Is this a video course?

No. This is an interactive, slide-based learning platform. Each lesson has rich text, animated diagrams, live code editors, and quizzes. You learn by reading, interacting, and doing, not by watching videos passively.

How long do I have access?

Forever. Both pricing tiers are one-time payments with lifetime access. This includes all current 766 lessons and any future content we add.

What level of experience do I need?

None. We start from absolute basics like 'What is latency?' and build up to distributed consensus protocols. The Foundation level assumes zero prior knowledge of system design.

How much does the system design course cost?

7.99 US dollars for lifetime access globally, or 499 Indian rupees for lifetime access in India. One-time payment, no subscription, no hidden fees. 11 lessons are free with no signup required.

What technologies are covered?

Everything from DNS and load balancers to Kubernetes, Kafka, distributed databases, consensus protocols, stream processing, security architecture, and observability. We cover principles and real-world implementations used at Netflix, Google, Amazon, Uber, Stripe, and more.

Is this useful for system design interview preparation?

Yes. The lessons are structured around the exact topics asked in system design interviews at FAANG and top-tier companies. Interactive diagrams help you practice whiteboard-style explanations. Covers everything from URL shortener design to distributed payment systems.

How is this different from ByteByteGo or Educative?

766 interactive lessons (4x more than most competitors), 16 different diagram types that build step by step, real production examples from Netflix, Google, Amazon, Uber, and Stripe, and lifetime access for a one-time payment of $7.99 instead of annual subscriptions costing 100 to 200 dollars per year.

A mobile app logs a click at 10:00:00 local time. The phone is offline until 10:05:00 when it uploads. A Flink job processes it at 10:05:02. What is the event time and processing time?

Event time 10:00:00, processing time 10:05:02, Event time is when the business event happened on the device (10:00:00). Processing time is when the Flink operator handled the record (10:05:02). The 5 minute gap is the skew, which is what watermarks, allowed lateness, and side outputs exist to handle.

Why is a sales dashboard grouped by processing time dangerous?

Processing time dashboards assign events to the bucket when they were processed, not when they actually happened, so backlogs and catchups produce fake spikes, If a backlog clears at 09:00, every buffered event lands in the 09:00 processing time bucket, producing a fake spike that has nothing to do with customer activity. Event time based grouping assigns events to the hour they actually happened, so the history stays honest even after a catchup.

What metric should an on call engineer alert on to know a stream job is falling behind?

Event time lag, measured as wall clock minus max(event_time) seen, Processing time latency lies during a backlog because the job is still processing records instantly, they are just old records. Event time lag honestly reports that the job is minutes behind reality. Lyft's pricing pipeline and Uber's trip analytics both page on event time lag, not processing time latency.

Event Time vs Processing Time

Name: System Design Masterclass
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in Stream Batch Processing

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