# Improving AWS Glue performance
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**Baseline strategy for performance tuning**

In order to improve AWS Glue performance, you may consider updating certain performance related AWS Glue parameters. When preparing to tune parameters, use the following best practices:
+ Determine your performance goals before beginning to identify problems.
+ Use metrics to identify problems before attempting to change tuning parameters.

For the most consistent results when tuning a job, develop a baseline strategy for your tuning work.

Generally, performance tuning is performed in the following workflow:

1. Determine performance goals.

1. Measure metrics.

1. Identify bottlenecks.

1. Reduce the impact of the bottlenecks.

1. Repeat steps 2-4 until you achieve the intended target.

## Tuning strategies for your job type
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**Spark jobs**–follow the guidance in [Best practices for performance tuning AWS Glue for Apache Spark jobs](https://docs.aws.amazon.com/prescriptive-guidance/latest/tuning-aws-glue-for-apache-spark/introduction.html) on AWS Prescriptive Guidance.

**Other jobs**–you can tune AWS Glue for Ray and AWS Glue Python shell jobs by adapting strategies available in other runtime environments.