Virtual computing provides modern businesses with many advanced features. From data storage and processing to remote applications and software, organizations can take advantage of virtualized instances to perform important tasks on specialized equipment.
While cloud computing is a widely known form of virtualization, there are other types of remote servers available. Of the many options to consider, more companies are turning to edge computing for their time-sensitive data processing.
What Is Edge Computing?
Edge computing is a cloud deployment approach that brings enterprises and their applications closer to internet of things (IoT) devices and necessary servers. Businesses need to quickly turn around large amounts of data, so by placing servers closer to users, edge computing providers can speed up workflows and deliver results faster.
Why Is Edge Computing So Important to Enterprises?
As cloud storage continues to secure its position as the primary tool for managing scaling data, enterprise operations are left with a mass of data to oversee. As more devices are connected within an organization, it becomes challenging to process all data within a single infrastructure.
With edge computing, enterprises can process data closer to the point where it is created, which reduces latency without sending data to a cloud center to be processed.
Additionally, this data processing approach improves the speed at which teams can pull insights that drive business decisions.
Examples of Edge Computing
Edge computing can be deployed in a variety of environments. By placing computers and storage closer to operations, businesses canexperience efficiency improvements and get more done.
Edge computing is used for:
- Data processing
- Workflow optimization
- Security and safety monitoring
- Streaming media content
- Agricultural analysis
These areas are only a few of the ways that enterprises can use edge computing to access the real-time analytics that support better decisions.
Once an effective model is deployed, organizations will achieve the following:
- Manage workloads across multiple devices
- Reliably deploy essential applications to other edge locations
- Scale storage capabilities according to evolving enterprise needs and business goals
- Increase security
How Does Edge Computing Work?
Edge computing intelligently distributes the computing process to localized storage. By moving data processing from remote storage to near where the data is initially gathered, edge computing captures information more quickly and analyzes it before sending it to main processing centers.
This setup offers some added capabilities that are especially useful in IoT implementations and other distributed architectures.
Edge Computing vs. Cloud Computing vs. Fog Computing
Here are some key differences between the three types of computing:
Edge Computing |
Cloud Computing |
Fog Computing |
Localized, distributed processing and storage |
Centralized, remote processing and storage |
Data processing in edge environments and filtered through a mediator before storing in the cloud |
Cloud Computing vs. Edge Computing
For many businesses, the cloud offers a powerful solution that meets all their storage and processing needs. However, when a company requires real-time processing capabilities for distributed devices, a more flexible option is in demand.
Edge computing provides a means to assess and process data before it is sent to the cloud, giving decision-makers more options regarding how it should be used.
Fog Computing vs. Edge Computing
Like edge computing, fog computing is a way to process information before it is sent to the cloud, so users have more control over data flows. The primary difference between fog and edge computing is that fog storage is located further away from connected devices.
With this setup, data can be transferred from edge to fog before being moved into the cloud for long-term storage.
Key Benefits of Edge Computing
Edge computing is growing in popularity as a valuable option for businesses that want to process data without relying on a centralized service provider. This approach gives them more control over their data.
Autonomy
Having total control over data flows is a big benefit for organizations. When data is stored in cloud servers, issues or complications can arise when it is time to access the data. Edge computing allows data to be stored, processed, and delivered from the localized services under your care.
Data Sovereignty
Having a cloud server might be useful, but remote providers are located all over the world. This widespread nature makes it harder to determine the laws and governance strategies that apply to your data. Because edge computing architecture is locally deployed, it is easier to manage compliance.
Security
Whether physically or over the network, moving data presents vulnerabilities. Traffic backed up to a cloud server could be corrupted, lost, or stolen by malicious actors. Edge computing adds security because data is collected and processed without having to be sent over an external network.
Edge Computing for Enterprises Challenges
Enterprise organizations face a variety of challenges when deploying to edge servers in the real world. Given its architecture, edge computing can have some basic drawbacks, including:
Limited Capability
Because data is processed locally, edge computing relies on available computing power. This restriction may limit some organizations from using their data effectively.
Data Connectivity
While cloud computing provides a single point of access, edge computing is more distributed, making it harder to connect related data across multiple locations.
Security
Although they offer a more secure option than the cloud, enterprise organizations must manage their edge deployments separately. This additional responsibility can be a challenge for data security teams.
Data Lifecycles
Important data may not be needed forever. Prioritizing new data and properly disposing of the old can be expensive and introduce exposures. This reality means businesses using edge computing must be aware of their digital architecture life cycles.
Key Capabilities of Edge Computing
Edge computing offers many capabilities for collecting, processing, and storing data, including:
Managing Vital Software at Scale Administration
For businesses that rely on data, stable growth can be difficult. With edge computing, it is easy to oversee the adoption and use of digital tools, allowing your business to grow in the process.
Using Open-Source Technology
Investing in the necessary tools and software can be expensive. Open-source technologies provide a variety of professional-level functions at no cost.
Minimizing Security Concerns
Moving data over the network can complicate security policies, making it harder to protect valuable assets. Edge computing allows you to mitigate cloud security concerns.
Building a Comprehensive and Effective Multi-Cloud Environment
When it comes to digital architecture, no one solution will keep your data safe. By combining cloud, edge, and fog computing, you can operate securely and efficiently.
Explore Edge Computing with Seagate Lyve Cloud
Seagate delivers edge storage solutions that help enterprises control how data is stored and analyzed as it is consumed and scales. Examples of this include:
- Bringing applications closer to the source to reduce bandwidth costs.
- Benefitting from simple pricing structures with zero add-on charges.
- Easily moving large data sets to core clouds for faster insights.
- Adding security to vital data with additional encryption, ransomware protection, and replication.
Lyve Cloud is creating a better multi-cloud experience for the digital future. Explore how Lyve Cloud is driving transformation across industries. Contact us today to talk to a representative about your multi-cloud environment.
