AWS re:Invent is back, in-person, and with the new CEO of AWS, Adam Selipsky to kick off its 10th year anniversary! While it does feel a little strange to start the conference without Andy Jassy after all these years, Adam got things off to a big start, stepping deftly into the role. Adam led us through some fantastic customer stories from the likes of United Airlines and Nasdaq, and gave us the kinds of big announcements we’ve been waiting all year for. Adam’s keynote used the idea of pathfinders as it’s through-line, showing how the accomplishments and courage of amazing historical figures such as Roscoe Brown and Florence Nightingale mapped to the innovations within forward thinking modern companies.
While there were lots of new features and services announced at the keynote, these are highlights that caught our eye.
AWS Private 5G
AWS Private 5G will allow enterprises to set up scalable private 5G networks that are ready in days instead of months. As a managed service, customers will be able to focus more on their mobile devices and the data they generate instead of the network hardware, which AWS will deliver and manage.
As fleets of IoT enabled devices grow, and are often spread across large areas, using AWS Private 5G will allow customers to better manage those devices, and collect that increasing volume of data into their AWS environments, letting them more quickly make analysis-based decisions, all without the need to buy their own hardware or build telecom-level expertise.
AWS Private 5G is available in preview currently, within the United States, and more information can be found on the product page.
AWS has released their next-generation custom chipset with the AWS Graviton3 processor. These chips are capable of delivering up to 25% better compute performance, alongside performance increases of up to 2x for floating-point calculations and cryptographic workloads. The first instance to utilize this chipset is the C7g instance, which is designed for use in HPC, gaming, and other high compute workloads.
AWS’s previous generations of Graviton have provided customers with increased performance with lower costs, and this continues that trend. Customers will be able to run massive compute workloads faster, letting them reach their answers more quickly while also saving money.
These instances are currently available in preview, and to learn more about them see the AWS announcement.
Amazon SageMaker Canvas
In order to provide business analysts with the ability to more easily create accurate ML models and predictions, AWS has created Amazon SageMaker Canvas. This service provides users with a visual means to create ML pipelines, using a point-and-click interface and AutoML to connect data sources and identify the best model.
SageMaker Canvas will allow ML to be more accessible for those who don’t have a deep coding background, allowing analysts to quickly build predictions for a wide range of business-focused questions. Canvas is built to make these models and predictions easy to share within the organization, and the models can be further refined by data scientists if necessary.
AWS Mainframe Modernization
Moving mainframe workloads to the cloud is usually an onerous process, but with AWS Mainframe Modernization, AWS is looking to simplify and automate in order to speed it up. AWS Mainframe Modernization is a platform that will guide and assist with the migration process from the assessment stage right through to the replatforming or refactoring necessary to actually move the workloads. The platform can perform automatic code conversion from COBOL to Java during a refactor, or use middleware emulation to facilitate a replatform with as minimal changes as possible.
With many enterprise organizations looking to migrate legacy systems to AWS, a platform that helps accelerate what is historically a lengthy and extremely challenging process is a welcome addition to the tools at their disposal. The promise of potential refactoring to Java during that migration will allow those same organizations to have a larger number of developers who are able to contribute to the code bases and further modernize.
The product page contains more details on the platform and its capabilities.
Cell-Level Security and Governed Tables with Lake Formation
AWS LakeFormation makes the process of setting up and securing a data lake easier for organizations, but the sharing of limited views of data between teams within the organization has typically been challenging, and often resulted in multiple copies of data. AWS has just introduced governed tables and cell-level security features to Lake Formation to make that more simple. Cell-level security allows you to set access to specific columns and rows in query results, while governed tables allow for ACID transactions of S3 tables, letting multiple sources reliably make changes to data at the same time.
Giving organizations more flexibility over who can access the data within a data lake means that more work will continue to use the data lake as their source of truth, with less need to make external copies of data to restrict access. This means lower storage costs and better governance for internal security standards as well as compliance frameworks.
If you’re looking for help with leveraging any of these new services and features in your cloud native initiatives, get in touch with our team!