🎙️ Episode #247: Why Cloud Migration Doesn't Automatically Mean Cost Savings

Today we tackle the biggest misconception in enterprise IT: that moving to cloud automatically saves money. Chris from EPI-USE explains why treating cloud like "just another data center" becomes expensive, and how strategic assessment before migration prevents costly surprises.Hosted by Jon Myer → The Jon Myer Podcast | Recorded at AWS re:Invent 2025Key Topics Discussed:✅ Why 20-30% waste is typical (sometimes 60-70% in extreme cases)✅ WHALE Assessment: 2-week timeline, minimal client effort, AWS-funded✅ Real savings: Hundreds of thousands annually (30-40% reductions)✅ On-prem pays for capacity; cloud pays for provisioning—critical shift✅ AMD Epic processors: 11-15% efficiency gains without re-architecting✅ T-shirt sizing mistakes: Developers over-provisioning based on on-prem thinking✅ Finding forgotten NT4 systems and reducing footprint pre-migration✅ Processor flexibility: Last year Intel, this year AMD—change annually✅ Cloud Center of Excellence: Essential for guiding decisions✅ Not "Can it move?" but "When can it move?"—5-10 year strategic roadmapYouTube Timeline:0:00 - Welcome & Introduction1:05 - Why cloud migration doesn't automatically mean savings2:11 - Lift-and-shift requires immediate post-migration plan3:05 - Not everything should migrate (legacy, proprietary systems)3:53 - How much waste exists in pre-migration environments?5:10 - T-shirt sizing mistakes and over-provisioning6:36 - Pre-migration assessment: Reducing footprint before moving7:21 - Finding forgotten NT4 systems (turn it off, see who screams)9:03 - What is the WHALE Assessment?9:49 - Why AWS funds assessments that reduce spend10:40 - Timeline: 2 weeks, minimal client effort11:40 - Real savings: Hundreds of thousands annually (30-40%)12:37 - Optimization without re-architecting applications13:28 - AMD Epic processors: 11% efficiency gains generation-to-generation15:18 - Real-world examples: Switching processor types17:14 - Education gap: People forget about EC2 optimization18:49 - Cloud flexibility: Change processor types monthly if needed19:30 - How to get started with EPI-USE20:27 - Closing thoughts & thank you🔔 Don't forget to Like, Subscribe, and hit the notification 🔔 ✔ Subscribe: https://www.youtube.com/jonmyer/?sub_confirmation=1📱 Social Media Twitter: https://twitter.com/_JonMyerWebsite: https://jonmyer.comLinkedIN: https://www.linkedin.com/in/jon-myer/Spotify: https://open.spotify.com/show/0wjJzdIwctq4o4pTXM2KSFLike my sounds? Here's my audio source: https://www.epidemicsound.com/referral/fj9o9k#aws #awscloud #podcast #podcasting #costoptimization #finops #cloudcost #cloudoptimization

Denne episoden er hentet fra en åpen RSS-feed og er ikke publisert av Podme. Den kan derfor inneholde annonser.

Episoder(274)

HIMSS26 Ep#6 Technology Is Not a Governance Problem It Is a People Problem

Community health centers see one in seven Americans — and one in three in rural communities. Yet they operate with tight budgets, fragmented data, a growing shortage of providers, and the same cyberse...

27 Apr 23min

Ingram Micro Ep#13 Why Being Behind on Health IT Might Be Rural Health's Biggest Advantage

Rural health systems are underfunded, understaffed, and buried in fax machines. Meanwhile, large insurance payers are using automation and AI to deny claims faster than ever — and rural providers ofte...

20 Apr 19min

Ep#249 How leaders need to rethink their approach to AI altogether

Everyone is asking "can AI do this?" But that's the wrong question. The right questions are: does it have the right knowledge, the right tools, and clear enough instructions to do the job? And is your...

13 Apr 34min

Ep#12 Why Healthcare Data Migrations Get Stuck and How to Actually Finish One

Data migrations in healthcare have a reputation — difficult, delayed, expensive, and sometimes never fully completed. Years after an EHR go-live, organizations are still running legacy support contrac...

10 Apr 10min

Ingram Micro Ep#11 How a Major Health System Is Actually Delivering on the Promise of AI

Technology is changing every few weeks in healthcare — and health system leaders are expected to keep up, upskill their entire workforce, govern AI responsibly, and still deliver measurable outcomes. ...

9 Apr 24min

Ingram Micro HIMSS Ep#10 Why One Unpatched Device Is All It Takes to Bring Down a Hospital

A modern hospital can have 40,000 endpoints — laptops, lab stations, nursing workstations, medical IoT devices — and a razor-thin IT team responsible for keeping every single one of them patched, comp...

7 Apr 11min

HIMSS26 Ep#4 From Press 1 to Press Nothing - How Conversational AI Is Transforming the Healthcare

Healthcare call centers are still growing — even as patient portals improve. Patients call to confirm appointments they already know about, reschedule across multiple departments, and check on billing...

7 Apr 16min

Ingram Micro HIMSS Ep#9 How Vision AI Is Making Hospitals Safer Smarter and More Efficient

Hospitals want to be safe and open at the same time — welcoming to patients, families, and staff, but protected from weapons, wandering patients, drug diversion, and operational waste. That's exactly ...

7 Apr 41min