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08 of nine practices

Digital Transformation and Cloud Migration

Move on-premises data and applications to Azure, AWS, or Google Cloud, then tune them.

What's included

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A quiet server room opening toward bright daylight

Digital Qubits moves on-premises data and applications to Azure, AWS, or Google Cloud, then tunes them. Some workloads can move as they are. Others are worth redesigning for cloud storage and processing. We decide that after an inventory, not from a slogan about transformation. The move is phased, checked against the source, and supported after cutover.

A migration that starts with a tool and a date usually stalls on something nobody listed. We begin with an inventory of data sources, pipelines, reports, and the applications that depend on them. Each item is ranked by the value of moving it and by how hard the move will be. The first wave should be important enough to matter and small enough to finish. A finished wave teaches more than a program plan that tries to move the estate at once.

The approach is chosen workload by workload. A direct move is right when the application is stable and the goal is to leave a data center. A redesign is right when the current shape will be expensive or fragile on cloud storage and processing. We say which is which, and what the redesign would change. Orchestration, streaming, and batch processing are part of that choice when the workload needs them. They are not added because they are available.

The foundation comes before the first production workload. Networking, access controls, monitoring, and cost tracking are in place so the landing zone is something you can operate. A workload that arrives before those exist becomes the exception everyone is afraid to touch. We would rather delay a wave than arrive without a way to see cost, failure, and who can reach the data.

Each wave is validated. Row counts and key totals are reconciled against the source before anyone is asked to trust the new platform. Differences are explained, not averaged away. After cutover we tune performance and cost, retire the old path when the business has actually switched, and only then add the next capability. Retiring the old system is a dated decision, not a hope.

Digital Qubits can own the migration or add engineers to a program you are running. Tell us what still sits on premises and which report or application has to survive the move unchanged. We reply within one business day.

// What's included

Decided workload by workload.

  • 01An inventory of data sources, pipelines, and reports
  • 02A choice, workload by workload, between a direct move and a redesign
  • 03Networking, access controls, monitoring, and cost tracking
  • 04Migration in waves, with row counts and key totals checked against the source
  • 05Performance tuning after cutover, and a plan for retiring the old system

// How the work runs

From the first conversation through support.

When we deliver the work, every engagement follows the same path.

  1. 01

    Gather requirements

    We start by listening: goals, constraints, the systems you have, and what a useful result looks like.

  2. 02

    Design and prototype

    We shape the approach early and prototype so the trade-offs are visible before the full build.

  3. 03

    Build

    Hands-on engineers do the work in short iterations, with you close to the decisions.

  4. 04

    Test

    Requirements are tested against real user expectations early, not only at the end.

  5. 05

    Deploy

    We plan the cutover, train the people who will use what we built, and go live with a checklist.

  6. 06

    Support

    After go-live you still work with the people who did the work, for questions and stabilization.

// Related practices

Often paired with this work.