Edge Computing | Overview & Hands-On.

Edge Computing - Overview &  Hands-On.

Scope:

• Intro,
• The Concept:  Edge Computing,
• Why twtech Recommends the  use of  Edge Computing,
• Real-World Examples use cases,
• Edge Devices Types,
• Edge Computing vs. Cloud Computing,
• AWS support for Edge Computing,
• Final Tips
• Workflow Architecture for AWS Snowball.
• Project: Hands-on.

Intro:

• Edge computing is a distributed computing model where data processing happens close to the source of data generation, rather than relying solely on centralized cloud data centers.

 The Concept:  Edge Computing

• Edge computing brings computation, storage, and analytics closer to end devices (e.g., IoT sensors, smartphones, vehicles, cameras), 
• Edge computing reduces the need to send data back and forth to the cloud.

 Why twtech Recommends the  use of  Edge Computing

Benefit	Description
Low Latency	Real-time processing near the data source (e.g., industrial automation, autonomous vehicles)
Reduced Bandwidth	Only necessary data is sent to the cloud, minimizing network traffic
Improved Reliability	Local processing continues even with poor or intermittent internet
Data Privacy	Sensitive data can be processed locally instead of sending it to the cloud

 Real-World Examples Use cases

Use Case	Edge Role
Smart Factories	Analyze sensor data locally to adjust machines instantly
Autonomous Vehicles	Process data from cameras and LiDAR in real-time
Healthcare Devices	Monitor patient vitals and respond immediately
Retail Analytics	Analyze foot traffic and inventory locally in stores
Remote Oil Rigs	Process seismic or operational data on-site without internet dependency

 Edge Devices Types:

• IoT sensors,
• Routers with compute capabilities,
• Smartphones and tablets,
• AWS Snowball Edge, AWS IoT Greengrass,
• Edge servers/gateways (e.g., NVIDIA Jetson, Raspberry Pi, rugged edge devices).

 Edge Computing vs. Cloud Computing

Feature	Edge Computing	Cloud Computing
Location	Near data source	Centralized (data centers)
Latency	Low (real-time capable)	Higher (network-dependent)
Data Volume	Reduced data transmission	High data throughput
Use Case	Real-time, remote, or offline systems	High-compute, global access systems

 AWS support for Edge Computing

AWS supports edge computing via services and devices like:

• AWS Snowball Edge: Local compute + storage
• AWS IoT Greengrass: Extends AWS services to local devices
• AWS Wavelength: Edge infrastructure inside telecom 5G networks
• Amazon CloudFront: CDN with edge caching.

twtech Final Tips:

• At this juncture, aws will ship the snowball device to twtech address.  
• twtech will upload the data unto the snowball device and ship it back to aws.
• More Youtube resource on how a snowball edge device works.
• https://www.youtube.com/watch?v=bxSD1Nha2k8

• twtech migrates data into snowball device, then aws migrates the data shipped backed on the device to the  S3 bucket (twtechs3). 

NB:

• With help of an S3 lifecycle policy,  standard data in the bucket can then be migrated after a specified duration into Amazon Glacier.

Workflow Architecture for AWS Snowball.

Project: Hands-on

• How twech orders and use a snow family device to: upload data and ship back to aws.
• Go to aws service and search for: Snow family.

• Order an aws snow family device:
• Assign a name for the Job type: twtech-import-job
• Choose job type: Import into Amazon S3.

• Select a Snow devices:

• Choose your pricing option: on-demand, per day pricing.

• Select the storage type: s3 data transfer

• Select twtech S3 buckets: twtechs3, twtech-cloudfront-s3bucket

• Features and options: None

Security, shipping, and notification preferences
Security preferences

• Choose service access type: Create a service role:

From:

To:

• Shipping address: aws will ship the device to this twtech address