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AWS Trusted Advisor + PointFive are better together.

FinOps teams already rely on AWS Trusted Advisor for checks and visibility. In this AWS + PointFive session, Taylor Houck and Manas Satpathi show what comes next on the FinOps maturity curve: turning checks into owned, prioritized, remediated savings with AI Prompt Remediation, which turns findings into fixes engineers run in minutes.

Visit PointFive at booth #361 to learn more or schedule a meeting with our team at the link below.

Meet PointFive at AWS re:Invent - December 1- 5

Pre book a meeting or stop by booth #361

Watch the full webinar with AWS Trusted Advisor and PointFive

The US federal government is losing hundreds of millions of dollars every year because of outdated rules about buying cloud services.

Here's the problem in plain terms: The government has old laws that say you can't pay for services before you get them, and you can't commit to buying things for multiple years ahead.

Cloud companies like Amazon Web Services, Microsoft, and Google give big discounts to customers who pay upfront or commit to using their services for several years. But the government can't take advantage of these deals because of two old laws: the Advance Payments Act and the Anti-Deficiency Act.

Right now, agencies have two bad options:

The government spends about $16 billion each year on cloud services. If Congress changed the rules to allow multi-year cloud contracts, even a 10% savings would put $1.6 billion back in the budget. The actual savings could be much higher.

The U.S. government is the world's biggest technology buyer, yet it's the only one that can't get volume discounts because of its own rules.

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CFM Tips MCP Server transforms cost data into an AI assistant. This GitHub tool integrates with Amazon Q CLI for conversational cost optimization with a lot of services available.

Compute Optimizer automation rules enable scheduled optimization at scale. Automatically apply recommendations like EBS cleanup by tag or region with rollback options, reducing manual workload for routine cost reductions.

NAT Gateway recommendations identify unused resources. Compute Optimizer analyzes 32 days of CloudWatch metrics to flag idle gateways and show potential savings, available in all regions except GovCloud and China.

Transit Gateway cost allocation and Network Firewall metering policies enable accurate charge distribution at attachment or flow level, simplifying internal chargeback without manual billing work.

And many more, pre re:Invent AWS Teams go crazy with updates!

Read All AWS Updates

Custom handlers in Azure Functions Flex (GA) enable any language support. Use Go, Rust, or Deno with lightweight web servers while maintaining triggers and bindings, eliminating custom bridging code for better developer flexibility.

Read All Azure Updates

Reservation consumption visibility in Compute Engine and BigQuery billing exports improves cost transparency. New labels show actual reserved capacity usage, enabling accurate chargeback and better reservation planning across projects.

GKE fast-starting nodes (GA) reduce over-provisioning for Autopilot clusters. Quick node provisioning for short-lived jobs lowers idle capacity needs and TCO for bursty workloads.

Incremental Salesforce transfers to BigQuery (Preview) move only changed data, cutting transfer volume and ingestion costs for large datasets.

Read All GCP Updates

Your cloud bill is probably a mess right now, and it's not because you don't know what to do. It's because you keep falling into the same traps everyone else does.

The "We'll Fix It Later" Trap: Your team is rushing to migrate to the cloud. Deadlines are tight. So you lift and shift everything as-is, planning to optimize later. What was supposed to be temporary becomes permanent.

The "No One Knows Who Owns This" Problem: A developer spins up a test environment. No one adds tags. Weeks pass. Then someone notices a cost spike. No one remembers what it's for.

The "Alert Goes Nowhere" Issue: You set up cost alerts. The system sends emails when spending crosses a threshold. Everything seems fine. Alerts without ownership are just noise. They don't create action. They create fatigue.

The "End of Quarter Panic Buy" Mistake: The budget period is ending. Money is left over. Someone suggests buying three-year reserved instances to lock in savings and look smart to finance. Buying reservations in a rush is like buying a three-year gym membership on New Year's Eve because you feel guilty.

You don't need a perfect FinOps program. You just need to stop doing these four things that quietly sabotage your cost control.

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Know about how Anderson Oliveira got into FinOps and how he become a FinOps X speaker and book author. Learn with Anderson at FinOps Weekly Learn (with BLACKFRIDAY discount)

AWS just made a quiet change that could reshape how we pay for cloud services. They launched flat-rate bundles for CloudFront that include security, edge delivery, and protection services for one monthly price with no surprise charges.

This sounds small, but it might be the start of something much bigger.

If AWS expands this model to more services, your job changes significantly. Forecasting becomes about picking the right tier instead of predicting usage curves. Budgets become stable and predictable.

The Mobile Phone Comparison: Think about how mobile plans evolved. In the 1990s, you paid for every minute and every text message. Today, you pick a tier and stop thinking about it. AWS might be testing the same model for cloud services.

Impact on Moving Workloads Back On-Premises: One major reason companies move workloads back to their own data centers is predictability, not just raw cost. If AWS extends flat-rate bundles to compute and data services, that calculation changes. You could get the predictability of on-premises infrastructure without the capital expense and labor.

This small pricing experiment at the edge might be the first step toward cloud services that feel simple and predictable again, more like choosing a phone plan than managing a complex utility bill.

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Building your own FinOps tool feels great at first. You get dashboards running, your team celebrates, and leadership finally understands the cloud bill.

But then reality hits.

The problem starts small. Your simple dashboard grows into something much bigger. New cloud services launch. Pricing models change. APIs get updated. Each change needs someone to fix your tool.

The person who built it moves to another team. Documentation is thin. New engineers can't figure out how it works. Meanwhile, feature requests pile up faster than anyone can handle them. Here's the real cost that sneaks up on teams:

Your engineers spend time maintaining dashboards instead of building products that make money.

Hosting costs climb as more people use the tool. The tool becomes critical infrastructure but has no dedicated team to support it.

The article introduces a simple way to think about this. Early on, the value you get from your DIY tool goes up fast while costs stay low. But over time, value flattens out while costs keep climbing. Eventually the lines cross — that's when your DIY tool stops being worth it.

The author compares this to a hangover. The fun part is over. Now you're dealing with the consequences and trying to figure out what to do next.

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A research paper from IBM's Apptio team shows that most companies struggle with FinOps because they try to do everything at once.

This research looked at three years of real company data and found something useful. Companies that group related FinOps work into clusters get better results faster.

Here's what clustering means. Instead of jumping between different tasks, you focus on a small group of related activities that all point toward one business goal. You finish that cluster, show results, then move to the next one.The research found five common paths companies take:

Self-Fund Path: You need quick wins to prove FinOps is worth the money. Focus on rate deals, turning off unused stuff, and catching spending spikes. Goal is to save enough money in six months to pay for the FinOps team itself.

Visibility Path: You don't know who is spending what. Start with getting data in one place, tagging costs to teams, and building reports. Once you can see the spending, you can decide what to do about it.

Migration Path: You already do FinOps but you're switching tools. Just move your existing work to the new platform and keep things running.

Consultation Path: You want expert advice on what to do but your team will do the actual work.

Federated Path: Your company has many divisions. Central team provides tools and training. Each division runs their own FinOps work.

The research also found some newer patterns. Some companies focus on control first because they had a scary bill surprise. Others start with sustainability because investors or customers care about environmental impact.

This research gives FinOps teams something they've needed for a long time. A map that shows different routes to the same destination, so you can pick the one that fits your situation.

FinOps Expert from the Early Days

Dieter is one of the most well-known figures in the space. With work at Roku, Google and Netflix among other, he shared his knowledge in our podcast and summit!

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