India’s Scale Demands Planning For Failures Beyond Your Stack: Razorpay’s Prabhu Ram
Building reliable digital payments at India’s scale requires planning for failures in infrastructure a company does not control, according to…
Razorpay's SVP of engineering, Prabhu Ram, emphasizes the importance of designing resilient systems to handle failures in both internal and external infrastructure, especially at India's scale of digital payments.
What happened
Razorpay's SVP of engineering, Prabhu Ram, highlighted the need for companies to build resilient systems that can handle failures in both internal and external infrastructure. He emphasized that AI alone cannot compensate for weak engineering foundations and stressed the importance of observability in system monitoring. The discussion also touched on the role of AI in improving user responses by bringing models closer to data.
Why it matters
For AI developers and technology professionals, the article underscores the importance of building robust systems that can handle failures in both internal and external infrastructure. It also highlights the limitations of AI in compensating for poor engineering practices, which is critical for ensuring reliable digital services at scale.
- Resilience is essential for handling failures in both internal and external infrastructure.
- AI cannot compensate for weak engineering foundations or inadequate monitoring.
- Observability is crucial for effective AI deployment and system monitoring.
- Owning critical components in-house can improve control and reliability.
The bigger picture
The practical impact of the article is that companies must prioritize resilience and observability in their systems to meet user expectations for uninterrupted digital services. This is especially important in India's context, where digital payments and bookings are expected to function seamlessly.
The article concludes that building reliable digital services at scale requires a focus on resilience, observability, and strong engineering foundations, with AI playing a supportive role rather than a compensatory one.
Technical details
- Observability in system monitoring
- AI models being brought closer to data
- Seven layers of technology stack
- Resilience in digital payment systems
FAQ
Why is resilience important for digital payments in India?
Resilience is crucial because users expect uninterrupted payments and bookings, and failures in either internal or external infrastructure can disrupt these services.
Can AI compensate for weak engineering foundations?
No, AI cannot compensate for weak engineering foundations. It can compound problems if deployed without adequate observability and monitoring.
What is the role of observability in system monitoring?
Observability allows companies to monitor what is happening inside a system and identify issues quickly, which is essential for maintaining reliability and performance.
Which companies are examples of owning critical components in-house?
Apple, Microsoft, and Amazon are examples of companies that have brought critical components in-house, giving them greater control over their technology stack.
How is AI being used to improve user responses?
AI models are being brought closer to data to improve responses to users, allowing models to learn better and respond more effectively.
This summary and analysis were generated with AI from the original article and may contain errors. Read the original for the full story.
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Originally published by Inc42 AI News on Sep 30, 2026.
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