Disco – Enabling ML - Driven Growth Through DevOps and AWS Enablement

Client Snapshot

Industry: E-commerce / AI-Powered Checkout Solutions

Company Size: Startup

Region: United States

Website: https://www.disconetwork.com

Overview: Disco is a Shopify partner offering an AI-driven network that surfaces smart promotions to customers at checkout, creating mutual benefit across e-commerce businesses within the network.

The Challenge

  • Needed DevOps support to streamline machine learning pipeline development.

  • Long backend startup times were slowing developer velocity.

  • Lack of consistent DevOps practices and operational culture.

  • Limited visibility into metrics, alerting, and infrastructure performance.

  • Fragmented access management across teams and services.

  • Disconnected data platform operations spanning Glue, Redshift, and Snowflake.

  • High AWS costs with unclear optimization strategy.

Why They Chose Us

  • Strong background in DevOps transformation and AWS enablement.
  • Proven expertise in building scalable, efficient ML development pipelines.
  • Track record of helping startups own their cloud infrastructure and reduce costs.
  • Ability to integrate with fast-paced teams and drive real operational change.

Our Solution

We partnered closely with Disco’s machine learning and platform teams to modernize operations and improve system efficiency:

ML & Data Infrastructure Support:

  • Built streamlined development pipelines for ML model experimentation and deployment.

  • Maintained AWS Glue workflows, Redshift integration, and Snowflake data operations.

DevOps Transformation:

  • Accelerated backend startup performance through performance profiling and tuning.

  • Established DevOps practices and CI/CD pipelines to enable consistent delivery.

  • Introduced structured alerting, monitoring dashboards, and metrics visibility.

    Security and Access Management:

  • Implemented granular access controls across services and teams using IAM best practices.

    Cost Optimization & Platform Ownership:

  • Conducted cost analysis and applied right-sizing to reduce AWS spend.

  • Enabled internal teams to confidently operate and scale their AWS infrastructure.

Outcomes & KPIs

  • Empowered ML team with faster, more reliable model development workflows. 
  • Unified DevOps culture with automation, observability, and best practices.
  • Secured infrastructure with fine-grained IAM and team-based access policies.
  • Reduced AWS monthly spend while enhancing operational capabilities
  • Reduced backend application startup times, improving developer productivity.

Client Quote

“The Borealis team helped us go from reactive DevOps to owning our platform. They made our ML pipeline efficient, helped us get control of costs, and ensured we could grow without compromising performance or visibility.”
  • Disco Engineering Leadership

Future Roadmap

  •  Ongoing support for model lifecycle automation and performance tuning.
  • Further optimization of data platform and analytics integrations.
  • Scaling the network’s backend infrastructure to support rapid merchant growth.