Amazon Reports Q4 Sales Up 20% to $72.4B

Amazon Web Services (AWS) announced several enterprise customers during the quarter: Ellie Mae, Korean Air, Santander’s Openbank, and Pac-12 are going all-in on AWS; Mobileye and Guardian Life Insurance named AWS their preferred public cloud provider; Amgen will leverage AWS as its strategic infrastructure provider for the vast majority of its cloud infrastructure; and National Australia Bank announced they’ve chosen AWS as their long-term strategic cloud provider.

Amazon Web Services (AWS) announced several enterprise customers during the quarter: Ellie Mae, Korean Air, Santander’s Openbank, and Pac-12 are going all-in on AWS; Mobileye and Guardian Life Insurance named AWS their preferred public cloud provider; Amgen will leverage AWS as its strategic infrastructure provider for the vast majority of its cloud infrastructure; and National Australia Bank announced they’ve chosen AWS as their long-term strategic cloud provider.

AWS continued to expand its infrastructure in 2018 to best serve customers, launching the AWS GovCloud (US-East) and AWS Europe (Stockholm) Regions, and announcing plans for both the AWS Africa (Cape Town) as well as the AWS Europe (Milan) Regions. AWS now provides 60 Availability Zones across 20 infrastructure regions globally, with another 12 Availability Zones and four regions in Bahrain, Hong Kong SAR, Italy, and South Africa all coming online by the first half of 2020.

AWS added significant Amazon SageMaker capabilities, making it easier for customers to build, train, and run machine learning models: Amazon SageMaker Ground Truth produces high-quality labeled training data with easy access to public and private human labelers, saving time and complexity, and reducing costs by up to 70% when compared to human annotation; AWS Marketplace for Machine Learning includes over 150 algorithms and models (with more coming every day) that can be deployed directly to Amazon SageMaker; Amazon SageMaker Neo is a deep learning model compiler that lets customers train models once, and run them anywhere with up to 2x improvement in performance.

AWS placed reinforcement learning in the hands of all developers for the first time with the announcement of Amazon SageMaker RL, AWS DeepRacer, and the AWS DeepRacer League. Amazon SageMaker RL is the cloud’s first managed reinforcement learning service that allows any developer to build, train, and deploy with reinforcement learning through managed reinforcement learning algorithms; AWS DeepRacer is a 1/18th scale autonomous model race car driven using reinforcement learning models, trained using Amazon SageMaker, and is designed to give developers hands-on experience with machine learning; and the AWS DeepRacer League is the world’s first global autonomous racing league, open to everyone, allowing developers to put their skills to the test and race their cars and models against one another for a chance at prizes and glory.

AWS announced AWS Outposts, fully managed and configurable compute and storage racks that allow customers to run compute and storage on-premises, while seamlessly connecting to the rest of AWS’s broad array of services in the cloud. AWS Outposts come in two variants; first, an extension of the fast-growing VMware Cloud on AWS service that runs on AWS Outposts; second, AWS Native Outposts that allow customers to run compute and storage on-premises using the same native AWS APIs and control plane used in the AWS cloud.

At re:Invent, AWS announced two purpose-built database services, Amazon Timestream, a fast, scalable, and fully managed time series database for IoT, industrial telematics, application monitoring, and DevOps applications, and Amazon Quantum Ledger Database (QLDB), a highly scalable, immutable, and cryptographically verifiable ledger. AWS also announced Amazon DocumentDB, a fast, scalable, highly available, and fully managed document database service that supports MongoDB workloads. Developers can use the same MongoDB application code, drivers, and tools as they do today to run, manage, and scale workloads on Amazon DocumentDB and enjoy improved performance, scalability, and availability without having to worry about managing the underlying infrastructure.

AWS introduced Amazon Managed Blockchain a new service to help companies build applications where multiple parties can execute transactions without the need for a trusted, central authority. Amazon Managed Blockchain makes it easy to create and manage scalable blockchain networks using the popular, open source Ethereum and Hyperledger Fabric frameworks. With a few clicks in the AWS Management Console, customers can set up a blockchain network that can span multiple AWS accounts and scale to support thousands of applications and millions of transactions.

AWS announced six new instance offerings for Amazon Elastic Compute Cloud (Amazon EC2): A1 instances, which are powered by custom-designed AWS Graviton processors, based on the Arm architecture, for scale-out workloads; P3dn GPU instances, which are ideal for distributed machine learning and high performance computing applications, feature 100 gigabits per second (Gbps) network bandwidth, and give customers the most powerful and capable machine learning instances in the cloud; C5n instances, which deliver 100 Gbps network bandwidth, the most in the public cloud, for running advanced compute-intensive workloads; as well as new general purpose (M5 and T3) and memory-optimized (R5) instance types with AMD EPYC processors that are 10% less expensive than the current M5, T3, and R5 instances. The AMD-based instances provide additional options for customers who are looking to achieve cost savings on their Amazon EC2 compute environment for a variety of workloads, such as microservices, low-latency interactive applications, small and medium databases, virtual desktops, development and test environments, code repositories, and business applications.

AWS announced two custom chips: AWS Inferentia and AWS Graviton. AWS Inferentia is a high performance machine learning inference chip, custom designed by AWS, to help customers improve performance and lower the cost of running their inference workloads. AWS Inferentia will provide hundreds of teraflops per chip and thousands of teraflops per Amazon EC2 instance for multiple frameworks (including TensorFlow, Apache MXNet, and PyTorch), and multiple data types (including INT-8 and mixed precision FP-16 and bfloat16). AWS Graviton is a custom designed general purpose processor that uses the Arm instruction set. Offered in the new A1 instance family, AWS Graviton leverages AWS’s expertise in building hyperscale cloud systems, and is ideal for customers with scale out workloads.

AWS announced four new services that provide automation and prescriptive guidance to help customers build more quickly on AWS: AWS Control Tower, AWS Security Hub, AWS Lake Formation, and AWS Backup. AWS Control Tower gives customers an automated “landing zone” that makes it easy to set up their multi-account environment and continuously govern their AWS workloads with rules for security, operations, and compliance; AWS Security Hub is a central place to manage security and compliance across an AWS environment so that customers can quickly see their AWS security and compliance state in one comprehensive view; AWS Lake Formation makes it much easier for customers to build a secure data lake by simplifying and automating many of the complex manual steps usually required, including collecting, cleaning, and cataloging data; and AWS Backup is a centralized backup service that makes it faster and simpler for customers to back up their data across AWS services and on-premises, helping them more easily meet their business and regulatory backup compliance requirements.

AWS continued to expand on the industry’s broadest and most capable set of storage offerings with the introduction of the Amazon FSx family and additional storage classes for Amazon Simple Storage Service (S3). Amazon FSx for Windows File Server and Amazon FSx for Lustre are fully managed file system services that provide cost effective, scalable file storage for Windows and compute-intensive workloads. Amazon S3 Intelligent-Tiering automatically optimizes customers’ storage costs for data with unknown or changing access patterns by moving data to the most cost-effective storage tier; Amazon S3 Glacier Deep Archive delivers the lowest cost storage from any cloud provider at just $0.00099 per GB per month, making it ideal for customers who have large data sets they want to retain for a long time, letting them eliminate the cost and management of tape infrastructure, while ensuring that their data is well preserved for future use and analysis.