.NET and Java enterprise PaaS company Apprenda recently announced that it will be available in the Cisco Intercloud Marketplace. Slated for launch in the fall of 2015, the Cisco Intercloud Marketplace aggregates applications that run on Cisco’s Intercloud platform for building hybrid clouds. As part of the collaboration between Apprenda and Cisco, Apprenda will support Cisco SDKs and APIs. The partnership between Apprenda and Cisco underscores the co-implication between Platform as a Service vendors qua Apprenda and hybrid infrastructures such as Cisco’s intercloud, a “cloud of clouds” that facilitates the creation of hybrid, OpenStack-based clouds by delivering infrastructure and application development functionality. Apprenda’s forthcoming availability within the Cisco Intercloud Marketplace builds upon recent partnerships with Piston Cloud (recently acquired by Cisco) and Microsoft Azure in a clear sign that, with the exception of Pivotal Cloud Foundry, the days of a standalone PaaS platform may well be numbered as the industry churns out partnerships between application, database and infrastructure technologies such as the Basho Data Platform and Piston Cloud OS 4.0. The bottom line here is that PaaS is increasingly morphing into an appendage to IaaS-focused platforms albeit, a critical one by way of its ability to deliver a ready to use database and application stack that can be immediately consumed by developers.
Amazon Web Services and Microsoft Azure took the two leadership positions in its latest Magic Quadrant report for Magic Quadrant for Cloud Infrastructure as a Service, Worldwide. Amazon is the clear market leader and, according to Gartner, claims more than 10 times the computing capacity of the other 14 vendors represented in its Magic Quadrant report. Other vendors represented in the report include Google, Rackspace, IBM SoftLayer and VMware vCloud Air. Gartner estimates that the IaaS space will experience growth of 33% in 2015 and become a $16.5B market globally with an annual growth rate of 29.1% through 2019. In a press release about the report, Gartner noted that “the market for cloud infrastructure as a service (IaaS) is in a state of upheaval, as many service providers are shifting their strategies after failing to gain enough market traction.” The report’s finding that Amazon Web Services and Microsoft Azure represent the two market leaders means that the rest of the space will need to significantly differentiate their product offerings to flourish in an increasingly competitive space.
In a presentation from Day 1 of the OpenStack Summit in Vancouver, Jonathon Bryce, Executive Director of the OpenStack Foundation announced the rollout of the initial round interoperability protocols and testing to ensure that OpenStack distributions successfully interoperate with one another. Currently, 16 companies have interoperability testing results available and the OpenStack Foundation plans to ensure the application of its interoperability testing on all OpenStack-branded products during the remainder of 2015. Bryce also notes that over 30 OpenStack products and services in the marketplace have pledged to support federated identity. Bryce’s elaboration on the aggressiveness of the OpenStack Foundation’s efforts to ensure the development of a common OpenStack core stack across all distributions suggests that OpenStack is likely to live up to the promise of interoperability and open standards that constituted part of its core vision as an open source IaaS platform that allows customers to migrate workloads from one OpenStack environment to another with ease. Companies that have produced live interoperability results at present include IBM, SwiftStack, Red Hat, Bluebox, Rackspace and Mirantis.
On Monday, Google introduced Google Compute Engine pre-emptible virtual machines. Pre-emptible machines enjoy a 70% discount on standard pricing but may be shut down at any time and have a maximum runtime of 24 hours. The larger vision behind pre-emptible machines involves Google’s objective of reclaiming computing capacity depending upon the intensity and duration of other workloads within its public cloud environment. By shutting down pre-emptible machines and recovering compute capacity, the Google Cloud Platform can maintain a high degree of performance without spinning up additional VMs, thereby saving operational overhead and concurrently passing along some of the attendant cost savings to the customer. Given the unpredictability with which pre-emptible virtual machines may be shut down, they are suited only for select use cases such as massive data processing, data analytics, visual effects and simulations that are not time sensitive with respect to the allotted time period for their completion. Pre-emptible machines are ideal for applications that are architected such that they can handle the termination of a few VMs on a periodic basis. Meanwhile, customers stand to enjoy fixed pricing in addition to the 70% pricing discount and may subsequently decide to allocate a designated percentage of their fleet of VMs to pre-emptible machines in recognition of the way in which their computational processing is only minimally impacted by periodic VM shutdowns. Google announced pre-emptible virtual machines in conjunction with significant price cuts for VMs for Google Compute Engine amounting to a maximum of 30%. Google’s elaboration of Google Cloud Platform price cuts and the availability of pre-emptible machines indicate the intensity of competition in the IaaS space where prices skyrocket downward as major players such as Microsoft and Google intensify their assault on Amazon’s stranglehold on the leadership position in the IaaS space.
451 Research Group Report Shows AWS Leads IaaS Space Amidst Increased Competition From Microsoft Azure And Rackspace
According to a 451 Research Vendor Window assessment, the battle for IaaS leadership has intensified even though Amazon Web Services (AWS) remains the clear front-runner. Respondents to the 451 vendor evaluations revealed that 57% of enterprise customers use AWS whereas Microsoft Azure is used by 42% of customers. AWS was cited as the most important customer in 35% of all cases, ahead of Microsoft Azure, which garnered 20% of votes in the same category. Rackspace earned the highest ratings for the IaaS vendor capable of fulfilling Guaranteed SLAs and was tied with AWS for its ability to fulfill customer needs. While AWS received high ratings with respect to Experience and Technical Innovation, Microsoft Azure, in contrast, was rated lower than most of its competitors with respect to Experience and Support for Open-Source Software. Meanwhile, in the private cloud market, the 451 Research Vendor Window Assessment found that VMware claims a presence in 70% of enterprises with its ESX and vCloud virtualization platforms. Nevertheless, the survey also found that more than 70% of VMware customers have deployed other solutions for private clouds such as OpenStack or Microsoft Cloud OS, for example.
Michelle Bailey, Senior Vice President, Digital Infrastructure and Data Strategy at the 451 Research Group, remarked on the significance of the findings as follows:
While the 2015 Vendor Window for IaaS shows Amazon Web Services as the clear leader based on multiple metrics, Microsoft Azure, Rackspace and VMware’s vCloud Air are becoming competitive challengers. As more mainstream customers move business-critical workloads to cloud environments, the decision criteria for evaluating potential vendors change relative to early cloud adopters, and in turn so do the vendors under consideration.
Here, Bailey notes how the IaaS assessment reveals the emergence of “competitive challengers” to the leadership role of Amazon Web Services as the criteria for IaaS vendor selection evolves in relation to the evolving maturity of cloud adoption within the enterprise. The bottom line here is that, even though Amazon Web Services remains the most widely used and, in many ways, respected vendor within the IaaS space, enterprises are increasingly reviewing alternative options to AWS, particularly as the space features an increasing number of robust options that can variously go toe to toe with AWS regarding attributes such as customer service and ability to support SLAs. More importantly, the battle for IaaS market share is likely to become even more competitive as the progressive maturity of Big Data technologies and analytics means that enterprises are likely to seek cloud platforms that can not only support, but also streamline and simplify the adoption of Hadoop and NoSQL. Regardless, exciting times are ahead for the cloud industry as IaaS vendors mature their product and service offerings in ways that give customers the confidence to select multiple vendors to minimize risks of vendor lock-in while concomitantly enriching their knowledge of the IaaS space by sampling the heterogeneity of offerings available on the market today.
Amazon Web Services recently announced the availability of machine learning technology that allows developers to create predictive analytics by using the same algorithms that Amazon uses to manage its supply chain inventory and operations. Amazon’s Machine Learning platform empowers developers and data scientists with the ability to identify patterns and predictive analytics for data stored in Amazon S3, Amazon RedShift and Amazon Relational Database Service. By using Amazon Machine Learning, developers can obtain analytic insights without writing custom-built predictive analytics-based applications that require complicated scripting, debugging, code deployment and application management. In addition to enjoying the benefits of preconfigured machine learning libraries and wizards that accelerate access to pattern recognition and predictive analytics, Amazon Machine Learning enables customers to enjoy the benefits of a scalable platform capable of generating billions of predictions per day in real-time. Popular use cases for Amazon’s Machine Learning technology include the detection of fraud, the ability to personalize web-related content and deliver targeted marketing campaigns that iteratively become more effective in conjunction with the evolving sophistication of the predictive model. Amazon’s Machine Learning platform competes directly with Microsoft Azure’s Machine Learning platform that was released in public preview in July 2014. By rendering available the same technologies used by Amazon’s data scientists, Amazon adds yet another incentive for customers to leverage its ever expanding portfolio of cloud and big data products and services. The increasing availability of machine learning technologies underscores the democratization of analytics enabled by the contemporary cloud and big data revolution, even though many of the solutions available on the market remain proprietary and attached to usage of a larger IaaS platform.