How to Crack Samsara Coding Interviews in 2026

Samsara’s coding interviews are designed to assess how you engineer solutions for real-world physical operations—think fleets, equipment, and industrial data. The problems often mirror the company’s domain: processing streams of sensor data, optimizing routes, or managing state over time. While challenging, the interview has a predictable structure that you can prepare for systematically.

By the Numbers — Difficulty Breakdown and What It Means

Based on historical data, a typical Samsara coding round consists of about five questions. The breakdown is one Easy (20%), three Medium (60%), and one Hard (20%) problem. This distribution is crucial for your strategy.

The single Easy question is your warm-up and confidence builder; failing here is a major red flag. The three Medium problems are the core of the interview. Success here demonstrates solid algorithmic competence and clean coding. The single Hard question is the differentiator. You are not necessarily expected to produce a perfectly optimized solution under time pressure, but you must show strong problem-solving instincts, communicate your thought process clearly, and make meaningful progress. Your goal should be to ace the Easy and Medium problems while putting up a strong fight on the Hard one.

Top Topics to Focus On

The most frequent topics are Array, Sliding Window, String, Simulation, and Two Pointers. These are not random; they directly relate to Samsara’s work with time-series data, log parsing, and sequential event processing.

• Array & Two Pointers: Fundamental for manipulating datasets. Two Pointers is essential for optimizing operations on sorted data or finding pairs.
• Sliding Window: The most critical pattern for Samsara. It’s the go-to technique for analyzing contiguous subsequences in data streams—like calculating maximum load in a time window or the longest subarray meeting a condition.
• String: Often involves parsing logs, serial numbers, or GPS coordinates. Focus on efficient searching and manipulation.
• Simulation: Tests your ability to meticulously model a process, like a vehicle moving through a depot or a state machine for equipment status. It’s less about clever algorithms and more about robust, bug-free code.

Given its importance, here is a template for the Sliding Window pattern, which you must know cold. This example finds the length of the longest subarray with a sum less than or equal to a target k.

def longest_subarray_sum_at_most_k(nums, k):
    left = 0
    current_sum = 0
    max_length = 0

    for right in range(len(nums)):
        current_sum += nums[right]

        # Shrink the window from the left if sum exceeds k
        while current_sum > k:
            current_sum -= nums[left]
            left += 1

        # Update the maximum length of the valid window
        max_length = max(max_length, right - left + 1)

    return max_length

Preparation Strategy — A 4-6 Week Study Plan

A focused, topic-driven plan is more effective than random practice.

Weeks 1-2: Foundation. Master the top five topics. For each, solve 10-15 problems on a platform like CodeJeet, starting with Easy and progressing to Medium. Implement each solution in your primary language, then re-implement it in a second language to deepen understanding. Build your own code templates for Sliding Window and Two Pointers.

Weeks 3-4: Integration and Difficulty Ramp. Start mixing topics. Practice problems that combine patterns, like a Simulation that uses Array manipulation. Dedicate at least two full sessions to solving 4-5 problems in 60-70 minutes to simulate the interview's pace and mental stamina required. Begin tackling Hard problems; focus on understanding the solution approach even if you can't code it fully at first.

Weeks 5-6: Mock Interviews and Company-Specific Prep. Conduct at least 3-5 mock interviews with the exact Samsara format (5 questions, mixed difficulty). Use a timer and verbalize your thinking. In the final week, solve only Samsara-tagged problems. Review your error log and re-solve any problems you previously got wrong or solved inefficiently.

Key Tips

1. Communicate the "Why." When you choose Sliding Window over a brute-force approach, explain why: "This reduces the time complexity from O(n²) to O(n) because we process each element at most twice." This shows engineering judgment.
2. Prioritize Correctness First. For Simulation problems, a complete, correct, and readable solution is better than an optimized but buggy one. Write clear logic, then optimize if time allows.
3. Test with Edge Cases. Before declaring a problem finished, run through edge cases: empty input, single element, large values, negative numbers. State these aloud. It demonstrates professional habits.
4. Manage the Clock. If you hit a 10-minute wall on the Hard problem, pause. Summarize your current approach, state a simpler fallback (e.g., "I could implement a brute-force solution first to ensure correctness"), and ask the interviewer how they would like you to proceed. This is better than silent struggle.

Samsara’s interviews test for both algorithmic skill and practical, clean coding under constraints. Target the high-frequency topics, practice under timed conditions, and articulate your reasoning. Consistent, focused practice on the right material is the most reliable path to success.

Browse all Samsara questions on CodeJeet