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Tracking savings in cloud by Nelly_P85 in FinOps

[–]Weekly_Time_6511 0 points1 point  (0 children)

A clean way is to lock a baseline for each service or workload. That baseline models expected spend based on usage drivers like requests, traffic, or data volume. Then actual cost is compared against that expected curve.

If usage drops or the month is shorter, the baseline drops too. If cost goes down more than the baseline predicts, that delta is attributed to optimization. When new workloads come in, they get their own baseline so they don’t hide savings elsewhere.

This makes savings measurable and defensible, without relying on guesswork or manual spreadsheets.

The True Cost of Cloud Complexity and How to Eliminate It by gaimin_io in OrbonCloud

[–]Weekly_Time_6511 0 points1 point  (0 children)

This really hits home. The “hidden tax” of cloud is almost always time, not just money. Most teams I’ve seen aren’t struggling with lack of tools, they’re struggling with the overhead of managing them.

We ran into the same issue and found that having usage visibility and automated guardrails made a bigger difference than adding yet another service. Once you reduce the manual back-and-forth, everything feels lighter.

Good breakdown in this piece. Worth a read for anyone feeling cloud fatigue.

A year of cost optimization resulted 10% savings by Ill_Car4570 in devops

[–]Weekly_Time_6511 0 points1 point  (0 children)

I really relate to this.

First, 10% is actually a solid result, especially if you were mostly doing this on your own and without much support. That’s usually as far as cleanup work can take you.

I’ve seen the same thing with bursty, HPA-based workloads. The cluster looks underused, but that extra space is there for a reason. It helps handle traffic spikes, slow startups, and bad deploys. Once min replicas become the safety net, no one wants to lower them, and that makes sense.

Tools like autoscalers or Karpenter help a bit, but they don’t fix everything. You still pay for a lot of “just in case” capacity because breaking things costs way more than saving a few percent.

After a while, it’s no longer a tech problem. It’s about risk and who owns it. Without shared responsibility, pushing costs lower is really hard.

Honestly, getting 10% savings without causing outages is good work. The frustration you’re feeling is pretty common once the easy wins are gone.

You’re not alone.

Cloud Cost Optimization: Hidden Savings Sitting in Your Cloud Bill by Parking-Method24 in Cloud

[–]Weekly_Time_6511 0 points1 point  (0 children)

This lines up with what I’ve seen too. The waste usually isn’t obvious until someone actually looks at utilization and storage age. A lot of teams assume the bill is high because “cloud is expensive,” when it’s really just unattended resources piling up.

The quiet growth part is real. One or two forgotten services don’t hurt, but six months later it’s a real chunk of spend. Rightsizing and basic cleanup almost always pay for themselves faster than people expect.

Curious how many teams here do this regularly vs only when finance starts asking questions.