You’ve Moved to the Cloud. Now What? Building a Cloud-Native Operating Model

Migration Is Just the Beginning
Moving to the cloud is like moving house. You have relocated, unpacked, and settled in. But now comes the real work: figuring out how to live in your new space, use all the new features, and make it work for your lifestyle.

If you do not adapt your way of working, you’ll miss out on all the reasons you moved for – agility, speed, and scale.

 
Invest in Skills Early
Cloud platforms are only as effective as the people using them. It is easy to underestimate the knowledge shift required after migration.
One of the best things you can do post-migration is invest in upskilling, enablement, and role-based onboarding.

Every team does not need the same depth. Focus on persona-driven learning, like this:

Embed learning in team rituals: brown bag sessions, demo sessions, shadowing, and hands-on labs. Your platform will only scale if your people do.

 
What Does “Cloud-Native” Actually Mean?
Being cloud-native does not just mean your workloads are hosted in the cloud. It means your ways of working are designed for the cloud.

That includes:
• Using automation to avoid manual effort.
• Giving teams the ability to move fast, without compromising control.
• Being smart about cost but focused on value.
• Treating your data platform like a product that evolves, not just a project to maintain.

Key Ingredients of a Cloud-Native Operating Model
Let’s explore what it takes to make your cloud platform effective and sustainable.

Give the Platform an Owner
Without clear ownership, the platform ends up becoming everyone’s part-time job and nobody’s priority. Create a dedicated platform team that treats the data platform like a product. Their role includes:

• Onboarding support for engineers and stewards.
• Automation and CI/CD standards.
• Cost reporting and tagging enforcement.
• Support playbooks and adoption dashboards.

Clearly define personas, RACI assignments and platform-level support roles.

Automate What You Can
Manual setup slows teams down. Automate infrastructure, jobs, and environment promotion with tools such as:
• Terraform / Bicep for workspace provisioning.
• Databricks Asset Bundles for pipeline deployment.
• CI/CD pipelines for metadata and code versioning.

A solid DevOps model will help foster consistent automation, reduce environment specific failures, and build confidence across the lifecycle.

Make Everything Observable
A reliable platform is one where you can see what is happening.
Use observability tooling to track:
• Data quality pass rates.
• Job failures and latencies.
• Certified dataset usage.
• Query performance and response time.

Dashboards can be used not only by platform teams but also by governance leads and division owners. This ensures transparency for everyone not just tech teams.

From Cost Centre to Value Driver
One mistake many organisations make is treating the cloud platform as a back-end cost centre. But cloud should be a value enabler. To shift this mindset, you need to measure and communicate value clearly both direct and indirect.

Here are some ROI indicators:

The takeaway? Do not just show cost savings show outcomes. Track platform performance like a product: usage, satisfaction, and impact.

Govern for Empowerment, Not Just Control
Governance should feel like enablement, not bureaucracy. Embed governance into platform workflows by:
• Enforcing certification before sharing.
• Requiring metadata completeness and steward sign-off.
• Auditing approvals and usage logs.

Certification is a contract of trust. Sharing uncertified data should be discouraged by design, not just policy.

Track Adoption to Drive Improvement
Adoption is not just a “nice to have” it’s a health indicator. Some examples:
• Logins, queries, and dataset usage are tracked passively.
• Success metrics like onboarding time or dataset rejection rate are surfaced automatically.
• Divisions are given access to dashboards showing their own activity and cost profile.

Why it matters: If adoption is low, something is broken. Maybe onboarding is too complex. Maybe users do not trust the data. You will not know unless you track it.

Final Thoughts: Operate to Innovate
Getting to the cloud is a milestone, not the finish line. The real transformation happens after migration when your teams adopt new ways of working, data flows with confidence, and governance happens as part of delivery, not in hindsight. Cloud-native operating models are not just about tools. They are about ownership, measurement, and culture.

If you are building your post-migration strategy, here’s the checklist:
• Assign clear roles and responsibilities.
• Invest in contextual upskilling.
• Automate infrastructure and deployments.
• Track cost and value.
• Certify and govern data proactively.
• Treat adoption as a leading signal.