Google Cloud Platform For Beginners

Define the cloud as virtualized resources accessed on demand with pay-as-you-go pricing, shifting it from capital to operating expenditure, and addressing total cost of ownership, security, performance, and scaling misconceptions.

Compare the cloud's total cost of ownership with traditional data centers by revealing every bill item—traffic, storage, databases, and managed services—while exposing overlooked power, cooling, and maintenance costs.

Compare cloud security and performance design by highlighting centralized security, least-privileged security model, and intrusion detection; distinguish cloud benefits from data centers and apply the order of magnitude rule.

Using GCP enables agility and competitive advantage by removing the need to buy hardware, while supporting horizontal and vertical scaling and easy decommissioning of retired apps.

Start with a Google Cloud Platform account and projects, build a network and virtual machines, then explore storage, databases, and services for big data and machine learning.

Move security and monitoring to the design phase when adopting Google Cloud Platform to ensure governance, compliance, and audits from the start, with the customer responsible for PCI application certification.

Every resource in Google Cloud Platform belongs to a project for organization and security. Projects sit under an organization with folders, a root node, and a grace period with undo.

Explore identity and access management in Google Cloud Platform, outlining authentication, authorization, user types (Google accounts, service accounts, Google Groups, Cloud Identity domains), and permissions tied to API methods.

Explore how primitive and predefined IAM roles group permissions into bindings for users, groups, and service accounts, and how policies manage role-based access across Google Cloud Platform.

Learn to instrument every layer from compute and network to storage, database, and application, set thresholds and alerts, and achieve a 360-degree, unified monitoring view with stackdriver.

Define data centers and their compute, network, and storage infrastructure, including power and cooling, and highlight how Google's data centers emphasize security.

Explore how Google data centers ensure reliability with redundant power, cooling, and security modules. Understand how zones, regions, and multi-region deployments affect latency and performance across a global fiber network.

Explore zonal, regional, and multi-regional service scopes in Google Cloud Platform, balancing operational overhead, durability, fault tolerance, and latency. Learn how scope choices impact availability, backups, replication, and disaster recovery.

Explore Google Cloud Platform compute services, focusing on Google Compute Engine as the core option matching traditional data centers. Embrace a shift from monolithic, persistent infrastructure to temporary, consumable resources.

Explore Google Cloud compute services including Compute Engine, GKE, App Engine, and Google Cloud Functions; learn resource configuration, cost optimization with sustained use discounts and preemptive instances, and event-driven triggers.

Explore GCP network services: VPC with auto and custom modes, firewall rules, and hybrid networking with cloud VPN and cloud interconnect, shared VPC, plus global load balancing and cloud DNS.

Configure two gcp virtual machines in different zones, customize machine type and boot disk, enable ssh via network tags, and leverage vpc dns for inter-instance connectivity.

Learn core GCP storage options: persistent disks for block storage, Google Cloud Storage object stores, and Bigtable, a NoSQL database, with guidance on zonal, regional, and multi-regional deployments.

Discover GCP database options, from Cloud SQL (MySQL, PostgreSQL) to Cloud Spanner and Datastore, and assess regional versus zonal deployment and SQL query support.

Learn to move beyond operating system overhead and focus on application and user experience by choosing compute options from compute engine to app engine.

Learn about Google compute engine for deploying applications in a hybrid in-house and cloud environment, using managed instance groups, auto scaling, and cloud load balancing for high availability.

Discover deploying containers with GKE and App Engine on Google Cloud, including hybrid deployment and automated scaling, load balancing. Compare App Engine standard and flexible, with monitoring and rollback capabilities.

Understand how architectural decisions create operational ramifications and blast radius across teams, guiding high availability, fault tolerance, backups, and data accessibility in Google Cloud.

Learn how site reliability engineers prevent and resolve incidents by root cause analysis, incident response, monitoring, change management, and reducing toil while measuring availability through sla, slo, and sli.

Explore automation options in Google Cloud Platform, from cloud launcher and Deployment Manager to config files, Python templates, and Cloud SDK scripting for scalable infrastructure.

Assess the scope of the JCP ecosystem within Google Cloud Platform, and how many workflows and infrastructures can be deployed, while noting DCP's potential and Google's growing investments.