Snehal Ahire
Senior Software Engineer
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Snehal is a Senior Software Engineer with over six years of experience architecting and scaling backend systems across industries such as media, education, e-commerce, and healthcare. She brings deep expertise in building high-performance APIs, leading engineering teams, and solving critical performance challenges.
Her technical focus lies in optimizing Ruby on Rails applications, designing scalable service architectures, and integrating systems to offload compute-intensive workloads. Snehal has successfully led refactoring initiatives that reduced infrastructure costs and improved system reliability, all while mentoring developers and fostering strong team collaboration.
Outside of her engineering work, she is an avid painter, a passionate home cook, and a nature enthusiast. She finds parallels between nurturing plants and debugging complex systems—both requiring patience, curiosity, and care.
Rails Under a Microscope: Diagnosing Slowness at the Byte Level
We realised our legacy code didn’t need a rewrite — it needed a performance plan.
This talk shares how we tackled real production issues like memory bloat, slow queries, and Sidekiq queues piling up under load — where simple fixes like batching jobs or tweaking retries didn’t help much.
We thought ActiveRecord was the bottleneck, but fixing it only scratched the surface.
We tuned the garbage collector, optimised query access patterns, chose more efficient data structures, restructured background jobs, and introduced smarter database caching and indexing strategies.
I’ll share how we analysed query plans, fine-tuned database performance, and replaced slow, fragile logic with leaner, more explicit code paths that scaled better and failed less and Rails stayed right at the centre of it all.
Knowing the Rails Limits, GO-ing Behind Rails’ Back
This talk is about solving real-life scaling problems! I share my experience of our systems hitting performance issues with Sidekiq queues and complex validations. Simply adding batching, breaking jobs into chunks, or fine-tuning retry strategies overloaded the Rails app — and didn’t help.
We evaluated multiple options, but found that decoupling the heavy tasks into Go allowed us to keep Rails nimble while boosting performance.
I discuss how we use Go with Rails to handle jobs that are compute-heavy to harness the raw speed, concurrency and low memory instead of tapping into ActiveRecord or Rails’ magic.
Key takeaways:
* Gracefully evolve Rails to not do heavy lifting!
* Learn Patterns to offload CPU-bound or IO-bound tasks using Go
* Managing communication between heterogeneous tech stacks.
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