Resilience Solutions
CloudScale

Google Cloud

Google's public cloud, with particular strength in data analytics, machine learning and container orchestration.

What the architecture looks like underneath

Landing zone, network, compute, data and platform services — with governance running the height of the stack rather than bolted to one layer.

What it is

Understanding Google Cloud

Google Cloud is a public cloud provider whose differentiating services cluster around data and machine learning — BigQuery for analytics at scale, and a mature managed Kubernetes offering, given Kubernetes originated at Google.

Why it matters

For analytics-heavy workloads, separation of storage and compute with per-query billing can change the economics of large-scale analysis. For container-based platforms, the managed Kubernetes experience is well established.

Problems it addresses

  • “Our analytics workloads are constrained by warehouse capacity.”
  • “We need to run large-scale analysis without provisioning for peak.”
  • “Our container platform is expensive to operate ourselves.”

Capabilities

  • Data platform architecture

    BigQuery-centered analytics architecture and cost modeling.

  • GKE and container platforms

    Managed Kubernetes with an appropriate operational model.

  • Migration

    Workload assessment and migration.

  • Cost governance

    Query cost control, slot management and attribution.

Use cases

  • Large-scale analytics

    Serverless analytics over very large datasets without capacity planning.

  • Container platform

    Managed Kubernetes for teams without a dedicated platform function.

  • ML and data workloads

    Training and inference infrastructure alongside the analytics platform holding the data.

Before you commit

Prerequisites, governance and risks

The questions that determine whether this will work in your environment, rather than in a demonstration.

What has to be true first

  • Project and folder hierarchy design
  • Query cost governance before broad analytics access
  • Identity federation with the existing directory

Governance

Consumption-based analytics pricing means an ungoverned query can be expensive. Cost controls, quotas and query review are governance requirements rather than optimizations.

Risks

  • Unbounded query cost without quotas and monitoring
  • Smaller enterprise application ecosystem than the other major providers

Explore solutions using Google Cloud

Open the guided finder with this technology already selected, and see which capabilities apply to your goal, sector and environment — with the reasoning shown.

Start from a goal