Unable to attend re:Invent 2018, or missed the Keynote LiveStream? Don’t worry, Onica has you covered with a full recap of everything you missed…
AWS CEO Andy Jassy took the stage Wednesday morning at Amazon Web Services’ re:Invent 2018 conference, held annually in Las Vegas. This year’s event was host to record-breaking numbers, with 50,000 attendees from all over the world, and over 100,000 tuning in to watch Andy Jassy’s keynote LiveStream.
Jassy began his keynote articulating AWS’ leading position in the cloud market. He shared metrics around market share (currently @ 51.8 percent), pace of innovation, and depth of features compared to other cloud vendors. He called out key differentiators and product enhancements across the depth and breadth of security and compute capabilities, with emphasis on serverless and containers. On the subject of cloud storage Jassy lingered a bit, drilling down into what sets AWS apart in the context of block, object, and file storage as well as advanced data transfer capabilities. All in all, it provided a clear sense of how far AWS has come, the current state of the platform, and what we can expect in the future from the company.
As with previous re:Invent keynotes, Jassy was joined onstage by some of AWS’ more visible customers, who shared their stories about how their respective companies have found success on AWS. Dean DelVecchio, CIO of Guardian, spoke about how AWS enabled his Fortune 250 Insurance company to migrate 200 workloads to the cloud in 12 months, and ultimately shutter 100 percent of their legacy data centers. Ross Brawn, Managing Director, Motor Sports and technical director for the Formula One Group, also shared his organization’s success stories on AWS.
But, the most interesting news to emerge from the keynote was around new AWS products, and features added to existing offerings. The theme of the day was “Builders want it all, and they want in now,” underscored by a live performance of Queen’s “I Want it All” by an onstage band. Jassy talked about a “new kind of builder,” who wants to deploy new capabilities on AWS without becoming a subject matter expert on the underlying technology. Below is a quick recap of all the product announcements shared by Jassy in Wednesday’s keynote, with emphasis on these new kinds of democratized tools for these new kinds of builders:
S3 Glacier Deep Archive
This new storage class for S3 is designed for long-term data archival and is the lowest cost storage from any cloud provider. Priced from just $0.00099/GB-mo (less than one-tenth of one cent, or $1.01 per TB-mo), the cost is comparable to tape archival services. Data can be retrieved in 12 hours or less, and there will also be a bulk retrieval option that will allow customers to inexpensively retrieve even petabytes of data within 48 hours.
Amazon FSx for Windows File Server
A fully managed native Microsoft Windows file system so you can easily move your Windows-based applications that require file storage to AWS. Built on Windows Server, Amazon FSx provides shared file storage with the compatibility and features that your Windows-based applications rely on, including full support for the SMB protocol and Windows NTFS, Active Directory (AD) integration, and Distributed File System (DFS). Amazon FSx uses SSD storage to provide the fast performance your Windows applications and users expect, with high levels of throughput and IOPS, and consistent sub-millisecond latencies.
FSX for Lustre
A fully managed file system that is optimized for compute-intensive workloads, such as high performance computing machine learning, and media data processing workflows. Many of these applications require the high performance and low latencies of scale-out, parallel file systems. Operating these file systems typically requires specialized expertise and administrative overhead, requiring you to provision storage servers and tune complex performance parameters. With Amazon FSx, you can launch and run a Lustre file system that can process massive data sets at up to hundreds of gigabytes per second of throughput, millions of IOPS, and sub-millisecond latencies.
AWS Control Tower
This service helps you automate the set up a well-architected multi-account AWS environment using a set of blueprints that embody AWS best practices. Guardrails, both mandatory and recommended, are available for high-level, rule-based governance. You will have access to an integrated dashboard so that you can keep a watchful eye over the accounts provisioned, the guardrails that are enabled, and your overall compliance status.
This Optical Character Recognition (OCR) service will help you to extract text and data from virtually any document. Powered by Machine Learning, it will identify bounding boxes, detect key-value pairs, and make sense of tables, while eliminating manual effort and lowering your document-processing costs.
While not available today, you can sign up here for the Amazon Textract preview.
AWS Security Hub
This service will allow you to to centrally view & manage security alerts and automate compliance checks within and across AWS accounts. It will aggregate security findings from AWS and partner services and present you with built-in and customizable insights that are unique to your environment.
AWS Lake Formation
This fully managed service will help you to build, secure, and manage a data lake. You’ll be able to point it at your data sources, have it crawl the sources, and pull the data into S3. Lake Formation uses Machine Learning to identify and de-duplicate data, and also performs format changes in order to accelerate analytical processing. You will also be able to define and centrally manage consistent security policies across your data lake and the services that you use to analyze and process the data.
DynamoDB Capacity on Demand
A flexible new billing option for DynamoDB capable of serving thousands of requests per second without capacity planning. DynamoDB on-demand offers simple pay-per-request pricing for read and write requests so that you only pay for what you use, making it easy to balance costs and performance. For tables using on-demand mode, DynamoDB instantly accommodates customers’ workloads as they ramp up or down to any previously observed traffic level. If the level of traffic hits a new peak, DynamoDB adapts rapidly to accommodate the workload.
This is a fast, scalable, fully managed time-series database that you can use to store and analyze trillions of events per day at 1/10th the cost of a relational database. It is optimized for data that arrives in time order and for queries that include a time interval. It is a great fit for IoT, industrial telemetry, app monitoring, and DevOps data. Timestream automates rollups, retention, tiering, and compression so time-series data can be efficiently stored and processed. Timestream’s query engine adapts to the location and format of data making it easier and faster to query time-series data.
Amazon Quantum Ledger Database
This fully managed ledger database will allow you to track and verify the complete history of changes to your application data. It uses an immutable journal that maintains a sequenced, cryptographically verifiable record of all changes that cannot be deleted or modified. It is scalable and easy to use, supports SQL queries, and lets it run 2-3x faster than common blockchain frameworks.
This is a managed blockchain service that lets you quickly create and manage a scalable blockchain network using popular open source frameworks, Hyperledger Fabric and Ethereum, that you can use to transact and securely share data. It is designed to scale to meet the needs of thousands of applications generating millions of transactions, with simple mechanisms to invite new members, manage certificates, and track operational metrics.
Amazon Elastic Inference (Amazon EI) is an accelerated compute service that allows you to attach just the right amount of GPU-powered inference acceleration to any Amazon EC2 or Amazon SageMaker instance type. This means you can now choose the instance type that is best suited to the overall compute, memory, and storage needs of your application, and then separately configure the amount of inference acceleration that you need.
A machine learning inference chip designed to deliver high performance at low cost. AWS Inferentia will support the TensorFlow, Apache MXNet, and PyTorch deep learning frameworks, as well as models that use the ONNX format. AWS Inferentia provides high throughput, low latency inference performance at an extremely low cost. Each chip provides hundreds of TOPS (tera operations per second) of inference throughput to allow complex models to make fast predictions. For even more performance, multiple AWS Inferentia chips can be used together to drive thousands of TOPS of throughput. AWS Inferentia will be available for use with Amazon SageMaker, Amazon EC2, and Amazon Elastic Inference.
SageMaker Ground Truth
SageMaker Ground Truth makes it easy for for you to efficiently and accurately label the datasets required for training machine learning systems. SageMaker Ground Truth can automatically label a portion of the dataset based on the labels done manually by human labelers. You can choose to use a crowdsourced Amazon Mechanical Turk workforce of over 500,000 labelers, your own employees , or one of the Amazon-pre-screened third party vendors listed on AWS Marketplace. SageMaker Ground Truth uses innovative algorithms and user experience (UX) techniques to improve the accuracy of human labeling. Over time, the model gets progressively better by continuously learning from the labels created by humans, for increased automatic labeling.
Marketplace for ML
Including over 150+ algorithms and model packages, with more coming every day, AWS Marketplace offers a tailored selection for vertical industries like retail (35 products), media (19 products), manufacturing (17 products), HCLS (15 products), and more. Customers can find solutions to critical use cases like breast cancer prediction, lymphoma classifications, hospital readmissions, loan risk prediction, vehicle recognition, retail localizer, botnet attack detection, automotive telematics, motion detection, demand forecasting, and speech recognition.
Amazon SageMaker RL
Amazon SageMaker RL builds on top of Amazon SageMaker, adding pre-packaged RL toolkits and making it easy to integrate any simulation environment. Training and prediction infrastructure is fully managed, so that you can focus on your RL problem and not on managing servers.
Amazon DeepRacer/AWS DeepRacer League
AWS DeepRacer is the fastest way to get rolling with reinforcement learning (RL), literally, with a fully autonomous 1/18th scale race car driven by reinforcement learning, 3D racing simulator, and a global racing league. Developers can train, evaluate, and tune RL models in the online simulator, deploy their models onto AWS DeepRacer for a real-world autonomous experience and compete in the AWS DeepRacer League for a chance to win the AWS DeepRacer Championship Cup.
A machine learning service that makes it easy for developers to create individualized recommendations for customers using their applications.
A fully managed service that uses machine learning to deliver highly accurate time series forecasts, based on the same technology used at Amazon.com
This service will bring AWS to your existing data center, providing a consistent, seamless experience across on-premises and the cloud, and giving you the ability to run on-premises applications with the exact same Application Programming Interfaces (APIs), consoles, features, hardware, and tools that you use on AWS.
Amazon RDS on VMware
This is a fully managed service for on-premises databases. You can set up, run, and scale databases in VMware vSphere using the same tools already enjoyed by hundreds of thousands of RDS customers. You can build low-cost high-availability hybrid environments, implement disaster recovery to AWS, and do long-term archival in S3.
Thanks for reading, we hope this recap was helpful for those who missed the keynote. Stay tuned for another recap of Thursday’s keynote with AWS CTO Werner Vogels, which never fails to disappoint! Until then, happy re:Inventing and be sure to subscribe to our blog for continued re:Invent 2018 updates!