
Terraform-tracked change evidence
Every change lands as a reviewed Terraform pull request, with Cloud Logging diffs, cost impact, and an updated runbook attached to it.
Two recent Google Cloud Platform engagements. Full billing and uptime figures under MNDA; walkthrough on a scoping call.

Cloud and Data engagement,
Platform engineering lead, GCP rollout
Dcrayon moved our workloads onto Cloud Run and BigQuery, then sized committed use discounts against real usage. Our monthly GCP bill is now a line the board understands.
Monthly GCP bill vs committed use plan
p95 API latency after Cloud Run cutover
Google Cloud Platform engagement: GKE Autopilot rollout, Terraform-managed VPC and IAM, and Cloud Monitoring dashboards a lead SRE reviews each week.
Read Cloud and Data engagement's Case Study
Mid-market cloud and data brand,
Google Cloud Platform and data pipeline lead
Our BigQuery costs kept climbing with no owner. Dcrayon set up slot reservations, table partitioning, and budget alerts, and query spend became predictable again.
BigQuery query spend, before and after
Query cost per reserved slot
Google Cloud Platform engagement paired with Dataflow pipelines and Pub/Sub ingestion. A billing export queried in BigQuery set the starting picture.
Read Mid-market cloud and data brand's Case StudyHOW DCRAYON GOOGLE CLOUD PLATFORM WORKS

What ships as standard on every Dcrayon Google Cloud Platform build
Score, Plan, Compound. A GCP diagnostic, a one-quarter build plan, and the automation we run to keep cost and reliability in check.

A 150-factor review across five areas. The Google Cloud axis grades your project and folder layout, Committed Use Discount coverage, IAM and VPC Service Controls, Terraform state, and BigQuery adoption. Free on every proposal call.

A one-quarter plan that ties each GCP change, from GKE hardening to BigQuery tuning, back to a single operational metric you choose.

Our internal tooling audits your GCP projects against the Score axes and produces a ranked fix list with cost estimates your CFO can budget.
Three repeatable practices that make each Google Cloud Platform cycle safer and cheaper than the last.
Free Dcrayon Score readout in one business day. A five-area Google Cloud review mapped to your billing export and real usage, giving one 0-100 number plus a ranked gap list. No follow-on commitment.
A written 90-day Google Cloud plan tied to one operational metric you pick, such as p95 latency or cost per BigQuery query. A senior architect writes the Terraform and the SoW. Either side can end the work at day 90.
Weekly working session with your senior architect, plus a monthly cost-and-reliability summary your finance team can read. The work stacks: IAM and network hardening first, then GKE and BigQuery adoption, then Cloud Build automation.
Sibling Dcrayon services inside the Cloud and Data category. Programs clients often layer alongside Google Cloud Platform.

No trainees practicing on your production project. The certified GCP architect who plans your work also builds and runs it.

A written GCP diagnostic and a fixed estimate up front. You see the plan and the price before signing, not after a long discovery.

Every engagement includes practical machine learning on GCP: Vertex AI pipelines, BigQuery ML forecasting, and anomaly alerts on cost and traffic.

Weekly delivery plus a monthly report tying GCP spend and SLOs to your chosen metric, in plain numbers finance can act on.
Most Google Cloud Platform engagements begin within a few weeks of signing, once we have project access. Post-incident work is prioritized and starts sooner.
Both. Some clients hand us the whole GCP practice; others keep us as senior architect and escalation for their own engineers. We scope per account.
Most Google Cloud engagements start at Rs 4 to 8 lakhs per month in India, or USD 6 to 15 thousand per month for global clients. Audit-only work, such as a billing and IAM review, starts lower.
Yes. Every proposal call includes a free five-axis GCP Score readout, with no follow-on commitment required.