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Graph QL for CICD Integration
Arunraj Karnam,
Performance Test Engineer,
Cognizant Technology Solutions.
© 2020 Cognizant
Authors:
Vivek Rajagopal,
Performance Test Engineer,
Cognizant Technology Solutions.
© 2020 Cognizant
Contents
• Execution Challenges
• GraphQL
• Implementation
• Major Challenges addressed
• Other Benefits
© 2020 Cognizant
Execution Challenges
“Stand alone executions will have problem of losing track
and make them accountable for either Shift Left or Shift
Right processes”
“Test data preparation took 1-2 hours per test based on
complexity and requires manual updates into the CICD
Pipeline.”
“Customer requirement kept changing and ~6 load tests per
day were executed. Manual intervention for test data has
actually delayed the whole CICD process”
• A modern ways of building and
querying APIs
• It uses REST Technology
• It is String interpreted by a Server that
returns data in a specified Format
• GraphQL server Expose single
Endpoint
• Enables Declarative Data Fetching
GraphQL
© 2020 Cognizant
Implementation
• Create a GraphQL
project
• Deploy it into a
Web server Via
Repo
• Verify the same
through browser
• Replicate the same
and integrate in
Jmeter
• Once execution is
started, Test data’s
will be extracted
from the GraphQL
response
© 2020 Cognizant
© 2020 Cognizant
Major Challenges addressed
Running Performance tests
across various environments
Externalizing the environment
Clean up run
generated time
files
Building scalable data-driven script
without learning distributed systems
Accountable in Shift Right or
Shift Left model
Other Benefits
• Increasing code quality and ensuring the performance is addressed at the
component level itself
• Reduction of 10-20% hours for test data preparation per test based on the
script complexity
• Using the Azure DevOps the nightly jobs can be executed
• No Over fetching or under fetching the data
• Number of JMeter code check-in's will be reduced, except script changes if
Required
© 2020 Cognizant
Thank You

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#ATAGTR2020 Presentation - GraphQL for CICD integration

  • 1. Graph QL for CICD Integration Arunraj Karnam, Performance Test Engineer, Cognizant Technology Solutions. © 2020 Cognizant Authors: Vivek Rajagopal, Performance Test Engineer, Cognizant Technology Solutions.
  • 2. © 2020 Cognizant Contents • Execution Challenges • GraphQL • Implementation • Major Challenges addressed • Other Benefits
  • 3. © 2020 Cognizant Execution Challenges “Stand alone executions will have problem of losing track and make them accountable for either Shift Left or Shift Right processes” “Test data preparation took 1-2 hours per test based on complexity and requires manual updates into the CICD Pipeline.” “Customer requirement kept changing and ~6 load tests per day were executed. Manual intervention for test data has actually delayed the whole CICD process”
  • 4. • A modern ways of building and querying APIs • It uses REST Technology • It is String interpreted by a Server that returns data in a specified Format • GraphQL server Expose single Endpoint • Enables Declarative Data Fetching GraphQL © 2020 Cognizant
  • 5. Implementation • Create a GraphQL project • Deploy it into a Web server Via Repo • Verify the same through browser • Replicate the same and integrate in Jmeter • Once execution is started, Test data’s will be extracted from the GraphQL response © 2020 Cognizant
  • 6. © 2020 Cognizant Major Challenges addressed Running Performance tests across various environments Externalizing the environment Clean up run generated time files Building scalable data-driven script without learning distributed systems Accountable in Shift Right or Shift Left model
  • 7. Other Benefits • Increasing code quality and ensuring the performance is addressed at the component level itself • Reduction of 10-20% hours for test data preparation per test based on the script complexity • Using the Azure DevOps the nightly jobs can be executed • No Over fetching or under fetching the data • Number of JMeter code check-in's will be reduced, except script changes if Required © 2020 Cognizant