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 41 problems of 100
- #1easyfrequently asked
1. Two Sum
Given an array of integers and a target, return indices of the two numbers that add up to the target. Datadog asks this as a warmup but pushes candidates to discuss how the same hashmap pattern scales to streaming pair-detection over high-cardinality metric IDs.
- #2easyfrequently asked
2. Valid Parentheses
Given a string of brackets, determine if every opener has a matching closer in the correct order. Datadog frames this as a streaming log-parser warmup — the same stack discipline shows up when validating JSON log payloads on a high-throughput ingestion pipeline.
- #3easyfrequently asked
3. Merge Two Sorted Lists
Merge two sorted linked lists into one sorted list. Datadog uses this as a stepping stone toward merging K sorted time-series streams — the underlying two-pointer pattern is identical to how their backend stitches ordered metric shards.
- #6easyfrequently asked
6. Search Insert Position
Given a sorted array and a target, return the index where the target would be inserted. Datadog uses this as the bedrock for binary-search-on-time questions — every metric query that bisects timestamps uses this pattern.
- #7easyfrequently asked
7. Maximum Subarray
Find the contiguous subarray with the largest sum. Datadog phrases this as 'find the peak metric burst' — Kadane's algorithm runs in a single pass and ports directly to a streaming aggregator over a metric window.
- #9easyfrequently asked
9. Merge Sorted Array
Merge two sorted arrays in place, where the first has enough trailing space to hold both. Datadog uses this to test the reverse-iteration trick — the same backward-merge pattern they use when compacting two adjacent TSDB chunks without allocating a third buffer.
- #17easyfrequently asked
17. Best Time to Buy and Sell Stock
Find the max profit from one buy and one sell. Datadog frames this as 'find the largest spike in a metric stream' — single pass, constant memory, identical to their min-tracking aggregator.
- #19easyfrequently asked
19. Single Number
Every element appears twice except one. Find the singleton in O(n) time and O(1) space. Datadog asks this to test whether you know the XOR trick — a streaming-friendly aggregate that uses constant memory regardless of cardinality.
- #20easyfrequently asked
20. Linked List Cycle
Detect whether a linked list contains a cycle. Datadog uses this as the Floyd-tortoise warmup before more complex cycle-detection problems in their dependency-graph traversals.
- #21easyfrequently asked
21. Min Stack
Design a stack that supports push, pop, top, and getMin all in O(1). Datadog asks this because it's the same shape as a streaming min-aggregate that needs to handle rollbacks (transactional ingestion).
- #23easyfrequently asked
23. Majority Element
Find the element that appears more than n/2 times. Datadog asks this because the Boyer-Moore vote algorithm is the canonical streaming-aggregate pattern for finding a heavy hitter in one pass with O(1) memory.
- #29easyfrequently asked
29. Reverse Linked List
Reverse a singly linked list. Datadog uses this as the bedrock linked-list question — pointer manipulation here is required for harder problems like reverse-in-groups or merge-k-sorted.
- #30easyfrequently asked
30. Contains Duplicate
Determine if any value appears at least twice in an array. Datadog uses this as the hashset warmup before count-distinct and HyperLogLog discussions for high-cardinality tag streams.
- #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.
- #87hardfrequently asked
87. Serialize and Deserialize Binary Tree
Design serialize and deserialize for an arbitrary binary tree. Datadog uses this as the canonical wire-format question — same shape as their distributed metric-tree snapshot format that flows between ingest and query nodes.
- #88hardfrequently asked
88. Find Median from Data Stream
Design addNum and findMedian over a streaming sequence. Datadog asks this as the canonical streaming-percentile problem — two-heap solution is the exact pattern they use for p50 over a sliding metric window.
- #89hardfrequently asked
89. Sliding Window Maximum
Return the max of each sliding window of size k. Datadog asks this constantly — the monotonic deque is the exact algorithm they use for streaming max-over-window aggregations on real-time metric dashboards.
- #92hardfrequently asked
92. Merge k Sorted Lists
Merge k sorted linked lists into one sorted list. Datadog asks this because their query layer routinely merges K ordered metric shards into a unified stream — the min-heap pattern is identical.
- #98hardfrequently asked
98. Trapping Rain Water
Compute how much water gets trapped between bars. Datadog uses this for the two-pointer greedy proof — same shape as bounded peak-valley estimation in a streaming metric series.
- #100hardfrequently asked
100. Largest Rectangle in Histogram
Find the largest rectangle area in a histogram. Datadog uses this for the monotonic-stack pattern — same shape as their algorithm for detecting the largest sustained burst window in a metric stream.
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