Google Cloud Platform Support

Essentially, Google Cloud Platform is a suite of cloud computing services offered by Google. It offers various tools for computing, storage, data storage, networking, machine learning and other cloud-based services, all of which run on Google’s cloud infrastructure.

As GCP consultants, we help businesses unlock the full value of Google Cloud support services, from migration to optimisation.

GCP is known for its strong integration with Google’s robust global infrastructure, Vertex AI Platform and Gemini models with advanced data analytics and machine-learning capabilities, plus integration with other Google services. It offers unique features like BigQuery for data warehousing, TensorFlow for machine learning, and a global network that ensures low latency and high performance.

GCP uses a flexible pay-as-you-go pricing model, so you only pay for the resources that your organisation uses. Discounts are available via sustained use, committed use contracts, and free-tier services. As a trusted GCP partner, DeeperThanBlue helps businesses optimise their spend, secure credit terms instead of card payments, and access rebates for long-term agreements - which ensures maximum return on cloud investment.

Google Cloud Platform follows strict security protocols, supplying:

• Multi-layered security infrastructure
• Encryption at rest and in transit by default
• Identity and access management controls
• Compliance with global security standards

GCP offers various support plans ranging from free community support to premium support. At DeeperThanBlue our Service Desk operates 24/7 with access to Google Cloud Engineers and other technical experts. Clients can choose a Google Cloud support plan based on their needs and budget. Our support offering ranges from remote support through to a fully managed service with Google Cloud Platform (GCP).

Yes. Google Cloud Platform is designed to support many existing applications from a wide range of operating systems, programming languages, and frameworks, whether they run in virtual machines – hypervisors, containers or as microservices on Kubernetes (GKE). Google provides several tools to help you migrate your applications, such as Migrate for Compute Engine, which assists in moving virtual machines from on-premises or other cloud environments to GCP. Google Cloud Platform supports hybrid and multi-cloud environments, allowing you to run your applications across different cloud platforms and on-premises infrastructure.

BigQuery is a serverless and cost-effective enterprise data warehouse that works across clouds and scales with your data. We can help you integrate and manage BigQuery, giving your team access to its powerful analytics, business intelligence, and machine learning insights across multi-cloud environments.

Looker allows businesses to connect to various data sources, including databases, applications, and APIs, and offers powerful tools to create data models, visualise data, and generate reports. Our team will help you visualise, report, and analyse your business data seamlessly with Looker.

For technical teams, the choice usually depends on required throughput and latency. We typically recommend Cloud VPN for encrypted traffic over the public internet (ideal for lower bandwidth needs) or Dedicated Interconnect for a physical, direct-to-Google link for high-performance workloads. We also assist in configuring Shared VPCs, allowing your team to maintain a single network topology across multiple projects while ensuring strict isolation between development and production environments.

A VPC is your own private, isolated network within Google Cloud’s global infrastructure. It acts as a digital "fenced-off" area where you can securely run your servers, databases, and containers.

Unlike other cloud providers where networks are often limited to one specific location, a Google VPC is global. This means your resources in different countries can communicate with each other over Google’s private, high-speed fibre-optic backbone rather than the public internet. This provides

If your team wants to focus on writing code rather than managing infrastructure, GKE Autopilot is the technical best practice; Google manages the entire underlying node infrastructure, including security hardening and scaling. However, if your application requires specific hardware configurations (like GPUs for AI) or low-level control over the Kubernetes control plane, we help you implement GKE Standard, providing your architects with full "knob-turning" capability.

Technical bottlenecks in BigQuery often stem from unoptimised queries or table structures. We help teams implement Partitioning (by time or integer range) and Clustering to reduce the amount of data scanned, which significantly lowers costs and improves query speed. We also advise on using Materialised Views and BigQuery BI Engine for sub-second response times in high-concurrency dashboarding environments.

Hard-coding API keys or secrets is a major security risk. We recommend using Secret Manager integrated with Workload Identity. This allows your GKE workloads or Cloud Run services to act as a specific Service Account without ever needing to download and store static JSON keys. It ensures that even if an application is compromised, the attacker does not gain persistent access to your broader cloud environment.

As Terraform and Vault specialists, we help you implement a robust IaC pipeline. We focus on managing your "State Files" securely (using Cloud Storage with Object Versioning) and building modular Terraform templates. This ensures that your Dev, Staging, and Production environments are identical, preventing "configuration drift" and allowing for rapid, repeatable disaster recovery.

This is a common architectural crossroads. We typically guide teams based on the workload:

• Cloud SQL: For standard relational data (PostgreSQL/MySQL) that fits on a single instance.
• Cloud Spanner: For global applications requiring relational consistency (SQL) with the horizontal scale of a NoSQL database.
• Bigtable: For high-throughput, low-latency "NoSQL" workloads like IoT data or real-time personalisation.
• BigQuery: If the use case is analytical (OLAP) rather than transactional (OLTP).

Create and run virtual machines on Google’s infrastructure with a secure and customisable compute service. Take a look at the different virtual machine (VM) types available:

Predefined machine types: 

Custom machine types: 

Pre-emptible machines: 

Confidential computing: 

Rightsizing recommendations: 

At DeeperThanBlue, we offer reliable and secure object storage. Take a look at some of the key benefits below:

Transition to lower-cost classes easily

Multiple redundancy options

Easily transfer data to Cloud Storage

Storage classes for any workload

• Standard Storage: Good for “hot” data that’s accessed frequently, including websites, streaming videos, and mobile apps.
• Nearline Storage: Low cost. Good for data that can be stored for at least 30 days, including data backup and long-tail multimedia content.
• Coldline Storage: Very low cost. Good for data that can be stored for at least 90 days, including disaster recovery.
• Archive Storage: Lowest cost. Good for data that can be stored for at least 365 days, including regulatory archives.