(Cross posted from the txtWeb Engineering Blog)
At txtWeb, we were faced with a hard problem : handling peak loads during the IPL season without impacting our end to end response times. The End to End response time chart(E2E) below is an indicator of how our latencies were increasing with load:
As you can observe, it is very clear that as the requests per day increased, the latency also shoots up, which means that our end users are getting back delayed responses. This was an issue because the platform was able to scale up to the huge loads which txtWeb was receiving, but the delay was happening after the response message leaves the platform. This was a very important problem for us to solve, as this effectively meant on all the days we get huge number of requests, our end users would receive delayed responses.
What we did:
We made it a point to ensure that the transition to local numbers was a seamless experience for the end user and the ease of use was not impacted.
A typical user flow in pictures would as depicted in the image below:
This E2E response time in the graph below is a clear indicator of the improvements made:
Few important links:
List of txtWeb local numbers : http://goo.gl/wAi4O
Gopi Krishnan Nambiar
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