Asistente de clúster de IA

For a small development app with ~100 users, cost-effectiveness and
reliability are key. I recommend starting with an M10 cluster on AWS in
US_EAST_1 (N. Virginia). This tier supports your use case with enough
resources for development and light testing, while keeping costs
controlled. Avoid free (M0) since you already have one and FLEX is
unnecessary for your scale.
I'll suggest a configuration based on these requirements. Quick
questions to further optimize:
- Do you expect your dataset to grow beyond 10GB during development?
- Any other environments needed, like staging or test?
- Will more developers or services connect to this cluster soon?
Suggesting the config now.

For migrating a 100GB project to Atlas in Europe, I recommend the following:
- Use AWS as your cloud provider (most commonly used, but let me know if
  you prefer GCP or Azure).
- Select the region EU_WEST_1 (Ireland) to host your data in Europe.
- Choose at least an M40 instance (this tier is recommended for
       migrating and running production workloads with 100GB+ data, ensuring
  strong performance during data load and normal operations).
- Set storage to 150GB (100GB data + 30% headroom).
- Default disk IOPS for M40 will provide ample performance for both
  migration and ongoing workload.
Let’s proceed with this setup.
A few quick clarifications:
- Is this a production environment with performance/uptime requirements?
- Do you expect rapid growth in data or traffic soon?
- Any preference for AWS, GCP, or Azure within Europe, or should we
  proceed with AWS?
I’ll configure the cluster now with these optimized settings.

To keep monthly costs under $500, I recommend switching to an M30 tier.
This provides reliable performance for standard production workloads at
around $394/month on AWS, plus some buffer for backups and storage.
Here’s how I’ll configure it:
- Instance size: M30 (entry-level dedicated, good for most production
  apps)
- Region: N. Virginia (US_EAST_1) (stays consistent with your existing
  clusters)
- Disk size: 40GB (default for M30, suitable for moderate workloads)
- No additional IOPS or premium storage (keeps costs down)
- No analytics/search node or advanced add-ons
Let’s proceed with this cost-effective configuration.
Before finalizing, can you clarify:
- Is this cluster for production, staging, or development?
- What’s your estimated data volume (just rough amount of GB needed)?
- Any specific performance requirements (high writes, reads, etc.)?
I’ll now suggest the configuration for you.

Since you're expanding to India with 20,000 expected users, you’ll need
a production-grade cluster deployed in an appropriate Indian region for
low latency. I recommend AWS as the cloud provider (unless you have a
preference for GCP or Azure), using the AP_SOUTH_1 region (Mumbai).
For your user base and workload size, an M30 dedicated tier is a strong
fit—it’s ideal for mid-sized production apps. This setup will handle
moderate to high traffic and provides headroom as your user base grows.
I'll set:
- Cloud Provider: AWS
- Region: AP_SOUTH_1 (Mumbai, India)
- Instance Size: M30 (production-ready with sufficient resources)
- Disk Size: Default (40GB, upgrade later if data grows quickly)
To refine this setup:
- What type of workload will the cluster handle (e.g., read-heavy,
  write-heavy, analytics)?
- Any data volume estimate (GB/TB) for the first year?
- Any specific cost constraints?
Applying this recommendation now.