Autodesk on AWS

In this AWS Conversations With Leaders video, Amy Bunszel, executive VP of architecture, engineering, and construction design solutions at Autodesk, dives into the success of Autodesk and how they take risks, without being reckless. This approach created a culture of experimentation within the workplace, propelling them to solve complex problems as they build the right teams to scale at massive proportions.

Watch this conversation with Prakash Kota, CIO at Autodesk, about organizational strategies and best practices to empower people and business to succeed in the digital future.

Prakash Kota, Autodesk SVP & CIO, speaks about getting staff and leadership onboard with the company-wide enterprise workloads migration to the AWS Cloud and discusses how to motivate staff through AWS Training and Certification. A key learning from Autodesk's transformation has been to start small and expand fast by investing in your people to build a culture of continuous learning.

Autodesk uses machine learning models built on Amazon SageMaker to help designers organize and sort through thousands of generative design options. With Autodesk's generative design process, Edera Safety, a design studio from Austria, build a better and more efficient spine protector.

The Autodesk Data Platform (ADP) collects and processes product usage data, providing Autodesk’s operating teams with a product analytics platform. By migrating the ADP from a Spark-based processing system to AWS Lambda, Autodesk saves up to 90 percent in data processing costs annually. Today, Autodesk is able to process data in near real-time, providing timely analytics for business users to leverage for product improvements and other business opportunities.

To give its customers the power to work more quickly, effectively, and sustainably throughout project lifecycles, Autodesk needed to reimagine its infrastructure to support this complex, exponentially growing data. Learn about the five step framework that Autodesk used.

Autodesk built machine learning skills models using Amazon SageMaker that differed from typical classification models because they are designed to choose the correct team responsible for supporting users. This is in contrast to many models that attempt to predict the topic of a case and then route from that topic.

Autodesk chose AWS solutions to build and rapidly deploy a machine learning model for a new iteration of a forum called Community Match. The model matches the expertise of forum members with questions posed on the forum—the idea being to encourage community members who are experts on a particular subject to share their insider knowledge on Autodesk solutions. And whereas previously customers sought Autodesk support only to troubleshoot problems, now they take advantage of the knowledge within the shared community to use Autodesk software more effectively.

Developing a 360-degree view of customer financial metrics can give organizations the ability to make proactive decisions instead of being reactive with account team strategies. However, customer data is usually housed in various sources and requires a lot of effort to join metrics by mapping IDs, account names, and other fields. This data can be presented in conflicting formats, and the number of records can exceed what common data tools can handle. Autodesk leverages Trifacta on AWS to create a streamlined data pipeline process to automate the delivery of holistic customer analytics.

Autodesk creates design software that requires significant compute capacity for rendering. For Autodesk, the Rendering-as-a-Service (RaaS) workload was its single largest when measured by total spend. The company now relies on Amazon EC2 Spot Instances for significant cost savings on its RaaS function.

Although Autodesk benefited from its embrace of AWS, setting up new AWS accounts posed a challenge for the company’s two-person AWS Operations Team. Manual processes for account setup resulted in 2-week turnarounds on new-account requests and risked human error. Autodesk built a solution using serverless architecture to minimize the time and cost required for infrastructure management. With the solution, Autodesk developers now submit an online form to request a new account, and an API triggers the account-creation process. The solution, which also supports querying accounts by account number, email address, or IP address, took only a month to develop and launch.

Autodesk uses Amazon WorkSpaces instead of renting physical hardware to host its virtual workstations on zero clients, improving setup efficiency and reducing its carbon footprint. Using AWS, Autodesk sets up and deploys 450 workstations at its Autodesk University events, saving nearly a week’s worth of time and thousands of dollars.

AWS Support helps Autodesk focus on its core business instead of spending valuable time worrying about architecting its foundational AWS services. Autodesk thinks of AWS Support as its virtual infrastructure support team as if it was just another department or group within Autodesk because it knows it can contact them with no prior notice and get the level of support it needs.

Autodesk quickly designed, trained, and debugged a machine learning model on visual similarity. Using SageMaker Debugger, Autodesk improved Fusion 360 performance and saved both time and compute costs.

Learn about the architecture of Autodesk Shotgun Private Cloud, a cloud-based VFX Project Management application running on AWS. Autodesk Shotgun simplifies creative project management and unifies visual effects (VFX), animation, and games teams of all sizes. Shotgun is a scalable on-demand platform that can support just a few users to thousands—used by more than 1,000 studios globally to track millions of tasks each day. This walkthrough shows how AWS helps customers build robust SaaS applications that address even the most stringent security needs.

Autodesk migrated a mission-critical database with minimal downtime. This migration helped streamline the management and resiliency of the Autodesk SSO service, optimize costs, and reduce overhead for infrastructure maintenance. This blog details the pre-migration architecture, migration strategy, migration steps, and performance comparison.

Autodesk created an end-to-end ecosystem that standardizes the way it built, ran, and deployed software. One Amazon ECS cluster allows Autodesk to run both Linux and Windows workloads.