Cloud Capacity Planning: Best Practices for Chip Design | Synopsys Cloud
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Cloud capacity planning is an essential piece of any effective IT strategy. When you leverage cloud capacity planning effectively, it can improve service performance, increase agility, and reduce costs.  

Cloud capacity planning aims to match demand with available resources. It analyzes what systems are already in place, measuring their performance and predicting demand. Your organization can then provision and allocate cloud resources based on that demand. 

Before you can adjust a system's capacity, you need to understand and characterize its workload. A system uses processors, memory, storage, and networks to fulfill cloud computing requirements. Each resource's utilization rate varies. When the demand increases, one or more of these resources reaches its cap. 

Once you understand your workloads, you can plan your cloud capacity for each as well as overall.


Best Practices of Cloud Capacity Planning

Below are some best practices to leverage cloud capacity planning for your organization:

 

Evaluate

To achieve optimal performance cost-effectively, you must first evaluate your workload capacity requirements. Evaluating your current workloads before moving them to the cloud is essential. It is important to think about why workloads change and what happens when they do.  

 

Review

Next, look at your metrics to see how you use your infrastructure and how much capacity it needs. Your review should include instances when your usage spikes, as well as an assessment of how often these spikes occur, how big they are, and how long they last. Via utilization patterns, you can identify spikes and dips in server, application, and system usage. You'll need to consider business forecasts and historical trends. For example, knowing the capacity demands of a new customer for the following quarter can help you prepare a stronger plan. 

 

Strategize

To develop a cloud capacity planning strategy, you should assess your past infrastructure and capacity through feedback from business stakeholders. Whenever possible, automate the provisioning and deployment of cloud resources as part of your strategy. Your strategy should include a disaster recovery plan that details recovery times for your applications, systems, and servers. It should also discuss the potential impact and cost of downtime due to disaster. 

 

Ensure

Make sure your quotas match your capacity needs. A quota is a specific countable resource, like how many load balancers your projects can use simultaneously. Your goal in your cloud capacity planning effort should be to support business goals. You should be able to tell users what will happen with the cloud in three to six months regarding cost, response time, and availability. 


Benefits of Cloud Capacity Planning

You can derive a number of benefits from cloud capacity planning, including:  

 

Reduction of Costs

A strategic cloud capacity plan helps IT anticipate and plan for changes that may affect cloud resource management. Your IT team can better control, track, and adjust resource capacity, consumption, and related budgets or quotas when they understand business priorities and plans. 

 

Application Performance

Poor performance can lead to negative user experiences and increased customer churn. As part of strategic cloud capacity planning, IT can find and fix performance bottlenecks from systems and applications. Additionally, cloud capacity planning helps you find cost-effective ways to achieve optimal performance. 

 

Agility

Your IT team can effectively plan for unforeseen spikes in demand using historical data and usage patterns as part of effective cloud capacity planning. 


Cloud Capacity Planning and Synopsys

Cloud capacity planning can aid any organization that uses cloud computing to improve performance. Chip makers and small businesses looking to leverage the cloud for their chip projects can benefit immensely from cloud capacity planning.

With Synopsys Cloud’s FlexEDA model, you can free yourself from capacity and license limitations. Since Synopsys Cloud unshackles all capacity constraints, projects can be broken into faster cycles with more time spent on innovating and less on scheduling. At the same time, you need to plan your cloud capacity to ensure your chip projects run smoothly. 


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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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

Venkata Ravella is vice president of Information Technology at Synopsys, where he leads a world-class IT infrastructure team that has built large-scale engineering and business infrastructure on private and public clouds. Over the last 25+ years, he has held various roles in IT, with the majority of his time focused on engineering environment and infrastructure. He has in-depth experience building high-performing engineering environments, both on-prem and in-cloud, with an emphasis on reliability, scalability, and security at their core.

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