Edge Computing

Edge computing is the processing of data in remote locations and sending only salient data back to a central location, like a cloud provider or data center. The edge could be a small server in a factory, a store, a bank, or on a vehicle.

By 2030, the edge computing market is expected to grow with a revenue forecast of 156 Billion $USD, and CAGR of 37.9% to 2030. This is staggering - it is a sea change in the distributed computing landscape that is allowing for unprecedented insights into business driving growth. And it is necessary as we are approaching physical limitations in centralized compute power and network bandwidth.

Why Edge?

By reallocating compute and network resources to the edge you can much more effectively scale and process massive amounts of data. Making decisions closer to the endpoints translates into better customer UX, faster processing, and better SLAs with autonomy during network partitions.

Edge computing allows you to garner business insights that just aren’t possible due to bandwidth limitations with centralized computing - this is especially true with the adoption of AI at the edge. Efficiency, scalability, and faster decision making result in a clear competitive advantage.

With the vast amount of metadata and telemetry that is now able to be collected we are seeing innovations like smart manufacturing processes applied to serving a cup of coffee and predictive maintenance applied to not only factory equipment, but kitchen appliances.

Furthermore, with the proper edge deployment, you can quickly scale your technology with your business while maintaining business continuity.

Cloud computing has enabled unprecedented innovation and edge computing is the next step. Stay ahead of your competitors.

Industry 4.0

Industry 4.0 heavily utilizes edge computing for predictive maintenance, faster mechanical problem resolution, and smart manufacturing to increase efficiency and agility. Lower production costs and respond to market demands quickly to outperform your competitors.

Vision at the Edge

Image and Vision processing at the edge has a variety of use cases including quality assurance, theft prevention, surveillance, and customer loyalty. Decisions must be made quickly on large data sets such as images and video. Faster decision making results in a superior product, which provides more value to your customers - and revenue for your business.

Massive Multiplayer Online Gaming

Multiplayer game systems benefit from moving compute near customers, with the edge representing a POP with the lowest latency for players. This approach provides the best UX as well as an increased ability to quickly offer rewards and the most compelling purchase opportunities immediately after gameplay. Provide the best gaming experience and give your customers the opportunity to purchase upgrades and inventory before they're on to the next game.

Edge Architecture

Over the last several years I’ve had the opportunity to see many edge deployments across a number of different market segments. A wide variety of vertical markets leverage edge computing from modern restaurants to connected vehicles, maritime to retail. However, if you squint, they all start to look similar and have similar technical challenges and solutions. In fact, this informed the roadmap of the NATS.io project, which is my preferred OSS technology for edge computing.

The overarching technical goal of this architecture is a federated approach allowing for autonomy and telemetry collection at the edge without overwhelming the central system. Edge generated data is aggregated to send back with lazy consistency to back office systems for analysis, which could be cloud, on-premise, or a hybrid setup. Various services exist in the back end, at the edge and can potentially be moved as necessary - the communication patterns of services and streams are the same regardless of technology. A secure command and control plane extending to the edge may be utilized to update or roll back configurations, shut down devices or applications, or do things like pull log files. 



Technically, this can be done in a variety of ways: with an all-in-one technology like NATS.io, or utilizing a few technologies like MQTT paired with Redis.  K3s performs well at the edge with NATS as the primary communication medium. There are also a number of commercial technologies available - one size does not fit all and we can work with what is best suited for your needs.

This approach allows for scalability, ease of onboarding and deploying new edge nodes, and observability to build a future-proof system that is autonomous at the edge to ultimately give you a competitive advantage through faster time to market with a lower TCO.