There are different ways that an Azure App Service can be scaled to meet the changing demand of the application, by using options such as manual, automatic, and scheduled scaling, as well as scaling based on metrics and custom rules.
Category: Performance
Throttling: Keep your system in control, under any load
The Throttling design pattern is a software design pattern that limits the rate at which a process can be executed, in order to prevent overloading of resources, improve performance, and avoid service degradation or failure, by using techniques such as fixed rate, sliding window, token bucket, and leaky bucket.
Queue-Based Load Leveling: Smoothing out the bumps in high-traffic systems
Queue-Based Load Leveling pattern is a software design pattern that uses a queue as a buffer between the source of requests and the service that handles them, in order to smooth out spikes in traffic and prevent overloading of resources by allowing the service to process requests at a steady rate and temporarily store incoming requests that exceed the service’s capacity.
CQRS: Segregating read and write for a better performance
The Command Query Responsibility Segregation (CQRS) pattern is a software design pattern that separates the responsibilities of handling commands that change the state of the system from the responsibilities of handling queries that retrieves the state of the system, by using different models and data storage for read and write operations, in order to improve scalability, performance, and simplify the complexity of the system.
Performance optimization, the cloud way
Optimizing cloud performance involves identifying and addressing bottlenecks and inefficiencies in cloud-based systems and services to improve their speed, responsiveness, and overall performance, by using techniques such as load balancing, caching, autoscaling, monitoring and analysis, and choosing the right instance types and storage options, in order to ensure that the application and services running in the cloud are able to meet the demands of the users and transactions.