The cloud provides scalable support to state and local government workers.
During emergency situations, state and local governments will see an unprecedented load on their information technology infrastructure.
Citizens are live streaming governor and mayor briefings. They're searching for essential information on agency and healthcare services. And they're submitting forms for unemployment and other aid as quickly as they can. All of these requests for information can overload traditional data centers. At a minimum, this creates frustrated constituents. At its worst, it can prevent lifesaving information from getting to the public. Below, we’ve highlighted the essential differences between classic data center models and those based in the cloud, especially during high-traffic times.Classic (and Limited) Data Center Models
In the classic data center model used by many agencies, developers design systems to support a specific workload, such as the ability to stream videos to 100 simultaneous concurrent users. An organization’s IT team may have even built them as a highly available architecture with load balancers, redundant pools of servers, and high throughput network connections. However, when streaming demand grows exponentially overnight, an agency may still run out of compute or network capacity causing systems to slow down to a crawl or even fail. One way to prevent failure is with a modern cloud model.Modern (and Scalable) Cloud Model
Architecting your applications to be resilient to severe traffic peaks or unexpectedly high demand becomes much easier when you use the popular cloud services available today. In many cases, you can solve these situations by simply tying your existing on-premise applications to the cloud where you can use the services to augment your current capacity. Alternately, you can lift the whole workload to the cloud for even further enhanced performance. One example might be to use a cloud provider’s content delivery network (CDN) to distribute content to your end-users, offloading your existing servers and networks. Another example would be to use a cloud providers’ intelligent DNS service to distribute traffic to your on-premise services until they are at peak capacity, then distribute to a copy in the cloud or at another location. State and local governments can leverage many cloud services to scale workloads to meet increased citizen demand. Here are a few examples of how:Content Distribution
- A global CDN to distribute or stream cached content from edge network locations spread across the globe
- Compression services to reduce network bandwidth from data source to distribution point
Scaling
- Auto-scaling technologies to scale servers and processes almost infinitely based on load
- Load-balancing to automatically re-route traffic to newly scaled services
- Advanced DNS to intelligently distribute traffic to various services or locations
Compute and Storage Optimization
- Infinite storage capacity to avoid running out of space
- Dynamic performance tuning to accommodate traffic spikes
- In-memory cache to reduce data fetches
- Simple web threat protection such as DDoS
Flexibility
- Infinite pay-as-you-go resource usage allowing you to scale-up services and storage when needed and scale-down when no longer needed
- Immediate access to specialized server types and configurations, such as GPU-based systems
- Unlimited pay-as-you-go data processing capacity for batch processes or one-time needs
