The 17 New Product Announcements from AWS re:Invent so far in 2017
We are near the end of Amazon’s annual re:Invent conference in Las Vegas and the cloud-computing behemoth has already announced 17 completely new products and upgrades for current products. I wanted to take the time to compile the full list of the AWS re:Invent announcements to give you a brief description of the new product or service and the ability to check out the full release.
Keep in mind, most of the descriptions are selected quotes from the release articles because, well, AWS is pretty good at explaining their own tech.
In no specific order at all, here are the announcements that have come out of the event so far:
Guard duty – Continuous Security Monitoring & Threat Detection
GuardDuty is a machine learning powered security tool that is continuously analyzing multiple data streams. These streams are a combination of public feeds like threat intelligence feeds, malicious IP addresses, and devious domains, while also monitoring for any unauthorized or seemingly malicious activity in your AWS accounts.
“GuardDuty operates completely on AWS infrastructure and does not affect the performance or reliability of your workloads. You do not need to install or manage any agents, sensors, or network appliances. This clean, zero-footprint model should appeal to your security team and allow them to green-light the use of GuardDuty across all of your AWS accounts.”
Bare Metal Instances With Direct Access to Hardware
“[VMware] told us that they wanted to run their virtualization stack directly on the hardware, within the AWS Cloud, giving their customers access to the elasticity, security, and reliability (not to mention the broad array of services) that AWS offers.”
After creating this bare metal access for VMware, Amazon has just launched a preview of the i.3 metal instance so that it is available for all AWS customers!
AWS AppSync – Build Data-Driven Apps with Real-Time and Off-Line Capabilities
AWS AppSync aims to bring the power of GraphQL real-time data retrieval and dynamic query execution in the form of a new managed service by Amazon. “With AppSync developers can simplify the retrieval and manipulation of data across multiple data sources with ease, allowing them to quickly prototype, build and create robust, collaborative, multi-user applications.”
H1 Instances – Fast, Dense Storage for Big Applications
“The new H1 instances are designed specifically for [ running very large MapReduce clusters, hosting distributed file systems, Using Apache Kafka to process voluminous log files, and so forth]. In comparison to the existing D2 (dense storage) instances, the H1 instances provide more vCPUs and more memory per terabyte of local magnetic storage, along with increased network bandwidth, giving you the power to address more complex challenges with a nicely balanced mix of resources.”
Amazon MQ – Managed Message Broker Service for ActiveMQ
AmazonMQ is a managed message broker service for the open-source Apache ActiveMQ that will allow you to get started with just a few clicks. Essentially, Amazon will take administer and take responsibility for broker provisioning, patching, failure detection & recovery for high availability, and message durability. Read the full release here >>
Amazon Sumerian – An Easy Way to Create VR, AR, and 3D Experiences
“The Amazon Sumerian service enables you to create, build, and run virtual reality (VR), augmented reality (AR), and 3D applications with ease. You don’t need any 3D graphics or specialized programming knowledge to get started building scenes and immersive experiences. “
“You can import FBX, OBJ, and Unity projects in Sumerian, as well as upload your own 3D assets for use in your scene. In addition, you can create digital characters to narrate your scene and with these digital assets, you have choices for the character’s appearance, speech and behavior.”
AWS media services – Process, Store, and Monetize Cloud-Based Video
“Today we are launching an array of broadcast-quality media services, each designed to address one or more aspects of the challenge that I outlined above. You can use them together to build a complete end-to-end video solution or you can use one or more in building-block style.”
“In true AWS fashion, you can spend more time innovating and less time setting up and running infrastructure, leaving you ready to focus on creating, delivering, and monetizing your content. The services are all elastic, allowing you to ramp up processing power, connections, and storage and giving you the ability to handle million-user (and beyond) spikes with ease.”
DeepLens – Get Hands-on Experience With Deep Learning
AWS is taking a deep dive into the world of AI hardware with their new product DeepLens. DeepLens is a small camera that lets you take a hands-on approach to training AI models with Machine learning programs built into the hardware.
The camera packs a lot of power into a small device, including: “a 4 megapixel camera that can capture 1080P video, accompanied by a 2D microphone array. An Intel Atom® Processor provides over 100 GLOPS of compute power, enough to run tens of frames of incoming video through on-board deep learning models every second. DeepLens is well-connected, with dual-band Wi-Fi, USB and micro HDMI ports. Wrapping it all up, 8 gigabytes of memory for your pre-trained models and your code, makes this a powerful yet compact device.”
Amazon Neptune – A Fully Managed Graph Database Service
Amazon Neptune is a “fast and reliable graph database service that makes it easy to gain insights from relationships among your highly connected datasets. The core of Amazon Neptune is a purpose-built, high-performance graph database engine optimized for storing billions of relationships and querying the graph with milliseconds of latency. Delivered as a fully managed database, Amazon Neptune frees customers to focus on their applications rather than tedious undifferentiated operations like maintenance, patching, backups, and restores.”
SageMaker – Accelerated Machine Learning
“Amazon SageMaker is a fully managed end-to-end machine learning service that enables data scientists, developers, and machine learning experts to quickly build, train, and host machine learning models at scale. This drastically accelerates all of your machine learning efforts and allows you to add machine learning to your production applications quickly.”
Here are the 3 main components:
- Authoring: Zero-setup hosted Jupyter notebook IDEs for data exploration, cleaning, and preprocessing. You can run these on general instance types or GPU powered instances.
- Model Training: A distributed model building, training, and validation service. You can use built-in common supervised and unsupervised learning algorithms and frameworks or create your own training with Docker containers. The training can scale to tens of instances to support faster model building. Training data is read from S3 and model artifacts are put into S3. The model artifacts are the data dependent model parameters, not the code that allows you to make inferences from your model. This separation of concerns makes it easy to deploy Amazon SageMaker trained models to other platforms like IoT devices.
- Model Hosting: A model hosting service with HTTPs endpoints for invoking your models to get realtime inferences. These endpoints can scale to support traffic and allow you to A/B test multiple models simultaneously. Again, you can construct these endpoints using the built-in SDK or provide your own configurations with Docker images.
AWS Rekognition Video – Deep Learning Based Video Recognition
Amazon is adding to their current Rekognition product with the ability to analyze video.
“Amazon Rekognition Video is a new video analysis service feature that brings scalable computer vision analysis to your S3 stored video, as well as, live video streams. With Rekognition video, you can accurately detect, track, recognize, extract, and mod
erate thousands of objects, faces, and content from a video.”
Amazon Translate – Real-time Language Translation
“Amazon Translate is a high-quality neural machine translation service that uses advanced machine learning technologies to provide fast language translation of text-based content and enable the development of applications that provide multilingual user experiences. The service is currently in preview and can be used to translate text to and from English and the supported languages.”
Amazon Transcribe – Accurate Speech to Text at Scale
Amazon Transcribe is able to “analyze audio files stored on Amazon Simple Storage Service (S3) in many common formats (WAV, MP3, Flac, etc.) by starting a job with the API. You’ll receive detailed and accurate transcriptions with timestamps for each word, as well as inferred punctuation.”
Amazon Kinesis – Serverless Video Ingestion and Storage For Vision-Enabled Apps
“You now have the power to ingest streaming video (or other time-encoded data) from millions of camera devices without having to set up or run your own infrastructure. Kinesis Video Streams accepts your incoming streams, stores them durably and in encrypted form, creates time-based indexes, and enables the creation of vision-enabled applications. You can process the incoming streams using Amazon Rekognition Video, MXNet, TensorFlow OpenCV, or your own custom code, all in support of the the cool new robotics, analytics, and consumer apps that I know you will dream up.”
Amazon Comprehend – Continuously Trained Natural Language Processing
“Amazon Comprehend analyzes text and tells you what it finds, starting with the language, from Afrikans to Yoruba, with 98 more in between. It can identify different types of entities (people, places, brands, products, and so forth), key phrases, sentiment (positive, negative, mixed, or neutral), and extract key phrases, all from text in English or Spanish. Finally, Comprehend‘s topic modeling service extracts topics from large sets of documents for analysis or topic-based grouping.”
“The first four functions (language detection, entity categorization, sentiment analysis, and key phrase extraction) are designed for interactive use, with responses available in hundreds of milliseconds. Topic extraction works on a job-based model, with responses proportional to the size of the collection.”
AWS IoT Analytics – Delivering IoT Analytics at Scale and Faster Than Ever Before
“AWS IoT Analytics is a fully managed service of AWS IoT that provides advanced data analysis of data collected from your IoT devices. With the AWS IoT Analytics service, you can process messages, gather and store large amounts of device data, as well as, query your data. Also, the new AWS IoT Analytics service feature integrates with Amazon Quicksight for visualization of your data and brings the power of machine learning through integration with Jupyter Notebooks.”
Amazon Free RTOS – Enabling Billions of Devices to Securely Benefit from the Cloud
“Amazon FreeRTOS is an IoT microcontroller operating system that simplifies development, security, deployment, and maintenance of microcontroller-based edge devices. Amazon FreeRTOS extends the FreeRTOS kernel, a popular real-time operating system, with libraries that enable local and cloud connectivity, security, and (coming soon) over-the-air updates.”
And More to Come….
Since re:Invent has not come to a close yet I will continue to add new product releases to this article throughout the week. Follow TriFin Labs on LinkedIn if you want an easy way to stay up to date with all of the new product offerings announced at this years re:Invent!
Lastly, if you are looking to deploy a solution to AWS, we have a team of engineers just waiting to get their hands dirty with all of these new products. You can get a free 15-minute consultation with one of them to talk about how you can take advantage of all that AWS has to offer by contacting us today.
About Shane Rostad
Shane Rostad is a marketing manager for TriFin Labs that loves to share his knowledge and learnings about tech through writing. When he's not reading you can find him exploring Florida's parks or loitering in a local coffee shop.