GigaOm Radar for Full-Stack Edge Deploymentv1.01

1. Executive Summary

Full-stack edge deployment solutions are cloud-managed and cloud-connected hyperconverged tools that provide all the capabilities necessary to run applications at customers’ preferred locations for local data collection and processing.

These solutions bring a cloud-like experience to edge locations, which are otherwise difficult to manage at scale with traditional IT practices, especially in a DevOps-oriented and agile organization. These solutions are labeled as full-stack because they offer customers all the required technologies at all levels to manage their edge deployments. For example, customers do not need to provide or manage operating systems (OSs).

This means that the solutions can run on bare metal hardware, providing type 1 hypervisors, or OSs with type 2 hypervisors and/or containerization engines. The solutions can then deploy and run applications, often by self-service mechanisms consumed from a service catalog. Advanced solutions can enable customers to build their applications natively on the platform, which can take advantage of edge-native runtimes. Further, administrators can interact programmatically with the solution and provide a suite of visibility and troubleshooting tools.

These solutions are also labeled as “edge deployments” to differentiate them from as-a-service edge solutions, such as those provided by content delivery networks (CDNs) or edge development platforms. In other words, full-stack edge deployments are “near edge” solutions.

Particularly important use cases are those for which applications need:

• To run in air-gapped environments with limited or unstable network connectivity.

• To support latency-sensitive use cases for near-real-time processing.

• To enable data to remain local due to legislative or regulatory requirements.

• To act as an alternative where data transfers from the edge are prohibitive from either a performance or cost point of view.

• To simplify cloud architectures, especially in geographically distributed scenarios.

• To remove dependencies on cloud platforms because customers have no control over the underlying infrastructure and virtualization technologies.

• To optimize costs, such as through storage cost savings using storage tiering and minimizing data transfer costs.

The solutions that qualify to be in this report all deliver full-stack edge deployments but come from different backgrounds and can tackle specific use cases. We capture the differences in their ability to scale, which must be delineated in terms of support for scaling-up, scaling-out, and scaling-down.

Those that scale up can support large workloads and massive amounts of data to be stored and processed on their nodes; those that scale out can manage thousands of geographically distributed nodes; and those that scale down offer lightweight virtualization and runtimes that consume very small amounts of compute and memory resources, suitable for internet of things (IoT) deployments and small form-factor devices. It’s important to note that a vendor can deliver on more than one of these scalability types.

This is our first year evaluating the full-stack edge deployment space in the context of our Key Criteria and Radar reports. This GigaOm Radar report examines 16 of the top full-stack edge deployment solutions and compares offerings against the capabilities (table stakes, key features, and emerging features) and nonfunctional requirements (business criteria) outlined in the companion Key Criteria report. Together, these reports provide an overview of the market, identify leading full-stack edge deployment offerings, and help decision-makers evaluate these solutions so they can make a more informed investment decision.