PaaS provides increased flexibility by allowing developers to quickly scale their applications up or down as needed, without having to worry about the underlying infrastructure.

Diagonal scaling is not a common type of scaling in PaaS. Horizontal scaling involves adding or removing instances of the application, while vertical scaling involves increasing or decreasing the resources allocated to each instance.

Horizontal scaling involves adding or removing instances of the application, while vertical scaling involves increasing or decreasing the resources allocated to each instance.

Horizontal scaling does not simplify management, as it can be more complex to manage multiple instances of an application than a single instance.

Vertical scaling does not reduce cost, as it typically involves increasing the resources allocated to each instance of the application.

Automatic scaling simplifies management by allowing the PaaS to automatically scale the application based on predefined rules, without the need for manual intervention.

Disk space is not a common metric used for automatic scaling, as it is typically not a limiting factor for application performance.

Using a single database for all data is not a best practice for designing scalable and elastic applications, as it can create a single point of failure and limit the ability to scale the application horizontally.

The primary challenge of achieving elasticity in PaaS is complexity, as it requires careful planning and design to ensure that the application can scale seamlessly and efficiently.

Using a single database for all data is not a common strategy for achieving elasticity in PaaS, as it can create a single point of failure and limit the ability to scale the application horizontally.

The primary benefit of using a message queue for achieving elasticity in PaaS is increased scalability, as it allows the application to handle more requests by decoupling the components of the application and enabling them to process messages asynchronously.

Encrypting traffic between the application and the client is not a common use case for a load balancer in PaaS, as this is typically handled by a web server or application server.

The primary benefit of using a distributed cache for achieving elasticity in PaaS is improved performance, as it allows the application to store frequently requested data in memory, reducing the number of requests to the database and improving the overall responsiveness of the application.

Security is not a common challenge associated with achieving elasticity in PaaS, as PaaS providers typically offer robust security features and mechanisms to protect applications and data.

The primary benefit of using a container-based PaaS for achieving elasticity is increased scalability, as containers are lightweight and portable, making it easy to scale applications up or down by adding or removing containers.