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Have you heard of distributed cloud computing and wondered whether it could help your business? This article describes distributed cloud computing by detailing its advantages and disadvantages.
Distributed cloud computing occurs when a cloud provider distributes cloud services to various geographic locations. The public cloud provider then operates and updates these services. Garner that by 2024 most cloud service platforms will provide at least some distributed cloud computing services that execute at the point of need.
With distributed cloud computing, companies can meet specific application performance and responsiveness requirements, as well as regulatory and governance compliance mandates. Companies can also ensure other conditions, such as that cloud infrastructure be located outside the typical availability zones of cloud providers.
Understanding Distributed Cloud Computing
In distributed cloud computing, all the computing power of a cloud provider is distributed wherever a customer needs it: on-premises in data centers or private clouds or off-premises in public cloud data centers.
Distributed cloud computing extends the provider's centralized cloud with geographically distributed micro-clouds. The provider controls all distributed infrastructure centrally, including operations, updates, governance, security, and reliability. Everything is accessible as a single cloud and managed from a single control plane.
Distributed cloud computing offers extra features as well. Users can request that certain data remain within specific regions or that they meet a specific latency or throughput target. These features are included in service level agreements (SLA) between the user and the cloud provider.
Major cloud providers integrate their technology into dispersed cloud data centers to ensure they appropriately place data, computing, and storage to transparently meet SLAs.
Exploring the Benefits
Distributed cloud computing can boost performance because it eliminates latency issues and reduces the risk of global network outages and control plane issues. Its advantages include:
- Hybrid cloud and multi-cloud visibility. Distributed cloud provides organizations with visibility. From one console, it manages the hybrid cloud and multi-cloud infrastructure.
- Scalability. Expanding a dedicated data center or building new centers in different geographies can be expensive and time-consuming. Distributed cloud computing allows organizations to expand to edge locations without building out.
- Lower latency. By relocating the processing tasks closer to the end user, distributed cloud computing reduces latency and increases the responsiveness of services. Data is then processed locally instead of at a centralized server, resulting in a superior user experience.
- Compliance with regulations. Many data privacy laws prohibit personal information from leaving the country. A distributed cloud infrastructure makes it much easier for organizations to process personal information where users live.
- Content delivery. By storing and delivering video content closer to users, distributed cloud computing can improve streaming video content performance and the user experience.
- BCP/DR. Distributed cloud computing makes it easier to plan for BCP and DR for your applications.
- Internet of Things. Many applications rely on real-time data analysis, including smart buildings, video surveillance, manufacturing automation, self-driving cars, and healthcare applications. These applications cannot wait for data to travel to a central data center. Distributed clouds deliver low latency for these applications.
Potential Challenges
It is important to keep in mind certain disadvantages, though, including security and bandwidth issues.
- Security. Distributed clouds can be tricky to secure with resources scattered worldwide. They can also be co-located with other servers and storage.
- Data backup. Distributed cloud computing may require rethinking backup and recovery strategies to ensure data stays in the right place.
- Bandwidth. In a widely distributed cloud environment, each location may use a different connectivity model. Moving more computing to the edge can therefore stress broadband connections and require them to upgrade or adapt.
The Intersection of Distributed Cloud and Edge Computing
An extension of distributed cloud computing is edge computing. With edge computing, data is processed near the place where it is generated. The edge storage and computing resources connect to larger cloud data centers for analysis and bulk storage.
The future requirements for edge computing focus on reducing round-trip response times, lowering the power consumption of edge applications, and ensuring there is enough processing power to handle tasks. Next-generation chips will meet these needs by reducing latency and power consumption and including artificial intelligence.
To help with next-generation chip design, 草榴社区' cloud-based electronic design automation (EDA) solutions enable you to scale in a safe environment, boosting productivity and lowering turnaround time and costs. Our solutions are endorsed by semiconductor foundries to work with their libraries and process design kits.
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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About The Author
Venkata Ravella is vice president of Information Technology at 草榴社区, 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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