Forecast Aurora Storage IO costs

1

My customer already has a regular RDS instance and thinking about elevating to Aurora for better MAZ/RR dual purposing. I would like to use metrics from their existing RDS to forecast the aurora storage IO cost?

I am thinking something like this

  • Cloudwatch
  • Volume Read IOPs
  • Volume Write IOPs
  • Sum over 30 days

However, I am unsure if the metrics stored in cloudwatch have the right data to use as an estimate for aurora.

I am concerned the statistics CW captures current IOPs @ at a point in time (not ideal for aurora), or is cloudwatch capturing the sum of IOPs between and including points in time(ideal for aurora)

What’s the best approach here?

AWS
preguntada hace 4 años2102 visualizaciones
2 Respuestas
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Respuesta aceptada

Not sure about the accuracy of the estimate you are looking, but if you're looking for a ballpark figure, this calculation I use seems to match the AWS cost calculator estimates.

The most difficult part is calculating the average IOs per day, as this number fluctuates. If you can approximate that on a daily basis, then:

Total monthly IO cost = ((Average Read IOPS + Average Write IOPS)*86400*30)/1000000 x {cost per million IO-month}

For example: for a system that does 250 Read IOPS and 500 Write IOPS per day, at $0.20 per million IOs/month = $388.80

Again, this is a ballpark figure made with those assumptions. This number would be accurate if we could sum-aggregate the number of IOs per day.

respondido hace 4 años
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EXPERTO
revisado hace un mes
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Here is a deep dive on the Aurora-specific reasons why there could be different numbers of I/Os in Aurora than in RDS: https://aws.amazon.com/blogs/database/planning-i-o-in-amazon-aurora/

The way Aurora batches together the I/O operations could reduce the number of I/Os substantially from what you see in RDS. Certain features like Aurora PostgreSQL cluster cache management or Aurora parallel query could bump the I/O number back up somewhat. X2 instances have twice as much RAM as the comparable R instances and so can have bigger buffer caches; that can be another way to bring the I/O numbers down.

AWS
respondido hace un año
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EXPERTO
revisado hace un mes

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