What is Cloud Elasticity? | VMware Glossary

Cloud Elasticity refers to the ability of a cloud system to adjust its capacity for CPU, memory, and storage resources in response to changing demands. It can be automatic or manual, with the former requiring no advance capacity planning and the latter involving notifications to the organization about low resources. The cloud provider’s monitoring tools dynamically allocate resources without disrupting ongoing operations.

The level of elasticity in a cloud provider determines its ability to autonomously adapt to workload changes by provisioning or deprovisioning resources. This eliminates the need for manual resource monitoring by IT staff. Cloud Elasticity is closely associated with horizontal scaling and public cloud providers that offer pay-as-you-go services. Real-time cloud expenditures align more closely with the actual consumption of services, allowing businesses to scale virtual machines based on demand fluctuations.

Cloud Elasticity enables organizations to handle unexpected increases in demand without maintaining standby equipment. They can leverage the cloud’s resources and return to on-premises operations when the demand subsides. This results in cost savings related to infrastructure, human capital, and overall IT expenses.

Without Cloud Elasticity, organizations would have to pay for unused capacity and manage and maintain it, leading to wasteful spending and inefficiencies. Cloud Elasticity helps avoid over-provisioning and under-provisioning, which respectively involve deploying more resources than needed or insufficiently meeting demand.

Over-provisioning wastes capital, while under-provisioning can lead to latency, user dissatisfaction, and loss of business. Cloud Elasticity allows for rapid scaling up or down of capacity, either automatically or manually, such as through cloudbursting or adjusting resource usage for cloud-based applications.

Cloud Elasticity eliminates the need to purchase and install new infrastructure when demand changes, enabling organizations to meet unexpected spikes without advance planning. Pay-as-needed pricing ensures that resources are only paid for when in use, aligning IT expenditures with real-time demand. High availability and fault tolerance are facilitated, ensuring uninterrupted business services.

Cloud Elasticity improves efficiency by automating resource adjustments, allowing IT staff to focus on more valuable projects. It also speeds up time-to-market by providing capacity within minutes instead of weeks or months.

However, Cloud Elasticity is most beneficial for organizations experiencing rapid or periodic demand fluctuations. Predictable and steady demand scenarios may not benefit from its advantages. Challenges of Cloud Elasticity include the time required for provisioning, potential cloud provider lock-in, impact on security workflows, and the need for technical expertise to configure and manage the elastic system.

In summary, Cloud Elasticity enables cloud systems to dynamically adjust resources, resulting in cost savings, agility, pay-as-you-go pricing, high availability, efficiency, and faster time-to-market. However, it may not be suitable for organizations with predictable demand and comes with challenges related to provisioning time, vendor lock-in, security impact, and resource availability.

Source: https://www.vmware.com/topics/glossary/content/cloud-elasticity.html

Cloud Elasticity vs. Cloud Scalability: What’s the Difference?

Cloud Elasticity and Cloud Scalability: Understanding the Differences and Use Cases

Cloud scalability and cloud elasticity are two important criteria to consider when incorporating cloud services into your infrastructure. While these terms are often used interchangeably, they have distinct differences that are crucial for meeting the needs of your business effectively.

Scalability refers to the ability to handle changing application needs within the infrastructure. It involves adding or removing resources, either by scaling up (vertical scaling) through the addition of resources to existing instances or scaling out (horizontal scaling) by adding more copies of existing instances. Scalability is often more targeted and granular in nature when it comes to sizing resources.

Cloud scalability is ideal for businesses with predictable workloads, stable capacity planning, and consistent performance. It is a cost-effective choice when there is a constant workload or predictable growth, as it allows for efficient resource allocation.

On the other hand, cloud elasticity focuses on dynamically adjusting infrastructure resources to adapt to workload changes. It allows for resources to be added or removed as needed, maximizing their utilization. Elasticity is commonly associated with scale-out solutions and is often utilized in pay-per-use or pay-as-you-grow services. It is particularly beneficial in environments with ever-changing demands, such as e-commerce, retail, SaaS, and mobile.

To fully leverage elasticity, all resources in the infrastructure need to be elastic, including hardware, software, policies, and connectivity. While elastic services offer cost savings, they may not be suitable for environments with stable or predictable demand patterns. Performance guarantees can also be a challenge when relying solely on elastic resources.

An example where cloud elasticity is essential is in retail during peak seasons or special sales events. Instead of investing in additional permanent infrastructure capacity to handle short-term spikes in demand, an elastic solution allows for the temporary scaling of resources, reducing costs and providing unlimited headroom when needed. This flexibility also enables handling unanticipated sales activities throughout the year without compromising performance or availability.

Cloud scalability, on the other hand, involves increasing the size of the workload within existing infrastructure without impacting performance. It includes pre-planned capacity with headroom to accommodate peak demands. Scalability can be achieved through vertical scaling (scale-up) or horizontal scaling (scale-out), providing the necessary resources to prevent performance degradation.

For instance, a small business may provision infrastructure resources for a growing database application to ensure it has enough room to reach its maximum performance and capacity. Similarly, in the case of desktops for employees, scalability ensures that the infrastructure can handle the maximum number of users without sacrificing performance.

In some cases, cloud services offer both scalability and elasticity, allowing IT departments to adjust resources and services based on their needs while adhering to SLAs. However, it’s important to differentiate between the two and choose the most suitable option based on your business requirements. As a general rule, private cloud environments are more readily associated with scalability, while public cloud environments often provide greater elasticity.

IBM Turbonomic Application Resource Management is a solution that effectively manages and optimizes both cloud scalability and elasticity. It ensures performance, efficiency, and compliance while keeping your infrastructures right-sized for scalability and elasticity in real-time across on-premises, hybrid, and cloud environments.

Source: https://www.ibm.com/cloud/blog/cloud-elasticity-vs-cloud-scalability

Scalability and Elasticity in Cloud Computing

Scalability and elasticity are two essential concepts in cloud computing. Elasticity refers to the automatic expansion or compression of infrastructural resources based on fluctuating requirements, allowing for efficient workload management and cost minimization. It is particularly useful in scenarios where resource needs vary suddenly for a specific time interval. On the other hand, scalability is used to handle growing workloads while maintaining good performance. It involves the persistent deployment of resources to handle workload statically.

Cloud elasticity is crucial for mission-critical or business-critical applications where any performance decrease can result in significant business losses. It works by provisioning additional resources such as computing power, storage, and network assets when the number of client access increases, and reducing them when fewer clients are present. Elasticity is commonly associated with public cloud resources and is often featured in pay-per-use or pay-as-you-go services.

Flexibility in the cloud is mainly associated with scale-out solutions, allowing for dynamic addition or removal of resources as needed. It enables the infrastructure to grow or shrink on a case-by-case basis to accommodate changes in application requirements, resulting in optimal resource utilization and overall cost savings. The scope of flexibility extends beyond hardware to include software, network, QoS, and other configurations, depending on the environment.

However, flexibility can have negative implications depending on the circumstances, as certain applications may not guarantee performance. It is widely used in pay-per-use public cloud services, where IT managers only pay for the duration of resource consumption.

An example to illustrate the difference between cloud elasticity and scalability is an online shopping site that experiences increased transaction workload during festive seasons like Christmas. To handle this temporary surge in demand, the site can utilize cloud elasticity by provisioning additional resources. Once the season ends, the deployed resources can be withdrawn. In contrast, cloud scalability would be suitable for a company with a growing database size. The owner can request the cloud service vendor to scale up the database capacity to handle the increased workload.

Scalability can be categorized into three types: vertical scalability (scale-up), where the power of existing resources is increased; horizontal scalability, which involves adding resources in a horizontal row; and diagonal scalability, a combination of vertical and horizontal scalability.

In summary, cloud elasticity is used to address dynamic changes in workload for a short period, while scalability is employed to handle static increases in workload. Elasticity is commonly used by small companies with workload fluctuations, while scalability is utilized by large companies with persistent growth in customer base. Elasticity is a short-term planning approach for unexpected increases in demand, while scalability is a long-term planning strategy to address expected demand increases.

Source: https://www.geeksforgeeks.org/scalability-and-elasticity-in-cloud-computing/

Difference between Elasticity and Scalability in Cloud Computing

Scalability and elasticity are often confused in cloud computing, but they have distinct differences. Understanding these differences is crucial when considering cloud computing services for your infrastructure. Scalability refers to a system’s ability to handle increased workloads by adding resources without impacting performance, while elasticity involves adjusting resources to meet dynamic scaling needs. Scalability focuses on software architecture, while elasticity is related to the hardware layer or cloud infrastructure. Scalability strengthens hardware and increases the performance of computing resources, while elasticity adjusts resources to accommodate scaling demands. Scalability is essential for elasticity, as the latter relies on the former. Scalability is more suitable for long-term strategic needs, while elasticity addresses short-term tactical needs and unexpected changes. Both scalability and elasticity contribute to a system’s growth, but they operate under different conditions. Scalability is planned and manual, while elasticity is automatic and reactive. There are three types of scalability: vertical scaling (adding resources to improve server performance), horizontal scaling (adding elements for increasing workload demands), and diagonal scaling (combining horizontal and vertical scaling for flexibility and cost-effectiveness). Understanding the distinction between scalability and elasticity is crucial for optimizing system performance.

Source: https://middleware.io/blog/elasticity-vs-scalability/

What Is Elasticity in Cloud Computing & Why It Matters to EDA? | Synopsys Cloud

Elasticity in cloud computing refers to the ability to adjust the resources used by a cloud-based application, such as computer processing, memory, and storage capacity, to meet changing demands. It offers scalability, eliminating the need for capacity planning and concerns about peak engineering. By leveraging elasticity, you can avoid paying for unused or idle resources, thus avoiding additional equipment expenses.

Compared to on-premises infrastructure, elastic computing provides greater efficiency and reliability by automating services and avoiding slowdowns and interruptions. You can trigger cloud elasticity automatically based on workload trends or manually initiate it. This flexibility allows you to remove capacity when demand decreases, ensuring that you only pay for the resources you consume at any given time. As a result, there is no need to invest in or retire on-premises infrastructure to accommodate demand spikes.

Cloud elasticity differs from cloud scalability in that it allows you to match the allocated resources with the resources needed at any given time. Cloud scalability, on the other hand, enables you to add or remove resources within existing infrastructure to meet the changing needs of an application. This can be achieved through vertical scaling (scaling up or down by adding or removing resources to existing instances) or horizontal scaling (scaling out or in by adding or removing resources of existing instances).

Cloud elasticity is particularly important for Electronic Design Automation (EDA). With cloud-based systems, you can quickly scale up your EDA infrastructure as needed and easily shrink it back down when no longer required. In contrast, expanding the EDA capacity of on-premises networks typically involves borrowing existing capacity or ordering, setting up, and activating more servers. Cloud systems also provide greater redundancy compared to on-premises networks, offering data protection against natural disasters and human errors.

Synopsys, a leading provider of technology for semiconductor device design and verification, offers cloud-based EDA tools and optimized hardware platforms. Their cloud solutions enable users to leverage the full potential of elasticity in cloud computing, providing advanced compute and storage infrastructure and on-demand access to EDA software licenses. By partnering with industry-leading cloud providers, Synopsys simplifies the deployment of EDA on the cloud and enhances chip design workflows without disrupting established practices.

The author of the text is the Senior Director of Cloud Engagements at Synopsys, responsible for facilitating successful adoption of cloud solutions for EDA workflows. With over 25 years of experience in the EDA industry, the author is proficient in managing business-critical engagements and holds an MBA degree from the Haas School of Business, UC Berkeley, and an MSEE from the University of Houston.

Source: https://www.synopsys.com/cloud/insights/what-is-elasticity-in-cloud-computing.html

Cloud elasticity: What is elasticity in cloud computing?

Cloud elasticity in cloud computing refers to the ability of a cloud computing service to dynamically adapt and meet the changing demands of an organization. It allows businesses to scale up or down quickly and cost-efficiently, adjusting the capacity of resources such as CPU, storage, and memory. Elasticity is essential because it prevents resource constraints and enables autonomous optimization of costs. It helps businesses respond to dynamic market needs, boosts confidence in application and infrastructure support, and avoids disruptions that could impact company revenues. Network-as-a-service (NaaS) solutions support cloud elasticity by providing customized and prioritized traffic management, allowing organizations to scale their bandwidth according to demand. NaaS complements the elastic capabilities of the cloud, empowering businesses to set ambitious growth targets and navigate unforeseen events. Elasticity is not the same as scalability, and it is not exclusive to a specific company.

Source: https://www.verizon.com/business/resources/articles/s/what-is-cloud-elasticity-in-cloud-computing/

What Is Cloud Elasticity? (+How Does It Affect Cloud Spend?)

Cloud elasticity is a key feature of cloud computing that allows users to dynamically adjust their computing resources based on demand without disrupting system performance. It involves the ability to rapidly gain or reduce computing resources such as CPU, RAM, bandwidth, and storage capacities as needed. This process is often automatic in cloud computing.

Elasticity ensures that you can scale up resources when you need them and release them when they are no longer required, preventing server overloads or idle resources. It is crucial to act quickly to avoid disruptions or wastage of cloud budget. Public cloud providers like Amazon Web Services (AWS) and Google Cloud offer rapid elasticity, allowing them to allocate varying resources to dynamic customer demands.

There are four forms of elasticity in cloud computing: scaling up or down (vertical scalability) and scaling out or in (horizontal scalability). Although cloud elasticity and cloud scalability are often used interchangeably, they are distinct concepts. Scalability refers to adding or reducing resources within an existing infrastructure to accommodate workload changes, while elasticity focuses on the ability to rapidly adjust resources to handle dynamic workloads.

Cloud elasticity is exemplified by real-life scenarios. For instance, an insurance company can handle the surge in traffic during policy renewal periods by leasing additional virtual machines to manage the demand. E-commerce businesses can provision more resources to handle increased traffic during limited-time offers. Streaming services like Netflix utilize elastic cloud services to handle sudden spikes in viewership.

The benefits of cloud elasticity include balancing performance with cost-effectiveness, as cloud providers offer pay-per-use pricing models, allowing users to pay for the resources they actually use. It also enables smooth service delivery by combining with cloud scalability to meet changing computing needs without overloading systems or incurring excessive costs.

However, cloud elasticity may not be necessary for businesses with stable demand, as scalability alone may suffice. Cloud cost optimization is another important consideration, as it aligns computing resources with workload demands and ensures cost-efficiency. Some cloud platform services support elasticity, while others may require additional tools like CloudZero for cost visibility and optimization.

CloudZero is a platform that helps engineering teams monitor and analyze cloud costs, providing insights into specific cost drivers and allowing users to group costs by feature, product, service, or account. It helps businesses understand how cloud costs impact unit economics and make cost-informed decisions.

Source: https://www.cloudzero.com/blog/cloud-elasticity

What is Cloud Elasticity in Cloud Computing?

Cloud elasticity in cloud computing refers to the dynamic allocation of resources, such as compute, storage, and memory, in response to changing demands. Its purpose is to avoid over-provisioning or under-provisioning a service or application. Over-provisioning leads to unnecessary expenses, while underprovisioning restricts user access. Cloud elasticity should not be confused with cloud scalability, as they serve different purposes. Cloud scalability enables a system to adapt to gradual changes in demand over time, while cloud elasticity ensures uninterrupted access during sudden spikes in user demand. Cloud elasticity is crucial in various use cases, such as websites for auctions or concert tickets that experience short bursts of high traffic.

Source: https://blog.iron.io/what-is-cloud-elasticity/

What is the difference between scalability and elasticity?

Scalability refers to the capacity to meet an increasing workload, while elasticity refers to the ability to increase or reduce capacity to match both increasing and decreasing workloads. In a scaling environment, available resources can exceed future demands, whereas in an elastic environment, resources closely match current demands. Scalability adapts to workload increases incrementally through resource provisioning, while elasticity adapts to both workload increases and decreases through autonomic provisioning and deprovisioning of resources. Scalability can be achieved by increasing the power of a single computer resource or by utilizing a group of resources, while elasticity handles varying workloads through dynamic resource usage. Scalability meets long-term strategic needs, enabling a company to meet expected service demands, whereas elasticity meets short-term tactical needs, allowing a company to respond to unexpected changes in service demand. Scaling up and scaling out are examples of scalability, where the former increases the capacity of an individual server, and the latter involves adding multiple servers. Elasticity, on the other hand, allows for scaling up or scaling down capacity as needed. To illustrate, scaling up is like an individual increasing their power to meet growing demands, while scaling out is akin to building a team to address those demands. Similarly, elasticity can be compared to a film actor adjusting their body weight to meet different requirements in the film industry.

Source: https://stackoverflow.com/questions/9587919/what-is-the-difference-between-scalability-and-elasticity