Instance in Cloud Computing: Definitive Guide

One commonly used term in the cloud computing ecosystem is instances. When people talk about how cloud computing has helped them scale their applications with fewer expenses, they talk about how they utilized these instances. Through this article, we will explain everything about these instances in cloud computing.  

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What is Instance in Cloud Computing?

An instance in cloud computing is nothing but a virtual server that is running the application. The instance is also referred to as a virtual machine or server, but in the cloud ecosystem, the term instance is always preferred over the others.

These instances are provisioned according to the need of the users, and they are upgraded or downgraded with the cloud software. Moreover, these instances can be created on demand and terminated if not required.

Users can either use one or more instances to execute their tasks. They can also group multiple instances for their tasks. These instances can also be created in multiple geographical regions throughout the world. 

The instances have a predefined base security and networking configuration from the cloud provider, and users can add their own configuration policies according to their needs.

These instances can either be created manually from the cloud software or automated with the API or SDK of the cloud provider. For example, the instance in AWS is known as EC2, and the instance in Google cloud is known as compute engine.

What is Instance in AWS?

The Amazon Web Service (AWS) provides many instances for different workloads. These instances are provisioned through one of their services called Elastic Compute (EC2). Here's a list of different types of instances from AWS.

Point to be noted, AWS EC2 follows code names to divide different types of instances, the code name is defined as T2, T3, M5, etc, and these instances have sub-divisions as well, such as T2.micro, T2.medium, and so on.

1. General Purpose Instance

The general purpose instance is ideal for standard use, such as web servers, these instances have an equal share of processing power, memory, and networking resources.  

For example, the general purpose instance can deploy simply to the mid-size web servers. It is well suited for: 

1. Application servers 
2. Internal organization application 
3. Side/University projects  
4. Simple Cache servers 

2. Compute Optimized Instance

The compute-optimized instance is ideal for workloads that need high processing power. These resources are optimized to provide high computing power.

For example, the compute-optimized instance can be used for applications that process many datasets to predict results. It is well suited for: 

1. Scientific research projects. 
2. Complex data science projects. 
3. Game servers.  
4. Batch data processors.  

3. Accelerated Computing Instance

The Accelerated computing instance provides hardware accelerators and is suitable for applications that require intensive graphic rendering or analyzing a huge number of visual data such as images or videos.  

For example, the accelerated computing instance can be used for complex machine learning models. It is well suited for: 

1. Graphic rendering 
2. Image and video processing models 
3. Complex analytical workloads 

4. Memory Optimized Instance

The memory optimized instances are ideal to deploy memory-intensive applications without compromising performance.  

These instances deliver high performance for applications that require processing large data sets in the memory.  

For example, the memory optimized instances are applicable in big data analytics. It is well suited for: 

1. High-performance databases 
2. Big data analytics 
3. Distributed in-memory caches 

5. Storage Optimized Instance

The storage optimized instance is optimized to increase the persistency of the storage to read and write data at a very high speed. It is ideally used for databases that require higher read and write speeds. It is well suited for: 

1. Database Indexers 
2. Search engines functions 

The cloud engineers decide which instance is suitable according to the workload. It is crucial to make sure every aspect of the requirement is considered while choosing an instance, this is often handled by a certified cloud architect.  

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How do Cloud Instances Work?

The instances in cloud computing are like your own server but in the form of a virtual machine in the cloud. These instances are created and managed from the cloud software or via APIs. These instances can be configured with memory, graphics processing, CPU, and other requirements.

An instance can have more security and network configuration according to the user's need. These configurations can be new or imported from pre-defined policies.

Users can choose any operating system to set up their application/server. The cloud provider will charge users only for the resources they use. Users are can create and destroy as many instances as they like.

Types of Workloads That Can be Run on a Cloud Instance

There are many workloads for which cloud instances are the best choice. Cloud provides the resources on demand so that there won't be any sort of interruption for its users. Here are the few common workloads that cloud instances handle:  

1. Compute Intensive

These workloads depend on computing power (processor) a lot. For example, machine learning models use high computing power while processing large datasets and applying mathematical equations.

Scientific research projects might run tests with huge varieties of inputs that need high computing power. Similarly, many applications might need high computing power, hence cloud provides compute-optimized instances for this use case.

2. Memory Intensive

These workloads depend a lot on the machine's memory. For example, running a distributed cache in memory is an expensive task and requires a lot of memory to store the data. 

And real-time data processors might store the data in memory to apply filters and equations to them. Similarly, many applications might need a large memory, hence cloud provides memory optimized instances for this use case.  

3. Graphics Intensive

These workloads depend a lot on the machine's GPU. For example, running AR/VR application required a lot of GPU capacity to render the visuals. Other services such as video streaming and live conferencing, require a lot of GPU capacity.

Similarly, many applications might need high GPU power, hence cloud provides graphic optimized instances for this use case.

Instance Life Cycle

An instance, right from the time it is created undergoes various stages in its life cycle. Here are some of those lifecycles:   

• Provision 
• Pending  
• Running 
• Stopped 
• Restarting 
• Terminated

1. Provision

The provision is the phase where the users send a request for an instance according to their needs. The cloud would then provide an instance according to the user's need.  

2. Pending

After provisioning, the instance enters a pending state so that the security and network configuration can be applied before it is ready.  

The instance also goes into a pending state when the user modifies the requirement of the instance so that the changes can be applied.  

3. Running

The instance would be functional and ready to use when it is in a running state. An instance enters a running state only when all the necessary configurations are applied. When the instance is in a running state, users can start interacting with it.  

4. Stopped

When users need to stop their instance for a short period of time, they can turn the instance off.

This would allow them to modify the settings or maybe debug some issues related to their application. The instance enters the stopping stage before going to the stopped stage. The users won't be billed for an instance that is stopped.

5. Restart

The instance enters the restart stage when users manually restart the instance or when the users choose to start the stopped instances.  

6. Terminated

The instance enters terminated stage when users choose to terminate the instance after its use. Terminating causes its corresponding data in the instance store volume to be removed.   

What is an Instance Group?

An instance group is a collection of instances managed as a single entity. These instances would have the same machine type, image, and the same configuration. All instances in an instance group go through the same lifecycle simultaneously.  

Policies and configurations can be updated to all the instances inside the group. Cloud provides supports two types of instance groups.

1. Managed Instance Group

The managed instance group let users scale their workloads and make them highly available with help of automated services such as autoscaling, auto-deployments across multiple regions, automatic updating, etc.

With this service, users don't have to worry about the infrastructure or any other configuration, the cloud provider manages the infrastructure for the user.

2. Unmanaged Instance Group

The user has to take care of infrastructure setup and configuration, such as adding load balancers to distribute the requests properly, also scaling it themselves. Here the users would get the freedom to apply their own strategy to handle their workload.  

Importance of Cloud Instances

A cloud instance allows people to scale beyond traditional physical boundaries. With the help of the cloud, people don’t need to worry about the underlying hardware when deploying workloads on a cloud instance. Some of the cloud instances benefits are: 

1. Scalability

Cloud instances allow users to scale computing resources according to their workload requirements. For example, if an application gains more users, it experiences huge traffic that slows down response time, so by increasing cloud resources such as the CPU, memory, storage, and network resources to the particular instance, the traffic surge can be easily handled.  

2. Infrastructure Maintenance

The cloud instance allows users to focus more on their applications and requirements than the infrastructure.  

With cloud instances, users can a virtual machine on demand and start using it instead of setting up a physical server and handling the hardware supplies. 

3. Security

Cloud instance provides security in many aspects such as data encryption to protect any data that it handles, access protection to allow only whitelisted requests and authorization to allow only authorized users to access the instance to update and modify it.   

4. Fault Tolerance

Users can leverage redundancy by using many duplicate instances for backup. They are especially useful for managing memory-intensive workloads like data processing. For example, an application can still run on other instances in Mumbai and US, if a cloud instance hosted in Asia fails.   

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Conclusion

The cloud instances handle workloads and allow users to scale their applications without worrying about maintenance. This allows users or organizations to introduce many innovative projects with less cost and time.

Due to so many uses with cloud instances, many organization set up their own private on-premise cloud instance or use virtual machines from the cloud software. KnowledgeHut learn Cloud Computing from scratch will help you in learning more about the instances and become an industry-ready cloud engineer.