Madhavi Patel

SPEAKERS

Madhavi Patel

Madhavi Patel has 10 years of IT experience in Non-Functional testing with background of development and production support, currently working as a Performance Test Lead with Leading UK Financial organization where she is responsible for the end to end non- functional testing life cycle right from Requirement gathering, Risk Assessment, Impact Analysis, Test Strategy & approach, developing & enhancing scripts/ scenarios, Application monitoring and analysis of performance results, performance tuning, defect triage , Reporting and sign off. She has excellent communication, collaboration , team building and Strong Technical Analytical Skills and is a quick learner with adaptable and flexible attitude.

Topic: AWS Performance Testing – How to do it Right


Abstract: What is AWS? AWS is amazon web service which provides on demand cloud computing platforms.
Cloud computing is changing the way application are deployed, monitored and used by the end users. Cloud offers a virtually infinite pool of resources for computing, storage and networking resources where applications can be scaled as desired.
So how do you measure the performance of these applications in the cloud?
Performance testing in cloud is different from that of traditional applications. The main aim of the Performance testing is to measures the various parameters such as system throughput, latency, multiple parallel users, different load profiles and various other performance metrics. Cloud-based testing lets you get the maximum by utilizing a cost-effective means of testing applications at scale. Performance testing of cloud services need not be complex. We need to consider each large problem and break it down till we get something small and manageable to solve that problem.
This paper will focus on AWS cloud performance testing concepts and Real-Time Scenario Testing with AWS which will include Uploading files in S3 buckets using a performance tool like JMeter, Files Processing by Talend Application, Redshift Storage and publishing processed data on website.
Performance test data generation for is also a major and complex process as we need to create large volume of data to simulate production like scenarios but it can be simplified using various test data creation utilities which saves manual efforts.

Some of the key aspects that will be covered in Paper are:
• AWS Introduction (S3, Amazon Redshift, EC2 services)
• Strategy and Prerequisites
• Types of performance tests you can perform on cloud.
• Test Data Creation
• JMeter Use in Execution
• Known issues and resolution
• Monitoring using Splunk and Amazon Redshift Audit Logs

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