Business Agility

Business Agility covers using the technical agility delivered by virtualization and cloud computing to improve business agility, performance and results. This includes the agility derived from the proper implementation of Agile and DevOps methodologies, the agility derived from proper application and system architectures, (Read More)

the agility derived from the proper implementation of Infrastructure as a Server (IaaS), Platform as a Service (PaaS) and Software as a Service (SaaS) clouds, the agility derived from proper monitoring of the environment coupled with a process to resolve problems quickly, and the agility derived from have continuous availability through the use of high availability and disaster recovery products and procedures in place.

Software Defined Data Center Cloud Management

SDDC.Management.Stack.Reference.ArchitectureThe entire purpose of constructing an Software Defined Data Center is to allow new data center services to be rapidly provisioned in response to business demands. But the business does not just want a data center service. The business wants and needs either a full development environment in support of custom application deployment, or a full business application delivered as a service. Cloud Management is the crucial layer of software that adds application level services to SDDC services to create solutions for the business. Continue reading Software Defined Data Center Cloud Management

Software Defined Data Center Analytics

SDDC.Management.Stack.Reference.ArchitectureMoving the configuration of the environment from the hardware that supports the environment to a layer of software which can collectively manage all of the storage, networking, compute, and memory resources of the environment is one of the main points of the SDDC. Once all of the configuration of the data center is moved into software, and some of the execution of the work is moved into software, SDDC Data Center Analytics will play a critical role in keeping your SDDC up and running with acceptable performance. Continue reading Software Defined Data Center Analytics

BMC to be taken private; Out with Old – In with the New

BlindDinosaurThere are reports in Bloomberg and the Wall Street Journal Online that BMC is in talks with Bain Capital and Golden Gate Capital to be taken private. This is after Quest Software tried to go private last year only to end up being acquired by Dell who is now itself in talks to go private and while there are also rumors that private equity investors are looking at Compuware as well. So what is going on here? Continue reading BMC to be taken private; Out with Old – In with the New

How Will VMware Win Against Microsoft?

DataCenterVirtualizationWhile VMware is still the undisputed leader in enterprise data center virtualization, it is also very obvious that Microsoft has made (and continues to make) significant inroads into both the broader data center virtualization market and into VMware’s own enterprise customer base. The general perception is that Microsoft Hyper-V is now “good enough” to run most production workloads, that it is close enough (or at parity) in functionality and performance to vSphere for customers to be able to move workloads from vSphere to Hyper-V, and that vSphere is “expensive” and Hyper-V is “free”. So how will VMware win against Microsoft? Continue reading How Will VMware Win Against Microsoft?

The Big Data Back End for the SDDC Management Stack

SDDC.Management.Stack.Reference.ArchitectureIn, Building a Management Stack for Your Software Defined Data Center, we proposed a reference architecture for how one might assemble the suite of management components that will be needed to manage a Software Defined Data Center (SDDC). In this post we take a look at the need for that management suite to be supported by a multi-vendor big data datastore, and take a look at who might provide such a data store.

The Need for a Multi-Vendor Management Data Store in Your SDDC Management Stack

So why you ask, will a SDDC require a set of management products that will in turn require a multi-vendor big data back end. The reasons are as follows:

  1. The whole point of moving the configuration and management of compute, memory, networking and storage out of the respective hardware and into a software layer abstracted from the hardware is to allow for configuration and management changes to happen both more quickly and more automatically (which means very quickly). Each configuration change or policy change is going to create a blizzard of management data.
  2. If you look at all of the horizontal boxes in our Reference Architecture (below) each one of them along with the vertical IT Automation box will be generating data.
  3. The rate of change in the SDDC will be high enough so as to require fine grained and very frequent monitoring at every layer of the infrastructure.
  4. Just combining the number of layers with the rate of change with the need for fine grained and high frequency monitoring (5 minutes is an eternity) creates a big data problem.
  5. Finally, the need to be able to to cross layer root cause analytics (where in the software or hardware infrastructure is the cause of that application response time problem) means that the root cause analysis process has to cross domains and layers. This in and of itself calls for a common data store across management products.

The Software Defined Data Center Management Stack Reference Architecture



Who Could Provide the Multi-Vendor Big Data Repository?

There are two basic criteria for being able to provide such a repository. The first is that you have to have one, or have the intention to build one. The second is that since it is multi-vendor, you have to have the technical capability to, and the business model to partner with the vendors whose products will feed this datastore. The rest of this post is entirely speculative in nature as it is based upon who could do what, not upon who is doing what. To be clear, no vendor listed below has told us anything about what they intend to do in this regard. The rest of this post is based entirely upon what people are shipping today and the author’s speculation as to what might be possible.


If there is one vendor who has an early lead in filling this role it would be Splunk. Splunk is in fact the only vendor on the planet from whom you can purchase an on-premise big data datastore, which is today based upon shipping and available products being populated by data from management products from other vendors.  In fact if you go to SplunkBase do searches on things like APM, monitoring, security, and operations you will find a wide variety of Splunk written and vendor written applications that feed data into Splunk. Now it is important to point that today, when a vendor like ExtraHop Networks or AppDynamics feeds their data into Splunk they are not making Splunk in THE back end datastore for their products. They are just feeding a subset and a copy of their data into Splunk. But this is a start, and it puts Splunk further down this road than anyone else. Needless to say, if the vision of the multi-vendor datastore is correct, and Splunk is to become the or one of the vendors who provides this, then Splunk is going to have to entice a considerable number of software vendors to trust Splunk to perform a role that no vendor today trusts any other vendor to perform.


In, VMware Fleshes Out SDN Strategy with NSX, we went through how VMware is combining Nicira into its Network Virtualization offering, NSX. In the VMware announcement there was a link to a blog post, “Open Source, Open Interfaces, and Open Networking” contained the following fascinating statement:

Statistics Collection & Telemetry

“Another area of focus for an open networking ecosystem should be defining a framework for common storage and query of real time and historical performance data and statistics gathered from all devices and functional blocks participating in the network. This is an area that doesn’t exist today. Similar to Quantum, the framework should provide for vendor specific extensions and plug-ins. For example, a fabric vendor might be able to provide telemetry for fabric link utilization, failure events and the hosts affected, and supply a plug-in for a Tool vendor to query that data and subscribe to network events”.

Needless to say, it is highly unlikely that VMware would choose to make the current datastore for vCenter Operations into the “framework for the common storage and query of real time performance data“. Rather it is much more likely that VMware would build its own big data datastore with the people and the assets that VMware acquired when VMware acquired the Log Insight technology and team from Pattern Insight. VMware therefore clearly has the technology building blocks and the people to pull this off. You could also argue that they would not have make this acquisition if there were not intentions to go at least somewhat in this direction. The key challenge for VMware will then be the multi-vendor part. VMware has no relationship of technical cooperation with any other management software companies other than Puppet Labs, so this is clearly an area where VMware has a long way to go.

New Relic

New Relic is the hands down market leader for monitoring Java, .NET, Ruby, Python, and PHP applications in the cloud. New Relic offers cloud hosted APM as a Service and has gone in four years from a brand new company to now having more organizations using its product than the rest of the APM industry combined. New Relic recently raised $75M from top tier investors and is rumored to be positioning itself for an IPO in the 2014-2015 timeframe. New Relic already makes its data available to third parties in its partner program via a REST API. It is not much of a stretch for New Relic to consider becoming the management platform in the cloud, partnering with adjacent vendors and becoming a vendor of the multi-vendor cloud datastore. Again all of this is pure speculation at this point.

The Pivotal Initiative

The Pivotal Initiative is a new company formed with assets and people from EMC and VMware lead by former VMware CEO Paul Maritz. These assets consist of the application platform PaaS products from VMware (Gemfire, Spring, vFabric and CloudFoundry), and the big data assets fromEMC (GreenPlum). The stated ambition is to deliver a way to build and deploy big data applications that is radically better than the incumbent method and tackle giants like IBM, Microsoft, and Oracle in the process. This means that the focus of both the application development assets and the big data assets is most likely to be upon solving business problems for customers, not IT management problems for customers. However, it would not be inconceivable for a third party company to license these technologies from Pivotal and build an offering targeting the multi-vendor management stack use case.


Consider the possibility that this multi-vendor big data datastore is in fact non on-premise, but in the cloud. If you are willing to consider that possibility, then it is not much of a stretch to consider that CloudPhysics a vendor with cloud hosted (delivered as a service) operations management solutions might step into this fray. One of the key reasons that CloudPhysics may be able to provide something of extraordinary value is that the company has a strategy of applying Google quality analytics to Google size data sets. The analytics come from a world class team of people some of whom previously worked at Google. The data today is collected by virtual appliances installed at CloudPhysic’s customer sites (in their respective VMware environments). If CloudPhysics is already collecting data across customers and putting it in its cloud, it is not too huge a stretch to consider the possibility that other vendors who also deliver their value as a service could partner up with CloudPhysics, combine their respective sets of data, and produce a 1+1=3 scenario for joint customers.


AppNeta is today a market leading vendor of a cloud hosted service, PathView Cloud, that measures the performance of the wide area network in between the users and branch offices of an enterprise and the enterprises back end data center. The back end is a true big data back end, built around true big data technologies. AppNeta is branching out into APM with its TraceView offering.  But network performance data and application performance data are just parts of the compete set of data that will get generated by the SDDC and about the SDDC by various management products. AppNeta does not today have a partner program to attract third party data to its management data cloud, but who knows what the future holds.


Boundary is an APM vendor with a cloud hosted big data back end that today focuses upon collecting the statistics from the network layer of the operating system that support applications running in clouds. If you think of New Relic as the vendor who is monitoring your application in the cloud, you can think of Boundary as the vendor who should be monitoring the interaction of your operation system underlying your application with the cloud.  Boundary has no partner program today, and no ability to add third party vendor data to its cloud datastore today, but again who knows what the future might hold.


The SDDC and the Cloud are going to require a new SDDC Management Stack that will need to be based upon a multi-vendor big data datastore. There will likely be on-premise and cloud hosted version of these datastores. Splunk, VMware, New Relic, The Pivotal Initiative, CloudPhysics, AppNeta, and Boundary are all excellent hypothetical suppliers of such a datastore.

Public Cloud Reality: Do we Stay or Do We Go?

CloudComputingSoon the backup power will be available for our new datacenter and the redesign to make use of VMware vCloud Suite is nearing completion. Soon, our full private cloud will be ready for our existing workloads. These workloads however now run within a XenServer based public cloud.  So the question is, do we stay in a poorly performing public cloud (mentioned in our Public Cloud Reality series) or move back to our own private cloud? As the Clash put it “Should I Stay or Should I Go Now.” Continue reading Public Cloud Reality: Do we Stay or Do We Go?