Cloud computing is a game changer in our digital era, it has changed the way we process, access and store our information. Cloud Computing has allowed us to have access to the data anywhere in the world on line and without investing a high amount of money in hardware and software. But, hey, we have to deal with some other tricks the cloud has. Lets to dig in about these limitations before we can get into the title of this article. Cloud computing has a lot of benefits, however it has some opportunity areas, were we can improve its powerful services, here some of them: bandwidth, privacy, security, and, latency (yes, its always latency). That’s where edge computing comes in.
Ok, now, what is Edge Computing?
The use of Edge Computing technology brings a new level to the Cloud, the process of the data is made inside the network demarcation, which makes it faster and more secure. Now-a-days the IoT devices are right in our homes just to the reach of our fingertips or voice commands, these devices perform its tasks locally without using the cloud to process data, that is called Edge Computing. This is very significant since reduces the data transfer and processing speed and obviously its response time, all of this, of course, compared to the Cloud performance.
Both, Cloud and Edge computing have opportunity areas where they can compliment each other with a distributed architecture to improve their performance, efficiency, and reduce the operation costs. Here are some of the good reasons (I would say the best reasons) to combine edge and cloud computing:
– Reduced latency:
Yes, latency, You and I again, face to face (I’m watching you). Edge computing can process data in real time without having to wait for the cloud. This can improve the user experience and enable new applications that require low latency, such as telematics, autonomous devices, AR, smart manufacturing, and several other high demanding automatic processes.
– Bandwidth:
Edge computing can filter and compress data before sending it to the cloud. This can reduce the network congestion and save bandwidth costs.
– Security:
Once processed, data can be ciphert from Edge (computing), then upload it to the cloud with a higher security transfer. Sensitive data such as patients names/diseases, companies’ calculations or salaries are protected from the continuous attempts to hijack the cloud servers.
– Reliability:
Edge computing can operate independently even when the cloud connection is unavailable or unreliable. This can ensure the continuity of critical services and applications.
What are some of the most complex challenges by combining these two technologies?
– Complexity and Deployment:
The more devices are in the Edge computing, the more complex becomes. Work on devices deployments under Edge Computing requires a lot of effort and patience, work, a well defined security framework and standardization.
– Standardization:
Most of the standardization is related to other industry areas but IT, however, standardization in IT plays a key role to improve response time in its services. By standardizing the processes, equipment and configurarion from these different platforms in all Edge computing ecosystem, the workload and complexity slides down significantly.
– Increased trade-offs:
Edge computing requires balancing between the benefits and costs of local processing versus cloud processing. This can depend on various factors, such as the type of application, the amount of data, the quality of service, and the available resources.To overcome these challenges, edge and cloud computing need to work together in a seamless and coordinated way.
– Orchestration:
Orchestration manages and coordinates the communication between the devives living in the same neighbor, this is an important task since keeps communication and interaction to the ecosystem. By having this interaction and coordination with all its peers in the network, orchestration can be used to discover new devices, provide automated configuration, health monitoring, updates and even load balancing the workload.
– Edge analytics:
This one of the best resources generated by Egde Computing. Data analytics enhances the devices’ ability to extract data and transform it to a meaningful data visualization through the cloud. This is helpful if you use Machine Learning, AI or any other technique to process data in real time or likely.
– Collaboration:
Edge Collaboration is the ability to communicate and support the network devices up to the cloud level. Some of the protocols used by Edge Computing are: MQTT, CoAP, HTTP/2, WebSockets, gRPC, or QUIC.
In the end, if we understand the capabilities of both technologies together, we could find advantages of both of them, to achieve important and sustainable goals in our companies, by supporting better performance, efficiency, security, reliability, scalability, flexibility, innovation, and value for our data-driven application.
– Bitvorous.
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