Amazon Web Services Continues To Increase IaaS/PaaS Market Share According To Synergy Research Group

A recent article by the Synergy Research Group (Synergy) claims that Amazon Web Services continues to dominate the IaaS and PaaS space in terms of revenue. According to Synergy, Amazon Web Services increased its quarterly revenue by 55% to over $700M in Q3 of 2013, whereas the aggregate of revenue for Salesforce, IBM, Windows Azure and Google was less than $400M for the same time period. Worldwide, total IaaS and PaaS revenues exceeded $2.5 billion for the quarter, with IaaS accounting for 64% of cloud revenues, a surprisingly small proportion given the limited penetration of platform as a service within the enterprise. Synergy Research’s John Dinsdale remarked on the company’s findings as follows:

We’ve been analyzing the IaaS/PaaS markets for quite a few quarters now and creating these leadership metrics, and the relative positioning of the leaders really hasn’t changed much. While Amazon dwarfs all competition, the race is on to see if any of the big four followers can distance themselves from their peers. The good news for these companies and for the long tail of operators with relatively small cloud infrastructure service operations, is that IaaS/PaaS will be growing strongly long into the future, providing plenty of opportunity for robust revenue growth.

Here, Dinsdale remarks that the “race is on to see if” Salesforce, IBM, Microsoft and Google can decisively secure second place in the battle for IaaS/PaaS market share. Strikingly, Microsoft, Google and IBM have revenues that are very close to one another, even though one might reasonably expect Microsoft’s Azure platform to edge out its competition given its earlier entry into the market than IBM and Google’s Compute Engine (GCE). That said, IBM’s sizeable IaaS revenue derives largely from its acquisition of SoftLayer, which itself had a rich and venerable history that predated IBM.

Synergy’s chart illustrating Q3 IaaS and PaaS revenues is given below:

Notable omissions from the findings include Rackspace, HP, Oracle, Pivotal One and Red Hat, the middle three of which (HP, Oracle and Pivotal One) are still relatively nascent, and hence justifiably excluded from the present calculation. As Dinsdale notes above, however, “the good news for these companies” and for remainder of the space is that revenues are set to increase significantly in the near term. Going forward, one of the key questions for subsequent IaaS market share analyses will be whether OpenStack’s momentum and gradual maturation propels disproportionate growth amongst OpenStack-based cloud platforms for vendors such as HP, IBM, Oracle, Rackspace and Red Hat.

New Relic Partners With Google To Support Google Compute Engine For Application Monitoring

On Monday, New Relic announced that it will join the Google Cloud Platform Partner program as a monitoring and application analytics application for Google Compute Engine. As a result of the partnership, Google Compute Engine customers will have free access to New Relic for “large-scale computing workloads on Linux virtual machines in Google’s data centers hosted on Google Cloud Platform.” Existing Google Compute Engine customers that are already using New Relic will receive the Google Cloud Platform Starter Pack, which features $2,000 toward the use of either Google Compute Engine or Google App Engine. Google Compute Engine customers can now use New Relic to keep track of the performance and health of applications as well as their larger IT environment. Meanwhile, Google will participate prominently at New Relic’s first technology conference, FutureStack13, from October 24-25.

New Relic’s partnership with the Google Compute Engine platform builds upon another recent partnership, namely, its integration into the Cloud Foundry Java “buildpack” that Cloud Foundry uses for application deployment. With just a few clicks of the mouse, developers can now use New Relic to monitor the performance of Java applications in Cloud Foundry development, testing and production environments.

Iterative Computation Between Vertices In Pregel and Apache Giraph

As a follow-up to our post on Facebook’s use of Apache Giraph, I wanted to return to Pregel, the graphing technology on which Giraph was based. Alongside, MapReduce, Pregel is used by Google to mine relationships between richly associative data sets in which the data points have multi-valent, highly dynamic relationships that morph, proliferate, aggregate, disperse, emerge and vanish with a velocity that renders any schema-based data model untenable. In a well known blog post, Grzegorz Czajkowski of Google’s Systems Infrastructure Team elaborated on the importance of graph theory and Pregel’s structure as follows:

Despite differences in structure and origin, many graphs out there have two things in common: each of them keeps growing in size, and there is a seemingly endless number of facts and details people would like to know about each one. Take, for example, geographic locations. A relatively simple analysis of a standard map (a graph!) can provide the shortest route between two cities. But progressively more sophisticated analysis could be applied to richer information such as speed limits, expected traffic jams, roadworks and even weather conditions. In addition to the shortest route, measured as sheer distance, you could learn about the most scenic route, or the most fuel-efficient one, or the one which has the most rest areas. All these options, and more, can all be extracted from the graph and made useful — provided you have the right tools and inputs. The web graph is similar. The web contains billions of documents, and that number increases daily. To help you find what you need from that vast amount of information, Google extracts more than 200 signals from the web graph, ranging from the language of a webpage to the number and quality of other pages pointing to it.

In order to achieve that, we have created scalable infrastructure, named Pregel, to mine a wide range of graphs. In Pregel, programs are expressed as a sequence of iterations. In each iteration, a vertex can, independently of other vertices, receive messages sent to it in the previous iteration, send messages to other vertices, modify its own and its outgoing edges’ states, and mutate the graph’s topology (experts in parallel processing will recognize that the Bulk Synchronous Parallel Model inspired Pregel).

The key point worth noting here is that Pregel computation is marked by a “sequence of iterations” whereby the relationship between vertices is iteratively refined and recalibrated with each computation. In other words, Pregel computation begins with an input step, followed by a series of supersteps that successively lead to the algorithm’s termination and finally, an output. During each of the supersteps, the vertices send and receive messages to other vertices in parallel. The algorithm terminates when the vertices collectively stop transmitting messages to each other, or, to put things in another lexicon, vote to halt. As Malewizc, Czajkowsk note in a paper on Pregel, “The algorithm as a whole terminates when all vertices are simultaneously inactive and there are no messages in transit.” Like Pregel, Apache Giraph uses a computation structure whereby computation proceeds iteratively until the relationships between vertices in a graph stabilize.

Google Includes 79 More Patents In Open Patent Pledge

On Thursday, Google announced that 79 more patents will be part of its Open Patent Non-Assertion (OPN) Pledge. The announcement builds upon Google’s March OPN commitment to refrain from suing users of designated patents, in an attempt to support open-source collaboration and innovation. The key proviso, however, is that Google reserves the right to sue if it is attacked first. The 79 patents relate to data center operations such as “middleware, distributed storage management, distributed database management, and alarm monitoring” whereas the first 10 patents that Google introduced to OPN had to do with MapReduce. Although the patents included in OPN thus far focus on back-end technologies, Google intends to additionally include software for “consumer products that people use every day” in OPN going forward, according to a company blog post. Google’s commitment to OPN represents a gesture to work toward building a tech culture marked by fewer instances of aggressive patent litigation although the move is unlikely to have a significant impact unless other tech companies make similar commitments to non-offensive patent litigation.

Google Maps and Google Earth Form Core Of International Disaster Recovery Application

Google Earth and Google Maps will now be leveraged to provide assistance for first responders to international disasters such as earthquakes, fires, floods and hurricanes. On Tuesday, the Network Centric Operations Industry Consortium selected NJVC to provide a platform as a service (PaaS) application that draws upon Google’s geospatial data to enable users to view, share and publish maps and other terrestrial/street views when responding to international disasters. NJVC will use the Cloudcuity AppDeployer application to integrate data from the Google Maps Engine and Google Earth Server to allow respondents to use Google’s familiar search and mapping technologies when planning and executing responses to complex humanitarian disasters (CHD). Known as GeoCloud, the integrated technology solution provides a “virtual organization of response teams” that allows respondents both within, and across teams to share relevant disaster-related geospatial data as required. Kevin L. Jackson, vice president and general manager, NJVC cloud services, remarked on the value of GeoCloud and its partnership with Google as follows:

Through the cohesive PaaS solution to be delivered by NJVC, first responders will have access to the cloud services that they need—whenever and wherever they need them—and all disaster response activities will be managed from one secure interface. GeoCloud is the glue to bond disparate apps into one powerful virtual community for first responders. NJVC is thrilled that Google’s technologies will provide the geospatial data backbone for the platform for cycle two of this historic community cloud demonstration.

The concept of data sharing across a global consortium of partners in the event of an international disaster was proposed by the National Geospatial-Intelligence Agency (NGA), which wanted to respond to the problem whereby disaster respondents leveraged different and conflicting maps and visual representations of the terrain of interest. As a result, the NGA sought to understand the capacity of the private sector to deliver “open standards-based geospatial data to first responders via multiple, interoperable cloud infrastructures.”

The Network Centric Operations Industry Consortium awarded $350,000 to NJVC for the first phase of the project to build the basic infrastructure for creating a unified platform for cloud-based data sharing. In the second and current phase of the project, which began in early June, NJVC will demonstrate the functionality of its GeoCloud PaaS solution in the context of data regarding the 2010 earthquake in Haiti. Over and beyond the specific use case of humanitarian disasters, the larger vision for NGA concerns the project of delivering a “global geospatial community cloud” within a form that accommodates interoperability across different cloud platforms to ensure standardization and consistency of data so that teams are literally “fighting off the same map,” according to a 2010 NCOIC GEOINT plenary briefing presentation.

Windows Azure IaaS Takes Aim At Amazon Web Services Via Price, Functionality And Service

This was the week where Microsoft announced the general availability of Windows Azure Infrastructure as a Service. More than a simple declaration of production-grade availability, Microsoft’s announcement about its IaaS platform delivered the strongest possible elaboration of its intent to compete head to head with Amazon Web Services in the IaaS space to date. In a blog post, Microsoft’s Bill Hilf accurately assessed enterprise readiness with respect to cloud adoption by noting that customers are not interested in replacing traditional data centers with cloud based environments. Customers typically want to supplement existing data infrastructures with IaaS and PaaS installations alongside private cloud environments and traditional data center ecosystems. In other words, hybridity is the name of the game with respect to enterprise cloud adoption at present, and Hilf’s argument is that no one is better suited to recognize and respond to that hybridity than Microsoft. In conjunction with the general availability of its Azure IaaS platform, Microsoft pledges a commitment to “match Amazon Web Services prices for commodity services such as compute, storage and bandwidth” alongside “monthly SLAs that are among the industry’s highest.”

Microsoft also announced new, larger Virtual Machine sizes on the order of 28GB/4 core and 56 GB/8 core in addition to new Virtual Machine image templates featuring a gallery of image templates including Windows Server 2012, Windows Server 2008 R2, SQL Server, BizTalk Server and SharePoint Server as well as VM templates for applications that run on Ubuntu, CentOS, and SUSE Linux distributions. Overall, the announcement represents an incisive and undisguised assault on the market dominance of Amazon Web Services within the IaaS space that is all the more threatening given Microsoft’s ability to match AWS in price, functionality and service. The key question now is the degree to which OpenStack and Google’s Google Compute Engine (GCE) will emerge as major players within the IaaS space. OpenStack has already emerged as a major IaaS player, but it remains to be seen which distribution will take the cake at the enterprise level. Nevertheless, analysts should expect a tangible reconfiguration of IaaS market share by the end of 2013, with a more significant transformation in place roughly a year from the release in general availability of Google’s Compute Engine, which was released in Beta in June 2012.