起因
Since I was selected as AWS Community Hero in early 2020, I have encountered the epidemic and have not flown for three years. It is a great honor to be invited to physically log in to the AWS annual developer conference re:Invent 2022 in Las Vegas this year. I am very happy to be able to experience all kinds of live events again.
In the past few years, I began to look at the (keynotes) of various developer conferences, technical conferences, and seminars, especially the content of AWS re:Invent. Try to find out why the speaker organize the speech in such order of certain topics, which topics may be pulled out in comparison, and so on.
As in the past, at the beginning of the full text, I will first try to grasp the structure of the speech, then put some observations and inferences, and then put some running notes in each paragraph for future search and use. There are extended readings at the end of the article, which can enrich the background situation or information of the speech content. I also hope to have the opportunity to lead everyone to reason together why this product or function was launched at this time point, where the trends of various industries around the world are going. Read more, compare more, and refer more. Maybe we can avoid some minefields of misjudgment. In the case of limited resources, if we go in the wrong direction, the market may not give us a chance to cut it off and practice again. My reasoning is not necessarily correct, just as a kind of practice and sharing.
New services or new launches are marked with [NEW 🚀]
in this article, so that you can press Command/Ctrl+F to search on the inner page.
This article deliberately removes most of the product links first, so that everyone can focus on reading (we are all less focused these days, aren’t we?). If you need a product link, you can refer to the AWS Product List that I organize regularly.
I also welcome everyone to give me some feedback or corrections (also come and see if there is a chance to include these materials in ChatGPT 2022). Then let’s get started!
Contents
tl;dr
The 2022 keynote is AWS CEO Adam Selipsky’s second re:Invent keynote. Continuing from his former CEO Andy Jassy’s mention of “Still early days for cloud” in 2020, Adam started with “It’s still early days” in his first year. Then in his second year, Adam began to develop his own style.
Laying a good foundation from the bottom —> Unpacking async made easy —> Connecting everything —> Implementation to solve problems.Echoing the other three keynotes:
- Laying a good foundation and draw salary from the bottom
- Unpacking async made easy
- Connecting everything
- Implementation to solve problems
Structure
This year’s Adam Selipsky Keynote’s two-hour keynote speech structure paragraphs, the order is exactly the same as last year’s keynote speech The order is completely reversed, he did not arrange the theme this year, but by introducing four environments, corresponding to four paragraphs.
The four paragraphs are:
- Vast 👉 Space 👉 Data
- Unfathomable 👉 Deep Sea 👉 Security
- Extreme 👉 Antarctica 👉 Compute
- Possibilities 👉 Imagination 👉 Application
Ppening
- Various application scenarios for various customers
- Leading now, so thinking about the next generation
- 100% renewable energy by 2025 —> ESG
- Water positive by 2030 —> ESG
- Reduce cost —> It is sort of a continuation of last year’s IT still early theme. Constantly reducing spending for customers is also one of the steps in the entire Amazon flywheel.
- Carrier: 40% reduction in costs of ERP
- GILEAD: more than 60M saving
- AGCO: 78% reduction in costs
- Flexibility to scale up or down
- Airbnb details road map to lower cloud costs —> savings of USD 63.5M 在疫情期間用量降低,所以雲端成本也馬上跟著減少 27%。
- Innovate faster
- Be prepared for anything
1. Vast 👉 Space 👉 Data
- Telescope
- In 1609, Galileo got the story of the improved telescope with convex lens, telescope 10x,
- It took centuries for humans to get into the rocket generation,
- Then we send telescopes into space to directly detect all kinds of visible and invisible light, 2014 Hubble Telescope, 2019 James Webb Space Telescope
- 1,000,000,000,000,000,000,000,000 stars
- In order to explore this vast starry sky, humans need a variety of tools, including launching various rockets, satellites, building space stations, etc. —> need various systems and teams to work together to piece together and interpret various observation data
- Data explosion
- How to manage this large and continuously generated data is a problem.
- The vast realm… of data
- expedia group - 600B AI prediction per year
- SAMSUNG - 1.1 B users make 80,000 requests per second
- Pinterest - 1 exabyte of data
- Exploring the vast data realm
- Right tools (Databases + Analytics + ML/AI)
- Databases
- Amazon Aurora —> First talk about compatibility, and then talk about performance is several times faster than the original
- Analytics
- AWS Analytics Services —> He deliberately left one without “Serverless” in the lower right corner, and everything else has
- Amazon Redshift
- [NEW 🚀] OpenSearch Service Serverless (Preview) —> A-ha!
- ML/AI
- AI services
- Amazon SageMaker
- Guest: Biljana Kaitovic, EVP, Digital & IT and Group CIO, ENGIE
- energy provider in France
- World Energy Actor | ENGIE
- Tesla invented alternating current in 1882
- 9,000 in 1882 —> 180,000 terawatt-hours TODAY —> 270,000 in 2050 (50% increase)
- Accessible, affordable, secure, green
- data and digital play a key role in energy transition —> No wonder there are a bunch of energy-related agendas out this year?!
- 1 - optimizing renewable energies
- 2 - managing decentralized energy - Solar power generation on each roof - mentioned blockchain
- 3- reducing energy usage - IoT
- more than 1 petabyte data
- commonDataHub
- 60% savings on runtime in the cloud
- Databases
- Integration
- combine the data from different data source
- ETL —> nightmare
- “… thankless, unsustainable black hole”
- A better way
- (4 points here)
- A Zero ETL future…
- [NEW 🚀] Amazon Aurora zero-ETL integration with Amazon Redshift (Available in Preview Today)
- Near real-time analytics and ML on transactional data
- Consolidate data from multiple Aurora databases
- Updates automatically and continuously
- Serverless - no infra to manage
- Apache Spark
- [NEW 🚀] Amazon Redshift integration for Apache Spark (GA)
- Governance
- Control vs Access
- Too much control —> Silos
- Too much access
- [NEW 🚀] Amazon DataZone (Coming Soon)
- Bringing data and people together
- data producers
- Set up business data catalog
- Populate with metadata, labels…(缺)
- data consumers
- search and browse catalog, request access
- Define data projects
- data producers
- Analytics integrations
- Redshift, QuickSight, Athena, Partner API
- Bringing data and people together
- Control vs Access
- Insights
- Amazon QuickSight
- [NEW 🚀] Operational paginated reports
- Amazon QuickSight Q - Ask Q questions directly
- [NEW 🚀] ML-powered forecasting with Q (GA Today)
- [NEW 🚀] "Why" questions with Q (GA Today)
- Amazon QuickSight
- The vast realm of data summary —> next realm?
- Right tools (Databases + Analytics + ML/AI)
2. Unfathomable 👉 Deep Sea 👉 Security
- Pressure chamber, sonar
- Confidence to explore —> Talked about Digital transformation
- Secure Global Infrastructure
- Secure and agile
- Confidence to build and explore
- Identity and access mgmt
- Detection and response
- Amazon GuardDuty
- Amazon GuardDuty EKS Protection <— Amazon GuardDuty now protects Amazon Elastic Kubernetes Service clusters
- [NEW 🚀] Container runtime threat detection for GuardDuty
- Amazon GuardDuty
- Network and application protection
- Data protection
- Thousands of security solutions - There are a bunch of security solutions on the Marketplace
- OCSF - Open Cybersecurity Schema Framework
- [NEW 🚀] Amazon Security Lake (Available in Preview Today)
- —> I wonder if the usage of partner solutions is not enough after putting them on the marketplace? Simply repackage it to make it easier for everyone to use, a win-win situation.
- Divide into four quadrants to disassemble: AWS vs Partner + Source vs Analytics
- Memo: Adam has a layout that follows the slides, so move around appropriately! :p
3. Extreme 👉 Antarctica 👉 Compute
- Memo: In the opening video of this section, there is really super bright flashing lights on the scene to simulate lightning!
- Antarctica
- Captain Robert F. Scott
- Roald Amundsen
- ponies, snow dogs
- “Good enough” simply isn’t good enough
- F1 - Reduced simulation time by 70%
- Epic games - 100M+ players supported (Real-time gaming)
- Nielsen - Hundred of billions of events per day
- 600+ instance types (last year 475)
- AWS Nitro
- Graviton3 - 25% faster than Graviton2
- directTV use Graviton3 to support 5G network
- [NEW 🚀] C7gn Instance for EC2, Powered by Graviton3 (Available in Preview Today)
- Memo: EC2 instance type name has
g
in it
- Machine Learning
- Training —> train model
- Trn1 Instance for EC2 -50% lower training cost —> published last year
- qualtrics XM - 40% reduction in cost
- Trn1 Instance for EC2 -50% lower training cost —> published last year
- Inference —> Run predictions with the model
- [NEW 🚀] Inf2 Instances for EC2 (Available in Preview Today)
- Training —> train model
- High Performance Computing (HPC)
- Dana-Farber Cancer Institute - 48x more target drug molecules identified
- Designed for HPC
- EC2 Instances for HPC workloads
- Compute intensive - Hpc6a
- Compute and network intensive - [NEW 🚀] Hpc7g (Coming soon)
- Data and memory intensive - [NEW 🚀] Hpc6id (GA Today)
- Guest: Cedrik Neike, CEO, Digital Industrials, SIEMENS
- Space Perspective - Revolutionizing space travel —> Space Perspective dot com
- 1- Siemens software on AWS
- Siemens star-CMM+ Multiphsics simulation software
- Amazon EC2 c5 instances
- 92% Fortune 500 use Siemen Software
- 24 of 25 cars manufacturers use our software
- Dream it —> Make it
- Industrial Revolution 4.0
- Siemens + AWS
- AWS has helped Siemen move industrial software to the cloud —> Yesterday, I chatted with people from Arm that they also have a department that cooperates with AWS to connect the software (firmware + cloud) on both sides.
- A modern factory produces 2,200 TB of data per month (OT side)
- Unlocking the potential of industrial data
- example: NORTHVOLT
- Factory gateway —> Kinesis —> Lambda —> DynamoDB —> RDS + S3 —> Athena
- We scale good ideas
- MENDIX - 200,000 users?
- Closing
- 1- Siemens software on AWS
- 2- Combinging AWS cloud services with industrial data
- 3- Enabling builders with low-code application tools
- Spatial Simulation
- 3D engines - Unreal Engine & Unity
- traffic control simulation
- [NEW 🚀] AWS SimSpace Weaver (GA) - Run massive spatial simulations without managing infra
- All your extremes —> The end of the previous paragraph?!
4. Possibilities 👉 Imagination 👉 Application
- Imagination not only lets us create new worlds, it lets us live in them. –> I thought I was going to start talking about web3 and Metaverse XDD, but it’s actually the application scenarios of real customers in various industries. I like to listen to this passage every time I keynote, and it’s relatively close to the scene.
- Removing constraints
- Amazon Connect - Contact center in the cloud
- 10M+ Connect interactions per day
- Priceline has thousands of people answering the phone at home at night
- [NEW 🚀] ML driven forecasting, capacity planning, and scheduling (GA)
- [NEW 🚀] Contact Lens with agent performance management (Available in Preview Today)
- [NEW 🚀] Agent workspace with guided step-by-step actions (Available in Preview Today)
- (Canned applause this year?!)
- Supply chain complexity
- [NEW 🚀] AWS Supply Chain (Available in Preview Today)
- Unified UI
- Select data source e.g. EDI, SAP, S3 –> In the future, Amazon.com (should) be able to connect EDI easily! :p
- Data lake
- Inventory
- ML prediction
- New insights
- In review
- [NEW 🚀] AWS Supply Chain (Available in Preview Today)
- Amazon Connect - Contact center in the cloud
- Combining disparate ideas
- Protected environments for analyzing data
- [NEW 🚀] AWS Clean Rooms (Preview in a few weeks)
- Great place to clear your data! –> Can I change it to call API in the future when entering the clean room? :p
- Market behavior data, reporting data, user data —> AWS Clean Rooms
- Relevant campaigns while protecting customer data
- Clean room setup —> Data collaboration (Outline first, details later)
- [NEW 🚀] AWS Clean Rooms (Preview in a few weeks)
- Identity Resolution
- Healthcare
- Guest: Liz Homans, CEO, Lyell Immunopharma
- 40/100 people will develop cancer in their lifetime
- 2000 of you could one day be a person with cancer
- 250 of us are already cancer survivors
- Cell therapy is the next frontier —> As big as space, as small as cells
- 90% of all cancers are solid tumor cancers
- Then enter the T cell classroom :p
- Testing T-cell therapies today
- LyFE
- All of possible workshop
- AWS for Health
- Challenges of omics
- cost
- scale
- specialist tools
- privacy
- Omics classroom
- [NEW 🚀] Amazon Omics (GA)
- Guest: Liz Homans, CEO, Lyell Immunopharma
- Retail
- Just walk out technology by amazon
- “Amazon one” Waving hands and palms, oh no, it’s the checkout? !
- Protected environments for analyzing data
- Collaboration
- Closing
- Transforming X
- Transforming innovation
- Transforming penalties of failure
- Transforming decision making
- Transforming culture
Next step
If you feel that this thread dismantling note has caught the key points you want to read and is helpful to you, I hope to continue this kind of in-depth article in the future, welcome to pat and feed me a coffee ☕, or forward the article to your friends and colleagues, community, thank you for your encouragement and support.
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