Date |
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Authors | |||||||||
Status | Done | ||||||||
Summary | Some users experiencing issues with TIS, describing it as “crashing and slow loading over a couple of days”. | ||||||||
Impact | Users unable to use TIS
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Notified by Users on Teams channel
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Resolution
Replacing TCS tasks
Increased the TCS tasks memory from 2GB - 3GB
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Timeline
All times BST unless otherwise indicated.
11:28 Numerous requests to TCS start responding with a “Bad Gateway” error. Logs show that all 3 tasks were receiving and processing some activity.
1229 user reported problem on Teams “TIS being slow / crashing when doing updates - A few of us in Wessex are experiencing issues with TIS when trying to do updates - it keeps crashing and is being really slow loading over the past couple of days.”
1300 Message acknowledged
1328 Last minute when multiple requests to TCS failed. Some errors occurred later, close to 3 pm & 5-6pm
1342 Errors spotted on esr-sentry channel so ESR services stopped to prevent potential errors
1353 Service restarted and reported to users that looks resolved
1410 Users confirmed things back to normal
16:00 Logs relating to ESR checked and ESR services restarted
11:00 Applicant records from 8th Oct sent out
12:00 Notification records from 8th Oct sent out excluding stale
Triggered a 502 error by overloading the tcs service on stage with a high volume of requests to increase CPU utilization
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5 Whys (or other analysis of Root Cause)
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Q. Why was TCS erroring and not returning data
A. TCS was unable to process the requests in a timely manner due to high CPU utilization and memory.
Q. Why were there not enough tasks to handle the increased load?
A. Auto-scaling was not enabled, so the system did not automatically scale up the number of tasks in response to the surge in traffic.
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Action Items
Action Items | Owner | |||||||||
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Implement Auto-Scaling & Enhance Monitoring and Alerts |
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See also:
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Lessons Learned
Importance of Auto-Scaling: The absence of auto-scaling left the system vulnerable to unexpected traffic surges, highlighting the critical need for automated scaling mechanisms to handle dynamic workloads efficiently.
Proactive Resource Management: Relying solely on static resource allocation can lead to bottlenecks during periods of high demand. Regular reviews of scaling configurations and resource management policies are essential to ensure the infrastructure can adapt to changing load patterns.
Monitoring and Early Detection: Enhanced monitoring and alerting are crucial for identifying system strain early. By detecting potential issues before they affect service performance, proactive interventions can be made to avoid disruptions.
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