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Rust on GCP

This course is part of Rust for Data Engineering Specialization

Instructor: Noah Gift

Included with

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8 modules

Gain insight into a topic and learn the fundamentals.

Beginner level

Recommended experience

1 week to complete

at 10 hours a week

Flexible schedule

Learn at your own pace

8 modules

Gain insight into a topic and learn the fundamentals.

Beginner level

Recommended experience

1 week to complete

at 10 hours a week

Flexible schedule

Learn at your own pace

What you'll learn

Build a Rust handler that reads from Cloud Storage, queries BigQuery via REST or Storage Read API, and deploys to Cloud Run
Apply Pub/Sub push subscriptions with content-hash idempotency keys and concurrency × max-instances backpressure caps
Gate Rust GCP services on cargo-audit, cargo-deny, and GitHub Actions CI with secure-by-design defaults from the first commit

Skills you'll gain

Tools you'll learn

Details to know

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Build your subject-matter expertise

This course is part of the Rust for Data Engineering Specialization

When you enroll in this course, you'll also be enrolled in this Specialization.

Learn new concepts from industry experts
Gain a foundational understanding of a subject or tool
Develop job-relevant skills with hands-on projects
Earn a shareable career certificate

There are 8 modules in this course

Build production data pipelines on Google Cloud using Rust — predictable latency, single-digit-megabyte containers, and errors that fail at compile time instead of 3 a.m. This course shows engineers how to read from Cloud Storage, query BigQuery (REST jobs.query for small results, Storage Read API for million-row Arrow scans), and deploy distroless handlers to Cloud Run with sub-100 millisecond cold starts. You'll learn the gcloud CLI and Cloud Shell workflow, choose the right GCS client crate stack (google-cloud-storage, tonic, tokio), and configure Pub/Sub push subscriptions with idempotent content-hash handlers and backpressure controls. Production discipline comes through cargo-audit, cargo-deny, secure-by-design defaults, and CI gates on GitHub Actions. By the end, you'll have a working pattern for shipping a Rust ETL handler that survives at-least-once delivery, distroless image scans, and concurrent load — all on the GCP services you already pay for.

Module details

The three properties Rust gives you on Google Cloud — predictable latency, tiny containers, and honest errors — and how the GCP analytics services compose into ingest-transform-serve pipelines.

What's included

4 videos8 readings

4 videosTotal 17 minutes

Why Rust on Google Cloud3 minutes
Onboarding to Google Cloud8 minutes
Google Cloud Analytics Services3 minutes
Data Engineering Pipelines on GCP3 minutes

8 readingsTotal 80 minutes

Key Terms: Why Rust on Google Cloud10 minutes
Reflection: Why Rust on Google Cloud10 minutes
Key Terms: Onboarding to Google Cloud10 minutes
Reflection: Onboarding to Google Cloud10 minutes
Key Terms: Google Cloud Analytics Services10 minutes
Reflection: Google Cloud Analytics Services10 minutes
Key Terms: Data Engineering Pipelines on GCP10 minutes
Reflection: Data Engineering Pipelines on GCP10 minutes

The browser-hosted developer environment that ships pre-wired with gcloud, plus the local CLI install for engineers who want the same tools on their own machine.

What's included

4 videos8 readings

4 videosTotal 21 minutes

Demo: Google Cloud Shell4 minutes
Demo: Cloud Shell Editor5 minutes
Demo: Installing the Google Cloud CLI SDK6 minutes
Demo: gcloud Command-Line Tool5 minutes

8 readingsTotal 80 minutes

Key Terms: Demo — Google Cloud Shell10 minutes
Reflection: Demo — Google Cloud Shell10 minutes
Key Terms: Demo — Cloud Shell Editor10 minutes
Reflection: Demo — Cloud Shell Editor10 minutes
Key Terms: Demo — Installing the Google Cloud CLI SDK10 minutes
Reflection: Demo — Installing the Google Cloud CLI SDK10 minutes
Key Terms: Demo — gcloud Command-Line Tool10 minutes
Reflection: Demo — gcloud Command-Line Tool10 minutes

Buckets, storage classes, and lifecycle rules — and the Rust client patterns (streaming uploads, resumable sessions, ADC) that consume them efficiently from a tokio runtime.

What's included

4 videos8 readings

4 videosTotal 14 minutes

Cloud Storage Strategy4 minutes
Overview: GCP Storage Options2 minutes
Storage Comparison4 minutes
Rust Cloud Storage Client Patterns4 minutes

8 readingsTotal 80 minutes

Key Terms: Cloud Storage Strategy10 minutes
Reflection: Cloud Storage Strategy10 minutes
Key Terms: Overview — GCP Storage Options10 minutes
Reflection: Overview — GCP Storage Options10 minutes
Key Terms: Storage Comparison10 minutes
Reflection: Storage Comparison10 minutes
Key Terms: Rust Cloud Storage Client Patterns10 minutes
Reflection: Rust Cloud Storage Client Patterns10 minutes

The two BigQuery APIs Rust services use — REST jobs.query for small JSON results and the Storage Read API for million-row Arrow scans — and the prompt-engineering pattern for ML.GENERATE_TEXT.

What's included

3 videos6 readings

3 videosTotal 26 minutes

BigQuery and Prompt Engineering10 minutes
Exploring Data in BigQuery13 minutes
BigQuery from Rust: REST and Storage Read3 minutes

6 readingsTotal 60 minutes

Key Terms: BigQuery and Prompt Engineering10 minutes
Reflection: BigQuery and Prompt Engineering10 minutes
Key Terms: Exploring Data in BigQuery10 minutes
Reflection: Exploring Data in BigQuery10 minutes
Key Terms: BigQuery from Rust — REST and Storage Read10 minutes
Reflection: BigQuery from Rust — REST and Storage Read10 minutes

Volume, velocity, and cost trade-offs for big data on GCP, the three-zone (raw / transform / serving) pipeline pattern, and how GCE, GKE, Cloud Run, App Engine, and Cloud Functions each fit the trigger model.

What's included

5 videos10 readings

5 videosTotal 21 minutes

Big Data Challenges2 minutes
Building Data Pipelines3 minutes
Compare Compute Offerings3 minutes
Demo: Extending a Cloud Function10 minutes
Data Pipeline Triggers3 minutes

10 readingsTotal 100 minutes

Key Terms: Big Data Challenges10 minutes
Reflection: Big Data Challenges10 minutes
Key Terms: Building Data Pipelines10 minutes
Reflection: Building Data Pipelines10 minutes
Key Terms: Compare Compute Offerings10 minutes
Reflection: Compare Compute Offerings10 minutes
Key Terms: Demo — Extending a Cloud Function10 minutes
Reflection: Demo — Extending a Cloud Function10 minutes
Key Terms: Data Pipeline Triggers10 minutes
Reflection: Data Pipeline Triggers10 minutes

Distroless containers, Cloud Run deploys from source or image, App Engine Flex with custom runtimes, and the Pub/Sub push pattern for idempotent ETL handlers with concurrency-bounded backpressure.

What's included

4 videos8 readings

4 videosTotal 18 minutes

What is Distroless?3 minutes
Demo: Rust Microservice on Cloud Run7 minutes
Demo: Rust on App Engine Flex5 minutes
Cloud Run for Rust ETL Workers3 minutes

8 readingsTotal 80 minutes

Key Terms: What is Distroless?10 minutes
Reflection: What is Distroless?10 minutes
Key Terms: Demo — Rust Microservice on Cloud Run10 minutes
Reflection: Demo — Rust Microservice on Cloud Run10 minutes
Key Terms: Rust on App Engine Flex10 minutes
Reflection: Rust on App Engine Flex10 minutes
Key Terms: Cloud Run for Rust ETL Workers10 minutes
Reflection: Cloud Run for Rust ETL Workers10 minutes

cargo-audit and cargo-deny against the RustSec advisory database, the secure-by-design properties Rust enforces at compile time, GitHub Actions matrix builds, and the energy-efficiency case for Rust over Python at scale.