie disparate data sources together in Splunk to create a cohesive view or dashboard. Organizations with a few (or one) mission critical application that was of such high value that it warranted a dedicated support team could easily justify the investment in learning required to pull this off. Organizations with thousands of business critical and performance critical applications saw this as an infinitely high cliff.
The Prelert Anomaly Detective for Splunk
The Prelert Anomaly Detective automatically learns the normal patterns of the Splunk data. It then automatically identifies anomalous behavior in the Splunk data and uses the ability of the Splunk Query Language to find cross-correlated data and events.
The Prelert Anomaly Detective allows for a significant advance in how customers use Splunk and its data. Today most customers use Splunk as a forensics tool to find the problem, after some other tool or user has reported the problem. The combination of the Prelert Anomaly Detective with Splunk allows Prelert to notify customers of anomalies that the customer did not even know to go look for and that can easily be leading indicators of problems that have not yet been reported.
The most frequently encountered barrier to virtualizing business critical applications is a “concern” on the part of the application owners that the applications will “not run as well”, or “not perform as well” in a shared and dynamic virtual environment as it does in a dedicated physical environment. Depending upon who has what political power, these concerns can stop the project to virtualize these applications dead in its tracks. Continue reading Virtualizing Business Critical Applications – Managing Applications Performance→
As VMware progresses towards virtualizing more and more business-critical and performance-critical applications, the tools and processes by which the virtualized data center needs to be managed need to change. As a first step, it is important to separate workloads into three groups: Tactical (no one cares if they go down for a while), Business-Critical (they must be up all of the time), and Performance-Critical (they not only must be up, but must deliver excellent response time all of the time).