In today's race to the cloud, companies often take the path of least resistance, or "lifting and shifting" existing apps without modification. Yet, to maximize gains from a cloud migration, it is frequently preferable to update workloads to leverage cloud native capabilities. This guided technical demo progresses through seven different means of replatforming and refactoring an application, illustrating the pros and cons of each architecture.

In this briefing, we discuss the most common solutions and capabilities available in today's software ADC (application delivery controller) market. As companies embark on their digital transformation journey, software-based load balancers quickly become a topic of discussion to replace the dependable bare metal load balancing solutions of the past. Modernized lightweight virtual load balancers bring agility and speed to infrastructure teams, enabling them to adapt to DevOps and increasing business demands around application security. WWT will offer insight on the best use cases for each solution and can even discuss where a combination of multi-OEM solutions may be the ideal. Our goal is to have a vendor-agnostic discussion; however, we can also focus your briefing on specific products and ecosystems.

The use of artificial intelligence (AI) and machine learning (ML) is more ubiquitous than ever before. Companies want to take advantage of AI/ML algorithms to deploy models that allow them to make more informed decisions. Their data science teams are busy writing code, loading data, and validating models, but run into challenges when trying to deploy a model into production and continuously update and refresh thereafter. The production process is highly manual and often inconsistent across the enterprise. This briefing provides insight into the techniques developed to expedite data science teams' initiatives and ensure successful deployment of ML leveraging an MLOps capability.