smartspend.cloud
Case Study

How ylytic.com Saved ~$2,500/month on Azure

A comprehensive cloud optimization project that reduced monthly spending by 50% without disrupting operations.

$5,000
Monthly Spend Before
$2,500
Monthly Spend After
$2,500
Monthly Savings
50%
Cost Reduction

About ylytic.com

ylytic.com is a seed-funded influencer marketing AI startup that provides influencer discovery, real-time analytics and reporting. As a growing company, they needed to optimize their cloud infrastructure costs while maintaining performance for their AI workloads.

Seed-funded AI startup
Heavy compute requirements
Growing customer base
Challenge

Rising cloud costs for DB and VMs were creating huge cloud bills on AWS/Azure. They needed immediate cost reduction as their startup credits on Azure were about to expire, without which the monthly profits would be affected.

Optimization Strategy

VM Resources Optimization
Right-sizing and optimizing virtual machine instances

What We Did:

  • Analyzed CPU and memory utilization patterns across all VMs
  • Right-sized over-provisioned instances to match actual usage
  • Implemented auto-scaling for variable workloads
  • Added swap memory to instances to prevent crashes for smaller spike loads

Results:

$500/month saved
20% reduction in compute costs
Cosmos MongoDB Optimization
Database performance tuning and cost optimization

What We Did:

  • Combined the different DBs into broadly 3 categories, reducing the per DB server cost
  • Implemented efficient indexing strategies for analyzing the log queries
  • Moved some of them out of Geo Redudancy which is adding to twice the cost
  • Moved performance critical workloads to MongoDB Atlas

Results:

$1500/month saved
60% reduction in database costs
GPU Infrastructure Migration
Optimized AI server infrastructure for better performance and cost

What We Did:

  • Migrated AI workloads to cost-effective GPU instances
  • Optimized model serving with efficient instance types by moving from 3 8vCPU/32GB VMs to 2 4vGPU/28GB instances

Results:

$500/month saved
20% reduction in AI infrastructure costs

Implementation Timeline

1

Week 1-2: Analysis & Planning

Comprehensive audit of existing infrastructure and cost analysis

2

Week 3-4: Quick Wins Implementation

VM right-sizing and database optimization for immediate savings

3

Week 5-8: Database & GPU Migration

Careful migration of AI workloads to optimized GPU infrastructure and combining serveral DB instances

4

Week 9-12: Monitoring & Fine-tuning

Performance monitoring and additional optimizations

"The optimization process was seamless and didn't disrupt our operations. We saw savings in the first few months itself. The detailed analysis helped us understand exactly where our money was going, and the phased approach meant we could validate each change before moving to the next. Highly recommend for any startup looking to optimize their cloud spend."
Kartikey Yadav, CEO, ylytic.com
Influencer Marketing AI Startup

Ready to Achieve Similar Results?

Get a free consultation to see how much your startup could save with proven cloud optimization strategies.

Built with v0