We’re pleased to announce that the 2016 Magic Quadrant for Cloud Infrastructure, Worldwide has been published. (Link requires a Gartner subscription. If you’re not a Gartner client, there are free reprints available through vendors, and various press articles, such as the Tech Republic analysis. Note that press articles do not always accurately reflect our opinions, though.)
Producing the Magic Quadrant is a huge team effort that involves many people across Gartner, including many analysts who aren’t credited as co-authors, administrative support staff, and people in our primary-research and benchmarking groups. The team effort also reflects the way that we produce an entire body of IaaS research as an integrated effort across Gartner’s research divisions. (The approach described below is specific to our IaaS research and may not apply to Gartner’s assessments in other markets.)
Whether you already have a cloud IaaS provider and are just looking for a competitive check-up, you’re thinking of adding one or more additional providers, or you’re just getting started with cloud IaaS, our work can help you find the providers that are right for you.
The TL;DR list of assessments:
- Magic Quadrant (market and technical evaluation)
- Evaluation Criteria (230+ technical and service traits to look for in a provider)
- In-Depth Assessments (detailed assessments of specific providers against the Evaluation Criteria)
- Critical Capabilities (use-case-based technical evaluations; 2016 update coming soon)
- CloudHarmony and Tech Planner Cloud Module (real-world stats and cost-performance comparisons)
- Peer Insights (IT leaders review providers)
Gartner has produced a Magic Quadrant for Cloud IaaS since 2011. The MQ is our overall perspective on the market, looking at the provider solutions from both a technical and business angle. Gartner clients can use the interactive MQ tool to change the weightings of the criteria to suit their own evaluation priorities (if you read the detailed criteria descriptions, there’s an explanation of how each criterion maps to buyer priorities). The interactive MQ can also be used to get a multi-year historical perspective.
The MQ covers public, hosted private, and industrialized outsourced private cloud IaaS; it’s not just a public cloud MQ. We look at multi-tenant and single-tenant, located in either provider or customer premises, cloud IaaS offerings. We also look at the full range of compute options (VMs, bare-metal servers, containers) that are delivered in a cloud model (API-provisionable via automation, and metered by the hour or less), not just VMs. In addition, we consider some integrated PaaS-layer services (we call these cloud software infrastructure services, which include things like database as a service), but we have a separate enterprise application PaaS MQ for pure aPaaS. While we consider the provider’s overall value proposition in the context of cloud IaaS (including their ability to deliver managed services, network services, etc.), this isn’t a general cloud computing or outsourcing MQ.
2016 marks our sixth iteration of a pure cloud IaaS MQ. Previously, in 2009 and 2010, we included cloud IaaS in our hosting MQ, but by 2010, it was already clear that the hosting and cloud IaaS buyer wants and needs were distinctly different. Since 2011, we’ve produced a global cloud IaaS MQ, along with three regional hosting MQs (suitable for customers looking for dedicated servers or managed hosting on a monthly or annual basis), and three regional data center outsourcing MQs (which include customized private cloud services as part of a broader portfolio of infrastructure outsourcing capabiities). Not every infrastructure need can or should be met with cloud IaaS.
The core foundation of our assessment is our Evaluation Criteria for Cloud IaaS. Over the years, we’ve converged the technical-detail questionnaire that we ask providers to fill out during the Magic Quadrant research process, with the Gartner for Technical Professionals (GTP) document that we produce to guide buyers on evaluating providers. This has resulted in nearly 250 service traits that the Evaluation Criteria document categorizes as Required (almost all Gartner clients are likely to want these things and these have the potential to be showstoppers if missing), Preferred (many will want these things), and Optional (use-case-specific needs). This gives us a consistent set of formal definitions for service features — things you can put a clear yes/no to. As a buyer, you can use the Evaluation Criteria to score any cloud IaaS provider — and even score your own IT department’s private cloud.
In the course of doing this particular Magic Quadrant, providers fill out very detailed questionnaires that list these service features and capabilities (broken down even more granularly than in the Evaluation Criteria), indicating whether their service has those traits, and they’re also asked to provide evidence, like documentation. We also ask them to provide other information like the location of their data centers, languages supported across various aspects of service delivery (like portal localization and tech-support languages spoken), a copy of their standard contract and SLAs, and so forth. We score those questionnaires (and check service features against documentation, and with hands-on testing if need be). We also score things like the buyer-friendliness of contracts, based on the presence/absence of particular clauses. Those component scores are used in many different individual scoring categories within the Magic Quadrant.
We also produce a set of In-Depth Assessments for the providers that our clients are most interested in evaluating. The In-Depth Assessments are detailed documents that score an individual provider against the Evaluation Criteria; for every criteria, we explain how the provider does and doesn’t meet it, and we provide links to the corresponding documentation or other evidence. The results of our hands-on testing are noted, as well. For many buyers, this minimizes the need to conduct an RFP that dives into the technical solution; here we’ve done a very detailed fact-based analysis for you, and the provider has verified the accuracy of the information. (Buyer beware, though: Providers sometimes produce something that looks like one of these assessments, even quoting the Gartner definitions, but with their own more generous self-assessment rather than the stringent Gartner-produced assessment!)
Then, we produce Critical Capabilities for Public Cloud IaaS (2016 update still in progress). This technical assessment looks at a single public cloud IaaS offering from each of the providers included in the Magic Quadrant. The same technical traits used in the other assessments are used here, but they are divided into categories of capabilities, and those capabilities are weighted in a set of common use cases. You can also customize your own set of weightings. In addition to providing quantitative scores, we summarize, in a fair amount of detail, the technical capabilities of each evaluated provider. This allows you to get a sense of what providers are likely to be right for your needs, without having to go through the full deep-dive of reading the In-Depth Assessments. (Critical Capabilities are also available to all Gartner clients and reprints may be offered by providers on their websites, whereas the In-Depth Assessments are only available to GTP clients.)
Performance, and price-performance, is important to many buyers. Gartner provides hardware benchmarking via a SaaS offering called Tech Planner. We offer a Cloud Module within Tech Planner that uses technology that we derived from our acquisition of CloudHarmony. We conduct continuous automated testing on many cloud IaaS providers, including all providers in the Magic Quadrant. We benchmark compute performance for the full range of VMs and bare-metal cloud servers offered by the provider, along with storage performance and network performance; we use this to calculate price-performance metrics. We monitor the availability of their services across the globe. We track provisioning times. All this data is used as objective components to the scores within the Magic Quadrant. Much of this data is directly available to Tech Planner customers, who can use these tools to calculate performance-equivalencies as well as determine where workloads will be most cost-effective.
Finally, we collect end-user reviews of cloud IaaS providers, called Peer Insights. IT leaders (who do not need to be Gartner clients) can submit reviews of their providers; we verify that reviews are legitimate, and it’s one of the very few places where you’ll see enter senior IT executives and architects writing detailed reviews of their providers. We use this data, along with vendor-provided customer references, and the many thousands of clients conversations we have each year with cloud IaaS buyers, as part of the fact base for our Magic Quadrant scoring.
More than a dozen analysts are directly involved in all of these assessments, and many more analysts provide peer-review input into those assessments. It’s an enormous effort, involving a great deal of teamwork, to produce this body of interlinked research. We’re always trying to improve its quality, so we welcome your feedback!
You can DM me on Twitter at @cloudpundit or send email to lydia dot leong at gartner.com.
Read Complimentary Relevant Research
Predicts 2017: Artificial Intelligence
Artificial intelligence is changing the way in which organizations innovate and communicate their processes, products and services. Practical...
View Relevant Webinars
The Education CIO Challenge: IT Is a Team Sport
This video will outline key Education CIO challenges and recommendations based on business and technology trends in education as well...
Comments or opinions expressed on this blog are those of the individual contributors only, and do not necessarily represent the views of Gartner, Inc. or its management. Readers may copy and redistribute blog postings on other blogs, or otherwise for private, non-commercial or journalistic purposes, with attribution to Gartner. This content may not be used for any other purposes in any other formats or media. The content on this blog is provided on an "as-is" basis. Gartner shall not be liable for any damages whatsoever arising out of the content or use of this blog.