Kubernetes Horizontal vs Vertical scaling

parameter

horizontal scaling

vertical scaling

Main Aim

Increasing/decreasing the number of machines

Adjusting the CPU and memory on existing machine

Best Use in

stateless applications

stateful applications

Scalability

High

Limited to maximum resources

Complexity

High

Lower

Tool Used

HAP ( Horizontal Pod Autoscaler )

VAP ( Vertical Pod Autoscaler )

Tolerance in fault cases

Higher, one fault doesn’t effect other

lower, one fault can effect other

cost

Can be cost-effective

Can lead to higher costs

Kubernetes Horizontal vs Vertical scaling

In Kubernetes, scaling is the most fundamental concept that makes sure applications run smoothly and consistently. Just consider a scenario where low resources are causing the application to freeze under the existing load. One potential solution is to manually assign the resources whenever this occurs, but it will take a lot of time. This is the place where scaling(moreover autoscaling) comes into action: the ability to scale applications to meet varying needs efficiently is one of the key features of Kubernetes.

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What Is Scaling In Kubernetes?

Scaling in Kubernetes simply means adjustment (dynamically), adjustment of the number of running models of an application or service based on the requirement/need. In Kubernetes with the help of scaling, we can easily manage our resources, and make sure they are consistently available and capable of handling variable requirements. In simple words, I would say it is the process of dynamically adjusting available resources....

Types of Scaling in Kubernetes

There are primarily two types of scaling,...

Horizontal Scaling

Horizontal scaling simply means adding more new servers to our infrastructure and distributing the workload across them. That is why this is also known as “scaling out.” The use of cloud services, especially those that provide auto-scaling and serverless computing, has made scaling workloads a breeze. This simplified approach has been confirmed to be highly useful for multiple cases....

Vertical Scaling

Vertical scaling focuses on increasing the capacity of the system, unlike horizontal which focuses on increasing the overall number of machines. Simply put we could say Vertical Scaling operates by adding more resources like CPU, memory, etc. Vertical Scaling is also called “scaling up.” Essentially this is upgrading the running system and the key part of Vertical Scaling. In other words, Vertical Scaling simply means we can switch to a distinct/different and more powerful machine without changing the actual number in the system ( i.e. upgrading to better model)....

Kubernetes Horizontal vs Vertical scaling

parameter horizontal scaling vertical scaling Main Aim Increasing/decreasing the number of machines Adjusting the CPU and memory on existing machine Best Use in stateless applications stateful applications Scalability High Limited to maximum resources Complexity High Lower Tool Used HAP ( Horizontal Pod Autoscaler ) VAP ( Vertical Pod Autoscaler ) Tolerance in fault cases Higher, one fault doesn’t effect other lower, one fault can effect other cost Can be cost-effective Can lead to higher costs...

Similarities Between Horizontal vs Vertical Scaling

Both horizontal and vertical scaling aim to enhance the application ability in order to handle the workload. Both horizontal and vertical scaling have Automated Scaling Options for each of the methods: horizontal scaling uses HPA (Horizontal Pod Autoscaler) and vertical scaling uses VPA (Vertical Pod Autoscaler). Horizontal and vertical scaling both help in improving performance and availability which also leads to better, more effective and efficient management and utilization of resources. Both are the integral tools that exist in the Kubernetes Ecosystem, and both focus on efficiency....

How To Use Scaling?

In order to use scaling we need configuring our cluster to automatically change by the number of pods. depend on workload needs(i.e. horizontal and vertical scaling). In,...

Vertical Scaling

Just like Horizontal Scaling, makes sure we have cluster and “kubectl”. Deploy components in the cluster in case they are not already established. Create a resource definition in a YAML file, for vertical scaling....

When to Use Scaling?

When an application experiences a sudden increase in workload while resource utilization is being monitored. Kubernetes provides the scaling tools in handling increased load and resource efficiency management. Performance optimization, high availability and fault tolerance to ensure high availability, we might scale the application across other nodes or even different regions. Performance optimization and Auto-Scaling for Dynamic Workloads is required. Preparing for Predicted Load Balancing , Microservices Architecture Scaling allows us to adjust resources for each microservice individually. Proper Deployment Strategies are needed....

Conclusion

Horizontal and Vertical both are scaling in Kubernetes serve the basic objective is to adapting applications to inconsistent workloads, via different mechanisms. Horizontal scaling is generally used in kubernetes stateless applications. It can easily handle sudden boosts in traffic by adding or subtracting pod replicas. And vertical scaling is more geared toward stateful applications. It concentrates on improving the power of current resources. In order to choose between horizontal and vertical scaling, it will always depends on application needs, infrastructure, configuration and version goals....

Kubernetes Horizontal and Vertical Scaling – FAQs

Can We Use Both Horizontal And Vertical Scaling Together?...