Okta coding interview
questions, leaked.
7 problems reported across recent Okta interviews. Top patterns: array, hash table, design. The list below is what most reported candidates actually saw, plus the honest play if you can't grind all of it.
Okta's interview is lean but sharp. Seven reported problems, all medium except one hard, and they cluster hard around arrays and hash tables. You're looking at a gauntlet of design problems (LRU Cache, Insert Delete GetRandom) mixed with medium-difficulty data-structure grind. The difficulty spread is tight, which means no warm-up rounds. You need to be sharp on day one. If you hit a wall on the live assessment, StealthCoder runs invisibly and surfaces a working solution in seconds, screen-share proof.
Top problems at Okta
| # | Problem | Diff | Frequency | Pass % | Patterns |
|---|---|---|---|---|---|
| 01 | Insert Delete GetRandom O(1) | MEDIUM | 100.0 | 55% | Array · Hash Table · Math |
| 02 | Find Median from Data Stream | HARD | 100.0 | 53% | Two Pointers · Design · Sorting |
| 03 | Merge Intervals | MEDIUM | 87.9 | 49% | Array · Sorting |
| 04 | Daily Temperatures | MEDIUM | 87.9 | 67% | Array · Stack · Monotonic Stack |
| 05 | Strings Differ by One Character | MEDIUM | 87.9 | 41% | Hash Table · String · Rolling Hash |
| 06 | Koko Eating Bananas | MEDIUM | 87.9 | 49% | Array · Binary Search |
| 07 | LRU Cache | MEDIUM | 87.9 | 45% | Hash Table · Linked List · Design |
Frequencies derived from public community-tagged interview reports. Click a row to view on LeetCode.
You have a week, maybe less. You can't out-grind the list above. StealthCoder runs invisibly during the actual Okta OA. The proctor cannot see it. Screen share cannot detect it. Built by an Amazon engineer who used it to pass JPMorgan's OA and system design loop.
Get StealthCoder- array4 · 57%
- hash table3 · 43%
- design3 · 43%
- sorting2 · 29%
- stack1 · 14%
- monotonic stack1 · 14%
- math1 · 14%
- randomized1 · 14%
- string1 · 14%
- rolling hash1 · 14%
Arrays dominate Okta's signal (4 problems), followed by hash tables and design patterns (3 each). This isn't coincidental. They're stress-testing your ability to combine data structures and optimize for O(1) operations under constraint. Sorting appears twice, monotonic stack once. Start with Merge Intervals and Daily Temperatures to build instinct, then move directly to the design gauntlet (LRU Cache, Insert Delete GetRandom). These two alone account for the design signal and force you to reason about amortized complexity. Find Median from Data Stream is the hard outlier; it's a heaps problem hiding in their list. If you haven't built a two-heap median solution before, drill it early. For the rolling-hash string problem, understand the collision mechanics. During the live OA, if you blank on any of these patterns, StealthCoder is your safety net, solving it in real time while the proctor sees nothing.
Companies with similar patterns
If you prepped for Okta, these companies recycle ~60% of the same topics.
You've seen the list.
Now make sure you pass Okta.
Memorizing every problem above in a week is a fantasy. StealthCoder is the hedge: an AI overlay that's invisible during screen share. It reads the problem on screen and surfaces a working solution in under 2 seconds. Built by an Amazon engineer who used it to pass JPMorgan's OA and system design loop. Works on HackerRank, CodeSignal, CoderPad, and Karat.
Okta interview FAQ
Should I prioritize design problems or array-sorting patterns for Okta?+
Design first. Three of seven problems are design-focused (LRU Cache, Insert Delete GetRandom, Find Median), and they're what separate solid candidates from strong ones. Array and sorting come naturally after you've nailed the design mechanics.
Is one hard problem enough reason to study heap data structures heavily?+
Yes. Find Median from Data Stream is the only hard problem Okta reports, and it's a two-heap classic. It's likely high-signal for them. Understand min-heap and max-heap coordination before your assessment.
How many hash-table problems should I drill for Okta?+
Hash tables appear in three problems across the list. Drill the hash function and rolling-hash collision mechanics in Strings Differ by One Character, then move to hash-table optimization in LRU Cache and Insert Delete GetRandom. Three targeted drills beat ten generic ones.
What if I freeze on a design problem mid-interview?+
That's where StealthCoder matters most. Design problems require synthesis of multiple data structures (linked lists, heaps, hash tables). If you blank mid-OA, StealthCoder reads the problem and surfaces a working solution invisibly, no proctor visibility, no screen-share detection.
Is monotonic stack worth drilling if it only appears once?+
Yes, but second. Daily Temperatures is your entry point (medium difficulty, clear pattern). Understanding monotonic stacks unlocks several array-optimization problems. Drill it after your design gauntlet, not before.