Rapid Elasticity in Cloud Computing: On-Demand Scaling for Business | Synopsys Cloud
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Have you found yourself seeking additional computing resources to quickly handle surges in your workload? Rapid elasticity in cloud computing provides a cost-efficient way to scale your resources with the dexterity traditional IT lacks.

Rapid elasticity in cloud computing refers to the cloud’s capability to scale quickly to meet demand. Consumers benefit from rapid elasticity because they can expand or reduce their resources how and when they would like.

Rapid elasticity is one of the five essential characteristics of cloud computing, along with on-demand self-service, broad network access, resource pooling, and measured service.

Cloud providers with elastic environments allow customers to use more resources as they need them or decommission the resources they no longer require. Rapid elasticity in cloud computing happens quickly in real-time.

Public cloud providers such as Amazon Web Services, Microsoft Azure, and Google Cloud support rapid elasticity in cloud computing. 


How Will Rapid Elasticity in Cloud Computing Help Your Business?

Let's take a look at the problems that rapid elasticity can solve.

Rapid elasticity enables you to scale resources up and down at any time, eliminating the need to keep additional infrastructure in reserve to handle dynamic workload surges. Cloud providers are considered more elastic if they can quickly adjust resources to your changing requirements.

Rapid elasticity also helps you avoid under-provisioning and over-provisioning computing resources. When you over-provision, you buy more capacity than you need. Conversely, under-provisioning occurs when you provide fewer than necessary resources.

Over-provisioning wastes money, while under-provisioning can cause disruption. Both issues create downtime which can decrease revenue and customer satisfaction. For short-term resource needs like website traffic spikes and database backups, rapid elasticity in cloud computing reduces the likelihood of dealing with such concerns. 


Rapid Elasticity: Advantages and Disadvantages

Like anything, rapid elasticity in cloud computing comes with its share of advantages and disadvantages. 

Advantages

Rapid elasticity in cloud computing provides an array of advantages to businesses hoping to scale their resources.

  • High availability and reliability. With rapid elasticity, you can enjoy a remarkably consistent, predictable experience. Cloud providers take care of scaling behind the scenes, keeping the system running smoothly and fast.
  • Growth-supporting. You can more easily adopt a growth-oriented mindset with rapid elasticity. With elastic cloud computing, your IT infrastructure becomes more agile and nimble, as well as more prepared to acquire new users and customers.
  • Automation capability. Rapid elasticity in cloud computing uses increased automation in your IT environment, which has many benefits. For example, you can free up your IT staff to focus on core business functionality rather than scalability.
  • Cost-effective. Cloud providers offer resources on a pay-per-use basis, so you only pay for what you actually use. Adding new infrastructure components to prepare for growth becomes convenient with a pay-as-you-expand model. 

 

Disadvantages

Though rapid elasticity in cloud computing provides a multitude of benefits, it also introduces a few complexities you should keep in mind.

  • Learning curve. Rapid elasticity takes some time and effort to fully comprehend and therefore benefit from. Your staff may need to familiarize themselves with new programming languages, cloud platforms, automation tools, etc.
  • Security. Since elastic systems only run for a short period, you must rethink how you handle user authentication, incident response, root cause analysis, and forensics when you are dealing with security. Luckily, experts like Synopsys provide accessible and reliable cloud security solutions to simplify this process.
  • Cloud lock-in. Rapid elasticity is a big selling point for public cloud providers, but vendors can lock you into their service. Do your research before settling on a public cloud provider to ensure you fully understand its offerings and your contract.

Rapid Elasticity and Chip Design

Rapid elasticity can help in cloud-based chip design. Rapid elasticity enables you to complete chip-design tasks like library characterization in days instead of weeks by providing on-demand access to as much computing power as needed.

Rapid elasticity perfectly suits chip design tasks characterized by bursts of activity in the cloud. With rapid elasticity in cloud computing, designers have the flexibility to tap into computing resources on demand without investing in infrastructure themselves.

Synopsys Cloud provides cloud-based electronic design automation (EDA) software built to leverage rapid elasticity in cloud computing for chip design and verification.


Synopsys, EDA, and the Cloud

Synopsys is the industry’s largest provider of electronic design automation (EDA) technology used in the design and verification of semiconductor devices, or chips. With Synopsys Cloud, we’re taking EDA to new heights, combining the availability of advanced compute and storage infrastructure with unlimited access to EDA software licenses on-demand so you can focus on what you do best – designing chips, faster. Delivering cloud-native EDA tools and pre-optimized hardware platforms, an extremely flexible business model, and a modern customer experience, Synopsys has reimagined the future of chip design on the cloud, without disrupting proven workflows.

Take a Test Drive!

Synopsys technology drives innovations that change how people work and play using high-performance silicon chips. Let Synopsys power your innovation journey with cloud-based EDA tools. Sign up to try Synopsys Cloud for free!


About The Author

Gurbir Singh is group director, Cloud Engineering, at Synopsys. He has a demonstrated history of leadership in the software industry. In his current role, he leads the development of the Synopsys Cloud product, which enables customers to do chip design on the cloud using EDA-as-a-Service (SaaS) as well as flexible pay-per-use models. Gurbir has run organizations to develop cloud SaaS products, machine learning applications, AI/ML platforms, enterprise web applications, and high-end customer applications. He is experienced in building world- class technology teams. Gurbir has a master’s degree in computer science, along with patents and contributions to publications. 

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