Over 50,000 attendees descended on fabulous Las Vegas, Nevada, for the 11th annual AWS re:Invent, serving up a week of inspiring talks, key insights, and exciting announcements!
Following a reduced-capacity event in 2021 and a virtual event in 2020, the Neon Capital of the World was shining brighter than ever with the buzz of the AWS community coming together again for sessions, keynotes, Q&As, and more.
We’re recapping what went down at the largest Amazon Web Services (AWS) conference, highlighting the most important announcements, insights, and developments from the cloud service provider to guide your use of AWS today, tomorrow, and across the following year.
Improving how we work with data
Data was one theme very much in the spotlight at re:Invent 2022, with a range of announcements concerning databases, data analytics, and data engineering.
AWS launched the general availability of fully managed RDS Blue/Green Deployments in Amazon Aurora and Amazon RDS at the start of the event. The feature enables users to perform blue/green database updates for Aurora with MySQL compatibility, RDS for MySQL, and RDS for MariaDB.
Amazon RDS for MySQL now also supports Amazon RDS Optimized Writes. Intended for RDS for MySQL customers with write-intensive database workloads, the announcement enables users to improve write throughput by as much as double, without costing an extra cent.
To simplify deployment, AWS is turning its attention to pre-integrating products, including the integration of its relational database, Aurora, and Redshift for cloud data warehousing. Integrating Amazon Redshift with Apache Spark means that AWS analytics and machine learning (ML) services can run Apache Spark applications on Amazon Redshift data, while Amazon Aurora’s integration with Amazon Redshift allows customers to run Amazon Aurora data with Redshift in real-time. The result? A zero-load future where customers don’t need to extract, transform, and load data between services.
One major highlight in a keynote by AWS CEO, Adam Selipsky, was the announcement of DocumentDB Elastic Clusters. The scalable, highly durable service manages the underlying infrastructure and elasticity for MongoDB workloads. Now generally available, the service is one of AWS’ fastest-growing, with big name customers like BBC and Samsung already using it for their workloads.
Bridging the skills gap brick by brick
The skills gap continues to be a major issue concerning not just the AWS community, but the wider ecosystem and industry too. At re:Invent, AWS presented a range of new initiatives aimed at bridging the skills gap through education and training.
AWS Machine Learning University is launching a new program that helps community colleges, minority-serving institutions (MSIs), and historically Black colleges and universities (HBCUs) teach database, AI and ML concepts. The free program, announced at re:Invent 2022, pairs an educator-enablement boot camp with a detailed curriculum to improve education around next-gen tech. In the long term, this bridges the skills gap by empowering budding talent from minority and disadvantaged backgrounds to learn, upskill, and grow.
In a further focus on cloud education, AWS unveiled plans to run six educator-enablement cohorts in 2023, providing students with free compute power to help them apply AI and ML concepts in a hands-on environment and experiment with tools in their own sandbox.
Momentum is building around AI and ML
AI and ML are developing at an excitingly rapid pace, bringing with them a whole host of new possibilities. At re:Invent 2022, AWS announced a range of updates aimed at simplifying the use of applications and democratizing access to everything AI and ML have to offer.
AWS revealed eight new updates to SageMaker at the conference to entice more customers to not just adopt AI, but to maximize its potential too.
New updates to the SageMaker machine learning service will improve governance attributes. For example, the launch of Amazon SageMaker Role Manager aims to simplify control access and user permissions for administrators, and a new tool named Amazon SageMaker Model Cards, helps data science teams simplify digital documentation and record keeping. AWS also introduced Amazon SageMaker Model Dashboard, offering a centralized interface within SageMaker to optimize tracking. Updates to Studio Notebook will enhance data preparation, and improve quality and automated model validation, and a new SageMaker workspace enables real-time collaboration between data teams.
Elsewhere, AWS introduced new AI features to a range of other services. Among the most notable, new capabilities in Amazon Textract will improve loan document processing, while updates to Amazon Transcribe (its automatic speech recognition service) will provide real-time call analytics to improve the service and customer experience clients can offer to their customers. That’s not forgetting updates to Amazon Kenra, with AWS announcing that it has improved the AI-based enterprise search service by supporting tabular search in HTML.
Optimizing the use of business intelligence
Amazon QuickSight, the serverless business intelligence service offered by AWS, has been upgraded with five new capabilities:
- QuickSight Q supports forecast and “why questions” to inform more data-driven decisions.
- QuickSight Q now auto-generates semantic information to reduce the time spent preparing data for natural language querying manually.
- Amazon QuickSight Super-fast, Parallel, In-memory, Calculation Engine (SPICE) provides high performance at pace and scale, able to process over 100 million queries every week.
- QuickSight Paginated Reports offers users a way to create, schedule, and share reports and data exports from a single fully managed service.
- QuickSight’s application programming interface (API) now boasts new features enabling users to create, manage, and edit business intelligence assets, optimizing migrations from on-premise systems.
Security remains a talking point
As the capabilities of technology continue to evolve and grow, unfortunately, so too do the capabilities of cybercriminals, meaning cybersecurity remained a top talking point at this year’s re:Invent.
At the conference, AWS announced a series of updates to its AWS security services. Perhaps the most notable was the debut of a new cybersecurity service, Amazon Security Lake, which creates a customized data lake for the customer by automatically centralizing security data from both cloud and on-premises sources.
Among the introduction of other new security features, Amazon Inspector and Amazon Macie will also receive updates.
Interestingly, AWS also placed a greater emphasis on collaborating with the wider security ecosystem at this year’s conference – perhaps a response to the lack of general consensus as to the role of a cloud provider versus third-party security vendors. For example, the introduction of the Open Cybersecurity Schema Framework (OCSF) has already received support from leading security vendors like Splunk, Rapid7 and Broadcom Inc.
Rescuing the supply chain
With a global supply chain crisis accelerated by a range of factors worldwide, at re:Invent 2022, AWS unveiled its intentions to explore supply chain solutions for the first time.
Debuting a new supply chain cloud application, the tool integrates with ML to assist large enterprises using multiple ERP systems to get a comprehensive, centralized view of suppliers, inventory, logistics, and more.
AWS has the (compute) power
At re:Invent 2022, AWS released a wave of updates to its compute services and a range of new industry-specific capabilities for running extremely heavy workloads, announcing three new Amazon Elastic Compute Cloud (EC2) instances powered by AWS-designed chips. These instances are intended to be the most cost-effective solution to running performance computing workloads at scale – useful for anything from mathematical modeling to weather forecasting, and usable in a range of applications across academia, business, and science.
The debut of AWS Graviton3E chips-powered Hpc7g instances supplies an economical solution to running high-performance computing (HPC) workloads, while new AWS Nitro Cards-powered C7gn instances ensure the optimal performance of network-intensive workloads, and new AWS Inferentia2 chips-powered Inf2 instances support large deep learning models.
With a more industry-specific focus, AWS introduced two new services for the space and healthcare industries: Amazon SimSpace Weaver and Amazon Omics.
Amazon SimSpace Weaver is a new fully-managed service assisting in building and operating large-scale space simulations, modeling dynamic systems with many data points. Creating a more sophisticated simulation environment than ever before, the application allows users to better visualize physical spaces and perform more immersive training, informing better decision-making while reducing time to deployment.
Amazon Omics is designed for bioinformaticians, researchers, and scientists. Announced as generally available at re:Invent, the service supports large-scale analysis and collaborative research, helping to store, query, analyze, and derive insights from genomic, transcriptomic, and other omics data.
