Elastic vs Non-Elastic Infrastructure

What is Non-Elastic Architecture

Non-elastic architecture is an approach to designing software systems that do not have the ability to dynamically adjust their computing resources in response to changes in workload demands. In a non-elastic architecture, the resources are allocated to the system in advance and are typically fixed, meaning that the system cannot easily scale up or down based on the workload demands.

It is typically used in traditional on-premises data center environments where resources are provisioned in advance and are not easily scalable, it is often built with a specific set of resources allocated to each component of the system.

For example, the web server may be allocated a specific amount of RAM, CPU, and storage capacity, and these resources may not be adjusted unless the system is taken offline and physically modified.

One of the primary disadvantages of non-elastic architecture is that it is not able to easily handle sudden spikes in traffic. If the system experiences a sudden increase in workload, it may become overwhelmed, leading to slow performance or even downtime. In addition, non-elastic architectures may be more expensive to deploy and maintain because they require the purchase of additional hardware to handle spikes in traffic.

What is Elastic Architecture

Elastic architecture is an approach to designing software systems that are able to dynamically scale their computing resources up or down in response to changes in workload demands. The goal of an elastic architecture is to ensure that the application can handle increases in traffic and usage without experiencing performance degradation or downtime.

The term "elastic" refers to the ability of the architecture to expand and contract in response to changing needs, much like a rubber band can stretch or shrink as needed. Elastic architectures are typically built on top of cloud computing platforms that provide on-demand access to computing resources.

By designing applications with an elastic architecture, developers can ensure that their systems can handle unpredictable traffic spikes, seasonal fluctuations in usage, and other factors that can impact performance. This can help to improve user experience, reduce downtime, and minimize infrastructure costs.

Ref: https://www.spiceworks.com/tech/cloud/articles/what-is-elastic-computing/

What are the differences

Some specific differences between elastic and non-elastic architectures include:

1. Scalability: An elastic architecture is designed to be highly scalable, allowing the system to handle large traffic spikes without experiencing performance degradation. A non-elastic architecture, on the other hand, may struggle to handle sudden increases in traffic, leading to slow performance or even downtime.

2. Cost: Because an elastic architecture can dynamically allocate and deallocate resources as needed, it can be more cost-effective than a non-elastic architecture, which may require the deployment of additional hardware to handle spikes in traffic.

3. Resilience: An elastic architecture is typically designed to be more resilient than a non-elastic architecture. In an elastic architecture, if a particular node fails, the system can quickly allocate additional resources to compensate. In a non-elastic architecture, a failure may lead to downtime or reduced performance until the system can be repaired.

Main Technologies in Elastic Architecture

Elastic architecture is typically built on top of cloud computing platforms and relies on a combination of technologies to enable dynamic scaling and resource allocation. Some of the main technologies used in elastic architecture include:

• Virtualization: Virtualization allows multiple virtual machines to run on a single physical server. This enables resources to be allocated and deallocated dynamically, allowing the system to adjust to changing workload demands.

• Cloud computing: Cloud computing platforms such as Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform (GCP) provide on-demand access to computing resources, enabling elastic architectures to scale resources up and down based on traffic demands.

• Containerization: Containerization is a lightweight form of virtualization that allows applications to be packaged with their dependencies and run in a consistent environment. Containerization can help to simplify application deployment and enable rapid scaling.

• Autoscaling: Autoscaling is a technique that allows the system to automatically adjust the number of computing resources allocated to it based on current workload demands. Autoscaling can be implemented using a variety of tools, such as AWS Auto Scaling or Kubernetes Horizontal Pod Autoscaler.

• Load balancing: Load balancing is the process of distributing incoming traffic across multiple computing resources to ensure that no single resource is overloaded. Load balancing can be implemented using a variety of tools, such as AWS Elastic Load Balancer or NGINX.

• Microservices: Microservices is an architectural pattern that structures an application as a collection of loosely coupled services. This approach can help to simplify application development, deployment, and management, and can also enable more granular scaling.

By combining these and other technologies, elastic architecture can enable highly scalable, resilient, and cost-effective software systems that can adjust to changing workload demands.

Main Use Cases

Elastic Architecture

Elastic architecture can be used in a variety of use cases where the workload demands of an application are variable and unpredictable, making it difficult to determine the amount of computing resources that will be required in advance. Some of the main use cases for elastic architecture include:

• Web applications: Web applications often experience spikes in traffic due to a variety of factors, such as seasonal changes, marketing campaigns, or viral content. Elastic architecture can enable web applications to dynamically adjust the amount of computing resources allocated to handle these traffic spikes.

• Mobile applications: Mobile applications may experience variable usage patterns depending on factors such as time of day or location. Elastic architecture can help mobile applications to adjust their resources to handle these variations in usage.

• Big data processing: Big data processing applications often require significant computing resources to handle large amounts of data. Elastic architecture can enable big data applications to scale resources up and down as needed, reducing the overall cost of processing.

• E-commerce: E-commerce applications may experience variable traffic patterns depending on factors such as product releases, sales events, or seasonal changes. Elastic architecture can help e-commerce applications to handle these fluctuations in traffic and ensure a positive user experience.

• Gaming: Online games can experience sudden spikes in traffic due to new content releases or events. Elastic architecture can help gaming applications to handle these traffic spikes and ensure that players can connect and play without experiencing lag or downtime.

Non-Elastic Architecture

Non-elastic architecture refers to a traditional approach to application design and deployment, in which resources are provisioned in advance and remain fixed, regardless of changes in demand. Here are some examples of non-elastic architecture:

• Monolithic architecture: In a monolithic architecture, an application is built as a single, self-contained unit, with all components tightly coupled together. This makes it difficult to scale the application horizontally, as adding resources requires scaling the entire monolith.

• Client-server architecture: In a client-server architecture, the application is divided into two parts: a client that interacts with the user interface and a server that handles the application logic and data storage. While this architecture can support multiple clients, it can be difficult to scale the server-side resources to meet changes in demand.

• Three-tier architecture: In a three-tier architecture, the application is divided into three layers: presentation, application, and data storage. While this architecture provides greater separation of concerns and allows for more efficient scaling of each layer, it can still be difficult to adjust the resources allocated to each layer in response to changes in demand.

• Virtual machine-based architecture: In a virtual machine-based architecture, the application is deployed on one or more virtual machines that are provisioned in advance. While this approach provides greater flexibility than physical hardware, it still requires manual provisioning of resources and can be difficult to adjust to changing demands in real time.

Main Design Patterns for Elastic Architecture

Design patterns are reusable solutions to common software engineering problems, and elastic architecture is no exception. Here are some of the main design patterns used in elastic architecture:

• Auto Scaling: This design pattern involves automatically scaling the number of computing resources in response to changes in workload demands. For example, if a web application experiences a sudden increase in traffic, the Auto Scaling pattern can automatically launch new instances of the application to handle the increased workload.

• Sharding: Sharding is a technique used to partition data across multiple computing resources, enabling horizontal scaling of the application. This design pattern is often used in large-scale data processing applications, where the data can be partitioned and processed in parallel across multiple instances.

• Circuit Breaker: The Circuit Breaker pattern is used to handle failures in a distributed system. It involves monitoring the health of the system and breaking the circuit to prevent further requests from being sent to a failing component. This helps to prevent cascading failures and ensures the overall availability of the system.

• Cache-Aside: The Cache-Aside pattern involves caching frequently accessed data in memory to reduce the number of database queries required. This can help to improve application performance and reduce the load on the database.

• Service Registry: The Service Registry pattern is used to manage the availability and location of services in a distributed system. This pattern involves registering services with a central registry and using the registry to discover the location and availability of services.

• Microservices: The Microservices architectural pattern involves breaking an application down into a collection of loosely coupled services that can be developed, deployed, and scaled independently. This can help to improve the scalability, resilience, and maintainability of the application.

By leveraging these and other design patterns, elastic architecture can provide highly scalable, resilient, and cost-effective software systems that can adjust to changing workload demands.

Pros and Cons Elastic Architecture​​​​​​​

Elastic architecture provides a number of benefits, but also comes with some challenges. Here are some of the main pros and cons of elastic architecture:

Pros:

1. Scalability: Elastic architecture allows applications to easily scale up or down in response to changes in workload demands, making it possible to handle sudden spikes in traffic or increase capacity as needed.

2. Resilience: By distributing computing resources across multiple instances, elastic architecture can help to ensure high availability and resiliency in the face of hardware failures, network disruptions, or other issues.

3. Cost-effectiveness: By using cloud computing resources only when needed, elastic architecture can help to reduce the overall cost of running an application.

4. Flexibility: Elastic architecture provides the flexibility to add or remove resources as needed, making it possible to quickly respond to changing business requirements or market conditions.

Cons:

1. Complexity: Elastic architecture can be more complex to design and implement than traditional, non-elastic architectures, as it requires specialized skills and knowledge of cloud computing platforms and related technologies.

2. Cost unpredictability: While elastic architecture can help to reduce the overall cost of running an application, the cost of cloud computing resources can be difficult to predict, especially if usage patterns are highly variable.

3. Performance variability: Elastic architecture can result in variable performance depending on the workload demands and the allocation of resources across different instances.

4. Data consistency: When using sharding or other data partitioning techniques in elastic architecture, it can be more difficult to ensure data consistency across multiple instances.

Pros and Cons Non-Elastic Architecture

Non-elastic architecture is a more traditional approach to designing software systems, where the amount of computing resources allocated to an application remains constant over time. Here are some of the pros and cons of non-elastic architecture:

Pros:

1. Simplicity: Non-elastic architecture is generally simpler and easier to design and implement than elastic architecture, as it does not require the use of specialized cloud computing technologies and related tools.

2. Cost predictability: With non-elastic architecture, the cost of running an application is generally more predictable, as the number of computing resources allocated to the application remains constant over time.

3. Performance consistency: Non-elastic architecture can provide more consistent performance, as the computing resources allocated to the application are fixed and not subject to change.

4. Data consistency: Non-elastic architecture can provide stronger guarantees of data consistency, as the application and data are not partitioned across multiple instances.

​​​​​​​Cons:

1. Limited scalability: Non-elastic architecture can limit the ability of an application to scale up or down in response to changes in workload demands, which can result in performance degradation or downtime during periods of high demand.

2. Limited resiliency: With non-elastic architecture, there is a greater risk of downtime in the event of hardware failures, network disruptions, or other issues, as the application is not distributed across multiple instances.

3. Limited flexibility: Non-elastic architecture can be less flexible in responding to changing business requirements or market conditions, as it may require manual adjustments to the computing resources allocated to the application.

4. Limited cost-effectiveness: Non-elastic architecture can be less cost-effective than elastic architecture in cases where the workload demands of an application vary significantly over time, as the application may require more computing resources than are needed during periods of low demand.

Summary

Elastic Architecture

It offers significant benefits in terms of scalability, resilience, cost-effectiveness, and flexibility, but also comes with some challenges, such as increased complexity, cost unpredictability, performance variability, and data consistency issues.

Non-Elastic Architecture

it offers the benefits of simplicity, cost predictability, performance consistency, and data consistency, but also comes with the drawbacks of limited scalability, resiliency, flexibility, and cost-effectiveness.