When working with AWS Glue, one of the most common questions data engineers ask is: How much will this job cost me? If you have a workflow that runs for 13 minutes, understanding the cost model of AWS Glue helps you avoid surprises on your AWS bill.

How AWS Glue Pricing Works

AWS Glue pricing is based on DPU-hours. A DPU (Data Processing Unit) provides a certain amount of CPU and memory resources to your Glue job.

• 1 DPU-hour costs $0.44 (in the us-east-1 region).
• You pay in increments of 1 second, with a 10-minute minimum per job run.
• Jobs can use multiple DPUs depending on the configuration. By default, a Spark job in Glue usually runs with 10 DPUs.

Example: 13-Minute Workflow

Suppose you run a workflow that orchestrates several Glue jobs, and the total execution time is 13 minutes.

Step 1 – Convert to hours

13 minutes ÷ 60 = 0.2167 hours

Step 2 – Cost of one DPU for 13 minutes

0.2167 hours × $0.44 = $0.095

Step 3 – Apply the DPU count

If your jobs use 10 DPUs:
$0.095 × 10 = ≈ $0.95 per workflow run

Possible Scenarios

• 2 DPUs (minimum): about $0.19 per run
• 10 DPUs (default): about $0.95 per run
• 20 DPUs (large jobs): about $1.90 per run

Monthly Cost

If you run this workflow once per day, the monthly cost would be:
$0.95 × 30 ≈ $28.50

If you run it every hour of the day, the cost grows significantly:
$0.95 × 24 × 30 ≈ $684 per month

Why This Matters

Understanding these costs is crucial for:

• Budgeting: estimating monthly charges before production.
• Optimization: reducing DPUs or execution time lowers cost.
• Scaling decisions: deciding whether Glue, EMR, or another ETL service is more cost-effective.

Conclusion

For a 13-minute AWS Glue workflow, the cost is roughly $1 per run with 10 DPUs. By monitoring job metrics and optimizing resource allocation, you can keep your ETL pipelines both efficient and cost-effective.