GCP (Google Cloud Platform)

What is Google Cloud Platform (GCP) and How Does It Work?

Google Cloud Platform (GCP) is a suite of cloud computing services, from Google, offering scalable infrastructure, data analytics, machine learning, and storage solutions, enabling businesses to build, deploy, and manage applications efficiently.

Google Cloud Platform

Organizations can use GCP to construct applications quickly while deploying them efficiently with scaling support.

Google Cloud Platforms provides Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and serverless computing environments. Google also offers many popular Software-as-a-Service (SaaS) products which are delivered upon GCP – well-known examples include the Google Workspace productivity suite, often used as an alternative to the Microsoft 365 suite.

For those deliberating on the choices between SaaS, PaaS and IaaS, see: SaaS vs PaaS vs IaaS: Examples, differences, & how to choose (eginnovations.com).


What are the Main Google Cloud Platform Services?

Once you log in to the Google Cloud Console, you gain access to a suite of over 100 services spanning multiple categories like computing, networking, storage, artificial intelligence (AI), machine learning (ML), and developer tools. These services enable businesses to build, deploy, and scale applications while managing enterprise resources such as databases, virtual machines, and Kubernetes clusters.

Google Cloud operates in four primary models:

  • Infrastructure as a Service (IaaS): Manage and scale virtual machines, storage, and network resources in the cloud with Compute Engine and Cloud Storage.
  • Platform as a Service (PaaS): Develop, host, and deploy applications seamlessly using App Engine or Cloud Run.
  • Software as a Service (SaaS): Leverage Google Workspace or other cloud-based tools for productivity and collaboration.
  • Serverless: Run applications and services without worrying about server management, utilizing solutions like Cloud Functions and Cloud Run.

GCP offers a free tier for evaluation and limited workloads, it says that its pay-as-you-go model ensures you only pay for the resources and services you actually use, making it a cost-effective option for enterprises of all sizes. In practice though, as with most major cloud vendors the best prices are offered to those prepared to lock-in to 1-year or 3-year commitments.

The GCE (Google Compute Engine) service operates in a very similar way to Amazon EC2 and Azure Virtual Machines. Rather than “instance types” or “VM families”, GCP uses the nomenclature “Machine Type”. From the pricing documentation, Pricing | Compute Engine: Virtual Machines (VMs) | Google Cloud, you will see equivalent models to their competitors – premium VMs offering GPUs, VMs optimized for compute, spot instance type VMs and so on.


What Hypervisor Does Google Cloud Platform Use?

Google Compute Engine VMs run on a physical host that uses Google's security-hardened, KVM-based hypervisor. Amazon’s EC2 uses a mixture of hypervisors also including KVM, whilst Azure uses Microsoft’s proprietary Hyper-V hypervisor. The KVM (Kernel-based Virtual Machine) is a Linux open-source project, as a major user of KVM, Google makes significant contributions to the KVM project and ecosystem.


How Does Google Cloud Compare With AWS and Azure?

All measures rank GCP’s share of the infrastructure and platform market as 3rd behind AWS and Azure. Q3 2024 figures suggest GCP’s share to be around 13% compared to 31% for AWS and 20% for Azure (see: Cloud Market Share For $84B Q3 2024: AWS, Microsoft, Google Cloud Lead).


Google Cloud vs AWS vs Azure: Service Comparison

GCP is known for its strengths in data analytics, AI, machine learning, and containerized workloads. Like other major cloud platforms, it offers extensive compute, storage, networking, and security services. The right choice depends on business requirements, existing investments, and technical priorities. Monitoring platforms such as eG Enterprise provide visibility across all major cloud environments and support those looking to build multi-cloud applications and microservice architectures.

Here’s a table mapping 15 top GCP services to broadly equivalent alternatives on the alternative AWS and Azure cloud platforms:

GCP Service AWS Equivalent Azure Equivalent
Google Compute Engine (GCE) EC2 Virtual Machines
Google App Engine Elastic Beanstalk App Service
Google Kubernetes Engine (GKE) Elastic Kubernetes Service (EKS) Azure Kubernetes Service (AKS)
Google Cloud Storage S3 Blob Storage
Google BigQuery Redshift Synapse Analytics
Google Cloud Pub/Sub SQS / SNS Service Bus / Event Grid
Google Cloud Functions Lambda Azure Functions
Google Cloud Spanner Aurora Cosmos DB
Google Cloud SQL RDS Azure Database (MySQL/PostgreSQL/SQL Server)
Google Cloud Dataflow Data Pipeline / Glue Azure Data Factory
Google Cloud Run Fargate Azure Container Instances
Google Cloud Firestore DynamoDB Cosmos DB
Google Cloud IAM IAM Azure Active Directory / RBAC
Google Cloud CDN CloudFront Azure CDN
Google Cloud Operations (was Stackdriver) CloudWatch Azure Monitor

GCP offers considerably fewer services than both AWS and Azure. This is one reason for GCP’s smaller market share. There are some types of service offered by both AWS and Azure which GCP does not have an equivalent offering for, notably GCP has not ended the EUC (End User Computing) market and has no VDI/DaaS offering equivalent to AVD or Amazon’s WorkSpaces.


Why is Google Cloud Monitoring Important?

So why do you need to monitor GCP performance? Here are some reasons to monitor GCP:

  • Cloud providers don’t guarantee great performance. Cloud provider SLAs (Service Level Agreements) are mainly about infrastructure availability. Organizations need ways to track how their applications and services are performing.
  • Google Cloud monitoring is important to make sure key services being used are operational.
  • Having Google Cloud monitoring in eG Enterprise allows customers to monitor on-prem and multi-cloud environments from one console.
  • Continuously track usage of resources and determine how to right-size and optimize cloud usage.
  • Identify the root cause of slowness when it happens: is it due to insufficient resource capacity, poor network connectivity, malfunctioning service, etc.?

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What metrics and measures should you monitor in GCP (Google Cloud Platform)?

Here are a few essential metrics that you will certainly need to measure for certain services:

  1. Google Cloud Infrastructure: Key metrics include:
    • Availability
    • Responsiveness
    • Response code
  2. Google Cloud Storage: For this you will want to be monitoring:
    • Status of Filestores
    • Filestore Disk utilization
    • Filestore I/O operations
    • Bandwidth usage of storage buckets
    • Memory/CPU usage of storage buckets
  3. Google Cloud Compute: Monitoring these metrics is essential:
    • Memory utilization of VMs
    • CPU utilization of VMs
    • Dropped packets
    • I/O activity of VMs
    • Registered VMs/Removed VMs
  4. Google Cloud Databases: Useful metrics include:
    • Resource utilization of each Bigtable/Spanner instance
    • Request failures to tables in Bigtables
    • I/O operations and resource utilization of each SQL instance
  5. Google Cloud Analytics: These metrics will alert you to issues:
    • Query execution time
    • Slot utilization
    • DAG (Directed Acyclic Graph) process parse time
    • Parsing errors in DAG
  6. Google Cloud Operations: Metrics to watch include:
    • Data ingestion
    • Log entry failures
    • Errors
  7. Google Cloud Billing: It’s a very good idea to monitor your costs in GCP, a few automated alerts will prevent unpleasant billing surprises, anomaly detection and alerting on these metrics will protect you:
    • Billing cost of each service/tag/label
    • Billing cost of each service in current month
Google Cloud Platform
Monitoring VMs and all the service tiers dependencies is easy with a turnkey solution such as eG Enterprise

What are popular tools to monitor GCP?

Popular tools to monitor GCP include Google Cloud Operations Suite (formerly Stackdriver), Datadog, New Relic, Dynatrace, eG Enterprise, Prometheus, and Grafana.

The choice of monitoring tools for GCP is often determined by how out-of-the-box a solution is and whether domain specific functionality is provided for key the services provided, e.g., is their domain specific support for GKE or Google Cloud Databases.

Increasingly, regulation in some sectors and cloud well-architected frameworks are mandating that organizations should have AIOps (Artificial Intelligence for IT Operations) features such as anomaly-detection in place. Regulations such as DORA for financial organizations in the EU mean that AIOps-enabled solutions such as eG Enterprise offer an easier path to compliance above Prometheus and Grafana where you have to build-your-own anomaly detection type functionality.

Looking for a Smarter Way to Monitor GCP?

Get unified visibility across GCP, AWS, Azure, and on-premises environments with eG Enterprise. Monitor performance, detect anomalies, and troubleshoot issues from a single console.


Can I monitor GCP alongside AWS and Azure, or alongside my on-prem infrastructure?

Yes, monitoring solutions such as eG Enterprise support multi-cloud and hybrid cloud monitoring. eG Enterprise supports other public clouds such as AWS, Azure and Alibaba, which can be monitored in the same way within a single console as Google Cloud Platform (GCP).

Frequently Asked Questions (FAQs)

Google Cloud Platform (GCP) is a cloud computing platform used to build, deploy, and manage applications and services. Organizations rely on it for infrastructure, data analytics, AI and machine learning, storage, networking, and application modernization. Solutions like eG Enterprise help teams maintain visibility into the performance and health of GCP-based environments.

We’ve written a deep dive into some of the most popular GCP services and their specific use cases, see: Top Google Cloud Platform (GCP) Services Explained with Use Cases.

You can explore the wider range of Google Cloud products, here: Products and Services | Google Cloud.

The main GCP services include Compute Engine for virtual machines, Kubernetes Engine for container orchestration, Cloud Storage for scalable data storage, BigQuery for analytics, Cloud SQL for managed databases, and AI services. Together, these services support application development, modernization, and large-scale data processing across cloud environments.

Learn more about the top Google Cloud Platform services in use, in our deep-dive article: Top Google Cloud Platform (GCP) Services Explained with Use Cases.

Google Cloud Platform monitoring is the process of tracking the performance, availability, utilization, and health of cloud resources and applications running on GCP. It helps IT teams identify bottlenecks, troubleshoot issues, and optimize workloads. eG Enterprise extends GCP monitoring with full-stack observability and deeper performance insights, see: Google Cloud Monitoring Tool for GCP Performance.

Google Cloud monitoring is used to collect and analyze metrics, logs, and performance data from cloud resources. It enables administrators to detect anomalies, receive alerts, monitor service health, and ensure applications meet performance goals. Effective monitoring helps improve uptime, user experience, resource efficiency, and operational reliability.

Yes, GCP can be monitored alongside other major cloud platforms through a unified observability solution. Multi-cloud monitoring helps IT teams compare performance, track dependencies, and troubleshoot issues across distributed environments from a single console. eG Enterprise delivers correlated visibility across cloud, on-premises, and hybrid infrastructures. eG Enterprise currently supports monitoring of public clouds beyond GCP, including Microsoft Azure, Amazon AWS and Alibaba.