Finding the next deal
while running the current one

A pending hardware refresh on a $23M annual IT budget gave us the opening. The CFO needed a defensible number before committing to any direction. We ran the CRA, built an AWS vs. Azure vs. multi-cloud financial model with 5-year projections, and handed leadership a board-ready business case. AWS came out $21M ahead over 5 years. The migration execution SOW followed.

The client had 759 apps and 149 servers on aging on-premises infrastructure and needed to pick a cloud. We ran the full platform comparison — AWS, Azure, GCP — with a quantified TCO model at each. GCP won on a combination of pricing and a $3.43M credit package that materially changed the payback math. The CRA produced the platform decision and migration roadmap.

4 global data centers, 1,052 servers, a lease clock ticking on at least two of them. The client knew they needed to exit on-prem but hadn't done the math. We built the full business case: $14.52M average annual cost as-is, dropping to $9M post-migration. AWS EDP + PS credits offset $7.1M of the $2.67M migration cost, bringing net PS spend to ~$1.19M. A clean deck the real estate team could use to accelerate the exit.

Coming out of bankruptcy, the client had made cloud commitments on both Azure and GCP that they were behind on attaining — 24,193 VMs across 13 sites, 120 Azure subscriptions, physical DCs they wanted to exit. This wasn't a clean advisory engagement. It was a mess to sort out. The $651K SOW covered the cloud business case, physical DC audit, landing zone assessment, 6Rs rationalization, and a Cloud Marketplace financial model to start burning down the commits.

A $10B+ healthcare company that acquired a hospital tech subsidiary 4 years earlier and never integrated the Azure environments. We scored both tenants against a 23-category WAF framework — parent at 71.6, the acquired company at 45.1. The gap was the story. Key finding: don't merge yet. HIPAA and GDPR constraints mean a premature merge creates more risk than it solves. Delivered the 24-month remediation and consolidation roadmap.

A top-3 global consulting firm wanted an outside perspective on its own Platform Engineering org. We ran a 12-dimension DevSecOps maturity scorecard across 4 internal platform squads (60–76% range), then ran VSM workshops with 5 product teams to find where the real bottlenecks were. Found that only 7% of their 14 scrum teams were adequately structured for the work they were doing. That's an uncomfortable finding to deliver to a firm that makes its living telling clients how to improve. We delivered it anyway. Cloud transformation scope behind that: $16M–$19M.

The entry point was a TechOps advisory engagement — org and operating model assessment for a 4-team function managing AWS infrastructure with an incumbent MSP alongside it. FinOps analysis identified $700K–$900K in immediate AWS savings, which was more than 6x the cost of the engagement in under 90 days. That result is now the commercial anchor for a $10M+ managed services conversation to displace the incumbent. Still working through 4 VP approvals.

M&A activity created two overlapping needs simultaneously. The acquirer needed technical due diligence on the target's ClickHouse/AWS data platform — Go/No-Go level analysis, four domains, ~$60K. And the target's leadership wanted BCP/DR documentation cleaned up before buyer scrutiny. We submitted both proposals within 3 days of each other. The 13TB MySQL-to-Aurora migration was part of the DR work, not the DD — that's the kind of detail that only surfaces when you're inside both conversations at once.

5-week CRA for a Microsoft-heavy regional bank. 156 servers, 25 application stacks, dual AWS + Azure pricing workbooks. The real question wasn't which cloud — it was whether their Hyper-V private cloud was still viable as an intermediate step, or whether Azure was the only defensible long-term path. We answered both. Also scoped the VMware VDI replacement as a standalone opportunity — Azure Virtual Desktop was the right answer there and gave the account team a second workstream to pursue.

2,600+ VMware VMs plus 26 IBM Power hosts with ~408 LPARs running SAP and Oracle EBS — two very different cloud cost profiles depending on how you model the IBM workloads. We built a dual-cloud financial model (AWS and Azure) with 5-year projections, RI scenarios, and rightsizing. By Year 3 the optimized AWS path was at $2.3M/yr vs. $4.25M as-is. The IBM Power question was the messiest part of the analysis and also the part the client couldn't get from anyone else.

Hadoop analytics migration for the world's largest specialty jewelry retailer. The interesting wrinkle was holiday seasonality — Oct through Feb is a completely different sizing requirement than the rest of the year, so the instance selection and pricing models had to reflect 150 peak days, not average utilization. We built three pricing scenarios. The bigger opportunity we surfaced was $500K+/yr in automation savings from stop/start scheduling on DEV, UAT, and PROD — something the ops team hadn't quantified before.

Cloud-agnostic CRA for a major Las Vegas resort. 1,850 VMs across two VMware DCs, 300 apps, a 100% cloud exit target by 2025. The AS/400 running the hotel management system and gaming floor was the first thing we scoped — two iSeries units across both sites, every other app in the estate had dependencies running through them. You can't sequence a migration without solving the AS/400 question first. We produced dedicated AS/400 upgrade notes and built the wave plan around that critical path. Phase 2 execution is the follow-on.

A provincial workers' compensation agency — hybrid DC + Azure, about 20% migrated at the time. They thought they had a DR plan. When we looked at it, the Azure Canada East landing zone had never actually been built. Estimated RTO was 4–10 weeks. We scored their DR maturity, evaluated three recovery options, and recommended the combination of IBM DB2 HADR, Azure Site Recovery, and a proper landing zone build that gets them to under 3 hours RTO with a 15-minute RPO. Phase 1 was documentation; Phase 2 is the implementation SOW.

60,000+ servers, three North American DCs pending sale, $520M AWS and $1.4B+ GCP cloud commitments behind attainment target. Five months of deep-dive work — Mail (400PB, GCP), Search (AWS), Central Data — focused on what could be moved fast enough to matter for the cloud commit clock. Not every migration is a strategy exercise. Sometimes it's an execution race and the question is just which workloads can move in time to hit an EBITDA target. That's what this was.