AWS re:Invent 2017 (27 Nov – 1 Dec) kicked off with a lot of excitement. The 2017 keynote revealed critical services to help AWS users explore machine learning and containerization.

Why I attended AWS Re:invent 2017?

The market is at the disruption point where the demand for dockers, containers, AI and other technology is exceeding the supply. There’s surely technical limitations and that’s why it becomes majorly important to keep yourself updated with industry news. A quick overview of why I went out of India and spent thousands of dollars to attend AWS re:Invent:

  • We have a team of 25+ continuously innovating and exploring technology. We polished our core AWS services like EC2, Redshift, S3, RDS, etc.
  • Get the news around new AWS products and features.
  • Get educated on technical best practices during +1000 breakout sessions on topics such as cloud architecture, continuous deployment, monitoring and management, performance, security, migration and more.

AWS re:Invent 2017 highlighted new services around augmenting reality, optimizing containerization, and machine learning. Here are some of the key takeaways:

1. Adapting Machine Learning

AWS’s SageMaker is a fully managed machine learning service. It helps engineers and data scientists to get machine learning models up and running on the cloud. If you wish to try SageMaker, there’s a free tier available. The price afterward, depends on building your model, training it and then hosting.

Similarly, there is DeepLens, a machine learning tool that works on video recognition.

2. Large-Scale Containerization with AWS

Amazon has introduced a new managed service, AWS EKS, to make it easy to run Kubernetes without installing and operating your own clusters. You can run containers without managing servers or clusters with the help of AWS Fargate. It supports both ECS & EKS.

3. Cost Reduction with Aurora Serverless

AWS announced Amazon Aurora Serverless where you can use AWS Aurora without spinning up RDS and be charged by the query. Pricing for Aurora Serverless is done via Aurora Capacity Units (ACUs) which starts at $0.06 cents/hour.

4. Releasing Alexa for Business

Amazon’s Alexa for Business is a voice command application that caters to the business. For using this, teams will require building the proper Alexa skills in order to support key workflows and interactions with software. Price starts at $3 per user and $7 per shared device.

5. Better Storage, Database, and Computing Services

AWS announced the T2, H1, and M5 unlimited instances. Those who want to work with the direct accessibility of bare-metal servers, AWS announced i3.metal. It allows the operating system to run directly on the underlying hardware while still providing access to all the cloud benefits.

6. Find Specific Bytes in Glacier and S3 for Cost Optimization

New features to Glacier and S3 allows performing simple SQL expressions to identify and pull out only the bytes you need from those objects. It enables to access specific bytes of data from storage and thus, reduces the need to retrieve entire data.

Making the Most Out of AWS

AWS is massive. The kind of products and services will help you boost the business productivity and enable automation. However, the cost is a major reason why companies struggle with AWS. To explore AWS services to the fullest efficiently, you need to AWS management.

We are certified AWS consulting partners and used our experience to reduce AWS cost by 25% in a month for one of our clients.


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