At my job, we have been working on re-platforming our single-page web app for the past few months, and we’re leveraging Amazon Web Services for rapid development. This is my first AWS project, so it’s a lot to take in. That process is going well, but there are still many services I haven’t even touched on.
Then I heard Amazon was hosting a AWS Summit in Atlanta, I decided to attend and see what I could learn and bring back to my team. Since there are more summits scheduled this year (and presumably ongoing), I’m writing to share my learnings, and to help anyone considering a future Summit.
Source: Amazon Web Services
The keynote address was delivered by Sandy Carter (Vice President of AWS Enterprise Workloads). Sandy focuses on helping various companies use and maximize AWS services to the fullest from an innovation perspective. Before that, she used to work at IBM. She is the author of Extreme Innovation: Three Superpowers for Purpose and Profit, and she also serves as an adjunct professor at Carnegie Mellon University Silicon Valley.
Sandy shared with us all valuable insights into how organizations around the world are embracing AWS technology at a ‘supersonic’ pace. This is all due to the rapid development and deployment capabilities AWS offers, coupled with the high customer-demand, and need of an immediate feedback loop for any given products/services in a competitive landscape. She pointed out that companies that offer Software-as-a-Service (SaaS) products are the key companies that AWS has benefited (Splunk, Dynatrace, and Pega) to name just a few.
From a technical perspective, the AWS services most utilized by companies is Lambda. Lambda is the most widely-used service in AWS, followed by S3, EC2, and Elastic Blockstore (EBS). Lambda and API Gateway are mostly used for building Microservices. Lambda functions are all event-driven. A subset of Lambda functions are also Step Functions. A new service AWS has recently launched is the Amazon QLDB (Quantum Ledger Database). It is a fully managed ledger database that provides a transparent, immutable, and cryptographically verifiable transaction log. Owned by a central trusted authority.
Artificial Intelligence and Machine Learning are the future of software development. Vision, speech recognition, language, chatbots, recommendation and forecasting engines are the data-driven conduits through which critical information will flow and businesses will need to rely on to make decisions to provide their top customer experience. Software Developers of today should explore AWS SageMaker to get started with AI and ML. AWS SageMaker allows for building, training, and deploying machine learning models.
‘Cloud Data lakes are the future’ — Sandy Carter