Suresh AWS Speaker certification
How is AWS approaching diversity, equity, and inclusion?
We believe our future is inclusive, diverse, and equitable across every race identity, gender identity, belief, origin, and community. Amazon requires employees to take mandatory inclusion training, regularly reviews its employment data to identify any pay imbalances or unusual attrition across demographics, and works hard to increase the number of underrepresented employees and leaders in the organization. Our culture is defined by our Leadership Principles, and our newest Leadership Principle, "Success and Scale Bring Broad Responsibility," reminds us that we must support our customers, partners, local communities, and the world at large to do better and be better.
What is event-driven serverless computing?
We thought about what customers were telling us and the reality was that they only needed to compute for a few seconds when some type of event occurred that triggered processing. And, there were many use cases where this was the case, such as extracting, transforming, and loading data for analytics and e-commerce, and automating scheduled tasks for IT processes. This is what put us on the path to Lambda and pioneering the event-driven, serverless computing space. This was a brand-new concept. Today, over a million customers are using AWS Lambda.
b.How is AWS different from other technology providers?
We're pioneers. Most large technology companies have lost their will and DNA to invent. They acquire most of their innovations. And again, it's a strategy that can work, it's just not ours. We like to hire builders who look at customer experiences that are flawed, then figure out how to reinvent them. In a space that's moving as fast as the cloud is, to be partnered with the company that has the most functionality, that's iterating the quickest, has the largest community, and had the vision for the cloud from the start without having to patch together acquisitions, that's very attractive.
a.How is AWS different from other technology providers?
We're unusually customer-focused. a. 90% of what we build is driven by what customers tell us matters, and the other 10% are things we hear from customers who may not articulate exactly what they want, but we try to read between the lines and invent on their behalf.
c.How is AWS different from other technology providers?
We're unusually long-term oriented. You won't see our folks show up at customers' doors a day before the end of the quarter or the day before the end of the year and try to harass them into a sale, not to be seen again for a year. We're trying to build relationships and a business that last longer than all of us in this room. And you do that by doing right by customers over a long period of time.
What is RedShift used for?
With Amazon Redshift, our fast, scalable data warehouse service, customers can perform complex queries on massive collections of structured data with up to 3x better price-performance than other cloud data warehouses. And Advanced Query Accelerator (AQUA) for Redshift, an innovative way to do hardware-accelerated cache, enables Redshift to run up to 10x faster than any other enterprise cloud data warehouse
Is the AWS Cloud secure?
Yes, and security will always be our top priority. AWS has been architected to be the most flexible and secure cloud computing environment available today. Our core infrastructure is built to satisfy the security requirements for military, global banks, and other high-sensitivity organizations. Our service offerings and associated supply chain are vetted and accepted as secure enough for top-secret workloads, which benefits all our customers globally. This is backed by a deep set of cloud security tools, with over 300 security, compliance, and governance services and key features. AWS also supports 98 security standards and compliance certifications, more than any other offering, including PCI-DSS, HIPAA/HITECH, FedRAMP, GDPR, FIPS 140-2, and NIST 800-171, helping satisfy compliance requirements for virtually every regulatory agency around the globe.
Cloud Leader - e. Most proven operational expertise
a. For over 16 years, AWS has been delivering cloud services to millions of customers around the world running a wide variety of use cases. AWS has the most operational experience, at greater scale, of any cloud provider. Internally, we say that there's no compression algorithm for experience, and that's because you can't learn certain lessons until you get to different milestones in scale.
What are some of the emerging technologies AWS is focused on (or strategic technologies, or technologies that customers are adopting?)
a. Machine Learning (ML)/Artificial Intelligence (AI): Although many companies have started using machine learning (ML), it's still being invented and reinvented. AWS has the most comprehensive set of AI and Machine Learning services for all skill levels. A few years ago, we launched Amazon SageMaker, the most complete end-to-end solution for ML with all the tools needed to build, train, and deploy ML models in one easy-to-use interface called SageMaker Studio. Over 100,000 customers are running machine learning on AWS, spurred by the broad adoption of Amazon SageMaker.
Cloud Leader - d. Most secure
a. Our core infrastructure is built to satisfy the security requirements for the military, global banks, and other high-sensitivity organizations. With over 300 security, compliance, and governance services and features. In addition, AWS supports 98 security standards and compliance certifications, including: PCI-DSS, HIPAA/HITECH, FedRAMP, GDPR, FIPS 140-2, and NIST 800-171, helping satisfy compliance requirements for virtually every regulatory agency around the globe.
Cloud Leader - b. Fastest pace of innovation
. In 2011, AWS released over 80 new significant services and features, followed by nearly 160 in 2012; 280 in 2013; 516 in 2014; 722 in 2015; 1,017 in 2016; 1,430 in 2017; and 1,957 in 2018; 2,345 in 2019, 2,757 in 2020, and 3,084 in 2021
What are the advantages of moving to the cloud? / Why are enterprises moving so quickly to the cloud?
five reasons companies are moving so quickly to the AWS cloud. The first is agility. AWS lets customers quickly spin up resources as they need them, deploying hundreds or even thousands of servers in minutes. This means customers can very quickly develop and roll out new applications, and it means teams can experiment and innovate more quickly and frequently. If an experiment fails, you can always deprovision those resources without risk. The second reason is cost savings. If you look at how people end up moving to the cloud, almost always the conversation starter ends up being cost. AWS allows customers to trade capital expense for variable expense, and only pay for IT as they consume it. And, the variable expense is much lower than what customers can do for themselves because of AWS's economies of scale. For example, Dow Jones has estimated that migrating its data centers to AWS will contribute to a global savings of $100 million in infrastructure costs. The third reason is elasticity. Customers used to over provision to ensure they had enough capacity to handle their business operations at the peak level of activity. Now, they can provision the amount of resources that they actually need, knowing they can instantly scale up or down along with the needs of their business, which also reduces cost and improves the customer's ability to meet their user's demands. The fourth reason is that the cloud allows customers to innovate faster because they can focus their highly valuable IT resources on developing applications that differentiate their business and transform customer experiences instead of the undifferentiated heavy lifting of managing infrastructure and data centers. The fifth reason is that AWS enables customers to deploy globally in minutes. AWS has the concept of a Region, which is a physical location around the world where we cluster data centers. We call each group of logical data centers an Availability Zone. The AWS Cloud spans 96 Availability Zones within 30 geographic regions around the world, with announced plans for 15 more Availability Zones and 5 more AWS Regions in Australia, Canada, Israel, New Zealand, and Thailand.
Serverless Computing
· In 2014, AWS pioneered the event-driven serverless computing space with the launch of AWS Lambda. AWS Lambda lets developers run their code without provisioning or managing servers, and customers never have to worry about scaling, patching, or managing any servers. It was a brand-new concept. With serverless, a whole generation of developers is going to grow up not thinking about managing servers and clusters. AWS Lambda allows customers to set a trigger with a few lines of code to spin up compute, improving agility and cost efficiency. You can trigger AWS Lambda from over 200 AWS services and software as a service (SaaS) applications—so you have a lot of flexibility in what you can build.
You've said that 90% of what AWS builds is what AWS customers ask for, while the remaining 10% is focused on strategic interpretations of customer needs. What's an example of something AWS built that customers asked for, and what's an example of a "strategic interpretation" of customer needs?
A good example of a service that we launched as a direct result of many customers asking for it is Amazon Redshift in February of 2013 So we launched Amazon Redshift, a fast, fully managed, petabyte-scale data warehouse service that makes it simple and cost-effective to efficiently analyze data using existing business intelligence tools A good example of a service that we launched as a direct result of many customers asking for it is Amazon Redshift in February of 2013Here again, customers had been fed up with what's been available for the last couple decades, especially the high cost, lock-in, punitive licensing terms, and complexity of old guard databases, and they asked us to come up with a better solution. Today, Amazon Aurora is the fastest growing service in the history of AWS and over a hundred thousand customers use it for their relational databases.
Instances
· We offer the fastest processors in the cloud and we are the only cloud with 800 Gbps ethernet networking. We have the most powerful GPU instances for machine learning training and graphics workloads, as well as the lowest cost-per-inference instances in the cloud. For example, AWS Graviton-based instances are the first ARM-based instances in a major cloud provider and deliver up to 40% better price performance over comparable x86-based EC2 instances for a wide variety of workloads. And the new AWS Graviton3 processors provide up to 25% better compute performance, up to 2x higher floating-point performance, and up to 2x faster cryptographic workload performance compared to AWS Graviton2 processors. We also built our Inferentia chip to reduce the cost of machine learning inference, and AWS Trainium, a high-performance ML training chip designed by AWS to deliver the most cost-effective ML training in the cloud.
Databases:
A growing number of organizations have felt constrained by their commercial-grade relational database options and have been really unhappy with their old guard database providers—these offerings are expensive, proprietary, have high-lock-in, and punitive licensing terms. But, to get the same performance on these open engines that you get in commercial-grade old guard engines takes a lot of work. Customers want the performance of commercial-grade databases with the pricing and friendliness of open engines. That's why AWS spent several years building our own relational database engine in Amazon Aurora, a fully managed MySQL- and PostgreSQL-compatible service that has several-times-faster performance than the typical high-end implementations in those community editions. Moreover, it's at least as durable, performant, and available as the commercial-grade databases, but at one tenth of the cost. Amazon Aurora is the fastest growing service in the history of AWS and over a hundred thousand AWS customers use it for their relational databases, and below for non-rdbms. AWS provides the broadest selection of purpose-built databases so you can use the right tool for the job, allowing you to save, grow, and innovate faster. Customers can choose from over 15 purpose-built engines to support diverse data models, including relational, key-value, document, in-memory, graph, time series, wide column, and ledger databases. For example, if you're Lyft, and you have millions of geolocation and driver combinations, you want a high-throughput, low-latency, key-value store like Amazon DynamoDB. Or if you're Tinder and you want to show your dashboards in microseconds, you want an in-memory database like Amazon ElastiCache. Or if you're doing work at the edge with IoT, where the data is coming in a timestream format, you want a time series database like Amazon Timestream.
Most Functionality
AWS has been continually expanding its services to support virtually any cloud workload, and it now has more than 200 fully featured services, including compute, storage, databases, networking, analytics, robotics, machine learning and artificial intelligence (AI), Internet of Things (IoT), mobile, security, hybrid, virtual and augmented reality (VR and AR), media, application development, deployment, and management
Cloud Leader - c. Largest community of customers and partners
AWS has the largest and most dynamic community, with millions of active customers every month and more than 100,000 Partners from over 150 countries—with almost 70% headquartered outside the United States.
What is a Share Responsibility model?
AWS manages and controls the components from the host operating system and virtualization layer down to the physical security of the facilities in which the services operate, and AWS customers are responsible for building secure applications. We provide a wide variety of best practices documents, encryption tools, and other guidance our customers can leverage in delivering application-level security measures>
Analytics
AWS provides the most purpose-built data and analytics services (which include built-in ML integrations) for a wide range of use cases. For example, customers can process vast amounts of data with Amazon EMR, which supports 21 different open source processing projects (Hadoop, Spark, HBase, Presto, and more), and run analytics on real-time streaming data with Amazon Kinesis. Amazon Kinesis Video Streams makes it easy to securely stream video from millions of connected devices to AWS for analytics, machine learning (ML), and other processing.
AWS Revenue
AWS revenue was $20.5 billion in Q3 2022, which grew by 27% year-over-year. AWS annualized revenue run rate was $82 billion in Q3 2022.
Containers
About two thirds of the containers that run in the cloud run on AWS. That's because while most other providers have one containers offering, typically a managed Kubernetes offering, AWS has three: 1/If what you value most is using the open source Kubernetes frame work, then we have our Amazon Elastic Kubernetes Service (EKS); 2/If what you value most is having the deepest integration with the rest of the AWS platform, you use Amazon Elastic Container Service (ECS), which we can do because since we control it, we can make sure that everything launches integrated with ECS right from the get-go; 3/And if what you value most in containers is running containers without having to worry about servers or clusters, then you use AWS Fargate, which is our serverless container offering, and it's much easier to run containers this way. We actually have a lot of customers who use two, or even three, of these container offerings, because different teams have different preferences and have different use cases. And with Amazon ECS Anywhere and EKS Anywhere customers can run ECS and EKS containers on-premises, on VMs, and other customer-managed infrastructure, alongside what they're running in AWS, for a seamless experience.
1. How was AWS started?
After over a decade of building and running the highly scalable web application, Amazon.com, the company realized that it had developed a core competency in operating massive scale technology infrastructure and data centers, and embarked on a much broader mission of serving a new customer segment—developers and businesses—with web services they can use to build sophisticated, scalable applications.
For running machine learning (ML) at scale and in production
Amazon EC2 Inf1 Instances, powered by AWS Inferentia chips, deliver up to 2.3x higher throughput and up to 70% lower cost per inference than comparable current generation GPU-based Amazon EC2 instances
Most Compute Instances
Amazon Elastic Compute Cloud (Amazon EC2) offers over 600 generally available instances—more than any other cloud provider
How many times the price was reduced?
As of September 14, 2022, we've reduced prices 129 times since AWS launched in 2006.
What is Hybrid cloud?
At AWS, we think of hybrid infrastructure as including the cloud along with other edge nodes, on-premises data centers being one of them. The way that customers have told us they want to consume our hybrid offering is with the same APIs, the same control plane, the same tools, and the same hardware that they're used to using in AWS Regions
What are 3 layers of ML?
At the top layer are AI services that mimic human cognition for customers that don't want to build ML models. The services make it really easy to incorporate AI (e.g. turning text to speech, transcribing audio into text, or translate text into multiple languages) into applications without having to build and train ML algorithms In the middle layer are ML services for data scientists and developers. If we want machine learning to be as expansive as we really want it to be, we need to make it much more accessible to people who aren't machine learning practitioners. Today, there are very few of these experts out there. So, we built Amazon SageMaker, a fully managed service that removes the heavy lifting, complexity, and guesswork from each step of the machine learning process, empowering everyday developers and scientists to successfully use machine learning. SageMaker is a step-level change for everyday developers and data scientists being able to access and build machine learning models At the bottom layer are frameworks and infrastructure for ML experts and practitioners—including advanced developers and data scientists—who are comfortable building, tuning, training, deploying, and managing models themselves, and working at the chips and framework level. Unlike other providers who offer only one framework, TensorFlow, AWS supports all of the major ML frameworks, including TensorFlow, MXNet, PyTorch, Caffe 2, etc.
What can we use for for real-time operational dashboards and Business Intelligence ?
Customers are also actively using Amazon OpenSearch Service (successor to Amazon Elasticsearch Service) for real-time operational dashboards, Amazon QuickSight for business intelligence with great visualizations and embedded machine learning, and Amazon Athena to instantly analyze data stored in S3 using standard SQL
1. Why does AWS continue to be the leader in cloud? (Also, "Why do customers choose AWS over other providers?")
Customers are choosing AWS over other providers because it has a lot more functionality, the largest and most vibrant community of customers and partners, the most proven operational and security expertise, and the business is innovating at a faster clip—especially in new areas such as Machine Learning and Artificial Intelligence, the Internet of Things, Serverless Computing, and custom-designed processors and chips.
Emerging Technologies b. IoT:
Customers can connect devices and operate them at the edge with FreeRTOS and AWS IoT Greengrass, and continually monitor and manage their smart devices from the cloud using services such as AWS IoT Core, AWS IoT Device Defender and AWS IoT Device Management. With AWS, customers have a single pane of glass that lets them decide what processing and analytics they want to do in the cloud, and what they want to do on the device itself (to eliminate round trip latency), with services such as AWS IoT Analytics, AWS IoT SiteWise, AWS IoT Events, and AWS IoT Things Graph
deliver the highest performance for ML training in the cloud
EC2 P4d Instances. To help customers be even more cost effective when training deep learning ML models, our Trn1 instances, based on our custom AWS Trainium chips, offer the most cost-effective ML training in the cloud and are the first EC2 instances with up to 800 gigabits per second networking
How does AWS rank in energy efficiency ?
Energy efficiency is a primary goal of our global infrastructure. The results of several studies conducted by 451 Research show that AWS's infrastructure is 3.6 times more energy efficient than the median of U.S. enterprise data centers surveyed, and up to 5 times more energy efficient than enterprise data centers in Europe and Asia Pacific. One of the most visible ways AWS is using innovation to improve power efficiency is our investment in AWS chips. EC2 compute instances powered by Graviton3 ARM processors use up to 60% less energy than comparable x86-based EC2 instances.
What are the biggest challenges for enterprises and large customers moving to the cloud? (Can also be used to answer "what separates those customers that are successfully migrating from those that aren't?")
First, the senior leadership team needs to be aligned and truly committed that they want to move to the cloud. It's easy for others to do nothing or block things if the leadership team isn't making the move a priority and building a culture for change. second, the most successful organizations moving to the cloud started with an aggressive top-down goal that forced the organization to move faster than it would have organically. Third, it's really important that organizations are trained on the cloud and comfortable with the concepts as part of the whole process. We train hundreds of thousands of people a year for that purpose. And last, sometimes we find that organizations can get paralyzed if they can't figure out how to move every workload. So, we often work with organizations to do a portfolio analysis to assess each application and build a plan for what to move short term, medium term, and last. This helps organizations get the benefits of the cloud for many of their applications much more quickly, and it really helps inform how they move the rest.
What steps has AWS taken to respond to the climate crisis?
In 2019, Amazon and Global Optimism co-founded The Climate Pledge, a commitment to reach net-zero carbon emissions by 2040—10 years ahead of the Paris Agreement over 300 companies across 29 countries have joined The Climate Pledge. As the first signatory, Amazon is on a path to power its operations with 100% renewable energy by 2025—five years ahead of its original target of 2030. Amazon is currently the world's largest corporate purchaser of renewable energy, and in 2021 we reached 85% renewable energy across our business, with more than 12 gigawatts (GW) of renewable energy production capacity across our global portfolio.
Why is AWS growing so fast?
In the cloud you just provision what you need—if it turns out you need less, you give it back to us and stop paying for it. That variable expense is lower than what virtually every company can do on its own because AWS has such large scale that we pass on to customers in the form of lower prices. In fact, we work relentlessly to lower prices. We've lowered our prices 129 times since AWS launched in 2006 (as of September 14, 2022). Cost is very compelling and almost always the conversation starter, but the number one reason that enterprises and governments are moving to the cloud is the agility and speed with which they can change their customer experience
Emerging Technologies c.Compute
Instances, Containers, and Serverless
How many Regions, and AZs are available in AWS?
No other cloud provider offers as many Regions with multiple Availability Zones connected by low latency, high throughput, and highly redundant networking. The AWS Cloud spans 96 Availability Zones within 30 geographic Regions around the world, with announced plans for 15 more Availability Zones and 5 more AWS Regions in Australia, Canada, Israel, New Zealand, and Thailand. Over time, we will be in most of the large developed geographies with regions. Gartner has said that the AWS Region and Availability Zone model is the best way to run enterprise applications that need to be available all the time.
Key points in Sage Maker
Tens of thousands of customers are now standardizing on top of SageMaker. Since we launched SageMaker in 2017, we have added more than 250 capabilities and features. To further democratize machine learning, we launched Amazon SageMaker Canvas, which enables business users and analysts to generate highly accurate machine-learning predictions using a visual point-and-click interface—with no coding required.
Data Lakes & Analytics:
The most popular choice for cloud data lakes is Amazon S3 because it has the most functionality, and unmatched availability, durability, and scalability. It's also the most secure object store. Amazon S3 hosts hundreds of thousands of data lakes for household brands such as Netflix, Airbnb, Moderna, Expedia, GE, and FINRA. In fact, more data lakes run on AWS than anywhere else
What is cloud computing?
The term "cloud computing" refers to the on-demand delivery of IT resources via the Internet with pay-as-you-go pricing. Instead of buying, owning, and maintaining your own data centers and servers, organizations can acquire technology such as compute power, storage, databases, and other services on an as-needed basis.
