Edge computing

As explained in Google Anthos in Action

Edge is a distributed computing environment located near the users, devices, or data sources that generate or consume workloads.

Edge computing places workloads near the users, devices, or data sources that generate or consume them. It supports rapid responses, near-real-time insights, reduced central data transfer, and continued operation when cloud connectivity is unstable. section 8.2.2 section 7.0

Deploy edge infrastructure according to location and responsibility:

• Telco edge uses operator data centers, points of presence, and network cabinets. section 8.2.2
• Public cloud edge uses provider or broadcaster points of presence and CDN edges. section 8.2.2
• Enterprise edge places smaller infrastructure in branch offices, retail stores, warehouses, and factories. section 8.2.2
• Expect a growing compute fleet and provide a central management plane capable of managing tens of thousands of nodes. section 8.2.2

Edge architectures keep latency-sensitive processing close to endpoints while sending non-real-time analytics, metadata processing, or model training to the cloud. Containerized workloads and Kubernetes-consistent platforms support this split across distributed sites. section 8.2.1 section 7.0

Smart retail queue management

A store camera streams checkout video through a 5G modem to a telecom edge location. An Anthos bare metal cluster runs a containerized machine-learning application that counts people in line and sends a request to open another register when a threshold is exceeded. Event metadata goes to Google Cloud for analytics and future model training, while video inference remains at the telecom edge. section 8.3.3

Figure 8.2 Edge deployment

Compare telco, public cloud, and enterprise edge placements and their distributed infrastructure roles. section 8.2.2

Figure 8.10 High-level architecture for an edge smart retail solution

Trace the smart retail path from camera and 5G transport through telecom-edge inference to cloud analytics. section 8.3.3

How Google Anthos in Action covers it

How deep it goes

Defines deployment categories, fleet-management needs, and a smart-retail architecture, but stops short of installation procedures.

Examples

Uses autonomous driving, smart cities, factories, surveillance, augmented reality, remote surgery, and retail queue management.

What it assumes

Assumes familiarity with cloud and Kubernetes deployment concepts while teaching edge locations, workload placement, and processing splits.

What you can do after

Operate/configure distributed edge architectures that keep real-time processing local and delegate analytics or training to the cloud.

How it connects

Connects edge computing with Kubernetes, Anthos, 5G, containerization, machine learning inference, and cloud analytics.

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Also explained in

• 

  liveBookmanning.com
  LLMs in ProductionA computing architecture that processes data near its source or point of use to reduce dependence on remote services.
• 

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  Digital Twins in ActionEdge computing is a computing architecture that processes data near the device or data source rather than exclusively in a remote cloud.
• 

  liveBookmanning.com
  Server-Side WebAssemblyEdge computing performs computation near the sources or consumers of data rather than exclusively in centralized cloud infrastructure.
• 

  liveBookmanning.com
  LatencyEdge computing is a computing approach that places computation and data processing near the users or devices that generate or consume the data.

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Related concepts

• edge deviceuses · An edge device is a computing device located near data sources, users, or operations that processes or uses data close to where it is generated or consumed.
• cloud computingcontrasts with · Cloud computing is the on-demand delivery of computing resources and services over a network from remotely managed infrastructure.
• computer visionused by · Computer vision is the field of computing concerned with using computational methods to extract and interpret information from images, video, and other visual data.
• deploymentkind of · Deployment is the process of making software, models, or other computational systems available to operate in a target environment.
• CDNincludes · A content delivery network is a distributed network of servers that caches or delivers digital content from locations near requesting users.
• meanaddresses · A mean is a measure of central tendency, calculated as the arithmetic average of values or, for a random variable, as the probability-weighted average of its possible values.

This explainer was generated by Manning's knowledge graph from the text of Google Anthos in Action. The section links point to the parts of the book it draws on.