Essential Cloud Architecture Design Principles for EDA

Gurbir Singh

Jun 29, 2022 / 4 min read

Synopsys Cloud

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Making a move to the cloud opens up access to substantial computing power and extensive storage. However, setting up a cloud environment can be challenging. This post presents key cloud architecture design principles that can guide a smooth transition.

A well-planned cloud architecture leverages benefits such as scalability and automation inherent in cloud computing. As cloud architecture forms the backbone of a vast network, it's crucial to meticulously plan the design.

To fully utilize the capabilities of the cloud, adherence to specific architecture principles is necessary. The following principles are important when designing cloud architecture.

1. Aim for Operational Excellence

By monitoring systems as they run, you can achieve operational excellence that results in increased value and improved processes and procedures.

Automation is a cornerstone of operational excellence. The cloud makes it easier to automate your infrastructure and the components that sit above it. You can repair, scale, and deploy your system much faster with automated processes than with human labor. Automation in the cloud isn't a one-time deal.

Monitoring your systems is another means to achieve operational excellence. For the health and security of your cloud system, be sure to supervise it from the start. Monitoring data streams not only tracks the system's health, but it can also tell you more about system usage and user behavior. For example, you can determine how many people use the system, which parts they use, the average latency, etc. You can also aggregate this data to create an overall picture of how efficiently the system is working.

2. Implement Security Measures

Security involves protecting data and systems, identifying and managing user access, and setting up controls to spot any potential risks.

You can use many of the security tools and techniques found in traditional IT infrastructure in the cloud. Cloud platforms usually allow you to design security controls, simplifying system use for administrators and IT staff. This process also makes it easier to audit the cloud environment.

In addition, cloud architectures take a defense-in-depth approach by relying on authentication between components. With such a  strategy, there are no security perimeters inside or outside. The architecture, therefore, feels more resilient, and the resulting services become easier to deploy.

3. Be Reliable

Reliability in cloud architecture refers to preventing and quickly recovering from failures to meet business and customer demands.

Having redundant resources for the same task is smart because you can remove single points of failure. You can implement redundancy in either standby mode—where functionality is still available during a power outage—or active mode—where requests distribute to multiple redundant compute resources. When one fails, the others handle the extra work.

Data storage must be reliable in protecting both data integrity and availability.  Specifically, horizontal scaling can improve fault isolation by grouping instances into shards instead of sending all user traffic to every node as in traditional IT.

4. Ensure Performance Efficiency

Focus on using IT and computing resources as efficiently as possible. Doing so involves selecting the right resource types and sizes for the workload, monitoring performance, and making informed decisions as business needs change.

Serverless architectures are one way to help improve performance. With these architectures, you can build event-driven and synchronous mobile, web, analytics, and IoT services without managing server infrastructure.

Ensuring performance efficiency across a workload often requires multiple approaches. Numerous solutions and features can improve performance in well-designed systems. You can effectively determine an efficient solution by choosing patterns and implementing them based on data. 

5. Optimize Costs

Cost optimization is all about avoiding unnecessary costs. Organizations must keep in mind where they spend money. They must also choose the right number of resources and analyze their spending over time, scaling to meet business needs without overspending.

Cloud architectures should be designed for cost optimization by doing the following:

  • Select the right type, configuration, and storage options to save money.
  • Implement auto-scaling to scale horizontally or down without extra cost.
  • Choose the right instance purchase options to reduce the cost of your computing capacity.

6. Cloud Architecture Design Principles and EDA

Once you have properly architected your cloud environment, you can leverage it for a range of activities. For example, you can leverage the cloud’s capabilities for chip design using electronic design automation (EDA) tools.

Traditionally, electronic design automation (EDA) tools have been optimized for local on-premises infrastructure, requiring substantial investments and optimizations to succeed. Moving them to the cloud is difficult, both technically and economically, but the benefits outweigh the challenges.

Well-architected cloud deployment for chip designers is scalable, elastic, and high-performing. It can provide a wide range of tools for improving performance, collaborating, and managing projects. For new companies or for those who need increased computing capacity, the cloud is a smart choice.

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.


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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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