Provide a detailed approach to analyze and improve end-to-end request latency in a web application. The request flows from a browser through a CDN, load balancer, API gateway, microservices, caches, databases, and third‑party services. How would you instrument both client and server to capture metrics such as TTFB, total blocking time, network RTT, queueing, service processing time, database query latency, cache hit/miss rates, and external dependency latency? How would you attribute latency to frontend vs. backend components, investigate p50/p95/p99 outliers, and identify bottlenecks? What changes or experiments would you run to reduce latency without regressing error rate or throughput, and how would you define SLIs/SLOs, dashboards, and alerts?

This question evaluates proficiency in end-to-end latency analysis, observability and instrumentation (client and server), distributed tracing, performance engineering, and SLI/SLO definition.

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Analyze end-to-end request latency | Adobe Interview Question

Analyze and Improve End-to-End Request Latency

Context

A user request flows: Browser → CDN → Load Balancer → API Gateway → Microservices → Caches/Databases → Third‑party services → Response to Browser. You need to analyze and reduce end‑to‑end latency without harming reliability or throughput.

Assume modern browsers (Navigation/Resource/Long Tasks APIs), HTTP/2+, and backend microservices where you can add distributed tracing and metrics.

Tasks

Instrument both client and server to capture:
- Client: TTFB, Total Blocking Time (TBT), network RTT, resource timing, and user-perceived completion.
- Server: queueing time, service processing time, database query latency, cache hit/miss rates, and external dependency latency.
Attribute latency to frontend vs. backend components across the whole path.
Investigate p50/p95/p99 outliers and identify bottlenecks.
Propose changes or experiments to reduce latency without regressing error rate or throughput.
Define SLIs/SLOs, dashboards, and alerts for ongoing monitoring.

Context

Assume modern browsers (Navigation/Resource/Long Tasks APIs), HTTP/2+, and backend microservices where you can add distributed tracing and metrics.

Tasks

Instrument both client and server to capture:

Client: TTFB, Total Blocking Time (TBT), network RTT, resource timing, and user-perceived completion.
Server: queueing time, service processing time, database query latency, cache hit/miss rates, and external dependency latency.

Attribute latency to frontend vs. backend components across the whole path.

Investigate p50/p95/p99 outliers and identify bottlenecks.

Propose changes or experiments to reduce latency without regressing error rate or throughput.

Define SLIs/SLOs, dashboards, and alerts for ongoing monitoring.

Analyze end-to-end request latency

Quick Overview

Analyze and Improve End-to-End Request Latency

Context

Tasks

Solution

Comments (0)

Analyze end-to-end request latency

Quick Overview

Analyze and Improve End-to-End Request Latency

Context

Tasks

Solution

Comments (0)