Akamai Coding Interview Questions
25 Akamai coding interview problems with full optimal solutions — 8 easy, 12 medium, 5 hard. Every problem ships with multiple approaches (brute-force first, then the optimal), complexity tables for each, company-specific tips on what an Akamai interviewer values, and a FAQ section.
Showing 6 problems of 25
- #1easyfrequently asked
1. Two Sum
Find two indices in an array whose values sum to a target. Akamai asks this as a warm-up to probe hash map reasoning and O(n) thinking — the kind of constant-time lookup that matters when processing billions of log entries per day at the edge.
- #20easyfrequently asked
20. Valid Parentheses
Determine whether a string of brackets is correctly nested. Akamai asks this to test stack-based reasoning — the same pattern underpins parsing HTTP header fields and configuration syntax that edge servers process at high throughput.
- #21easyfrequently asked
21. Merge Two Sorted Lists
Merge two sorted linked lists into one sorted list. Akamai asks this because merge is a fundamental building block for external sort — the same pattern used to merge sorted access logs from thousands of edge servers into a single chronological stream.
- #53easyfrequently asked
53. Maximum Subarray
Find the contiguous subarray with the largest sum. Akamai ties this directly to network throughput analysis — Kadane's algorithm is the canonical one-pass scan for detecting the peak burst window in a stream of per-second byte-delta measurements.
- #121easyfrequently asked
121. Best Time to Buy and Sell Stock
Find the maximum profit from one buy and one sell transaction in a price array. Akamai frames this as a running-minimum scan — the same streaming pattern used to compute latency baselines across billions of edge-server events in a single pass.
- #206easyfrequently asked
206. Reverse Linked List
Reverse a singly linked list in place. Akamai uses this to verify that candidates can reason about pointer manipulation without extra memory — a discipline that matters in high-throughput packet-processing code where heap allocations are expensive.