Secure Data Processing and Compliance with Assured Workloads

ADVANCED
130 minutes
5 tasks

In this lab, learners will build a secure environment in Google Cloud to process sensitive data while ensuring compliance with industry regulations. Participants will create a multi-tier application using Compute Engine and secure data storage with Cloud Storage, configuring robust access controls and encryption using Cloud KMS. The lab will guide students through setting up organization policies and configuring IAM roles to uphold security and compliance standards. This experience will bolster understanding of designing secure architectures in a controlled environment where sensitive operations require validation.

Scenario

Your organization, FinSecure Corp, requires a compliant data processing architecture to meet PCI DSS standards. Data must be managed within a secure boundary, ensuring end-to-end encryption and access transparency. FinSecure Corp processes thousands of transactions daily that need to be stored and secured according to strict compliance rules with a downtime tolerance of less than five minutes.

Learning Objectives

  • Implement IAM roles for secure access management.
  • Configure encryption using Cloud KMS for data protection.
  • Set up organization policies for compliant operations.
  • Develop secure Compute Engine instances with Shielded VMs.

tasks (5)

task 1: Configure IAM Roles

20 min

task 2: Enable Encryption with Cloud KMS

25 min

task 3: Apply Organization Policies

30 min

task 4: Deploy Secure Compute Engine Instances

35 min

task 5: Verify Compliance with Security Best Practices

20 min

Prerequisites

  • Basic understanding of Google Cloud IAM
  • Familiarity with Cloud KMS
  • Knowledge of organization policy constraints

Skills Tested

Implement IAM policies and access controlsManaging data security and encryptionDesigning for legislative and regulatory compliance