Edge computing is an emerging technology trend that is transforming how data is processed and delivered from the cloud to devices. The basic premise of edge computing is to process data closer to the source of the data, at the network edge, rather than sending all data to the cloud. This allows for faster processing times and reduced bandwidth usage. New companies focused on edge computing are emerging to enable this next generation of computing infrastructure.
What are the benefits of edge computing?
There are several key benefits that edge computing provides over traditional cloud-based processing:
- Lower latency – By processing data locally on edge devices rather than transmitting to the cloud, applications can achieve much lower latency. This is critical for uses like IoT, AR/VR, autonomous vehicles etc.
- Reduced bandwidth costs – Less data needs to be moved to and from the cloud, reducing network bandwidth requirements and costs.
- Improved reliability – Edge computing allows apps to continue functioning locally even if the connection to the cloud goes down.
- Enhanced security – Sensitive data can be processed and stored locally on the edge rather than transmitted to the cloud.
- Scalability – More devices and data sources can be handled by distributing processing to the edge rather than solely relying on the cloud.
These benefits make edge computing essential for supporting emerging technologies like 5G, IoT, robotics, and mobility solutions. New edge companies are focused on enabling these edge computing use cases.
What are the key capabilities needed for edge computing?
In order to deliver on the promise of edge computing, new solutions need to provide some key capabilities:
- Low latency data processing – Edge platforms need to support running compute right at the data source with minimal lag.
- Distributed architectures – Companies need to develop distributed systems that bridge the gap between cloud data centers and edge devices.
- Hardware-software integration – Tight integration between optimized hardware and software is needed for high-performance edge processing.
- Autonomy – Edge devices need to be able to automatically take actions on processed data and continue functioning, even without connectivity.
- Security – With data processed locally on remote edge devices, secured communications and data protection are critical.
- Management – The ability to remotely manage a large number of heterogeneous edge devices is key for scalability.
- Analytics – Making sense of vast amounts of data from edge devices requires analytics optimized for streaming edge data.
New edge companies are taking innovative approaches to building solutions with these critical enablers for edge computing use cases.
Who are the key players in the edge computing industry?
Some of the notable new companies focused on edge computing include:
- Vapor IO – Develops edge data centers and an edge platform for 5G and IoT applications. Recently raised $45M.
- Fastly – Provides an edge cloud platform for high-performance content and application delivery. Went public in 2019.
- Platform9 – Offers a SaaS solution for deploying and operating Kubernetes clusters in edge locations.
- Rigado – Specializes in edge gateways and software for managing edge devices and networks.
- FogHorn – Provides edge intelligence software for real-time data processing and industrial IoT use cases.
- Swim – Develops a edge intelligence platform for processing and analyzing streaming data.
- ClearBlade – Platform for enterprise IoT solutions to run at the edge. Raised $23M.
- AlefEdge – Works on 5G edge solutions and an edge Internet architecture. Part of the Linux Foundation.
Larger tech companies like AWS, Microsoft and Google are also making big investments in edge computing solutions. Overall there is rapidly growing interest and innovation in the edge computing space.
What are the key trends in edge computing?
Some of the important trends emerging in the edge computing industry include:
- 5G networks – The ultra-low latency and massive bandwidth of 5G is expected to drive many edge use cases like smart cities, industrial automation, and autonomous vehicles.
- Telco edge – Telecommunications companies are exploring edge computing infrastructure rollouts to support next-gen networks.
- Multi-access edge computing – Standardized architectures being developed to deploy applications at the edge of 4G and 5G networks.
- Intelligent edge devices – Devices like industrial controllers, drones, and autonomous robots are getting smarter edge processing capabilities.
- Edge data centers – Smaller, distributed micro data centers are being deployed in edge locations to enable low-latency computing.
- Edge AI – Machine learning models are being optimized to run faster and more efficiently on edge hardware.
- Edge-native platforms – New application development platforms designed specifically for edge environments.
These trends point to an exciting future where intelligence and automation extend from the cloud all the way to the true edge of networks.
What are examples of edge computing use cases?
Here are some examples of innovative use cases that companies are enabling with edge computing:
- Autonomous vehicles – Self-driving cars perform time-sensitive processing like object detection locally using on-board edge compute.
- Industrial automation – Edge devices like PLCs locally control processes in manufacturing plants with minimal latency.
- Smart energy grids – Real-time analytics at the edge helps intelligently balance power distribution across the grid.
- Remote asset monitoring – Edge compute deployed locally on rigs, pipelines etc. processes and analyzes real-time sensor data..
- Smart retail – Collecting analytics from edge sensors helps stores optimize layout, promotions, and customer engagement.
- Smart cities – Applications like traffic optimization, public safety, and infrastructure monitoring benefit from edge intelligence.
- AR/VR – Local edge processing reduces latency allowing for immersive extended reality experiences.
- Connected healthcare – Wearables and home health devices can securely process data locally before transmitting alerts.
These use cases demonstrate the versatility of edge computing for delivering real-time intelligent systems.
What are the challenges facing adoption of edge computing?
While the benefits of edge computing are compelling, there are also some key challenges that need to be addressed:
- Immature ecosystem – The edge ecosystem is highly fragmented. Open standards are still evolving.
- Lack of edge developer skills – Most developers are still focused on cloud development vs edge native programming.
- Cost of edge infrastructure – Deploying distributed infrastructure at the edge can be expensive.
- Data silos – Managing data across dispersed edge nodes is difficult vs centralized cloud.
- Security risks – Broader attack surface with data distributed across more edge endpoints.
- Interoperability issues – Getting hardware, software, networks to seamlessly work together remains challenging.
- Durability of devices – Ensuring reliability with remote edge devices operating in harsh real-world conditions.
Overcoming these challenges will require continued innovation by new edge companies as well as collaboration across the industry.
How will edge computing impact different industries?
Edge computing stands to significantly benefit industries dealing with highly distributed environments and missions critical applications including:
- Manufacturing – Enables time-sensitive control and automation, quality assurance using computer vision, predictive maintenance of equipment etc.
- Transportation – Low latency needed for autonomous vehicles, fleet tracking and logistics, smart traffic systems.
- Energy – Real-time optimization across distributed energy resources. Outage prevention.
- Retail – In-store analytics to engage customers, connected shelves for inventory optimization, cashier-less stores.
- Telecom – Essential for rolling out low-latency 5G networks and services.
- Healthcare – Securely extended care from hospital to homes. Remote patient monitoring with wearables.
- Government – Public safety and emergency response use cases. Smart city infrastructure and services.
Many industry verticals stand to benefit from the performance and localization advantages unlocked by edge computing.
Conclusion
Edge computing represents the next major evolution of networking infrastructure, enabling real-time intelligent systems. New companies focused on edge computing solutions are driving innovation across a diverse range of edge capabilities and use cases. While challenges remain, the momentum is building to unlock the full potential of edge computing across industries. Driven by 5G, IoT, and AI, the edge market outlook remains very bright into the foreseeable future.