Top 3 Takeaways From AWS re:Invent
Another year, another AWS re:Invent in the books. More than 24,000 cloud professionals, dealers and analysts flooded the Venetian, Mirage in Las Vegas in what appeared to be Amazon’s greatest cloud conference to date. I Naturally noticed a dramatic increase in foot traffic after attending the conference last year Always there are high demands and expectations about AWS’s latest technologies every year, that is the reason there was enough time to declare the event. The cloud giant did not disappoint. Below are 3 key takeaways from AWS re:invent:
AWS Wants to Make Your Life Easier
AWS always want to make it easy as possible to make your application and system. This was a passionate theme at the event, and there were announced many new services, including:
- AWS Elastic Container Service for Kubernetes: It is an open-source system to automate the deployment, scaling, and management of containerized applications. It’s been a long time coming, but AWS has finally delivered and now Kubernetes can compete against Microsoft and Google for customers.
- AWS Fargate: In typical fashion of AWS, AWS announced a product that the competition already offers, but enhanced it to make it even more attractive. The same situation is with Fargate. Farget allows you to run containers, but without having to manage a server or cluster. This is compared to EC2, but using containers instead of VMs.
- Amazon Aurora Multi-Master: Aurora is already a fully managed database service, but allows read / write multiple instances in multiple availability zones other than Multi-Master. As a former database administrator, it is easy for me to see the value in the service in this way.
- Amazon Aurora Serverless: This is basically a serverless database designed for highly variable workloads and customers only pay for the database resources they use on a second-to-none basis.
- Amazon DynamoDB Global Tables: This service automatically creates replication tables for multi-master rights in two or more AWS fields.
- Amazon S3 Select and Glacier Select: These are extensions of Amazon Athena. They enable the retrieval of a subset of data from an S3 object using simple SQL expressions. Now you can grab data from compressed files stored on S3 or Glacier without downloading any file.
2) Cloud Adoption Is Officially Mainstream
The trend of adopting cloud computing has been increasing over the years as IT decision-makers have realized that the benefits of flexible, scalable, cost-effective and highly available infrastructure stem from somewhat misleading concerns about cloud insecurity. Let’s go ahead. As a result, this year’s conference was about 50 percent larger than the previous year. An estimated 45,000 people attended and re: Inventory-filled conference halls in Venice, Encore, Mirage, Aria and MGM hotels. If you have not arrived in Las Vegas, it is difficult to describe the scale of this phenomenon, but the size reflects how popular cloud computing has become, in particular, AWS.
More than 1,000 learning sessions were conducted to demonstrate the comprehensive list of products and services from the AWS ecosystem and each was well attended. However, it was a keynote speech that proved that cloud adoption is now widespread, when Goldman Sachs managing director Roy Joseph stated how his company uses AWS for analytics. If investment banks are one of the industries adopting cloud computing, now adopting AWS, then cloud computing is officially mainstream.
3) Machine learning is the next battlefront
AWS has a qualified machine learning advisor at IBM Watson, and has announced several machine learning products to help them compete.
The Amazon DeepLens main product announcement was. Deeplane is an HD deep-learning enabled video camera that allows developers to easily get started in the world of machine vision. This was demonstrated with a simple “hot dog or not hot dog” example, during which the camera indicates if your food plate contains a hot dog. Obviously, it has more important uses, but it was an important demonstration. AWS wants to get developers building applications for DeepLens, which in turn gets more people using AWS products. The DeepLens product was so popular that people were literally fighting to get their hands on one: I heard a rumor of a scuffle spread across the line, waiting to see it.
AWS also announced Amazon Recognition Video, which allows you to upload videos to the cloud for real-time analysis to detect and identify faces and objects in live streams. Rekognition can also analyze files stored in Amazon S3 to detect, track, identify and remove faces, objects, and content.
In addition to those two flagship products, AWS has already announced a suite of services offered by other vendors, which will allow AWS to build greater ingestion in machine learning arena: Understand, which makes you bigger Allows to analyze documents in quantity; Translation, a language translation server; And describe a speech-to-text service. When these services are combined with existing Amazon Lex and Poli offerings, AWS will be one of the major players – if not the key player – in the machine learning space.
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