Growth and ROI: How a tech company managed to reduce cost and keep momentum

Scaling a startup is not easy: one minute you're celebrating your first hundred users, the next you're grappling with the chaos of rapid growth. But as we learned firsthand, rapid scaling can come with a hidden cost: ballooning cloud expenses.

Like many startups, initially the priority was speed over cost optimization.

When our AWS bill sky rocketed, they knew something had to change.

Through a series of infrastructure optimizations not only they significantly reduced their AWS costs but also improved performance. Here's a peek into the journey:

1. Nginx Microcaching: A Small Change, Big Impact

The origin servers were working overtime, handling a deluge of requests. By implementing Nginx microcaching, caching responses for a mere 1-2 seconds. This seemingly minor tweak slashed our origin server load by a staggering 70%. The result? A 35% reduction in EC2 instance costs, without sacrificing real-time data accuracy.

Lesson Learned: Don't underestimate the power of caching. Even a short cache duration can dramatically reduce server load and costs.

2. S3 Gateway Endpoints: Bypassing the NAT Gateway Bottleneck

The private subnet resources frequently accessed S3, leading to hefty NAT gateway data transfer fees. S3 gateway endpoints have been implemented, allowing direct access to S3 through the AWS network backbone. This simple change eliminated ~$0.045/GB in data transfer costs, saving us thousands of dollars monthly.

Lesson Learned: Understanding the nuances of AWS networking can lead to significant cost savings. Look for opportunities to optimize data transfer paths.

3. GitHub Actions: Ditching Self-Hosted CI

The self-hosted CI infrastructure, with dedicated build servers running 24/7, was a major cost driver. As a result the migration to GitHub Actions, a serverless CI/CD solution, reduced CI/CD compute costs by 80% while significantly improving build times.

Lesson Learned: Leverage managed services whenever possible. They often provide better performance and cost-effectiveness than self-managed solutions.

4. Athena-Powered Analytics: Serverless Data Warehousing

The traditional data warehouse solution was expensive and required constant maintenance. It was required to build a cost-effective data warehouse using AWS Athena to query optimized Parquet log files directly in S3. This serverless approach eliminated the need for expensive always-on database instances, resulting in an 80% cost reduction compared to the previous solution.

Lesson Learned: Embrace serverless technologies for data analytics. They offer pay-per-query pricing, eliminating the need for upfront infrastructure investments.

The FinOps Journey: It's Never Truly Over

These optimizations significantly reduced cloud expenses and improved the infrastructure's efficiency. But we know that FinOps is an ongoing process.

Keep monitoring spending, identify areas for further optimization, and explore new cost-saving strategies.