System Design Calculator
What is system sizing?
System sizing turns product behavior into a capacity envelope: the traffic each tier must serve, the reserve it keeps, the data it stores, and the failures it can absorb.
Step 1
Model
Model user demand and cache behavior, then provision benchmarked application and database capacity, headroom, failure domains, and storage replication.
Step 2
Observe
Trace requests from users to the data tier, compare demand with safe capacity, and identify the first bottleneck instead of relying on one headline server count.
Step 3
Challenge
Create a healthy baseline, then inject a launch surge, cache outage, zone loss, slow data tier, or retry storm and recover the design by changing the relevant assumption.
Turn product demand into a defensible capacity plan
Model the user peak, trace amplification through the request path, then test whether the provisioned architecture keeps its operating reserve under pressure.
Evaluated outcome
Design has reserve
Pressure test
Apply a failure or demand shock
Scenarios alter the evaluated request path without changing your saved assumptions.
3.7K RPS
80M requests/day before retries
1.2K RPS
80% effective read-cache hit rate
+704.8 RPS
Data tier is the limiting tier
$8.3K
31.3 TB physical storage
Follow demand as each tier transforms it
The selected scenario changes attempts, available nodes, or measured throughput. Node rings identify the tiers closest to or beyond their safe envelope.
Active scenario
Expected peak · Healthy day
Demand
Users and clients
3.7K RPS
533 Mbps peak response bandwidth
Demand shaping
Cache and request layer
80% hits
2.5K reads stop before the database
Compute
Application fleet
10/10 live
59% of safe capacity
State
Database tier
3/3 live
63% of safe capacity
Compare demand with safe operating capacity
Safe capacity subtracts your headroom before utilization is evaluated. A tier can be below its benchmark maximum and still violate the operating policy.
Application fleet
3.7K demanded / 6.3K safe RPS
59%
Database tier
1.2K demanded / 1.9K safe RPS
63%
925.9 RPS
4x peak ratio before scenario pressure
533 Mbps
18 KB average response payload
8.4 TB
365 days at 2 KB per write
31.3 TB
3x replication plus 25% index overhead
Architecture verdict
Design has reserve
Demand follows the workload assumptions and every failure domain is available.
First constraint
Data tier
- 30% reserve remains outside the safe-capacity line.
- Data tier is the tighter tier, so measure it first as demand changes.
10 live instances × 900 tested RPS × 70% operating share
= 6.3K safe RPS
3 live nodes × 900 tested RPS × 70% operating share
= 1.9K safe RPS