Five Disruption Vectors were chosen that highlight the suitability of each vendor to both the current and future of MLaaS platforms. Tech buyers can use the Disruption Vector analysis to assist in selecting products that best match their own situation.

Key findings of this analysis include the following points.

• A breakdown of the various aspects of machine learning (ML), and how each vendor scores in the disparate categories for image recognition and analysis, voice and speech analysis, and voice response shows that many vendors differentiate themselves with not only the number of raw services, but the capability of each service.
• It is important to compare the different vendor clouds on which these MLaaS services run, especially with the perspective of how that platform affects MLaaS workloads and costs, taking into account raw number of services.
• Developer productivity should be a paramount concern when deciding upon a vendor. Ancillary concerns like network speed, streaming capabilities, analytics, and other factors can dramatically impact developer productivity as well as end-user satisfaction. Additionally, many vendors like IBM and Microsoft have started to bundle their MLaaS services into solutions for particular use cases or verticals, reducing the time-to-market for apps that fit into those boxes.
• As a part of developer productivity, support may also be a concern, especially if machine learning is a discipline new to your organization. Most vendors roll their ML support into a general “cloud support” contract, but Google has created a dedicated services team specifically for ML.
• Google, Microsoft, and IBM are in a dead heat for top provider. AWS is showing up as 2^nd in the MLaaS arena, with their newly announced ML-specific services. It’s still too early to determine who will emerge as the clear leaders in the future. Although significant differences exist between the vendors, as features and capabilities coalesce around a standardized feature list, vendor offerings will start to closely resemble each other.
• Machine Learning is a broad umbrella under which many individual projects and use cases are grouped. Therefore, at the end of each vendor’s section, we call out several specific use cases and rate the individual platforms as useful for particular use cases.

Key:

• Number indicates company’s relative strength across all vectors
• Size of ball indicates company’s relative strength along individual vector

Source: Gigaom

The post Enterprise Machine Learning appeared first on Gigaom.

• A quick introduction to the value of containers and how they compare to VM-based services like Amazon Elastic Cloud Compute (Amazon EC2).
• A look at the importance of launching containers in the cloud and why this model is so beneficial from efficiency, maintenance, and cost perspectives.
• An in-depth review of CaaS offerings available at the “Top Three” cloud providers: Google Cloud Platform (GCP), Amazon Web Services (AWS), and Microsoft Azure.

The post Containers in the Cloud: What to look for appeared first on Gigaom.

This report will help IT organizations and application development teams prepare for the fast-approaching future state of modern software development and benefit from an increased focus on code quality and security.

Key findings of this report include:

• Code quality and security can no longer be an afterthought bolted onto the software development life cycle (SDLC).
• Tools such as test-driven development (TDD) are ill suited for today’s dynamic, heavily integrated stacks.
• Modern software development is a fast moving, highly fragmented, and highly distributed supply chain, with parts built by disparate teams, running on disparate platforms.
• Previous vulnerabilities such as Shellshock and Heartbleed highlight the fact that companies must increase code quality and security. Richer, faster end-to-end tests are needed, and these tests will require investment in appropriate resources, tools, and infrastructure.
• DevOps, continuous integration (CI), and continuous delivery (CD) are the preferred ways software companies enable development, testing, and delivery within fast moving, dynamic stacks.
• Static code-analysis tools add agility by enforcing code and security standards — common code problems that traditional testing may miss. This agility helps new developers understand inherited code.

Thumbnail image courtesy: iStock/Thinkstock

The post Coding to standards and quality: supply-chain application development appeared first on Gigaom.

Key findings in this Sector Roadmap include:

• The “talent crunch” will continue to be largest factor influencing adoption of a platform.
• Platforms that provide full end-to-end solutions from the integrated development environment to the back-end offer the most benefits for developer productivity and security.
• Open and plugable approaches are best-suited to take advantage of the rapid changes likely to continue in the mobile space.
• Network speed, MBaaS, analytics, and other factors can dramatically affect end user experience and developer productivity.
• Most vendors have their eyes on the IoT space and can offer a consolidated approach to deploy apps into yet-unknown platforms and form factors.

Key:

• Number indicates a company’s relative strength across all vectors
• Size of ball indicates a company’s relative strength along an individual vector

Source: Gigaom Research

Thumbnail image courtesy: iStock/Thinkstock

The post Sector Roadmap: cross-platform mobile development appeared first on Gigaom.

One result is that decisions made during design can be barriers to performance down the road. When new platforms launch, performance is typically an afterthought to be optimized later. This is short-sighted: Lack of performance out of the gate can quickly doom a web or mobile-based app (both referred to here as apps). It is imperative that performance considerations play a front-seat role in the entire UX equation.

User experience is heavily dependent on underlying technical structure, and those structural choices are often dictated by usability. To navigate the possibilities of native, hybrid, and responsive designs and the myriad backend services that support them, UX designers must have an intimate knowledge of the limits to which they can push app performance. This report will help designers make educated, value-driven decisions about app experiences.

Key findings include:

• The separation of an application’s content and logic is a necessary first step toward increased performance, but it must also be paired with a strategy that places both as close to the user as possible.
• By speeding the delivery of both static and dynamic content, a content delivery network (CDN) is the most effective tool to increase performance, usability, and user satisfaction.
• Cross-platform compilers abstract device-specific considerations from front-end design, increasing developer freedom and efficiency.
• A devops approach that pairs agile project management practices with case-specific tools is essential for fast, high-quality iterations.

Thumbnail image courtesy: iStock/Thinkstock

The post Total experience quality: integrating performance, usability, and application design appeared first on Gigaom.

The possibilities are staggering, but these “things” represent some significant challenges to app developers. Developers, in particular, will have to cope with an unprecedented explosion of supported devices and form factors, extensive network optimizations to make both the front end and back end more responsive, highly capable edge devices to which more processing may (and should) be pushed, and finally, a plan to capture, process, and wrangle business value and from all of the data these devices generate.

While each development project will require different skills, and the IoT is still in its earliest stages, there are certain tools with which budding IoT developers should be familiar. These include:

• IaaS, MBaaS, and REST APIs
• Cross-platform development tools
• CDNs and data streaming services (like PubNub)
• Big data ingestion, storage, and processing tools like Hadoop/HDFS, Spark, Storm, and Flume

Thumbnail image courtesy of iStock/Thinkstock.

The post A developer’s checklist for deploying the internet of things appeared first on Gigaom.

Key findings include:

• Public cloud infrastructure is excellent for many use cases, but it exposes only the most common 70 percent or so of the functionality that a business may need.
• The cost, control, and security benefits of a data center can be significant differentiators for business applications.
• Cloud-plus-data-center provides the best option for most businesses, maximizing cost, functionality, and agility benefits.

The post Cloud and data centers join forces for a new IT platform for internet applications and businesses appeared first on Gigaom.

This report defines PaaS, investigates the available options, and then supplies concrete recommendations for what to use where and when.

• PaaS solutions have been in the background for years, but they now range from traditional PaaS, which simply abstracts out the infrastructure for a single hosting provider, to PaaS solutions that provide model-based app building and deploy to public, private, and hybrid clouds.
• Organizations should be investigating choices and choosing a PaaS provider now to guard against cloud-provider lock-in.

The number of savvy developers a company has combined with its availability are primary criteria for determining if PaaS is the right choice and how much productivity gain can be realized.

The post Determining when PaaS is appropriate appeared first on Gigaom.

The typical enterprise will support multiple methodologies, and making them work together isn’t easy. From budget forecasting to performance benchmarking and accountability, agile presents new disruptions to traditional processes. At the same time, its more granular, responsive approach and the tools that support it can bring new efficiencies to the projects, teams, and organizations implementing them. This report will examine the current state and the future of the multi-methodology enterprise and examine procedural and technological changes that can help enterprises integrate agile methodologies into a larger ecosystem.

Key highlights include:

• A high-level overview of the palette of project-management methodologies available to enterprises, and how and where each can provide value.
• Discussion of the cultural, technical, and political barriers to agile adoption in the enterprise, and how focus on culture, people, and product are requirements for an organization planning on using agile.
• An examination of the software tools available that allow teams to collaborate and correspond in an agile fashion, and an investigation of how important tool choice is for the internal perception and support of agile.
• A look at how independent, and seemingly non-complementary methodologies can be threaded together in even large, complicated enterprise-level projects.
• Concrete direction and advice for CIOs, CTOs, and project managers on how to either introduce or expand agile adoption at their organization.

The post How to unlock the promise of agile in the enterprise appeared first on Gigaom.

As this report will demonstrate, the rules are changing quickly, but the good news is that, because of more cross-platform tools like Xamarin and database-sync capabilities, the game is getting easier to play. CIOs, CTOs, application developers, architects, and cloud service providers need to understand that:

• Tablets and smartphones are becoming more powerful every year, yet most mobile apps remain server-centric and network-intensive.
• As more power gets pushed to the edge, both users and developers will want to leverage that power. As more device types come into being, cross-platform, data-centric app design will become crucial.
• Peer-to-peer communication and client-side storage will free apps of network latency and connectivity concerns, extending interactions beyond today’s thin client-network dependence. They also will pose significant challenges to security and data integrity.
• The drastic and foundational changes coming in all layers of the mobile space—network, hardware, software, and, most importantly, data storage—require us to revisit many chapters of our app-design playbook.

Thumbnail image courtesy of flickr user Pays de Montfort en Brocéliande

The post Hybrid application design: balancing cloud-based and edge-based mobile data appeared first on Gigaom.