AWS Summit 2018: Amazon Targets Enterprise Developers for App Cloud Migration via ML, Microservices/Containers, and Serverless Computing

Charlotte Dunlap – Principal Analyst, Application Platforms

Summary Bullets:

• Amazon’s high-value services and cloud status make it a competitive threat against PaaS rivals

• Customers are concerned about the cost and effort involved in migrating applications from data centers to the cloud

Amazon has built a behemoth cloud business through its compute power and rudimentary platform services, bringing the notion of IT as-a-service to the masses early on. It has no intention of losing its popular cloud status to technology companies that are innovating in advanced cloud technologies such as AI/ML, chatbots, microservices/containers, and serverless computing.

Executives noted to attendees that this week’s conference was not a sales event, but about providing the 9,000 developers and systems admins with deep technical sessions, aimed at bringing the millions of businesses active on AWS into new realms of DevOps capabilities. Headlining the technical keynotes were Werner Vogels, VP and CTO, and Matt Wood, GM AI. New big name global customers and massive cost cuts gained by dumping traditional data center technology for cloud services was a key theme buoyed by graphics illustrating a fraction of the cost associated with moving and maintaining workflows onto the cloud.

Despite the heavy emphasis on new innovations – with Amazon announcing general availability of products initially announced at last fall’s AWS re:Invent – session attendee questions aimed at Amazon speakers centered on:

• Cost expectations of complex migrations

• How systems administrators transform to Python developers

• Whether Amazon has the necessary professional services to tackle massive transformations

In response, Amazon held up marquee customers running mission critical apps in the cloud as proof of the strength of its services and solutions, trying to demonstrate that it’s not only young businesses that are moving to AWS, but larger enterprises too. Amazon also noted the growing army of third party systems integrators that are available for helping enterprises’ cloud integrations.

Executives used the keynote spotlight to hammer home messaging on how it is attracting enterprise developers through innovation that will carry their cloud migration projects to new levels of operational and cost efficiency, while speeding the app development and iterative process. This is accomplished specifically through recently released integrations of ML (SageMaker), serverless computing (Lambda and Aurora Serverless), and containers (EKS and Fargate).

A recap of key AWS developer tools, architectures and technologies:

• Amazon’s recent release of SageMaker, a solution designed to make it easier and faster to build, train, and deploy ML algorithms as part of app development, was a key part of executives’ messaging during the conference. The technology complements Gluon, launched recently by Microsoft and AWS, a new DL library that uses high-level APIs, and pre-built/modular building blocks that enable developers to build and train their neural networks more quickly.

• Amazon’s mature Lambda serverless computing technology was recently enhanced via Serverless Application Repository platform, including a management console, a set of APIs, and CLI to better address infrastructure requirements, supported by Serverless Application Model (SAM).

• Amazon Aurora Serverless, in preview, builds on Aurora, and lets enterprises pay only for the database resources they use, down to the second. It’s aimed at supporting workloads that are highly variable.

• AWS Cloud9 is a cloud-based IDE for writing, running, and debugging code via a browser. AWS Code Services include CodeBuild, a managed build service that compiles source code, runs tests, and CodeDeploy, to automate code deployments to instances including Amazon EC2 and on-premises servers.

• Amazon Elastic Container Service for Kubernetes (EKS) is a managed platform for running container-based systems, with Fargate supporting more granular control over the infrastructure running the container apps.

• AWS DeepLens: a wireless deep learning enabled video camera to help developers (illustrated by examples including identifying dogs in a park, and reading children’s books upon seeing book titles).

Amazon is able to build on its early roots of providing customers with cloud services that are continually being enhanced as DevOps models evolve within its customer base. Amazon rivals, however, founded on providing enterprises with software solutions, are in position where they’re able to resonate with customers’ operations teams looking to make gradual moves to the cloud, initially through private/hybrid cloud scenarios. A number of Amazon’s conference sessions illustrated impressive migrations by customers’ operations teams able to largely shut down data centers in exchange for native cloud-based app development and deployments or lift and shift migrations. Those speakers were quick to admit, however, that the process is painful and requires an extremely high level of expertise, including a shift from systems administrator professionals to application developers, architects, and data scientists. Amazon would be wise to formalize and highlight any new programs around its professional services offering, which would help to reduce the investment requirements of these migrations.

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