AWS Blog

AWS GovCloud (US) Heads East – New Region in the Works for 2018

by Jeff Barr | on | in Announcements, AWS GovCloud | | Comments

AWS GovCloud (US) gives AWS customers a place to host sensitive data and regulated workloads in the AWS Cloud. The first AWS GovCloud (US) Region was launched in 2011 and is located on the west coast of the US.

I’m happy to announce that we are working on a second Region that we expect to open in 2018. The upcoming AWS GovCloud (US-East) Region will provide customers with added redundancy, data durability, and resiliency, and will also provide additional options for disaster recovery.

Like the existing region, which we now call AWS GovCloud (US-West), the new region will be isolated and meet top US government compliance requirements including International Traffic in Arms Regulations (ITAR), NIST standards, Federal Risk and Authorization Management Program (FedRAMP) Moderate and High, Department of Defense Impact Levels 2-4, DFARs, IRS1075, and Criminal Justice Information Services (CJIS) requirements. Visit the GovCloud (US) page to learn more about the compliance regimes that we support.

Government agencies and the IT contactors that serve them were early adopters of AWS GovCloud (US), as were companies in regulated industries. These organizations are able to enjoy the flexibility and cost-effectiveness of public cloud while benefiting from the isolation and data protection offered by a region designed and built to meet their regulatory needs and to help them to meet their compliance requirements. Here’s a small sample from our customer base:

Federal (US) GovernmentDepartment of Veterans Affairs, General Services Administration 18F (Digital Services Delivery), NASA JPL, Defense Digital Service, United States Air Force, United States Department of Justice.

Regulated IndustriesCSRA, Talen Energy, Cobham Electronics.

SaaS and Solution ProvidersFIGmd, Blackboard, Splunk, GitHub, Motorola.

Federal, state, and local agencies that want to move their existing applications to the AWS Cloud can take advantage of the AWS Cloud Adoption Framework (CAF) offered by AWS Professional Services.

Jeff;

 

 

Amazon Rekognition Update – Celebrity Recognition

by Jeff Barr | on | in Amazon Rekognition | | Comments

We launched Amazon Rekognition at re:Invent (Amazon Rekognition – Image Detection and Recognition Powered by Deep Learning) and added Image Moderation earlier this year.

Today we are adding celebrity recognition!

Rekognition has been trained to identify hundreds of thousands of people who are famous, noteworthy, or prominent in fields that includes politics, sports, entertainment, business, and media. The list is global, and is updated frequently.

To access this feature, simply call the new RecognizeCelebrities function. In addition to the bounding box and facial landmark feature returned by the existing DetectFaces function, the new function returns information about any celebrities that it recognizes:

"Id": "3Ir0du6", 
"MatchConfidence": 97, 
"Name": "Jeff Bezos", 
"Urls": [ "www.imdb.com/name/nm1757263" ]

The Urls provide additional information about the celebrity. The API currently return links to IMDB content; we may add other sources in the future.

You can use the Celebrity Recognition Demo in the AWS Management Console to experiment with this feature:

If you have an image archive you can now index it by celebrity. You could also use a combination of celebrity recognition and object detection to build all kinds of search tools. If your images are already stored in S3, you can process them in-place.

I’m sure that you will come up with all sorts of interesting uses for this new feature. Leave me a comment and let me know what you build!

Jeff;

 

AWS Greengrass – Run AWS Lambda Functions on Connected Devices

by Jeff Barr | on | in AWS Greengrass, AWS Lambda, IoT | | Comments

I first told you about AWS Greengrass in the post that I published during re:Invent (AWS Greengrass – Ubiquitous Real-World Computing). We launched a limited preview of Greengrass at that time and invited you to sign up if you were interested.

As I noted at the time, many AWS customers want to collect and process data out in the field, where connectivity is often slow and sometimes either intermittent or unreliable. Greengrass allows them to extend the AWS programming model to small, simple, field-based devices. It builds on AWS IoT and AWS Lambda, and supports access to the ever-increasing variety of services that are available in the AWS Cloud.

Greengrass gives you access to compute, messaging, data caching, and syncing services that run in the field, and that do not depend on constant, high-bandwidth connectivity to an AWS Region. You can write Lambda functions in Python 2.7 and deploy them to your Greengrass devices from the cloud while using device shadows to maintain state. Your devices and peripherals can talk to each other using local messaging that does not pass through the cloud.

Now Generally Available
Today we are making Greengrass generally available in the US East (Northern Virginia) and US West (Oregon) Regions. During the preview, AWS customers were able to get hands-on experience with Greengrass and to start building applications and businesses around it. I’ll share a few of these early successes later in this post.

The Greengrass Core code runs on each device. It allows you to deploy and run Lambda applications on the device, supports local MQTT messaging across a secure network, and also ensures that conversations between devices and the cloud are made across secure connections. The Greengrass Core also supports secure, over-the-air software updates, including Lambda functions. It includes a message broker, a Lambda runtime, a Thing Shadows implementation, and a deployment agent. Greengrass Core and (optionally) other devices make up a Greengrass Group. The group includes configuration data, the list of devices and the identity of the Greengrass Core, a list of Lambda functions, and a set of subscriptions that define where the messages should go. All of this information is copied to the Greengrass core devices during the deployment process.

Your Lambda functions can use APIs in three distinct SDKs:

AWS SDK for Python – This SDK allows your code to interact with Amazon Simple Storage Service (S3), Amazon DynamoDB, Amazon Simple Queue Service (SQS), and other AWS services.

AWS IoT Device SDK – This SDK (available for Node.js, Python, Java, and C++) helps you to connect your hardware devices to AWS IoT. The C++ SDK has a few extra features including access to the Greengrass Discovery Service and support for root CA downloads.

AWS Greengrass Core SDK – This SDK provides APIs that allow local invocation of other Lambda functions, publish messages, and work with thing shadows.

You can run the Greengrass Core on x86 and ARM devices that have version 4.4.11 (or newer) of the Linux kernel, with the OverlayFS and user namespace features enabled. While most deployments of Greengrass will be targeted at specialized, industrial-grade hardware, you can also run the Greengrass Core on a Raspberry Pi or an EC2 instance for development and test purposes.

For this post, I used a Raspberry Pi attached to a BrickPi, connected to my home network via WiFi:

The Raspberry Pi, the BrickPi, the case, and all of the other parts are available in the BrickPi 3 Starter Kit. You will need some Linux command-line expertise and a decent amount of manual dexterity to put all of this together, but if I did it then you surely can.

Greengrass in Action
I can access Greengrass from the Console, API, or CLI. I’ll use the Console. The intro page of the Greengrass Console lets me define groups, add Greengrass Cores, and add devices to my groups:

I click on Get Started and then on Use easy creation:

Then I name my group:

And name my first Greengrass Core:

I’m ready to go, so I click on Create Group and Core:

This runs for a few seconds and then offers up my security resources (two keys and a certificate) for downloading, along with the Greengrass Core:

I download the security resources and put them in a safe place, and select and download the desired version of the Greengrass Core software (ARMv7l for my Raspberry Pi), and click on Finish.

Now I power up my Pi, and copy the security resources and the software to it (I put them in an S3 bucket and pulled them down with wget). Here’s my shell history at that point:

Important Update: As one of my sharp-eyed colleagues on the AWS Security team pointed out, this is not a good way to distribute the secrets to the devices. I could have used the AWS CLI to download them from a encrypted bucket, copied them via cut and paste, or used a USB key.

Following the directions in the user guide, I create a new user and group, run the rpi-update script, and install several packages including sqlite3 and openssl. After a couple of reboots, I am ready to proceed!

Next, still following the directions, I untar the Greengrass Core software and move the security resources to their final destination (/greengrass/configuration/certs), giving them generic names along the way. Here’s what the directory looks like:

The next step is to associate the core with an AWS IoT thing. I return to the Console, click through the group and the Greengrass Core, and find the Thing ARN:

I insert the names of the certificates and the Thing ARN into the config.json file, and also fill in the missing sections of the iotHost and ggHost:

I start the Greengrass demon (this was my second attempt; I had a typo in one of my path names the first time around):

After all of this pleasant time at the command line (taking me back to my Unix v7 and BSD 4.2 days), it is time to go visual once again! I visit my AWS IoT dashboard and see that my Greengrass Core is making connections to IoT:

I go to the Lambda Console and create a Lambda function using the Python 2.7 runtime (the IAM role does not matter here):

I publish the function in the usual way and, hop over to the Greengrass Console, click on my group, and choose to add a Lambda function:

Then I choose the version to deploy:

I also configure the function to be long-lived instead of on-demand:

My code will publish messages to AWS IoT, so I create a subscription by specifying the source and destination:

I set up a topic filter (hello/world) on the subscription as well:

I confirm my settings and save my subscription and I am just about ready to deploy my code. I revisit my group, click on Deployments, and choose Deploy from the Actions menu:

I choose Automatic detection to move forward:

Since this is my first deployment, I need to create a service-level role that gives Greengrass permission to access other AWS services. I simply click on Grant permission:

I can see the status of each deployment:

The code is now running on my Pi! It publishes messages to topic hello/world; I can see them by going to the IoT Console, clicking on Test, and subscribing to the topic:

And here are the messages:

With all of the setup work taken care of, I can do iterative development by uploading, publishing, and deploying new versions of my code. I plan to use the BrickPi to control some LEGO Technic motors and to publish data collected from some sensors. Stay tuned for that post!

Greengrass Pricing
You can run the Greengrass Core on three devices free for one year as part of the AWS Free Tier. At the next level (3 to 10,000 devices) two options are available:

  • Pay as You Go – $0.16 per month per device.
  • Annual Commitment – $1.49 per year per device, a 17.5% savings.

If you want to run the Greengrass Core on more than 10,000 devices or make a longer commitment, please get in touch with us; details on all pricing models are on the Greengrass Pricing page.

Jeff;

Event: AWS Serverless Roadshow – Hands-on Workshops

by Tara Walker | on | in Events, Serverless | | Comments

Surely, some of you have contemplated how you would survive the possible Zombie apocalypse or how you would build your exciting new startup to disrupt the transportation industry when Unicorn haven is uncovered. Well, there is no need to worry; I know just the thing to get you prepared to handle both of those scenarios: the AWS Serverless Computing Workshop Roadshow.

With the roadshow’s serverless workshops, you can get hands-on experience building serverless applications and microservices so you can rebuild what remains of our great civilization after a widespread viral infection causes human corpses to reanimate around the world in the AWS Zombie Microservices Workshop. In addition, you can give your startup a jump on the competition with the Wild Rydes workshop in order to revolutionize the transportation industry; just in time for a pilot’s crash landing leading the way to the discovery of abundant Unicorn pastures found on the outskirts of the female Amazonian warrior inhabited island of Themyscira also known as Paradise Island.

These free, guided hands-on workshops will introduce the basics of building serverless applications and microservices for common and uncommon scenarios using services like AWS Lambda, Amazon API Gateway, Amazon DynamoDB, Amazon S3, Amazon Kinesis, AWS Step Functions, and more. Let me share some advice before you decide to tackle Zombies and mount Unicorns – don’t forget to bring your laptop to the workshop and make sure you have an AWS account established and available for use for the event.

Check out the schedule below and get prepared today by registering for an upcoming workshop in a city near you. Remember these are workshops are completely free, so participation is on a first come, first served basis. So register and get there early, we need Zombie hunters and Unicorn riders across the globe.  Learn more about AWS Serverless Computing Workshops here and register for your city using links below.

Event Location Date
Wild Rydes New York Thursday, June 8
Wild Rydes Austin Thursday, June 22
Wild Rydes Santa Monica Thursday, July 20
Zombie Apocalypse Chicago Thursday, July 20
Wild Rydes Atlanta Tuesday, September 12
Zombie Apocalypse Dallas Tuesday, September 19

 

I look forward to fighting zombies and riding unicorns with you all.

Tara

AWS Direct Connect Update – New Locations in North America and Europe

by Jeff Barr | on | in Announcements, AWS Direct Connect | | Comments

AWS customers can use AWS Direct Connect to establish a dedicated network connection from their premises to AWS. This gives them a more consistent network experience than a shared, Internet-based connection along with increased throughput and the potential to reduce network costs.

We have added several new Direct Connect locations already this year, and are adding even more today. This post summarizes the most recent additions to our roster!

The following locations are for the EU (Frankfurt) Region:

The following location is for the EU (Ireland) Region:

The US East (Ohio) Region:

The Canada (Central) Region:

And the US East (Northern Virginia) Region:

See the Direct Connect Product Details for a full list of new and existing locations.

Jeff;

 

Try Amazon WorkSpaces at No Charge for Up To 2 Months

by Jeff Barr | on | in Amazon WorkSpaces | | Comments

I am a big believer in hands-on experience. Except under very rare circumstances, the posts in my blog are written only after I have used the service in question. If you happened to read I Love My Amazon WorkSpace, you know that Amazon WorkSpaces is one of my most important productivity tools.

I would like to tell you about an opportunity for you to try WorkSpaces on your own at no charge. The new Amazon WorkSpaces Free Tier allows you to launch two Standard bundle WorkSpaces and use them for a total of 40 hours per month, for up to two calendar months. You can choose either the Windows 7 or the Windows 10 Desktop Experience, both powered by Windows Server. Both options include Internet Explorer 11, Mozilla Firefox, 7-Zip, and Amazon WorkDocs with 50 GB of storage.

In order to take advantage of the free tier you must run the WorkSpaces in AutoStop mode, which is selected for you by default. Unused hours expire at the end of the first calendar month and the free tier offer expires at the end of the second calendar month. After that you will be billed at the hourly rate listed on the Amazon WorkSpaces Pricing page.

To get started, follow the steps in the Quick Setup and choose a bundle that is eligible for the free tier:

This offer is available in all AWS Regions where WorkSpaces is available.

Jeff;

Cloud Directory Update – Support for Typed Links

by Jeff Barr | on | in Amazon Cloud Directory | | Comments

Earlier this year I told you about Cloud Directory, our cloud-native directory for hierarchical data and told you how it was designed to store large amounts of strongly typed hierarchical data. Because Cloud Directory can scale to store hundreds of millions of objects, it is a great fit for many kinds of cloud and mobile applications.

In my original post I explained how each directory has one or more schemas, each of which has, in turn, one or more facets. Each facet defines the set of required and allowable attributes for an object.

Introducing Typed Links
Today we are extending the expressive power of the Cloud Directory model by adding support for typed links. You can use these links to create object-to-object relationships across hierarchies. You can define multiple types of links for each of your directories (each link type is a separate facet in one of the schemas associated with the directory). In addition to a type, each link can have a set of attributes. Typed links help to maintain referential data integrity by ensuring objects with existing relationships to other objects are not deleted inadvertently.

Suppose you have a directory of locations, factories, floor numbers, rooms, machines and sensors. Each of these can be represented as a dimension in Cloud Directory with rich metadata information within the hierarchy. You can define and use typed links to connect the objects together in various ways, creating typed links that lead to maintenance requirements, service records, warranties, and safety information, with attributes on the links to store additional information about the relationship between the source object and the destination object.

Then you can run queries that are based on the type of a link and the values of the attributes within it. For example, you could locate all sensors that have not been cleaned in the past 45 days, or all of the motors that are no longer within their warranty period. You can find all of the sensors that are on a given floor, or you can find all of the floors where sensors of a given type are located.

Using Typed Links
To use typed links you simply add one or more Typed Link facets to your schema using the CreateTypedLinkFacet function. Then you call AttachTypedLink, passing in the source and destination objects, the Typed Link facet, and the attributes for the link. Other useful functions include GetTypedLinkFacetInformation, ListIncomingTypedLinks, and ListOutgoingTypedLinks. To learn more and to see the complete list of functions, take a look at the Cloud Directory API Reference.

Just as you can do for objects, you can use Attribute Rules to constrain attribute values. You can constrain the length of strings and byte arrays, restrict strings to a specified set of values, and limit numbers to a specific range.

My colleagues shared some sample code that illustrates how to use typed links. Here are the ARNs and the name of the facet:

String appliedSchemaArn   = "arn:aws:clouddirectory:eu-west-2:XXXXXXXXXXXX:directory/AbF4qXxa80WSsLRiYhDB-Jo/schema/demo_organization/1.0";
String directoryArn       = "arn:aws:clouddirectory:eu-west-2:XXXXXXXXXXXX:directory/AbF4qXxa80WSsLRiYhDB-Jo";
String typedLinkFacetName = "FloorSensorAssociation";

The first snippet creates a typed link facet called FloorSensorAssociation with sensor_type and maintenance_date attributes, in that order (attribute names and values are part of the identity of the link, so order matters):

client.createTypedLinkFacet(new CreateTypedLinkFacetRequest()
                                .withSchemaArn(appliedSchemaArn)
                                .withFacet(
                                      new TypedLinkFacet()
                                          .withName(typedLinkFacetName)
                                          .withAttributes(toTypedLinkAttributeDefinition("sensor_type"),
                                                          toTypedLinkAttributeDefinition("maintenance_date"))
                                          .withIdentityAttributeOrder("sensor_type", "maintenance_date")));

private TypedLinkAttributeDefinition toTypedLinkAttributeDefinition(String attributeName) {
 return new TypedLinkAttributeDefinition().withName(attributeName)
 .withRequiredBehavior(RequiredAttributeBehavior.REQUIRED_ALWAYS)
 .withType(FacetAttributeType.STRING);
}

The next snippet creates a link between two objects (sourceFloor and targetSensor), with sensor_type water and maintenance_date 2017-05-24:

AttachTypedLinkResult result = 
    client.attachTypedLink(new AttachTypedLinkRequest()
                               .withDirectoryArn(directoryArn)
                               .withTypedLinkFacet(
                                   toTypedLinkFacet(appliedSchemaArn, typedLinkFacetName))
                                   .withAttributes(
                                        attributeNameAndStringValue("sensor_type", "water"),
                                        attributeNameAndStringValue("maintenance_date", "2017-05-24"))
                                   .withSourceObjectReference(sourceFloor)
                                   .withTargetObjectReference(targetSensor));

private TypedLinkSchemaAndFacetName toTypedLinkFacet(String appliedSchemaArn, String typedLinkFacetName) {
   return new TypedLinkSchemaAndFacetName()
              .withTypedLinkName(typedLinkFacetName)
              .withSchemaArn(appliedSchemaArn);
}

The final snippet enumerates all incoming typed links of sensor_type water and a maintenance_date in the range 2017-05-20 to 2017-05-24:

client.listIncomingTypedLinks(
    new ListIncomingTypedLinksRequest()
        .withFilterTypedLink(toTypedLinkFacet(appliedSchemaArn, typedLinkFacetName))
        .withDirectoryArn(directoryArn)
        .withObjectReference(targetSensor)
        .withMaxResults(10)
        .withFilterAttributeRanges(attributeRange("sensor_type", exactRange("water")),
                                   attributeRange("maintenance_date", 
                                                  range("2017-05-20", "2017-05-24"))));

private TypedLinkAttributeRange attributeRange(String attributeName, TypedAttributeValueRange range) {
   return new TypedLinkAttributeRange().withAttributeName(attributeName).withRange(range);
}

private TypedAttributeValueRange exactRange(String value) {
   return range(value, value);
}

To learn more, read about Objects and Links in the Cloud Directory Administration Guide.

Available Now
Typed links are available now and you can start using them today!

Jeff;

Amazon Lightsail Update – 9 More Regions and Global Console

by Jeff Barr | on | in Amazon Lightsail | | Comments

Amazon Lightsail lets you launch Virtual Private Servers on AWS with just a few clicks. With prices starting at $5 per month, Lightsail takes care of the heavy lifting and gives you a simple way to build and host applications. As I showed you in my re:Invent post (Amazon Lightsail – The Power of AWS, the Simplicity of a VPS), you can choose a configuration from a menu and launch a virtual machine preconfigured with SSD-based storage, DNS management, and a static IP address.

Since we launched in November, many customers have used Lightsail to launch Virtual Private Servers. For example, Monash University is using Amazon Lightsail to rapidly re-platform a number of CMS services in a simple and cost-effective manner. They have already migrated 50 workloads and are now thinking of creating an internal CMS service based on Lightsail to allow staff and students to create their own CMS instances in a self-service manner.

Today we are expanding Lightsail into nine more AWS Regions and launching a new, global console.

New Regions
At re:Invent we made Lightsail available in the US East (Northern Virginia) Region. Earlier this month we added support for several additional Regions in the US and Europe. Today we are launching Lightsail in four of our Asia Pacific Regions, bringing the total to ten. Here’s the full list:

  • US East (Northern Virginia)
  • US West (Oregon)
  • US East (Ohio)
  • EU (London)
  • EU (Frankfurt)
  • EU (Ireland)
  • Asia Pacific (Mumbai)
  • Asia Pacific (Tokyo)
  • Asia Pacific (Singapore)
  • Asia Pacific (Sydney)

Global Console
The updated Lightsail console makes it easy for you to create and manage resources in one or more Regions. I simply choose the desired Region when I create a new instance:

I can see all of my instances and static IP addresses on the same page, no matter what Region they are in:

And I can perform searches that span all of my resources and Regions. All of my LAMP stacks:

Or all of my resources in the EU (Ireland) Region:

I can perform a similar search on the Snapshots tab:

A new DNS zones tab lets me see my existing zones and create new ones:

Creation of SSH keypairs is now specific to a Region:

I can manage my key pairs on a Region-by-Region basis:

Static IP addresses are also specific to a particular Region:

Available Now
You can use the new Lightsail console and create resources in all ten Regions today!

Jeff;

 

New AWS Certification Specialty Exams & Benefits

by Jeff Barr | on | in Training and Certification | | Comments

We are making two important updates to the AWS Certification program today. We are introducing two new AWS Certification Specialty Exams and our new AWS Certification Benefits Program, giving you another way to validate your skills and to showcase your expertise.

New AWS Certification Specialty Exams
Our new AWS Certified Advanced Networking – Specialty and AWS Certified Big Data – Specialty exams are designed for people with at least one current Associate AWS Certification and deep hands-on experience in the relevant specialty. These credentials can help you stand out from the crowd, get recognized, and provide more evidence of your unique technical skills.

New AWS Certification Benefits
Designed to help showcase your achievement and further advance your AWS expertise, tiered AWS Certification Benefits include newly designed AWS Certified logos and certificates, digital badges, free practice exams, branded merchandise, transcript sharing, and more. Benefits are accessed based on the AWS Certifications you have achieved. The more exams you successfully complete, the more benefits you will receive.

Access Your Specialty Exams and Benefits Today
Sign in to the AWS Training and Certification Portal using an Amazon account or (if you are an APN Partner) your APN Portal credentials. Then click on the Certification link on the AWS Training and Certification Portal to access your AWS Certification Account:

If you previously had an account in Webassessor, you can link your accounts so that your AWS Certification history shows in the portal (read “I already have an AWS Certification account in Webassessor. How do I access my AWS Certification history?” in the AWS Training FAQ to see how to do this).

Learn More
Check out the AWS Certifications FAQ and the AWS Training and Certification Portal FAQ if you have any questions.

Jeff;

AWS Online Tech Talks – June 2017

by Tara Walker | on | in Events, Webinars | | Comments

As the sixth month of the year, June is significant in that it is not only my birth month (very special), but it contains the summer solstice in the Northern Hemisphere, the day with the most daylight hours, and the winter solstice in the Southern Hemisphere, the day with the fewest daylight hours. In the United States, June is also the month in which we celebrate our dads with Father’s Day and have month-long celebrations of music, heritage, and the great outdoors.

Therefore, the month of June can be filled with lots of excitement. So why not add even more delight to the month, by enhancing your cloud computing skills. This month’s AWS Online Tech Talks features sessions on Artificial Intelligence (AI), Storage, Big Data, and Compute among other great topics.

June 2017 – Schedule

Noted below are the upcoming scheduled live, online technical sessions being held during the month of June. Make sure to register ahead of time so you won’t miss out on these free talks conducted by AWS subject matter experts. All schedule times for the online tech talks are shown in the Pacific Time (PDT) time zone.

Webinars featured this month are:

Thursday, June 1

Storage

9:00 AM – 10:00 AM: Deep Dive on Amazon Elastic File System

Big Data

10:30 AM – 11:30 AM: Migrating Big Data Workloads to Amazon EMR

Serverless

12:00 Noon – 1:00 PM: Building AWS Lambda Applications with the AWS Serverless Application Model (AWS SAM)

 

Monday, June 5

Artificial Intelligence

9:00 AM – 9:40 AM: Exploring the Business Use Cases for Amazon Lex

 

Tuesday, June 6

Management Tools

9:00 AM – 9:40 AM: Automated Compliance and Governance with AWS Config and AWS CloudTrail

 

Wednesday, June 7

Storage

9:00 AM – 9:40 AM: Backing up Amazon EC2 with Amazon EBS Snapshots

Big Data

10:30 AM – 11:10 AM: Intro to Amazon Redshift Spectrum: Quickly Query Exabytes of Data in S3

DevOps

12:00 Noon – 12:40 PM: Introduction to AWS CodeStar: Quickly Develop, Build, and Deploy Applications on AWS

 

Thursday, June 8

Artificial Intelligence

9:00 AM – 9:40 AM: Exploring the Business Use Cases for Amazon Polly

10:30 AM – 11:10 AM: Exploring the Business Use Cases for Amazon Rekognition

 

Monday, June 12

Artificial Intelligence

9:00 AM – 9:40 AM: Exploring the Business Use Cases for Amazon Machine Learning

 

Tuesday, June 13

Compute

9:00 AM – 9:40 AM: DevOps with Visual Studio, .NET and AWS

IoT

10:30 AM – 11:10 AM: Create, with Intel, an IoT Gateway and Establish a Data Pipeline to AWS IoT

Big Data

12:00 Noon – 12:40 PM: Real-Time Log Analytics using Amazon Kinesis and Amazon Elasticsearch Service

 

Wednesday, June 14

Containers

9:00 AM – 9:40 AM: Batch Processing with Containers on AWS

Security & Identity

12:00 Noon – 12:40 PM: Using Microsoft Active Directory across On-premises and Cloud Workloads

 

Thursday, June 15

Big Data

12:00 Noon – 1:00 PM: Building Big Data Applications with Serverless Architectures

 

Monday, June 19

Artificial Intelligence

9:00 AM – 9:40 AM: Deep Learning for Data Scientists: Using Apache MxNet and R on AWS

 

Tuesday, June 20

Storage

9:00 AM – 9:40 AM: Cloud Backup & Recovery Options with AWS Partner Solutions

Artificial Intelligence

10:30 AM – 11:10 AM: An Overview of AI on the AWS Platform

 

Tuesday, June 27

Hands On Lab

8:30 – 10:00 AM: Hands On Lab: Windows Workloads on AWS

Compute

12:00 Noon – 12:40 PM: Running a Highly Scalable Immersive Media Solution on AWS Using EC2 Spot Instances

 

Wednesday, June 28

Databases

10:30 AM – 11:10 AM: Design, Deploy, and Optimize SQL Server on AWS

 

The AWS Online Tech Talks series covers a broad range of topics at varying technical levels. These sessions feature live demonstrations & customer examples led by AWS engineers and Solution Architects. Check out the AWS YouTube channel for more on-demand webinars on AWS technologies.

Tara