Google Cloud Professional Cloud Architect: GCP Certification

Explore cloud resource management in Google Cloud, including quota, IAM, billing, and monitoring with Stackdriver. Understand how resources are organized, who has access, and what you pay.

Explore the Google Cloud resource hierarchy from organization to folders to projects. Permissions inherit from parent to child; a more permissive parent overrides restrictive policy.

Create a Google Cloud project with a globally unique project ID and a non-duplicated project name, then customize the layout and enable APIs and billing.

Attach up to 64 key-value labels to Google Cloud resources to organize, search, and monitor cost centers, environments, services, and resource status without affecting operations.

Learn how to create a google cloud compute engine instance and attach labels as key-value pairs. Explore viewing, updating, and filtering resources by labels in the console or with gcloud.

Understand how Google Cloud quotas cap per-project resources and API calls to prevent spikes and unexpected costs. View quotas in the console and request increases when needed.

Learn to view and manage project quotas in Google Cloud, filter compute engine quotas, edit quota requests, and understand API rate limits and IAM quotas for service accounts.

Explore cloud IAM to grant granular access to specific GCP resources, enforce least privilege, and manage who can do what on which resource via members, roles, and permissions.

Explore syncing active directory with google cloud via cloud identity for single sign-on, one-way or two-way federation, and understand primitive, predefined, and custom IAM roles.

Explore Google Cloud IAM policies, including bindings, audit configuration, and metadata, and learn how policy inheritance across resources enforces least privilege, while e tag helps concurrency control updates.

Understand how service accounts enable authentication between Google Cloud applications, with Google managed and user managed accounts, keys, and when to use each in cloud and hybrid on premise environments.

Create and manage service accounts in Google Cloud Console, enable the Compute Engine API, and assign default or custom service accounts with appropriate API scopes for compute and storage tasks.

Explore Google Cloud identity and access management best practices, focusing on policy inheritance across organization, folders, and projects, least-privilege grants, and using Google Groups to assign roles and audit membership.

Learn to manage Google Cloud IAM by assigning member roles, creating custom roles, handling service accounts and keys, and configuring policies and quotas for your project.

Explore how to set up and manage Google Cloud billing, including billing accounts, IAM roles, project linking, cost monitoring, exports to BigQuery, budgets and alerts.

Explore the Google Cloud billing overview, manage users and permissions, link a project to a billing account, and view cost reports by project or service and set budgets with alerts.

Export billing data to BigQuery from the Google Cloud console, create datasets, and run queries to analyze standard, detailed, and pricing billing information.

Explore the GCP operations suite, including stack driver for monitoring and logging, and tools such as logging, monitoring, error reporting, trace, debugger, and profiler to optimize performance and cost.

Explore how GCP centralizes logs in a single repository, enabling real-time and batch monitoring, export to cloud storage, BigQuery, or Pub/Sub, and project-specific log entries with retention rules.

Learn to create log exports in GCP by configuring sinks to cloud storage buckets or BigQuery, and filter by resource type like VM instances in Log Explorer.

Master cloud monitoring in Google Cloud Platform using dashboards, alerts, and logs to track uptime, resource status, and external apps, with Stackdriver agent and cross-project best practices.

Set up a cloud monitoring project and add projects to monitoring scope. Install the monitoring and logging agents on two Compute Engine VMs and explore VM metrics on the dashboard.

Navigate the VM instance dashboard in GCP cloud monitoring to view detailed metrics such as CPU, memory, disk, and firewall utilization, including top CPU processes and command-level data.

Configure uptime checks in cloud monitoring to verify instance health via tcp on port 80, with alerts, email notifications, and firewall rules.

Create and manage cloud monitoring alerts for VM CPU and disk utilization, set threshold-based conditions, configure email notifications, and navigate incident lifecycle from firing to auto closure.

Explore trace, error reporting, and debug tools to identify performance bottlenecks and latency in API calls across App Engine, GKE, and other GCP services.

Demonstrate trace, error reporting, and debugging tools in Google Cloud by deploying a sample app to App Engine and exploring standard and flexible environments.

Demonstrates using trace, error reporting, and the debugger to identify and fix App Engine deployment issues, view traces and errors, redeploy, and manage app versions.

Explore Google Cloud storage options, including persistent disks and blob storage, with relational stores like Cloud SQL and Cloud Spanner, and NoSQL like Cloud Bigtable, plus transfer services.

Explains Google Cloud Storage as a durable, scalable, rest-based object storage service, detailing buckets, objects, versioning, lifecycle policies, and access via http urls in Google Cloud Platform infrastructure.

Explore google cloud storage types—multi regional, regional, near line, and cold line—and learn how to choose the right option for global vs regional audiences, access patterns, SLA, and cost.

Learn to create and manage Google Cloud Storage buckets via the UI or Cloud Shell, including naming rules, regional versus multi-regional storage, the cost calculator, retention policy, and access controls.

Manage cloud storage using cloud shell to create buckets, upload and copy data between buckets, list contents, set permissions, enable versioning, and configure lifecycle with a json policy.

Launch a compute engine, grant storage admin permissions to the service account, and run a Python workflow to generate earthquake data, then persist results in a public cloud storage bucket.

Explore Google Cloud transfer services for cloud-to-cloud and on-premise data transfers. Enjoy secure, fast, and low-cost data movement with recurring transfers for backup, disaster recovery, and analytics.

Explore how to use the Google Cloud transfer service to move data between cloud storage sources, including Google Cloud Storage, Amazon S3, and Azure, with setup, credentials, and transfer scheduling.

Set up Google Cloud storage from a local machine or VM using the command line by configuring a service account, activating credentials, creating a bucket, uploading files, and managing ACLs.

Learn to use a customer generated encryption key to encrypt data in cloud storage, rotate keys, and manage decryption keys for reliable access and security.

Explore the managed database services on Google Cloud, including Cloud SQL, BigQuery, Big Data Cloud Store, and Cloud Data Store, and learn their use cases.

Learn how to select the GCP managed database service—Cloud SQL, Cloud Spanner, Cloud Bigtable, BigQuery, Cloud Datastore, and Firebase—using a decision tree that matches data type, workload, and mobile needs.

Explore Google Cloud SQL, a fully managed relational database for MySQL, PostgreSQL, and SQL Server with backups and pay-per-use pricing, and Cloud Spanner, globally distributed, horizontally scalable, and strongly consistent.

Learn to create a Cloud SQL db instance in the Google Cloud console, select MySQL, configure connectivity, storage, backups, and high availability, and manage users and databases.

Connect to a cloud sql instance via cloud shell, create and use databases, build tables, and run queries and imports to manage data in MySQL on Google Cloud.

Import bulk data into Cloud SQL by loading sql and csv files from a Google bucket, creating the recommendation database with tables for accommodation, rating, and recommendation.

Spin up a Cloud Spanner instance and choose regional or multi-regional deployments. Provision nodes and replicas, create databases and tables, and apply Cloud Spanner SQL features like interleave and cascade.

Discover how Google Cloud's BigQuery provides a serverless, fully managed data warehouse for massive datasets, enabling fast SQL queries, scalable analytics, and pay only for what you use.

Learn how BigQuery provides a serverless, scalable data warehouse with real-time analytics, external data processing, and seamless data transfer, backed by robust security and flexible pricing.

This case study shows moving analytics from Postgres to BigQuery reduces query times on datasets, while highlighting BigQuery's strengths for heavy, static analytics and its limitations with aggregation and joins.

Explore how to upload a csv to BigQuery, create datasets and tables with schema, load from Google Cloud Storage, and run sample SQL queries on world population data.

Learn to load and analyze nested JSON in BigQuery, convert to newline-delimited JSON, and apply auto or custom schemas for complex structures like city lived, children, and phone numbers.

Explore publicly available datasets in BigQuery to practice queries on large tables; public datasets are free to access, and you pay only for the queries you run.

Execute bq commands from cloud shell to create datasets and tables, upload data, and run queries in BigQuery.

Create a BigQuery dataset, upload wiki data from public buckets, and run simple and composite queries to measure execution time and understand aggregation impact.

Understand how the virtual private cloud (VPC) network provides global connectivity for Compute Engine, App Engine, and Kubernetes resources, with subnets, firewalls, and IAM policies to secure and manage traffic.

Explore Google Cloud's global VPC network, its subnets, how internal IP enables intra-VPC communication, how external IP handles cross-VPC access, and how firewalls with denial policies and tags govern traffic.

Explore internal and external IPs in GCP, how VPC subnets allocate addresses, and how global or regional external IPs and alias IP ranges enable inter-instance and cross-network communication.

Learn how routes in a VPC map destinations to next hops, guiding traffic between VPC resources and outside, via default, subnet, and custom routes, with firewall rules and priorities.

Explore how Google Cloud firewall rules control ingress and egress to VMs, are stateful, and enforced at the IPv4 network level.

Enable firewall rules logging to audit traffic with connection records, capturing source and destination IPs, protocol, ports, and time, and export to Google Cloud Logging, Pub/Sub, or BigQuery.

Create a custom VPC with subnets, tag instances, and apply ingress and egress firewall rules to allow or block traffic, test connectivity, and understand ICMP and port rules.