Ever been shocked by your cloud bill?

Despite having monitoring and cost tracking in place, we found ourselves in a situation where cloud costs kept creeping up — slowly at first, then all at once. Before we knew it, we were spending significantly more than expected.

This article is a continuation of Optimize Your Cloud Infrastructure Costs: It’s Never Too Early or Too Late, where I shared a high-level strategy for cost reduction. But as many teams discover, cost reduction is just one part of the equation — the real challenge is maintaining those savings without blocking innovation or slowing down the business.

In this follow-up, I’ll walk through the challenges we faced, the roadblocks that threatened cost control, and the strategies we implemented to ensure long-term cost governance.

Cost Optimization is Not a One-Time Fix

While initial cost-cutting efforts delivered immediate savings, we quickly realized that costs don’t stay down on their own. Without a structured management plan, cost reductions can easily be undone by new feature deployments, scaling inefficiencies, or a lack of awareness across teams.

To prevent this from happening, we needed to shift from one-time optimizations to continuous cost management — ensuring that every new decision considered cost efficiency from the start.

Challenges We Faced in Cost Optimization & Governance

1. New Feature Additions and Expansions

Organizations must scale with demand, and this often means deploying new infrastructure. While cost-conscious engineers may fear rising expenses, resisting expansion isn’t the answer. Instead, the goal should be to align growth with cost efficiency.

Solution:
➡️ Introduce auto-scaling, right-sizing, and demand-driven provisioning to prevent unnecessary over-provisioning.
➡️ Ensure development teams have cost visibility, so infrastructure choices are made with budget impact in mind.

2. Unplanned Weekend & Off-Hours Usage

As I highlighted in my previous article, lower environments don’t need to run 24/7. But sometimes, urgent releases or customer fixes require infrastructure to be active outside business hours, leading to unexpected cost spikes.

Solution:
➡️ Implement automated scale-down pipelines with manual overrides for urgent requirements.
➡️ Hold developers accountable for turning off environments once their work is done.
➡️ Monitor unplanned usage trends if usage is consistently high, consider a dedicated, optimized setup rather than relying on ad-hoc activations.

3. Migrations & Transition Costs

Every feature migration comes with a transition phase, where both old and new deployments run in parallel. If not tightly managed, this period can drag on for weeks or months, doubling infrastructure costs unnecessarily.

Solution:
➡️ Define clear ETAs for migration cutovers and set deadlines for retiring old deployments.
➡️ Have a checklist to ensure nothing is left running post-migration.

4. Unwanted Logs Driving Up Costs

One of the biggest and often overlooked contributors to cloud costs is excessive log generation, especially INFO and DEBUG logs containing payload details.

A single unnecessary INFO log in dev might seem harmless but in a production environment with thousands of requests per day, it could mean thousands of dollars wasted in log ingestion, storage, and analysis costs.

Solution:
➡️ Set log thresholds & alerts to detect excessive logging early.
➡️ Audit log volumes per environment regularly to ensure teams aren’t over-logging.

5. Unexpected Cost Spikes from Errors & Bugs

We once had a minor bug that caused redundant error logs, leading to an extra $350 cost in a single day. If we hadn’t caught it early, it could have cost tens of thousands of dollars over a few months.

Solution:
➡️ Implement anomaly detection for log surges.
➡️ Ensure logging includes relevant metadata so debugging is efficient without excessive verbosity.

6. Stale Resources & Forgotten Data

Teams often delay deleting old resources after a migration “just in case” — but these quickly add up to unnecessary expenses.

Solution:
➡️ Conduct periodic stale resource audits.
➡️ Set expiration policies for temporary infrastructure (e.g., PoCs, test environments).
➡️ Require justifications for keeping legacy resources active.

7. Organic Growth vs. Unexpected Cost Spikes

Not all cost increases are bad. Some indicate organic product growth or seasonal spikes, while others expose wasteful spending. The key is differentiating between them.

Solution:
➡️ Regularly track cost trends against user growth and business revenue.
➡️ Correlate infrastructure spend with customer adoption metrics.
➡️ Ensure cost spikes align with real, expected usage increases.

8. Unoptimized Reservations

Many engineers assume that once infrastructure is decommissioned, costs automatically go down. However, we realized that reserved instances and savings plans continued to incur charges, even for deleted resources.

Solution:
➡️ Review reservation commitments after decommissioning resources.
➡️ Return or exchange unused commitments whenever possible.
➡️ Align reservations with actual long-term needs, not just short-term capacity.

9. POCs Running Indefinitely

Some customer or feature POC environments remained active for months, even when customers or developers weren’t actively testing.

Solution:
➡️ Set expiration periods for customer PoCs.
➡️ Confirm active engagement before extending infrastructure usage.
➡️ Automate shutdown for inactive/expired PoCs.

10. Cost Reduction Offset by Another Cost Increase

A major challenge was that cost savings in one area were often canceled out by cost increases elsewhere.

For example:
- We decommissioned a feature, expecting lower costs.
- However, an error log surge increased log ingestion costs, canceling out savings.

Solution:
➡️ Monitor cost reductions across services to ensure that savings aren’t being offset elsewhere.
➡️ Conduct cost variance analysis to track how different cost components interact.

How We Built a Continuous Cost Management Strategy

1. Thorough Cost Analysis and Goal Setting

Before making any changes, we conducted a detailed evaluation to identify the high-impact optimization areas. Followed strategies discussed in my previous article to reduce the costs.

Next, set measurable cost reduction targets:

• Reduce cost by X% by the end of the month.
• Bring costs down to Y within two months.
• Maintain total cost below Z after initial optimizations.

Cost reductions aren’t just about one-time savings; they require ongoing management to prevent creeping costs from reversing progress.

2. Daily Cost Diff Analysis & Insights

Tracking daily cost differences helps detect unexpected increases early and allows teams to act before costs spiral out of control.

🔹 How we did it:

➡️ We implemented daily cost tracking at the subscription/account level to highlight cost fluctuations.

➡️ Automated platform insights reports such as:

• Error log surges
• Increased debug/info log volumes
• VM or Kubernetes node scale-ups
• Log ingestion trends and traffic spikes

➡️ Identified the justifications for differences in Cost based on the platform insights.

3. Weekly Cost Reviews: Driving Awareness & Action

With daily cost tracking in place, our weekly reviews focused on:

➡️ Confirming cost trends and discussing any unexpected increases.

➡️ Reviewing actions taken to address cost spikes.

➡️ Brainstorming new cost reduction opportunities.

➡️ Discussing long-term strategies for sustainable cost savings.

These meetings enhanced cost awareness across the team, encouraged ownership, and ensured faster response times to emerging cost issues.

4. Monthly Leadership Reviews for Strategic Planning

Our most strategic cost discussions happened in monthly meetings with product, SRE, and engineering leadership members. These reviews provided:

➡️ A detailed breakdown of cost fluctuations over the past month.

➡️ Root causes of major cost changes.

➡️ Discussion of strategic actions such as:

• Architectural changes required for optimizing costs
• Unwanted Feature decommissioning
• Migrations to cost-effective infrastructure
• Adjusting reservations or commitments

This meeting is essential for cost optimization. These meetings ensured leadership level awareness and alignment on cost-saving priorities.

Final Thoughts

Reducing cloud costs isn’t just about one-time optimizations — it’s about building a culture of cost awareness and governance that keeps expenses under control without slowing innovation. Our journey to a 33% cost reduction highlighted a critical truth: cost savings don’t sustain themselves unless there’s continuous monitoring, proactive adjustments, and accountability across teams.

📌 Key Takeaways:

✅ Cloud cost management is a shared responsibility — whether you’re an SRE, DevOps engineer, or developer, cost efficiency should be part of decision-making at every level.

✅ Awareness is key — teams need visibility into infrastructure costs so they can make informed choices that align with business objectives.

✅ Cost governance is ongoing — reducing costs is not a one-time fix but a continuous process that requires regular reviews, automation, and strategic alignment with leadership.

✅ Every cost increase needs a justification — by tracking trends, understanding where increases come from, and acting before they escalate, businesses can prevent unnecessary expenses while supporting growth.

By embracing a structured cost governance approach, continuously monitoring cost trends, and integrating cost-efficiency into engineering workflows, organizations can significantly cut cloud expenses without sacrificing performance or scalability.