Edge is a distributed system that puts forward data processing and data storage closer to the point of action or occurrence of an event. It aids in distributing data without latency and storage requirements on the network.
Edge is a distributed system that puts forward data processing and data storage closer to the point of action or occurrence of an event. Data processing at the edge makes immediate application of analytics and AI capabilities possible. Edge computing aids in distributing data without latency and reduced bandwidth and storage requirements on the network.
Edge computing allows data from internet of things devices to be analyzed at the edge of the network before being sent to a data center or cloud.
Despite its growing popularity, is it profitable to invest in edge computing? The below points will give a better idea of why edge computing is necessary:
Edge and cloud computing are two separate terms. A cloud is an IT habitat that abstracts, pools, and shares IT assets over a network. An edge is a computing position at the end of a network, along with the hardware and software at those physical spots. Below are major points of consideration in edge vs cloud:
| Parameters | Edge Computing | Cloud Computing |
|---|---|---|
|
Performance
|
Fast
|
Slow
|
|
Operational Cost
|
Low
|
High
|
|
Data Processing
|
Stored and processed locally
|
Stored and processed over cloud
|
|
Network Traffic
|
Low
|
High
|
|
Service Location
|
In edge network
|
Within the Internet
|
|
Vulnerability
|
Low probability
|
High probability
|
|
Service Scope
|
Limited
|
Global
|
|
Hardware
|
Limited capabilities
|
Scalable capabilities
|
|
Latency
|
Low
|
High
|
|
Control
|
Distributed
|
Centralized
|
Source: Research for Markets
Users do not have to rely on the cloud for data or computing as edge computing has a tiered architecture. Edge computing takes place where sensors and other instruments gather and process data. It quickens the processing before devices connect to IoT and send the data for further use. Edge computing will enable each farm to work without depending on the connection to the main server and make decisions based on data from local sensors.
This approach insulates the user applications and devices from non-working servers at central or regional data centers. Also, each tier is responsible for local connectivity and data synchronization in order to keep applications or devices connected to the data center.
The term “edge” means literally the edge of a distributed system, hence the name.
The tiered architecture discussed above has a lot of components that are dependent on each other, such as:
QA has a crucial role to verify the functionality of each of the above components and testing if they work together as an integrated system.
Also, edge computing can serve any number of edge devices which are usually IoT devices that include several components such as:
A tester can perform the below testing approach:
Benefits |
Challenges |
|---|---|
| Improved response time | Loss of data |
| Enhanced privacy & security | Geographic inconsistencies |
| Scalability | Needs more support |
| Reliability | Speed bottlenecks |
| Cost-effective | Difficult to monitor security breaches |
Edge computing is excessively dependent on learnings and solutions implemented in the cloud. Therefore, deployment and testing requirements need to be updated as per the new design, architecture. Testing can be beneficial not only in discovering the shortcomings but also in the system failures.
A quality assurance team can either go with the best possible strategies or emphasize the most affordable ones for the team. We at QASource have expertise in analyzing and defining the right approaches to test edge and cloud computing.
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