> ## Documentation Index
> Fetch the complete documentation index at: https://docs.cloudidr.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Use cases

> How teams use FlexCompute to save 30-40% on AWS infrastructure

FlexCompute works for any workload that runs on AWS EC2—from AI training to production web servers. Here's how different teams use FlexCompute to cut costs while maintaining performance and reliability.

## AI/ML Training & Inference

### LLM Training & Fine-Tuning

**Challenge:** Training large language models on GPU instances (p4, p5) costs thousands per hour. Reserved Instances require 1-3 year commitments, but training needs fluctuate project-by-project.

**Solution:** Use FlexCompute to access p5 instances at 30-40% discount with zero commitment. Spin up capacity when starting a training run, release when complete.

**Example:**

* Instance: 8x p5.48xlarge
* Training duration: 120 hours
* AWS On-Demand cost: \$76,800
* FlexCompute cost: \$51,840
* **Savings: \$24,960 per training run**

**Who uses this:**

* AI research labs
* LLM development teams
* Companies fine-tuning foundation models

***

### Computer Vision Model Development

**Challenge:** Training vision models requires GPU capacity (g5, g6 instances) but workload is inconsistent—intense during active development, idle between projects.

**Solution:** Pay for GPU instances only when training, not 24/7. FlexCompute provides g5/g6 instances at 30-40% discount without Reserved Instance lock-in.

**Example:**

* Instance: 4x g5.12xlarge
* Usage: 10 hours/day, 20 days/month
* AWS On-Demand cost: \$22,000/month
* FlexCompute cost: \$14,300/month
* **Savings: \$7,700/month**

**Who uses this:**

* Autonomous vehicle teams
* Medical imaging startups
* Security/surveillance companies

***

### Real-Time Inference Serving

**Challenge:** Serving LLM or vision model inferences at scale requires always-on GPU capacity, making Reserved Instances attractive—but capacity needs vary with user growth.

**Solution:** Start with FlexCompute instances, scale up as traffic grows, no upfront commitment. Maintain same performance as Reserved Instances at similar pricing but with full flexibility.

**Example:**

* Instance: 6x g6e.2xlarge (24/7)
* AWS On-Demand: \$12,096/month
* AWS Reserved (1yr): \$8,467/month (locked in)
* FlexCompute: \$7,862/month (no lock-in)
* **Savings vs On-Demand: \$4,234/month**
* **Flexibility vs Reserved: Cancel anytime**

**Who uses this:**

* AI API services
* Chatbot platforms
* Real-time recommendation engines

***

### Batch Inference Processing

**Challenge:** Processing large batches of inference requests (e.g., analyzing millions of images overnight) requires massive GPU capacity temporarily.

**Solution:** Spin up 20-50 GPU instances for the batch job, run for a few hours, release capacity. Pay only for hours used at 30-40% discount.

**Example:**

* Instance: 50x g5.xlarge
* Runtime: 6 hours
* AWS On-Demand cost: \$303
* FlexCompute cost: \$195
* **Savings: \$108 per batch job**
* Run 30 batches/month = \$3,240/month savings

**Who uses this:**

* Content moderation platforms
* Document processing services
* Data labeling companies

***

## Development & Testing

### CI/CD Pipeline Infrastructure

**Challenge:** Running comprehensive test suites requires substantial compute capacity, but tests run intermittently throughout the day, not 24/7.

**Solution:** Provision FlexCompute instances for CI/CD runners, scale to match build queue, release capacity during off-hours.

**Example:**

* Instance: 20x c5.4xlarge (running 8 hours/day)
* AWS On-Demand: \$1,835/month
* FlexCompute: \$1,193/month
* **Savings: \$642/month**

**Who uses this:**

* Engineering teams with frequent deployments
* Startups optimizing dev costs
* Companies with large test suites

***

### Staging & QA Environments

**Challenge:** Staging environments mirror production but don't need to run 24/7. Paying full price for environments used only during business hours wastes money.

**Solution:** Run staging on FlexCompute instances, schedule automatic shutdown outside business hours, pay only for uptime at discounted rates.

**Example:**

* Instance: 15x m6i.2xlarge (10 hours/day, weekdays only)
* AWS On-Demand: \$1,152/month
* FlexCompute: \$749/month
* **Savings: \$403/month**

**Who uses this:**

* Product teams with extensive QA needs
* Agencies managing multiple client environments
* SaaS companies with staging requirements

***

### Load Testing Infrastructure

**Challenge:** Load testing production systems requires spinning up hundreds of instances temporarily to simulate user traffic—expensive if using On-Demand rates.

**Solution:** Use FlexCompute to provision load testing infrastructure for hours or days, not months. Pay 30-40% less for the same capacity.

**Example:**

* Instance: 100x c5.2xlarge
* Duration: 8 hours (quarterly load test)
* AWS On-Demand cost: \$272 per test
* FlexCompute cost: \$177 per test
* \*\*Savings: $95 per test** ($380/year)

**Who uses this:**

* E-commerce platforms (pre-Black Friday testing)
* Gaming companies (launch testing)
* FinTech (stress testing)

***

## Batch Processing & Data Workloads

### Data Analytics Pipelines

**Challenge:** Running nightly ETL jobs on large datasets requires compute-optimized or memory-optimized instances, but jobs complete in 2-6 hours—not 24 hours.

**Solution:** Schedule FlexCompute instances to provision before job start, process data, release capacity when complete. No paying for 18+ idle hours daily.

**Example:**

* Instance: 10x c5.9xlarge (4 hours/day)
* AWS On-Demand: \$2,448/month
* FlexCompute: \$1,591/month
* **Savings: \$857/month**

**Who uses this:**

* Data engineering teams
* Business intelligence platforms
* Analytics-heavy SaaS companies

***

### Video Rendering & Transcoding

**Challenge:** Rendering video content requires high-compute instances but demand fluctuates—heavy during project work, idle between clients.

**Solution:** Provision rendering farm with FlexCompute instances on-demand, scale to match project queue, release when queue clears.

**Example:**

* Instance: 30x c6i.8xlarge
* Usage: Variable (15 hours/day average)
* AWS On-Demand: \$12,240/month
* FlexCompute: \$7,956/month
* **Savings: \$4,284/month**

**Who uses this:**

* Video production studios
* Streaming platforms
* Social media content creators

***

### Scientific Computing

**Challenge:** Research simulations require massive compute capacity for days or weeks, but projects are episodic—not continuous.

**Solution:** Access high-performance computing instances through FlexCompute for simulation runs without multi-year commitments.

**Example:**

* Instance: 20x c5.18xlarge
* Duration: 2 weeks per quarter
* AWS On-Demand: \$4,896 per simulation
* FlexCompute: \$3,182 per simulation
* \*\*Savings: $1,714 per simulation** ($6,856/year)

**Who uses this:**

* Research institutions
* Pharmaceutical companies (drug modeling)
* Engineering firms (finite element analysis)

***

## Production Workloads

### Web Application Servers

**Challenge:** Production web servers need high availability but capacity requirements vary with traffic patterns (daily/weekly fluctuations).

**Solution:** Run baseline capacity on FlexCompute instances, scale up during traffic peaks, maintain same reliability as Reserved Instances without commitment.

**Example:**

* Instance: 25x m6i.xlarge (24/7)
* AWS On-Demand: \$4,800/month
* AWS Reserved (1yr): \$3,360/month (locked in)
* FlexCompute: \$3,120/month (no lock-in)
* **Savings vs On-Demand: \$1,680/month**
* **Flexibility vs Reserved: Scale freely**

**Who uses this:**

* SaaS platforms
* E-commerce sites
* API services

***

### Microservices & API Backends

**Challenge:** Microservice architectures run dozens of small-to-medium instances. Reserved Instances make capacity planning difficult as service needs change.

**Solution:** Run all microservices on FlexCompute instances, adjust capacity per service independently, no commitment required.

**Example:**

* Instances: 50 mixed (t3, c5, m6i)
* AWS On-Demand: \$8,500/month
* FlexCompute: \$5,525/month
* **Savings: \$2,975/month**

**Who uses this:**

* Cloud-native applications
* Startups scaling rapidly
* Companies modernizing legacy apps

***

### Database Instances

**Challenge:** Running databases on EC2 (PostgreSQL, MySQL, MongoDB) requires memory-optimized instances running 24/7—expensive on On-Demand, inflexible with Reserved.

**Solution:** Use FlexCompute for database instances, maintain same performance and uptime, save 30-40% without multi-year commitment.

**Example:**

* Instance: 3x r7i.4xlarge (24/7, Multi-AZ)
* AWS On-Demand: \$7,272/month
* FlexCompute: \$4,727/month
* **Savings: \$2,545/month**

**Who uses this:**

* Companies running self-managed databases
* Teams avoiding managed database costs
* Applications with specific DB requirements

***

## Common Patterns Across Use Cases

### Pattern 1: Variable Workloads

**Best for:** Workloads that scale up/down daily, weekly, or seasonally\
**Savings:** Pay only for hours used, save 30-40% vs On-Demand\
**Examples:** Dev/test, CI/CD, batch processing

### Pattern 2: Project-Based Capacity

**Best for:** Capacity needed for specific projects, not continuously\
**Savings:** No idle costs between projects, no long-term commitments\
**Examples:** AI training, load testing, video rendering

### Pattern 3: Growing Production

**Best for:** Production workloads with unpredictable growth\
**Savings:** Reserved pricing without capacity lock-in\
**Examples:** SaaS apps, microservices, databases

***

**Ready to save on your workloads?** [Get started with FlexCompute →](/flexcompute/getting-started)

**Questions about your specific use case?** [Contact us →](mailto:hello@cloudidr.com)