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75. Find Peak Element

mediumAsked at Datadog

Find any peak element in O(log n). Datadog asks this for the non-monotonic binary-search pattern — peak detection in metric streams uses the same uphill-direction logic.

By Sam K., Founder, InterviewChamp.AI · Last verified

Source citations

Public interview reports confirming this problem appears in Datadog loops.

  • Glassdoor (2026-Q1)— Datadog onsite — direct analog to streaming peak detection.

Problem

A peak element is an element that is strictly greater than its neighbors. Given a 0-indexed integer array nums, find a peak element, and return its index. If the array contains multiple peaks, return the index to any of the peaks. You may imagine that nums[-1] = nums[n] = -infinity. You must write an algorithm that runs in O(log n) time.

Constraints

  • 1 <= nums.length <= 1000
  • -2^31 <= nums[i] <= 2^31 - 1
  • nums[i] != nums[i + 1] for all valid i.

Examples

Example 1

Input
nums = [1,2,3,1]
Output
2

Example 2

Input
nums = [1,2,1,3,5,6,4]
Output
5 (or 1)

Approaches

1. Linear scan

Walk and find any element greater than both neighbors.

Time
O(n)
Space
O(1)
for (let i = 0; i < nums.length; i++) { if ((i==0 || nums[i]>nums[i-1]) && (i==nums.length-1 || nums[i]>nums[i+1])) return i; }

Tradeoff: O(n) — violates the constraint.

2. Binary search uphill (optimal)

If nums[mid] < nums[mid+1], a peak exists to the right. Else, it exists at mid or left.

Time
O(log n)
Space
O(1)
function findPeakElement(nums) {
  let lo = 0, hi = nums.length - 1;
  while (lo < hi) {
    const mid = (lo + hi) >>> 1;
    if (nums[mid] < nums[mid + 1]) lo = mid + 1;
    else hi = mid;
  }
  return lo;
}

Tradeoff: O(log n) — walking uphill guarantees we converge to a peak.

Datadog-specific tips

Datadog grades on the 'walk uphill' insight. Since boundaries are -infinity, going uphill always lands on a peak. Articulate why the binary search converges before coding.

Common mistakes

  • Using <= instead of < — when nums[mid] == nums[mid+1], you can't tell which side has the peak (but the problem disallows equality).
  • Using hi = mid - 1 instead of hi = mid — could overshoot the peak.
  • Trying to find THE peak instead of ANY peak.

Follow-up questions

An interviewer at Datadog may pivot to one of these next:

  • Find Peak Element II (2D) — same idea per row.
  • Peak Index in Mountain Array (LC 852).
  • Datadog-style: locate a peak in a streaming metric without scanning the whole history.

Solve it now

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Output

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FAQ

Why does walking uphill find a peak?

If you always step toward the higher neighbor, and the boundary is -infinity, you must eventually reach a point where both neighbors are lower — a peak.

Multiple peaks?

Any one is acceptable. The binary search finds whichever lies in the uphill direction it chose.

More Datadog coding interview questions

See all Datadog problems →

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