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Breaking It Down: Edge Computing vs. Cloud Computing for Product Engineering

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“Computing is not about computers anymore. It is about living”.

So, our world’s all about data and connections these days, right?

And guess what’s super important? Computing infrastructure!

There are two ways to handle it: edge computing and cloud computing.

They both have their perks and downsides.

If you’re a software product owner, knowing the difference between edge vs. cloud computing is key for making smart decisions about your product’s architecture.

Let’s explore edge computing vs cloud computing and discuss their implications for software product development.

What is Edge Computing?

Edge computing refers to a variety of networks and devices located near the user.

Means, it’s about processing data closer to where it’s generated.

As a result, it allows faster data processing, and increased bandwidth, and ensures data sovereignty.

Since, edge computing processes data at a network’s edge, it reduces the travel of large volumes of data among servers, cloud, and devices to get processed.

This makes it ideal for modern applications such as data science and AI.

Still confused?

What Are the Benefits of Edge Computing?

According to Gartner, “Enterprises that have deployed edge use cases in production will grow from about 5 percent in 2019 to about 40 percent in 2024.”


Many heavy-duty applications such as deep learning, data processing, simulations, and video streaming have become pillars of modern life.

And all these applications are powered by edge computing.

In the future, we’re going to see even more such use cases hitting the production stage.

So, here are the benefits of edge computing.

1. Lower Latency

Data processing at the edge results in reduced data travel.

This is beneficial for applications that require real-time or low-latency processing, such as autonomous vehicles, AR, and industrial automation.

2. Reduced Cost

The reduced latency results in lower use of bandwidth and network resources, reducing the cost of network usage.

And because processing happens at the edge, less data needs to be sent to the cloud for further processing, leading to decreased cost.

3. Bandwidth Efficiency

By processing data locally at the edge, only relevant information is sent to centralized servers.

This can help optimize bandwidth usage, especially in scenarios where network connectivity is limited or expensive.

4. Model Accuracy

AI relies on high-accuracy models, especially for edge use cases that require real-time response.

When a network’s bandwidth is insufficient, it is usually remedied by reducing the size of data fed into a model.

Result? Image sizes are reduced, video frames are skipped, and audio sample rates are reduced.

5. Wider Reach

For traditional cloud computing, internet access is a must.

On the other hand, edge computing can process data locally without requiring internet access.

This extends the range of computing to previously inaccessible or remote locations.

6. Data Sovereignty

Edge computing enables you to keep all your sensitive data and compute inside the local area network and company firewall.

This approach minimizes vulnerability to cybersecurity attacks in the cloud and enhances compliance with strict and ever-changing data laws.

What is Cloud Computing?

Cloud computing revolves around delivering computing services over the internet.

It is about how you do computing, not where you do computing!

Cloud computing includes a network of remote servers hosted in data centers that offer databases, processing power, and storage.

What Are the Benefits of Cloud Computing?

Cloud computing is only growing and growing.

Because it gives organizations the ability to move faster, be more agile, and innovate their businesses.

Here are a few benefits of cloud computing.

1. Accessibility

Cloud computing breaks down geographical barriers.

It provides users with the freedom to access their data and applications from any device with an internet connection.

2. Lower Upfront Cost

Cloud computing eliminates the need to buy hardware, software, IT management, and round-the-clock electricity for power and cooling.

This enables you to get your applications to market quickly, with a low financial barrier to entry.

3. Scalability

This is the heartbeat of cloud computing.

It empowers businesses to effortlessly scale their operations to meet fluctuating loads.

Be it handling increased website traffic during product launches or scaling down for a certain period of time, the cloud’s flexibility is a key factor in maintaining optimal performance.

4. Performance & Uptime

Cloud computing is designed to deliver unparalleled speed and efficiency.

In fact, it also offers high availability with no downtime because they’re distributed across multiple cloud facilities.

5. Disaster Recovery

Disasters, whether natural or man-made, are unpredictable.

Cloud computing acts as a safety net with its backup and disaster recovery features.

Since it stores data in multiple locations, it can help prevent data loss in the event of unforeseen disasters.

6. Advanced Security

Cloud computing is synonymous with robust security measures.

It comes with professional-grade security protocols, including encryption, access controls, and regular audits.

Moreover, automated backups and recovery options further fortify data against potential threats.

Edge Computing vs. Cloud Computing: A Technical Comparison

HTML Table Generator
Edge Computing
Cloud Computing
 Location of ProcessingProcessing occurs close to the data source or device Processing takes place in centralized data centers 
Latency  Low latency due to proximity to data sourceHigher latency as data must travel to and from centralized data centers 
Bandwidth Usage Reduced bandwidth usage since only relevant data is sent to the cloud Higher bandwidth usage as data is sent to centralized servers 
Scalability Can be more scalable for distributed environments Scalable, but may face challenges in handling massive amounts of data 
 SecurityDistributed architecture can enhance security Security measures are implemented centrally 
Architecture Decentralized architecture with computing resources distributed at the edge of the network Centralized architecture with resources concentrated in large data centers 
 Processing PowerEdge devices often have limited processing capabilities. Cloud data centers boast high-performance computing capabilities 
 Data Transfer ProtocolsMay use protocols like MQTT or CoAP for IoT applications Utilizes standard internet protocols such as HTTP/HTTPS for data transfer 
 Data SynchronizationRequires mechanisms for synchronizing data across distributed edge nodes while ensuring consistency  Centralized data storage simplifies synchronization but may require careful design for consistency in distributed systems
Security Protocols  May involve protocols like DTLS or IPSec for secure data transfer May involve HTTPS, SSL/TLS, and encryption for data at rest and in transit
 Fault ToleranceDesigns must consider fault tolerance at the edge Cloud environments implement robust fault-tolerance measures at the infrastructure level 
Use Cases Ideal for applications that require low latency, such as IoT devices, real-time analytics, and critical industrial processes Suitable for a wide range of applications, including data storage, big data analytics, web-based applications, and SaaS products 
 CostCan be cost-effective for certain applications by reducing the need for extensive cloud resources Costs can vary and may include factors such as data storage, data transfer, and usage of computational resources 

There are several scenarios where edge computing can be a suitable choice:

  • It is ideal when low latency is crucial.
  • In cases where transmitting large volumes of data to a centralized cloud is costly
  • When data security and privacy are high priority
  • Applications involving autonomous systems, such as self-driving cars and drones
  • It is beneficial when there is intermittent or limited network connectivity.
  • When strict regulatory requirements regarding data storage and processing
  • If your application is going to generate a high volume of data, such as IoT devices.
  • It is beneficial when dealing with a large number of devices generating data simultaneously.
  • Applications that require real-time analytics
  • If your application experiences intermittent and unpredictable workloads.

Here are some situations in which opting for cloud computing might be beneficial:

  • If your workload or application requires dynamic scaling to handle variable workloads efficiently.
  • If you do not want to invest heavily in on-premises infrastructure.
  • Want greater flexibility and agility
  • If your business operates globally or you have users in different geographic locations.
  • When robust backup and disaster recovery features are top priority
  • For faster time-to-market
  • You want your employees to collaborate and communicate with each other in real-time, irrespective of the user’s location.
  • If your organization wants to consolidate its IT resources and reduce the burden of managing physical hardware.
  • Want to focus more on core business activities rather than dedicating resources to maintaining IT infrastructure?

Embrace Tomorrow’s Technology Today!

The decision isn’t about picking sides but finding a sweet spot that aligns with your software product’s soul.

For low latency and model accuracy, edge computing steps up to the plate.

On the flip side, cloud computing stands tall when flexibility, scalability, and centralized data management is top priority.

At Azilen, we understand the significance of this decision.

And we are ready to propel your software product development journey – from idea to implementation and all the way to product success!

Our passion for innovation, blended with a commitment to engineering excellence, ensures that your product not only overcomes the challenges of today but adapts to the opportunities of tomorrow.

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