In a wonderful keynote presentation, Andy Jassy stressed over and over on the importance of reinventing yourself. Based on Gartner’s statistics, he pointed out that very few companies have ever stayed on top. And this is because they stop re-inventing themselves. Aptly said, “re-invent when you can — not when it is necessary”. Re-invention should be a culture and a way to go, and not a fallback solution. He stressed on a few patterns and anti patterns to re-inventing.
- You cannot fight gravity. Anything will go down unless you pull it up. You need to consistently work for improvement, rather than being pacified by the current state.
- Carnivalize yourself — else someone else will do it anyway. Be proactive in identifying and eliminating the wasteful and inefficient parts that retard your movement
- Solve problems for customers. Innovate, by understanding the customer’s problems. Not just because you like to. Not because the competition is innovating. The direction and passion has to come from the urge to solve customer’s problem.
- Speed is of paramount importance. Many others have seen the problem that you have seen. Many others knows how to solve it. But the you should work to hit the market first
- As you grow, take all effort to ensure you don’t complicate. Complexity kills agility and the ability.
He also an overview of the wide range of domains and services that AWS provides. And announced the much awaited new service offerings. Here are some that I found really impressive:
Lambda Container Support
The serverless revolution brought about by the Lambda functions is a tempting option for anybody taking a fresh step into a new application. A lot of recent effort and investments have got into development of containers and dockers — and may are held back because of this. Now with the Lambda Container Support, we can place the containers onto a Lambda function — giving us the best of both the worlds.
Automated infrastructure provisioning and deployment of serverless and container-based applications. You can create service templates to provide standardized infrastructure and deployment tooling for serverless and container-based applications. Such templates can be used to automate application or service deployments.
AWS Glue Elastic Views
This is a top up on the AWS Glue is the standard ETL solution we have. With elastic view, we can create kind of materialized views on data — using simple SQL syntax. AWS Glue Elastic Views supports many AWS databases and data stores, including Amazon DynamoDB, Amazon S3, Amazon Redshift, and Amazon Elasticsearch Service. AWS Glue Elastic Views is serverless and scales capacity up or down automatically based on demand, so there’s no infrastructure to manage.
AWS Sagemaker Data Wrangler
SageMaker Data Wrangler, can simplify the process of data preparation and feature engineering, and complete each step of the data preparation workflow, including data selection, cleansing, exploration, and visualization from a single visual interface.
AWS Sagemaker Feature Store
Amazon SageMaker Feature Store is a purpose-built repository where you can store and access features so it’s much easier to name, organize, and reuse them across teams. SageMaker Feature Store provides a unified store for features during training and real-time inference without the need to write additional code or create manual processes to keep features consistent.
Amazon DevOps Guru
Extending the concepts of Code Guru, DevOps Guru can be used to predict a system failure. Amazon DevOps Guru is a new machine learning (ML) powered service that gives you a simpler way to measure and improve an application’s operational performance and availability and reduce expensive downtime — no machine learning expertise required.
Amazon QuickSight Q
This service is set to revolutionalize BI. Powered by NLP and ML models trained based on the domain knowledge, QuickSight Q allows you to query, analyze and display data without the need of any query language. It can understand plain English and requests made in a natural language are sufficient to gather and analyze the available data.
- Lens Realtime — An NLP based service to monitor ongoing conversations with customers. In a call center, it is important to monitor the staff and the calls in progress, so that we can train them properly and prevent any customer dissatisfaction. The Connect Lens Realtime takes it a step further, to analyze conversations in real time, so that a supervisor can interrupt any conversation that is likely going wrong.
- Customer Profile — An NLP based service meant to improve efficiency of the agent. Based on the ongoing conversation, it pulls out the expected, required data from available sources and gets it ready for the agent before it is required.
- Voice ID — Another NLP based service that reduces the need for customer authentication at a call center. Based on the voice, it can identify the customer and get things ready for the agent, so that he does not have to spend time on it.
A wide range of services to enable hybrid computing at a much larger scale. It is no more a server rack on your campus, now the cloud is penetrating a wide range of segments. With smaller outpost servers, to additional local Zones, AWS is set to revolutionalize the hybrid computing paradigm. Very soon, there would be no different between your campus and the cloud. You won’t have to migrate your applications to the cloud. The cloud will enter your campus.