redBus on AWS

Since all our applications, workloads, data are on AWS the obvious choice was to leverage AWS Sagemaker. Our recent feature of review classification has been built over this.

redBus also has incorporated AWS Lambda services into many of its internal applications. Lambda allows one to run code without the need of provisioning and managing servers and scales automatically. This is particularly interesting for use cases that can be compute intensive but runs at specific intervals. Like a report service which runs once or twice a day, that may need to pour over huge volumes of data and then compute and send results. There are also other use cases for which we are using Lambda. For instance we use this for processing and compressing images uploaded by customers. We also use Lambda for running the backend of our Alexa skill and our self-help chat bot.

While AWS as a solution provides a great deal of flexibility to launch instances or services and scale up quickly, one thing that bothers almost everyone would be the cost factor. In our experience of being on AWS, we have seen that they have been continuously working towards bringing down prices. However that being said, costs can really spiral out if one were not to keep an eye on the same.

There are a few reasons where we at redBus have seen cost spikes. The primary one has been where instances that were launched either for temporary scale ups or for running a small workload or POCs not being shut down post its use. Scenarios like using older generation or wrong types of instances for the wrong work load. For example, using a compute intensive instance for workloads not needing the same. In such cases you could end up spending much more than what you should have ideally.

However all is not grey and bleak. There are a few things that one could follow to get some costs down.

1. Purchasing and Optimal utilization of RI. We have seen that if planned well, purchased and by ensuring optimal usage, we have got roughly 30%+ savings. And if you can take these for longer durations with upfront payment then the savings could be much more. However one would need to be extremely sure of a long term commitment and that could very well depend on your business, system architecture and plans on how your system would evolve.

2. Look at utilizing Lambda’s where possible. We have seen that moving short burst workloads on to Lambda has helped us save almost 70% costs.

3. Monitor and shut down unused instances regularly. We have seen this can be a source of big leakage.

4. Look at Spot Instances. redBus has moved some of its workloads over the last few quarters onto Spot Instances. And we have seen good savings and the plan is to move more possible instances on to spot.

5. Finally, have a look at your architecture. Over a few years’ time, your code can become bulky and non-optimized. I also firmly believe that simplifying things can, not just help scale faster, but management, distribution etc. would also be extremely simplified. I can assure you, based on the work which we have done on redBus, that we have been able to save some good money by simplifying some of our systems. We also work closely with AWS SME’s to do ‘well architected review’ and identify areas of improvements.

Hope this article gives you some insights into how we are leveraging AWS at redBus and our experiences in trying to optimize costs would help you in some way.