Strategies for Managing High-Traffic Events With Temporary Server Scaling

Traditional servers can run for many years, but servers in a cloud-native architecture can run for weeks, days, or even less. When a server is viewed as a temporary resource, users can shift their architecture to a more dynamic view, which is capable of handling enormous variations in scale and workflow.

There are about 1.09 billion websites in 2024, and 252,000 new ones are created every day. The number of active websites is just under 193 million. A new website is launched every three seconds, and still, no website is immune to high traffic events.

What is temporary server scaling?

Servers that are deployed to the public cloud or a data center using a traditional approach are long-lived. However, they need continuous updates, patching, etc. More memory, CPU, and disk space are required to scale a traditional server. If you don’t back up these servers consistently, you can lose months of hard work, and you might not be able to rebuild the server.

Temporary scaling does away with the need to configure a single, long-lived server. With temporary scaling, one takes advantage of so-called server elasticity: the on-demand growth or reduction of a resource for a certain period. A high-traffic event is a classic example. You can scale the server temporarily when you need to. This is possible with fast shared hosting. According to expert predictions, the shared hosting market will grow at 15% a year and reach $72.2 billion by 2026.

Elasticity vs. scalability

Server elasticity is about pooling, managing, and automating resources as needed. You can do this with any resource: CPU, storage, memory, databases, network bandwidth, web apps, deployment platforms, etc.

Elasticity and scalability are not the same thing. Scalability involves resource growth or shrinkage over time, while elasticity relates to a certain period. An example is a retailer experiencing a server shortage during the Christmas season. This will cause a number of problems when they try to take online orders with increased web traffic at that specific time of year.

Elasticity is usually managed by using scaling groups. More rarely, it can be achieved manually or through automation scripts.

Use of server scaling groups

Scaling groups make it possible to manage servers that perform the same tasks together. This allows the user to increase or decrease the servers in the group according to demand. You configure these scaling groups with a minimum and maximum threshold for the number of required servers. Then, you assign rules to the group to allow it to increase or decrease based on the current workload.

You add more servers to the group when you need burst capacity. As the capacity requirements decline, the number of servers can be reduced as needed until you reach the minimum threshold.

Distributing requests via load balancing

You usually place a load balancer in front of the group to direct requests to a server within it. Load balancers can assign requests based on a server’s current workload. You assign at least one public domain name to a load balancer, letting it respond to all requests for a given server. 

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