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    Home » Edge computing vs. cloud computing: What’s the difference?
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    Edge computing vs. cloud computing: What’s the difference?

    By Doris DuJune 21, 2024Updated:June 24, 2024No Comments4 Mins Read
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    • Tech giants invest in edge computing for faster data processing.
    • Cloud computing remains essential for scalable storage solutions.

    Edge computing and cloud computing are transforming the way we process and store data. Understanding their differences can help businesses and individuals make informed decisions about their digital infrastructure.

    1. Definition and core concepts

    Edge computing involves processing data closer to where it is generated, such as on local servers or devices, rather than relying on a centralised data centre. This approach reduces latency and bandwidth usage by minimising the distance data must travel.

    Cloud computing relies on remote servers hosted on the internet to store, manage, and process data. This model provides scalable resources and services, making it ideal for handling large amounts of data and complex computations.

    2. Performance and latency

    Edge computing excels in scenarios where low latency is critical. By processing data locally, it reduces the time needed to send data to a centralised cloud and back. This is particularly beneficial for applications like autonomous vehicles, real-time analytics, and IoT devices, where immediate data processing is necessary.

    Cloud computing, on the other hand, can experience higher latency due to the distance data must travel to reach centralised servers. Despite this, cloud services have advanced significantly, with content delivery networks (CDNs) and edge servers helping to reduce latency issues.

    3. Scalability and flexibility

    Cloud computing offers unmatched scalability. Businesses can easily scale their computing resources up or down based on demand, without the need for significant upfront investment in hardware. This flexibility makes cloud computing suitable for dynamic workloads and businesses with varying resource needs.

    Edge computing, while offering lower latency, can be limited in terms of scalability. Adding more local processing units can be costlier and more complex compared to leveraging the virtually limitless resources of the cloud. However, hybrid models that combine edge and cloud computing can offer a balanced solution.

    4. Security and privacy

    Edge computing enhances security and privacy by keeping sensitive data closer to its source, reducing the risk of exposure during transmission. This can be particularly important in industries like healthcare and finance, where data privacy is paramount.

    Cloud computing, while generally secure, involves transmitting data over the internet, which can be a concern for sensitive information. However, major cloud providers invest heavily in robust security measures and compliance certifications to protect data.

    5. Cost considerations

    Edge computing can be cost-effective for reducing bandwidth costs and avoiding the expenses associated with high-latency data transmission. However, the initial investment in local infrastructure and maintenance can be significant.

    Cloud computing typically offers a pay-as-you-go model, allowing businesses to pay only for the resources they use. This model can be cost-effective for businesses that need to scale resources dynamically without significant upfront costs.

    Also read: Edge or cloud computing? What are the differences?

    Also read: 3 key security risks of cloud computing

    Industry examples

    Amazon Web Services (AWS) and Microsoft Azure are prominent examples of cloud computing platforms that provide vast resources and services for businesses of all sizes. They offer a range of services, from storage and databases to machine learning and AI.

    Edge computing is increasingly being adopted in sectors like manufacturing, where real-time data processing is critical for operations. For instance, General Electric uses edge computing to monitor and analyse data from industrial equipment in real time, improving efficiency and reducing downtime.

    The future is hybrid

    Future trends indicate a growing convergence of edge and cloud computing. Hybrid models, where edge devices handle immediate data processing and cloud servers manage long-term storage and analytics, are becoming more popular. This approach leverages the strengths of both models, providing a comprehensive solution for modern computing needs.

    Choosing between edge and cloud computing depends on specific requirements such as latency, scalability, security, and cost. Businesses must assess their needs and consider hybrid solutions to harness the benefits of both technologies effectively.

    Edge and cloud computing each offer unique advantages. As technology continues to evolve, a hybrid approach that leverages the strengths of both models will likely become the norm. Embracing this hybrid future can help businesses stay competitive, efficient, and secure in an increasingly digital world.

    cloud computing digital infrastructure edge computing
    Doris Du

    Doris Du is a reporter at BTW Media. She graduated with a master's degree in Translating and Interpreting from The Hong Kong Polytechnic University. Send tips to d.du@btw.media.

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