agtech

Tagging unstructured data

Tagging AWS infrastructure for security, costing, and resource identification

Results

We successfully tagged all AWS data and compute resources to better track costs and calculate the cost to serve. We developed the needed processes, standards, and resources to classify data, both at rest and in transit. Also, we better prepared our client to prevent and recover from digital attacks and potential disasters.

Easier tagging & redefining

With a simple command integrated into their DevOps pipeline

Reusable toolset

With command line tools and built in documentation

Ready for the worst

Improved cybersecurity & disaster recovery resources/reporting

Background

San Francisco

Our client’s data didn’t give a comprehensive view of cost and resource tracking and made them dependent on a specific tool. So we helped tag critical AWS data (including RDS, EC2, DynamoDB, S3, and Lambda) to be classified before it was stored throughout the data lifecycle.

Team

Project management
Back end development
QA

Build type

Greenfield

Tech stack

Python
AWS

What we did

New possibilities

Our client was locked into using an inefficient platform with a feature set limited by a lack of AWS tagging. Our tagging efforts allowed the client to track costs and resources by the team.

Secure & traceable

We ensured key data records and systems would be auditable and traceable with a better reporting process powered by our rapid tagging.

Improved reporting process
Auditable, traceable records

Ready for disasters

To better handle disasters and understand the resources needed to recover from them, we ensured the AWS architecture would be classified as a priority if an incident occurred. This also enabled quick reporting of priority groups as our client evolves and grows.

Long term strategy

We focused not only on quick wins but also on the organization’s long-term goals and digital farming platforms. This made it easy to roll up costs around their data-driven products and services.

Related work

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