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Google Cloud Certified Professional Cloud Security Engineer

A Professional Cloud Security Engineer enables organizations to design and implement a secure infrastructure on Google Cloud Platform. Through an understanding of security best practices and industry security requirements, this individual designs, develops, and manages a secure infrastructure leveraging Google security technologies. The Cloud Security Professional should be proficient in all aspects of Cloud Security including managing identity and access management, defining organizational structure and policies, using Google technologies to provide data protection, configuring network security defenses, collecting and analyzing Google Cloud Platform logs, managing incident responses, and an understanding of regulatory concerns.


Course Key Learnings:

  • Understanding the Google approach to security
  • Managing administrative identities using Cloud Identity.
  • Implementing least privilege administrative access using Google Cloud Resource Manager, Cloud IAM.
  • Implementing IP traffic controls using VPC firewalls and Cloud Armor
  • Implementing Identity Aware Proxy
  • Analyzing changes to the configuration or metadata of resources with GCP audit logs
  • Scanning for and redact sensitive data with the Data Loss Prevention API
  • Scanning a GCP deployment with Forseti
  • Remediating important types of vulnerabilities, especially in public access to data and VMs

Course Content:

Module 1: Foundations of GCP Security

  • Understand the GCP shared security responsibility model.
  • Understand Google Cloud’s approach to security
  • Understand the kinds of threats mitigated by Google and by GCP.
  • Define and Understand Access Transparency and Access Approval (beta).

 Module 2: Cloud Identity

  • Cloud Identity
  • Syncing with Microsoft Active Directory using Google Cloud Directory Sync
  • Using Managed Service for Microsoft Active Directory (beta)
  • Choosing between Google authentication and SAML-based SSO.
  • Best practices, including DNS configuration, super admin accounts.
  • Lab: Defining Users with Cloud Identity Console.

Module 3: Identity, Access, and Key Management

  • GCP Resource Manager: projects, folders, and organizations.
  • GCP IAM roles, including custom roles.
  • GCP IAM policies, including organization policies.
  • GCP IAM Labels
  • GCP IAM Recommender.
  • GCP IAM Troubleshooter.
  • GCP IAM Audit Logs
  • Best practices, including separation of duties and least privilege, the use of Google groups in policies, and avoiding the use of primitive roles
  • Labs: Configuring Cloud IAM, including custom roles and organization policies.

Module 4: Configuring Google Virtual Private Cloud for Isolation and Security

  • Configuring VPC firewalls (both ingress and egress rules)
  • Load balancing and SSL policies
  • Private Google API access.
  • SSL proxy use
  • Best practices for VPC networks, including peering and shared VPC use, correct use of subnetworks.
  • Best security practices for VPNs
  • Security considerations for interconnect and peering options
  • Available security products from partners.
  • Defining a service perimeter, including perimeter bridges.
  • Setting up private connectivity to Google APIs and services.
  • Lab: Configuring VPC firewalls.

Module 5: Securing Compute Engine: techniques and best practices

  • Compute Engine service accounts, default and customer-defined.
  • IAM roles for VMs
  • API scopes for VMs
  • Managing SSH keys for Linux VMs
  • Managing RDP logins for Windows VMs.
  • Organization policy controls: trusted images, public IP address, disabling serial port
  • Encrypting VM images with customer-managed encryption keys and with customer-supplied encryption keys
  • Finding and remediating public access to VMs.
  • Best practices, including using hardened custom images, custom service accounts (not the default service account), tailored API scopes, and the use of application default credentials instead of user-managed keys.
  • Lab: Configuring, using, and auditing VM service accounts and scopes.
  • Encrypting VM disks with customer-supplied encryption keys.
  • Lab: Encrypting disks with customer-supplied encryption keys
  • Using Shielded VMs to maintain the integrity of virtual machines.

Module 6: Advanced Logging and Analysis

  • Cloud Storage and IAM permissions
  • Cloud Storage and ACLs
  • Auditing cloud data, including finding and remediating publicly accessible data
  • Signed Cloud Storage URLs.
  • Signed policy documents
  • Encrypting Cloud Storage objects with customer-managed encryption keys and with customer-supplied encryption keys.
  • Best practices, including deleting archived versions of objects after key rotation.
  • Lab: Using customer-supplied encryption keys with Cloud Storage
  • Lab: Using customer-managed encryption keys with Cloud Storage and Cloud KMS.
  • BigQuery authorized views
  • BigQuery IAM roles.
  • Best practices, including preferring IAM permissions over ACLs.
  • Lab: Creating a BigQuery authorized view.

Module 7: Securing Applications: techniques and best practices

  • Types of application security vulnerabilities
  • DoS protections in App Engine and Cloud Functions.
  • Cloud Security Scanner.
  • Lab: Using Cloud Security Scanner to find vulnerabilities in an App Engine application.
  • Identity Aware Proxy
  • Lab: Configuring Identity Aware Proxy to protect a project.

Module 8: Securing Kubernetes: techniques and best practices

  • Authorization
  • Securing Workloads.
  • Securing Clusters
  • Logging and Monitoring.

Module 9: Protecting against Distributed Denial of Service Attacks

  • How DDoS attacks work.
  • Mitigations: GCLB, Cloud CDN, autoscaling, VPC ingress and egress firewalls, Cloud Armor (including its rules language).
  • Types of complementary partner products.
  • Lab: Configuring GCLB, CDN, traffic blacklisting with Cloud Armor.

Module 10: Protecting against content-related vulnerabilities

  • Threat: Ransomware
  • Mitigations: Backups, IAM, Data Loss Prevention API
  • Threats: Data misuse, privacy violations, sensitive/restricted/unacceptable content.
  • Threat: Identity and Oauth phishing
  • Mitigations: Classifying content using Cloud ML APIs; scanning and redacting data using Data Loss Prevention API.
  • Lab: Redacting Sensitive Data with Data Loss Prevention API.

Module 11: Monitoring, Logging, Auditing, and Scanning

  • Security Command Center
  • Stackdriver monitoring and logging
  • Lab: Installing Stackdriver agents
  • Lab: Configuring and using Stackdriver monitoring and logging
  • VPC flow logs.
  • Lab: Viewing and using VPC flow logs in Stackdriver.
  • Cloud audit logging
  • Lab: Configuring and viewing audit logs in Stackdrive
  • Deploying and Using Forseti
  • Lab: Inventorying a Deployment with Forseti Inventory (demo)
  • Lab: Scanning a Deployment with Forseti Scanner (demo).

Course Prerequisites
  • Prior completion of Google Cloud Fundamentals: Core Infrastructure or equivalent experience
  • Prior completion of Networking in Google Cloud Platform or equivalent experience
  • Knowledge of foundational concepts in information security

Target Audience:
  • Cloud information security analysts, architects, and engineers
  • Information security/cybersecurity specialists
  • Cloud infrastructure architects
  • Developers of cloud applications.

International Student Fees: 400 US$



Flexible Class Options

  • Week End Classes For Professionals  SAT | SUN
  • Corporate Group Trainings Available
  • Online Classes – Live Virtual Class (L.V.C), Online Training

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