1 point by debugger432 1 year ago flag hide 14 comments
johnsmith 1 year ago next
Great question! Debugging large-scale applications can be quite challenging. Some best practices I've found are: (1) divide and conquer to break down the problem into smaller, manageable pieces, (2) use logging extensively, (3) utilizing distributed tracing tools, (4) use a staged approach to roll out changes, and (5) make sure to have good monitoring and alerting in place.
janedoe 1 year ago next
@johnsmith Great points! I'd also like to add (6) use automated testing wherever possible, (7) use a modular architecture, and (8) use a step-by-step troubleshooting method. It can also be helpful to have a dedicated debugging environment, separate from production.
devopsdude 1 year ago next
@janedoe Great suggestions! I would also like to add (16) having a clear and concise documentation, (17) utilizing automation and scripting to speed up debugging and (18) having a good communication with the team members and knowledge sharing.
automationking 1 year ago next
@devopsdude Yes, automation is key. Additionally, (24) using Continuous Integration/Continuous Deployment (CI/CD) pipeline, (25) having monitoring in place that can automatically rollback changes if something goes wrong.
deploymaster 1 year ago next
@automationking Yes, CI/CD pipeline is important. Additionally, (31) using blue/green deployment, (32) having rollback procedures in place, and (33) monitoring and logging the deployment process.
deployninja 1 year ago next
@deploymaster Yes, monitoring the deployment process is important, Additionally, (40) using canary releases, (41) having a disaster recovery plan in place and (42) automating the deployment process can help to reduce the risk of deployment errors.
cpplover 1 year ago prev next
@johnsmith Definitely, logging and tracing are crucial. Also, (13) using a code profiling tool can help you identify performance bottlenecks, (14) having a thorough understanding of the deployment environment, and (15) maintaining a detailed and up-to-date inventory of all components and dependencies in the system.
profilingguru 1 year ago next
@cpplover Profiling the code is very helpful, I would also suggest (21) using memory profiling, (22) understanding the garbage collection mechanisms and (23) using a code review process before deploying to production.
memleakman 1 year ago next
@profilingguru Yes, memory management is important, I would also suggest (28) using tools to detect memory leaks, (29) understanding how to use pointers, and (30) following best practices for memory management in the language you're using.
memoryman 1 year ago next
@memleakman Yes, memory management is important, Additionally, (37) using smart pointers, (38) using value semantics and (39) using memory pools can help to reduce memory fragmentation.
codejammin 1 year ago prev next
I agree with both of you. Additionally, (9) using a debugging tool that supports breakpoints and single-stepping can be very helpful, (10) making sure to understand the underlying technology stack, (11) keeping the application code simple and easy to understand, and (12) ensuring that all dependencies are up-to-date and well-maintained.
testingmaster 1 year ago next
@codejammin Yes, testing is crucial. I would also suggest (19) using different types of testing like unit, integration, and end-to-end testing and (20) automated testing can help to catch bugs early in the development process.
testerpro 1 year ago next
@TestingMaster Yes, testing is important, I would also suggest (26) having test cases well-defined and (27) using test-driven development approach.
testguru 1 year ago next
@testerpro Yes, test cases should be well-defined, Additionally, (34) using mutation testing, (35) using property-based testing and (36) using test data management can help to improve the quality of tests.