GCP specialists for your dedicated team.

Where GCP fits in a long-term product team.

GCP is frequently adopted sideways. A team starts with BigQuery for analytics, then adds storage, then a service, and eventually runs a production estate that grew without a plan. Project structure and IAM decided retrospectively are harder to fix than they would have been to set.

Its data services are strong, and that is usually the reason to be there. Where an organisation is on GCP for analytics but runs its applications elsewhere, the sensible question is whether the split is deliberate or just how it happened.

What your dedicated team does with GCP.

GCP estates frequently start in analytics and grow into production without anyone deciding they should. Project structure and IAM set retrospectively are harder to correct than to establish, and the correction is the sort of work that never wins against a feature unless it is separately assigned.

When the estate mainly serves models, the main constraint is usually operational, and a dedicated MLOps team is the better fit than general platform work.

Common GCP use cases.

• Project and IAM structure Boundaries set deliberately so environments are separated and permissions can be reasoned about.
• Data platform operations BigQuery, pipelines and scheduling run as one platform, with no stray one-off jobs.
• Cost attribution Labels and budgets applied so analytical spend can be traced to the team generating it.

Adding GCP skills to your team.

GCP work is handled by your dedicated cloud and DevOps team, alongside data specialists on one agreement when the estate mainly serves analytics.

GCP specialists join your team remotely as dedicated, full-time team members, selected, employed and managed by us in Chiang Mai and Bangkok. Companies that hire offshore developers through Azendo add the skill at the next monthly cycle.