What are clusters
Cluster computing has seen a substantial increase in adoption over the past decade.
From startups to big corporations, clustering-based architectures are increasingly being used to deploy and manage applications in the cloud.
What is a cluster?
A computing cluster (or computer cluster) is a group of two or more computers (nodes) that work in parallel to achieve a common goal.
This allows you to distribute workloads consisting of a large number of individual and parallelizable tasks between the nodes in the cluster.
As a result, they can leverage the combined memory and processing power of each computer to increase overall performance.
How to create a clustering
To build a cluster computer, individual nodes must be networked to enable internal communication.
The computer cluster software can then be used to join the nodes.
It can have a shared storage device and/or local storage on each node.
Typically, at least one node is designated as the leading node and acts as an entry point to the cluster.
The leader node can be responsible for delegating incoming work to the other nodes and, if necessary, aggregating the results and returning a response to the user.
Ideally, a cluster works as if it were a single system.
Types of cluster computing
Computer clusters can generally be classified into three types:
- High availability or failover
- Load balance
- High-performance computing
and can identify itself in multiple types at the same time.
For example, one hosting a web server is likely to be highly available and load-balanced.
What are the key benefits of cluster computing
Availability:The accessibility of a system or service over a period of time, usually expressed as a percentage of availability during a given year (e.g. availability of 99.999% or five 9)
Resilience:how well a system recovers from a failure
Fault tolerance:the ability of a system to continue to provide a service in the event of a failure
Reliability:The likelihood that a system will work as expected
Redundancy: Duplication of critical resources to improve system reliability
An application running on a single machine has a single point of failure, which makes the reliability of the system poor.
If the machine hosting the application shuts down, you will almost always experience downtime when restoring the infrastructure.
Maintaining a level of redundancy,which helps improve reliability, can reduce the amount of time an application is unavailable.
This can be achieved by preemptively running the application on a second system (which may or may not receive traffic) or by having a cold system (not currently running) preconfigured with the application.
These configurations are known as active-active and active-passive configurations,respectively.
When an error is detected, an active-active system can immediately fail-over on the second machine, while an active-passive system will failover once the second machine is active.
High Availability Clusters
Computer clusters consist of multiple nodes that run the same process at the same time and are therefore active-active systems.
Active-active systems are generally fault tolerant because the system is inherently designed to handle the loss of a node.
If a node fails, the remaining nodes are ready to absorb the workload of the failed node.
That said, a cluster that requires a leader node should run a minimum of two leading nodes in an active-active configuration.
This can prevent the cluster from becoming unavailable if a leading node fails.
Using a cluster can improve system resiliency and fault tolerance, allowing for greater availability.
Clusters with these characteristics are called "high availability" or "fail-over" clusters.
Load Balancing Cluster
Load balancing is the act of distributing traffic across nodes to optimize performance and prevent each individual node from receiving a disproportionate amount of work.
You can install a load balancer on the leading nodes or provision it separately from the cluster.
The load balancer can detect if one node is broken, and if so, it will divert incoming traffic to the other nodes.
This configuration is often a high-availability cluster at the same time.
High Performance Clusters
When it comes to parallelization, clusters can achieve higher levels of performance than a single machine.
This is because they are not limited by a certain number of processor cores or other hardware.
In addition, horizontal scaling can maximize performance by preventing the system from depleting resources.
High Performance Computing(HPC) clusters take advantage of the parallelizability of computer clusters to achieve the highest possible level of performance.
Clusters in the cloud
Before the public cloud,computer clusters consisted of a set of physical machines that communicated over a local network.
Creating a cluster of computers involved careful planning to ensure that it meets present and future requirements, as physical scaling could take weeks or even months.
In addition, those on site or self-managed were not resilient in the event of regional disasters, so other security measures had to be in place to ensure redundancy.
In a nutshell, it is therefore a group of nodes hosted on virtual machines and connected within a virtual private cloud.
Using the cloud can greatly reduce the time and effort required to get up and running, while also providing a long list of services to improve availability, security, and maintainability.
Containers and cluster relationship
Containers have eliminated many of the burdens of deploying applications.
Differences between local and remote environments can be largely ignored (with some exceptions, such as CPU architecture), application dependencies are provided within the container, and security is improved by isolating the application from the host.
Using containers has also made it easier for teams to leverage a microservices architecture, where the application is broken down into small, loosely coupled services.
Deploying containerized applications across nodes can substantially improve the availability, scalability, and performance of your web application.
Running multiple containers per node increases resource utilization, and ensuring that one instance of each container is running on more than one node at a time prevents the application from having a single point of failure.
However, this leads to another problem: container management.
Managing containers in a cluster of ten nodes can be tedious, but what to do when it reaches a hundred, or even a thousand nodes?
Thankfully, there are numerous container orchestration systems, such as Kubernetes,that can help your application scale.