Santa Ghosh

Cloud resource optimization is a critical aspect of ensuring efficient and cost-effective cloud operations. AWS offers a comprehensive set of services and tools that enable organizations to optimize their cloud resources effectively. Take a look at auto scaling services or/and storage optimization or/and monitoring and analytics tools. These are all tools and services which can help you massively. With its broad range of services, automation capabilities, and advanced monitoring tools, AWS empowers organizations to achieve optimal resource utilization, minimize waste, and maximize the value derived from their cloud investments, making it a compelling choice for cloud resource optimization.

I think there are just a few simple steps which makes that very easy. Work backwards! Define your Goal you want to achieve and then see what brings you there. We from AWS help our customer to understand and choose the right thing from them. It´s not only to choose the right service, i think more important is to choose the right partner and then everything can be very easy

Cloud computing performance optimization is one of the must do´s otherwise using Cloud Services does not make sense. One of the first steps is to right-size your instances by selecting the appropriate instance types and sizes based on your workload requirements. AWS offers a wide range of instance types optimized for different use cases, such as compute-optimized, memory-optimized, or accelerated computing instances. Utilizing Auto Scaling can also help dynamically scale your resources up or down based on demand, ensuring you have the right amount of resources available while optimizing costs.

If you consider to use AI to optimize your demand forecasting also think of the right choice of the LLM. We all know public LLM´s with which we played around and were impressed what that offers us BUT we should also consider that in demand forecasting we use sensitive data. Halluzinations or random responses could cost us a lot of money. In that UseCase we cannot accept that and above everything we do not want to train a public model. This sensitive data should always stay private and you should definitely pick a model which is specialized on that UseCase.

Advantages are going from saving time, to various improvements in the process to save a lot of money in the end. I think the question should not be what advantages do AI offer, better we think backwards. What is the goal you want to achieve and how could technology support in that. Here are a few customer stories for inspiration: https://aws.amazon.com/forecast/customers/

To improve the customer experience by using demand forecasting to estimate future customer demand by using machine learning needs guidance. By predicting future demand and purchasing patterns, you can plan ahead for supply chain optimization and inventory management. We from AWS developed an example Guidance to increase demand forecast accuracy, analyze various internal and external variables, and highlight low-code, no-code, or other advanced approaches. You can find that here: https://aws.amazon.com/de/solutions/guidance/demand-forecasting-for-retail-on-aws/?did=sl_card&trk=sl_card