Azure Services

Azure is broad enough that the platform is rarely the constraint. What decides whether a migration lands is the order things are done in: identity, network and guardrails before workloads, and a per-application decision about what deserves rewriting instead of a blanket lift and shift.

Iseyon designs the landing zone, moves the workloads, builds the data platform on top, and hands the environment to the team that will operate it.

Foundation and migration

Landing zone first

We set up management groups, subscriptions, network topology, identity and policy before the first workload arrives, so naming, tagging, segmentation and guardrails are properties of the environment rather than decisions each project makes for itself. The landing zone is defined as code, so a new subscription inherits the same controls instead of starting empty.

Migration approach

We start from a dependency map rather than a server list, because the thing that breaks a cutover is usually an integration nobody documented. Applications are grouped into waves, and each one gets its own decision: rehost where the workload is fine as it is, replatform onto managed database or app services where operations are the real cost, re-architect where the application itself is the constraint, and retire what nobody uses. Every wave has a tested rollback, and cutovers are rehearsed before they are performed.

Compute, storage and networking

We build with the core services chosen for the workload rather than for uniformity: virtual machines and scale sets, App Service or containers, managed disks and Blob Storage, virtual networks with private endpoints, and load balancing. Availability zone strategy, backup, and recovery time and recovery point targets are agreed with the business before the design is fixed, then tested rather than assumed.

Data platform

Data engineering

We build ingestion and transformation with Azure Data Factory, Databricks or Fabric pipelines onto Data Lake Storage, in layers: raw landing, a cleaned and conformed layer, and models published for consumption. Pipelines are parameterized and incremental, so adding a source is a configuration change rather than another copy of the same pipeline.

Business intelligence

We connect Power BI to governed models instead of to raw tables, so a KPI has one definition and access rules live in one place. Refresh schedules and gateway paths are designed together with the data pipelines, not bolted on afterwards.

Machine learning

We use Azure Machine Learning for the parts of the lifecycle that need discipline: versioned data and models, reproducible training, and deployment with monitoring for drift and cost. Anything we put into production has an owner and a rollback path.

Security, governance and operations

Identity and access

We build on Microsoft Entra ID with role-based access, groups rather than named individuals, conditional access, and managed identities so applications stop holding credentials. Secrets go into Key Vault, and access reviews are set up as a recurring process with an owner.

Governance and compliance

Azure Policy, resource tagging and diagnostic settings are applied from the landing zone, so configuration drift is detected rather than discovered. Defender for Cloud and Log Analytics give one place to see posture and produce evidence, which is what an audit actually asks for.

Cost management

We tag for chargeback, set budgets and alerts per subscription, rightsize after observing real load, and apply reservations or savings plans only where usage has proven steady. The client is left with cost reporting they can read by team and by application.

DevOps and automation

Infrastructure ships as code through Azure DevOps or GitHub Actions, with environment promotion, approvals, and the same pipeline for every environment. Nothing that matters gets configured by hand in the portal.

Integration and modernization

We integrate Azure with the systems that stay: on-premises databases, third party SaaS, and line of business applications, using API Management, Service Bus and Event Grid where messaging beats point-to-point coupling. Sequencing keeps the business running while the estate changes underneath it.

What we hand over

We build so the client's own team can run it. Where Iseyon stays involved afterwards, it should be a choice rather than the consequence of nobody else knowing how the environment works.