The AWS Summit took place in Toronto on Thursday, October 3rd. AWS Summits are generally free to attend and take place in many different cities around the world. Positioned as a learning conference, they’re a fantastic way to connect with other people in the AWS world, learn about upcoming releases, chat with vendors, and more. The Toronto edition reportedly drew over 4500 people, who attended over 77 sessions, including a keynote presentation, chalk talks and breakout sessions, among other events. Here are four popular topics of conversation from the day:
The keynote speech featured Eric Gales, Country Manager of AWS Canada and Joshua Burgin, Tech Advisor to the SVP at AWS, as well as two customers discussing how AWS helped their businesses scale. Burgin really drove home the point about the summit being an educational one. And with over 165 services (and counting) available, it’s not hard to see why he called AWS the “broadest and deepest platform for today’s builders”. Lets dive into some of the highlights:
1. Amazon Aurora:
Amazon Aurora was one of the hottest topics of the day. Aurora is a fully managed relational database system built for the cloud. Having released the functionality that makes it compatible with MySQL in 2018, the next step was to do the same for PostgreSQL. And Amazon delivered over the past summer.
Why is this so exciting? Well, MySQL and PostgreSQL combine the agility, scalability and reliability of commercial databases with the simplicity and cost-savings generally only found in open-source databases. The exact same tools and applications used with MySQL and PostgreSQL can be used with Amazon Aurora. It’s up to five times faster than MySQL and up to three times faster than PostgreSQL. With the recent release of PostgreSQL, customers can create database instances that only run when needed and automatically scale up or down on demand. As with many Amazon Services, customers only pay for their usage and storage costs.
Last year, Amazon reported that Aurora was its fastest growing service in the history of AWS. We can’t wait to see what future functionality becomes available down the road.
2. VMware Cloud is on the Rise:
Jointly developed by AWS and VMware, the VMware Cloud service launched in August 2017. It’s an integrated cloud service that allows organizations to effortlessly migrate and extend their on-premises VMware vSphere-based environments to the AWS cloud. Although Amazon didn’t release hard figures, a report said that it now has four times the number of VMware Cloud on AWS customers than it did a year ago, and that deployment of virtual machines is rising. As privacy and data concerns escalate, we think hybrid cloud platforms will continue to gain momentum.
3. Watch out for Amazon Outposts:
Another hybrid solution offered by AWS, Amazon Outposts is a private, on-premises version of its public cloud infrastructure. Announced in December 2018 at Amazon’s re:Invent conference, the service will be available to use by the end of 2019.
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Outposts is an on-premise database center that extends either a Native AWS cloud environment or VMware Cloud on AWS. Services running on the Outpost can easily work with any AWS service or resource running in your center’s cloud. This service was built to run exclusively in connected, on-premises environments (for disconnected, remote environments, we recommend checking out Snowball Edge). In September, Matt Garman, VP of AWS Compute Services, wrote a post about Outposts, which goes into more detail about what customers can expect from it’s anticipated release.
4. AWS AI for improved customer experience:
We attended a chalk talk and lecture on how it’s possible to add intelligence to applications using AWS AI Services.
When Amazon went about designing these AI solutions, they wanted to put machine learning in the hands of every developer. They worked hard to solve the tough problems that hold so many people back from using machine learning, and have come up with a slew of pre-trained AI services. This is a huge benefit to tech teams that otherwise wouldn’t have the time or resources to train an API. The AWS APIs are continuously learning and integrate very easily with existing services.
One of the areas where AI has proved to be really useful is in contact centers. We’ve used AWS AI services in many of our contact center projects in tandem with Amazon Connect with great success.
A common misconception people have is to think their AI problem is only unique to their business. One presenter said that couldn’t be further from the truth. AI can be used for so many different businesses and customize in so many different ways. Here are just a few of the AI services highlighted at the summit:
Although lots of documentation has moved online, many businesses still have paper documents – records from medical or dental offices, insurance and tax forms, and more – that require processing. Textract automatically extracts text and data from scanned documents. What’s really cool about Textract is that it’s not just an optical character recognition (OCR) service. Regular OCR will read characters but that information often requires extra layers of manual formatting and configuration. Textract uses OCR but can also identify contents of form fields and of information stored in tables.
Amazon Comprehend is a natural language processing (NLP) service that uses machine learning to extract insights and sentiment from text. Coupled with Amazon Textract, Comprehend could wade through customer support tickets, transcripts, emails and more, flagging negative sentiment and highlighting positive interactions, all with the goal of helping you provide a better user experience.
Amazon Transcribe is an automatic speech recognition service that allows anyone to add speech-to-text capability to their applications. We’re particularly excited about the possibilities for this one within Amazon Connect. Using the API, it’s possible to transcribe a customer/agent phone call in real-time. Not only does this give you a text record of the interaction for future reference, we could also apply Amazon Comprehend to it to analyse customer sentiment.
Amazon Translate is a neural machine translation service that offers quick and affordable translation in over 21 languages. According to the Amazon website, “neural machine translation is a form of language translation automation that uses deep learning models to deliver more accurate and more natural sounding translation than traditional statistical and rule-based translation algorithms.”
We watched a live demo of an English customer service call being translated to Spanish as the customer and agent spoke. There are two modes available, batch processing or streaming. Translate could recognize multiple speakers and everything was translated to Spanish, with an English record kept above it (the demo in question made use of Amazon Translate as well).
Amazon has grown from a company that sold books to one that offers complex database and AI solutions for use by companies worldwide. Spending a day at the summit helped reinforce how easy it is to customize and scale your technical offerings.
For information on how Perficient experts can help you make the most of AWS in your business, please get in touch with us.