Datadog Coding Interview Questions
100 Datadog coding interview problems with full optimal solutions — 31 easy, 54 medium, 15 hard. Every problem ships with multiple approaches (brute-force first, then the optimal), complexity tables for each, company-specific tips on what an Datadog interviewer values, and a FAQ section.
Showing 22 problems of 100
- #31mediumfrequently asked
31. Add Two Numbers
Add two non-negative integers represented as reversed-order linked lists. Datadog uses this to test carry-propagation logic — the same logic as their atomic-counter rollup across pipeline stages.
- #32mediumfrequently asked
32. Longest Substring Without Repeating Characters
Find the length of the longest substring with no repeating characters. Datadog asks this as the sliding-window foundation — the same pattern they use for windowed deduplication of streaming events.
- #35mediumfrequently asked
35. 3Sum
Find all unique triplets that sum to zero. Datadog uses this as the cornerstone two-pointer + dedup question — the same pattern needed for finding triple-correlations in cross-metric anomaly detection.
- #41mediumfrequently asked
41. Search in Rotated Sorted Array
Search for a target in a rotated sorted array in O(log n). Datadog asks this because their TSDB indexes can be rotated chunks (after compaction crosses a boundary), and bisect must still work correctly.
- #42mediumfrequently asked
42. Find First and Last Position of Element in Sorted Array
Find the first and last index of a target in a sorted array using O(log n). Datadog asks this because their TSDB needs range-bisect (start and end of a value range) for every query that filters by timestamp.
- #47mediumfrequently asked
47. Group Anagrams
Group strings that are anagrams of each other. Datadog asks this because the canonicalize-then-hash pattern is identical to how they group equivalent metric series by sorted-tag-keys for query deduplication.
- #49mediumfrequently asked
49. Jump Game
Determine if you can reach the last index given an array of max jump lengths. Datadog asks this for the greedy max-reach pattern — same shape as a streaming reachability check over a partially-observed graph.
- #50mediumfrequently asked
50. Merge Intervals
Merge all overlapping intervals. Datadog asks this constantly because it's the foundation of compaction — merging overlapping metric chunks, log batches, or active session windows is the same problem.
- #57mediumfrequently asked
57. Sort Colors
Sort an array of 0s, 1s, and 2s in place in one pass. Datadog asks this as the canonical Dutch National Flag warmup — same three-way-partition trick they use for tagging metric series by priority.
- #61mediumfrequently asked
61. Validate Binary Search Tree
Determine if a binary tree satisfies BST properties. Datadog asks this for the bounds-passing recursion pattern — same shape as validating an ordered range invariant on a hierarchical metric store.
- #62mediumfrequently asked
62. Binary Tree Level Order Traversal
Return a binary tree's level-order traversal grouped by level. Datadog uses this as the BFS-foundation question — same level-batched pattern they use for paginated tree expansion in their query layer.
- #68mediumfrequently asked
68. Longest Consecutive Sequence
Find the longest sequence of consecutive integers in an unsorted array in O(n). Datadog asks this for the start-only expansion trick — same pattern as compacting consecutive timestamps in a sparse metric block.
- #71mediumfrequently asked
71. LRU Cache
Design a cache with get and put operations in O(1). Datadog asks this constantly — every metric ingestion pipeline has an LRU at some boundary for resolving high-cardinality tag IDs to interned values.
- #74mediumfrequently asked
74. Find Minimum in Rotated Sorted Array
Find the minimum value in a rotated sorted array in O(log n). Datadog asks this because their TSDB rotates compacted chunks across the time axis, and locating the pivot is the prerequisite for any range query.
- #77mediumfrequently asked
77. Kth Largest Element in an Array
Find the kth largest element in an unsorted array. Datadog asks this for the min-heap-of-size-k trick — same streaming aggregate they use to maintain top-K leaderboards over high-cardinality metric streams.
- #78mediumfrequently asked
78. Course Schedule
Determine if you can finish all courses given prerequisite pairs — equivalent to detecting a cycle in a directed graph. Datadog asks this because their dashboard-dependency graph and metric-rollup DAG must remain acyclic.
- #79mediumfrequently asked
79. Implement Trie (Prefix Tree)
Implement a Trie with insert, search, and startsWith. Datadog uses this as the gateway to prefix-search problems — same shape as their tag-name autocomplete that serves their high-cardinality search UI.
- #80mediumfrequently asked
80. Minimum Size Subarray Sum
Find the minimum length contiguous subarray whose sum is at least target. Datadog asks this for the variable-size sliding-window pattern — same shape as their alert-window optimization over a metric stream.
- #81mediumfrequently asked
81. Number of Islands
Count connected components of '1's in a 2D grid. Datadog uses this as the canonical grid-BFS/DFS question — same shape as counting active service clusters in a service-mesh observability view.
- #83mediumfrequently asked
83. Coin Change
Find the minimum number of coins to make a target amount. Datadog asks this for the unbounded-knapsack DP pattern — same shape as their resolution-stitching algorithm that selects the minimum number of pre-aggregated buckets to cover a query window.
- #84mediumfrequently asked
84. Longest Increasing Subsequence
Find the length of the longest strictly increasing subsequence. Datadog asks this for the patience-sorting O(n log n) trick — same shape as their monotonic-history compression for time-series anomaly trend detection.
- #85mediumfrequently asked
85. Top K Frequent Elements
Return the k most frequent elements. Datadog asks this for the heap-of-size-k + bucket-sort alternative — same shape as their top-K leaderboard for hottest metric series in a high-cardinality stream.
Related interview-prep guides
Beyz AI Alternatives in 2026: 7 Tools Compared (Screenshot + Stealth Helpers)
Beyz AI is a screenshot-and-clipboard interview helper that surfaces AI answers on a hidden overlay during online assessments and live rounds. The 2026 reality: candidates search for alternatives because of detection anxiety on monitored OAs, the $30+/month price tag with feature ceilings, and the narrow scope (coding-OA-shaped use only). This guide ranks the 7 best Beyz AI alternatives in the same screenshot-helper category, with InterviewChamp.AI compared honestly alongside, plus how to pick based on your specific interview gauntlet.