Now that AWS: reInvent 2021 in Las Vegas has wrapped up, it’s time to look back and see what the highlights were. What were the top stories?
The #1 Story at AWS:reInvent
There were plenty of stories at the show. From improved processors (i.e., Graviton 3), to IoT TwinMaker to Private 5G. But the #1 story a AWS: reInvent had to be machine learning (ML). How AWS supports it and how they enable users to take advantage of it. And the star of the ML show? SageMaker.
According to Bernard Marr, reporting about AWS: reInvent on LinkedIn, “Contributing to the ongoing drive to put machine learning and analytics abilities in the hands of as many people as possible – the “democratization of data science” – Selipsky announced the launch of Canvas for Amazon’s machine learning service, SageMaker.”
The goal of course is to give the power of ML to practitioners who are not experts at ML, and this is where Canvas for SageMaker comes in. “Canvas is a ‘no-code’ solution that uses visual tools to allow anyone with no formal background in data science to start analyzing, interrogating, and querying data in an intuitive way, automating tasks such as data cleansing and transformation while making it simple to train models and generate insights from the information.”
There were other stories at the show as well. Many that flew under the radar, but were perhaps just as impactful. Cloud migration has been an important step in digital transformation for some time. So, it should come as no surprise that AWS is increasing its support in this area.
At the show, AWS announced its AWS Mainframe Modernization. According to the press release, “AWS Mainframe Modernization makes it faster and easier for customers to migrate mainframe and legacy workloads to the cloud and benefit from the superior agility, elasticity, and cost savings of AWS.”
There are two ways to use AWS Mainframe Modernization. Customers can transform “legacy applications into modern Java-based cloud services” or they “can keep their applications as written and re-platform their workloads to AWS reusing existing code with minimal changes.”
According to the company, “AWS Mainframe Modernization provides all the development, testing, and deployment tools necessary to automate the migration from mainframe and legacy environments to AWS.” Do you know what’s missing from that list? Security.
While AWS continues to make it easier and easier for customers to migrate to their cloud, it hasn’t eliminated the need for those same customers to have to secure their newfound cloud deployment. This is due, in part, to the shared responsibility security model for cloud deployments.
The AWS customers who need help with cloud deployments are likely the same customers who need help with securing their cloud deployments. And that’s where CloudModeler comes in.
CloudModeler is a “one-click” automatic threat modeling utility that integrates directly with AWS. Not only does CloudModeler build threat models in your cloud environment in just a few steps, but it keeps the threat models up to date by continuously monitoring the cloud environment for changes. And in the cloud, those changes happen all the time—too frequently to monitor manually.
If you’re thinking about migrating your legacy workloads to AWS (or any of the other major cloud providers), checkout CloudModeler. The folks at ThreatModeler are happy to show you how it works.