- Scalability in AWS application design
- Scaling serverless vs. server-based applications
- Scaling files
- Storage design approaches
- Design approaches to scaling data and data storage
- Scaling SQL queries
- Understanding Data Migration Service
- Scaling applications
Skill Level Advanced
- [Lynn] Popularity is a good thing, right? Have you ever had a situation where your application had to scale because of an unexpected customer demand? Was your application able to scale in a reliable, predictable, and cost-effective way? We're gonna answer these questions in this course. I'm Lynn Langit, and in this course, we're gonna take a look at how best to scale applications on the Amazon ecosystem. We're gonna look at scaling through a number of different lenses. We're gonna start by looking at scaling networks.
We're not only going to consider scaling the information once it's inside of the Amazon ecosystem, but importantly, as it goes up, from your on-premise location, or from anywhere in the world, and then possibly comes back down, which is a key aspect of scaling properly. We're gonna look at working with VPCs and associated objects, and we're gonna look at some of the newer architectures, which don't use servers, rather use serverless services, such as S3 and DynamoDB. Speaking of DynamoDB and S3, we're also gonna look at most optimal methods for scaling both files and data, and this is increasingly becoming a unified world, with the emerging modern architectures, like the data lake.
We're gonna take a look at the practicalities of implementing these new architectures, and their impact, which is very positive, on scalability. We'll also look at more traditional applications, those that use server clusters, such as RDS, EMR, and Redshift. We will then apply our learning to understanding how best to scale a series of common architectures, and this will include everything from dynamic websites to machine-learning-driven IoT applications.
We have lots to cover, so let's get started.