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Increasingly, organizations utilize cloud computing to remain competitive and accelerate innovation. When interacting with cloud providers, you'll encounter questions about cloud native vs cloud agnostic design.
It is important to understand both options thoroughly before making a decision.
What is Cloud-Native?
A cloud-native architecture lets developers build applications native to a particular cloud environment. This approach offers software teams sophisticated features and plugins within a proprietary cloud platform.
What is Cloud Agnostic?
A cloud-agnostic architecture aims to design applications that can run seamlessly across any cloud provider. Unlike cloud-native applications, cloud-agnostic services are not dependent on a single cloud platform’s toolkit. Instead, they integrate with a mix of open-source and vendor-provided tools.
Cloud Native vs. Cloud Agnostic
The cloud-native environment presents development teams with a very different experience than the cloud-agnostic environment, even though both lead to the same goal — hosting distributed applications in the cloud.
The table below presents a detailed comparison of the features of cloud-native vs cloud-agnostic design:
Features |
Cloud Native |
Cloud Agnostic |
|---|---|---|
| Portability | Difficult to move applications ported to different cloud providers. | Applications can be moved anywhere and never locked into a specific provider. |
| Performance | Components work on a small segment, increasing performance overall. | Wide range of features and options that customers can use to maximize performance. |
| Flexibility | Applications benefit from a cloud platform's built-in provisions for networking, monitoring, and other underlying architecture concerns that stymie large development efforts. | Developers are not restricted to one cloud platform's capabilities or tools and can incorporate open-source tools, libraries, and integrations. |
| Resilience | Microservices enable resilience, meaning a component failure doesn’t affect the overall ecosystem. | Applications provide redundancy and improve recovery speed in the event of a failure; services can be switched to another platform if the initial platform experiences a disruption. |
| Costs | Customers are charged based on a combination of licensing and data storage requirements, following a pay-as-you-go model. | Cloud-agnostic architecture has greater accessibility to open-source tools, providing more direct control over costs and the ability to make spending adjustments as needed. |
| Implementation | Cloud native is a new paradigm that will require a cultural shift for successful implementation. | Cloud agnostic has to happen at the developer level, making implementation challenging. |
| Time to Market | Pre-built templates, tools, and ready-to-use infrastructure speed up time to market for applications. | The complexity of developing cloud-agnostic applications and features means that it can take longer for projects to get off the ground. |
| Scalability | Cloud-native systems are easy to scale up or down to meet business needs. | Cloud-agnostic apps and services can move across cloud platforms, which means they can quickly scale up to meet demand. |
You don’t have to go all in when choosing a cloud strategy. Cloud-native and cloud-agnostic approaches are not mutually exclusive.
For example, an organization could adopt a cloud-agnostic strategy when developing core business apps and services so that the continuity of the business model does not depend on a particular cloud provider. Then, the organization could use cloud-native architecture for ancillary apps and services so they can run at high speed.
You might consider using a cloud-native approach to develop consumer-facing web applications as a first step. Then, you can slowly transition to a cloud-agnostic architecture after acquiring the specialized resources necessary to build a cloud-agnostic infrastructure.
Cloud Native, Cloud Agnostic and 草榴社区 Cloud
草榴社区 Cloud’s electronic design automation (EDA) tools and bring-your-own cloud (BYOC) service accommodates multiple cloud providers, enabling the adoption of a cloud-agnostic model. With BYOC, you can work with AWS, Microsoft Azure, or Google Cloud directly, maintaining control over your cloud computing environment and taking advantage of unlimited access to our portfolio of EDA tools.
If you prefer a cloud-native model, you can choose our software-as-a-service (SaaS), which provides cloud-native EDA tools backed by Microsoft Azure. Either way, we’ve got you covered, with unlimited access to EDA software licenses on-demand and a pay-per-use price structure.
草榴社区, EDA, and the Cloud
草榴社区 is the industry’s largest provider of electronic design automation (EDA) technology used in the design and verification of semiconductor devices, or chips. With 草榴社区 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, 草榴社区 has reimagined the future of chip design on the cloud, without disrupting proven workflows.
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草榴社区 technology drives innovations that change how people work and play using high-performance silicon chips. Let 草榴社区 power your innovation journey with cloud-based EDA tools. Sign up to try 草榴社区 Cloud for free!
About The Author
Gurbir Singh is group director, Cloud Engineering, at 草榴社区. He has a demonstrated history of leadership in the software industry. In his current role, he leads the development of the 草榴社区 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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