Industry

Enterprise

Technology transformation at scale

I help enterprises modernize their technology stack and build new digital capabilities. From legacy modernization to digital transformation, I bring startup velocity to enterprise scale.

At a glance
Regulations
5 frameworks
KPIs tracked
6 core metrics
Reference stacks
5 patterns
Services
4 engagements
Case studies
0 published
Perspective

How I think about enterprise

The architecture, the trade-offs, and where I push back on conventional wisdom.

Enterprise transformation is rarely a technology problem and almost always an organizational one. The COBOL still works. The mainframe is still cheaper than its replacement on paper. The 800-line stored procedure has tribal knowledge embedded in it that nobody documented. My consulting in this space starts by accepting these realities - you cannot rewrite the core, you have to migrate around it, and you have to do it without breaking the thing that pays for the migration.

The strangler fig pattern is still the right answer most of the time. Identify a bounded context, build a modern service alongside, route traffic incrementally through a façade, and decommission the legacy module when traffic reaches zero. I design these migrations with explicit dual-write windows, shadow-read validation, and rollback gates at every step. Zero-downtime migration is the standard, not a nice-to-have, because the business cannot pause while IT modernizes.

Identity is the foundation everything else stands on. SAML 2.0 and OIDC for human auth, OAuth 2.1 for service-to-service, SCIM for provisioning, mTLS for backend trust. I help enterprises consolidate around a single identity provider - Okta, Entra ID (formerly Azure AD), or Ping - and build the federation primitives that let new SaaS tools onboard in days rather than quarters. JIT provisioning, group-mapped RBAC, and centralized audit logs are table stakes.

Cloud strategy in the enterprise is rarely "lift and shift" anymore. It's a hybrid story - workloads that belong on-prem for data gravity or regulatory reasons, workloads that move to managed services for elasticity, and a control plane that spans both. I architect around Kubernetes as the portability layer, Terraform for multi-cloud IaC, and a clear FinOps practice so the bill doesn't become a board-level surprise. Cloud infrastructure done right is a margin lever, not a cost center.

The hardest part of enterprise work is engineering org design. Conway's Law is real - your software architecture will mirror your communication structure whether you want it to or not. I coach leadership teams on platform-vs-product team boundaries, the right level of decentralization, and how to introduce internal developer platforms that accelerate teams without imposing top-down dogma. See an enterprise modernization story or book time to scope a transformation.

Challenges

What teams struggle with

The recurring problems I see on enterprise engagements.

  • 1Legacy system modernization
  • 2Enterprise integration requirements
  • 3Compliance and governance
  • 4Change management and adoption
  • 5Vendor and technology consolidation
How I help

Capabilities I bring

Concrete engineering work that resolves the challenges on the left.

  • Legacy system modernization strategy
  • Enterprise architecture design
  • SSO and identity management
  • Compliance automation
  • Digital transformation roadmapping
Metrics

What teams measure

The KPIs leadership obsesses over in this sector. Most tie back to performance and architecture decisions made years before the dashboard was built.

01

DORA metrics

Deployment frequency, lead time for changes, change failure rate, MTTR - the canonical engineering health quad.

02

Cost-to-serve

Infrastructure + platform spend per business transaction; the FinOps North Star.

03

Audit findings closure rate

How quickly identified control gaps are remediated; a quarterly board metric.

04

License consolidation savings

Vendor rationalization wins - usually 15-30% over a 24-month consolidation cycle.

05

Mean time to onboard a new SaaS

Procurement + security + integration cycle time; reflects identity and integration maturity.

06

Internal developer NPS

Platform team's customer satisfaction; correlates with retention and shipping velocity.

Reference stacks

Stacks I see most often

Patterns I reach for first when scoping a enterpriseengagement. I don't pick technologies for novelty - read more about how I choose.

1

Kubernetes (EKS/AKS/GKE) + Terraform + Argo CD on a shared platform team

2

Okta or Entra ID for IdP, with SCIM-driven provisioning into every downstream system

3

Snowflake or Databricks data platform with Collibra/Alation governance

4

ServiceNow for ITSM, integrated with Slack/Teams via custom workflow apps

5

Datadog or Splunk for observability, Wiz or Prisma Cloud for CSPM

Technologies

Tools of the trade

The platforms and frameworks I lean on for enterprise work.

Building for Enterprise?

Let's discuss your specific challenges and how technology can help you ship safely, sleep well, and keep regulators happy.

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