Hashicorp Interview Questions (11+ Questions)

The server is used by multiple teams with their own credentials, meaning each team has a username. We need to identify which user, meaning which team is running most number of processes, meaning count regardless of CPU or memory. We need to take list of running processes by typing PS a x. Use a WK to isolate only first column we can type print dollar sign $1 Sign one means first column. We can do sort to sort this. This will do an alphabetical sort, and then we can use unique hyphen C. Unique gives us unique values and Hy C will give us number of occurrences. Dev team has highest number of running processes. We need to write the name of the team into the solutions TXT file.

Troubleshoot intermittent service failures by tracking file modifications in Linux. Learn how to use the find command to locate files under /etc modified within the last 24 hours, filter results by user ownership (e.g., the nginx user), and format output with timestamps for easy correlation with deployment windows. This guide covers auditing configuration drift, identifying unauthorized or accidental script changes, and verifying file integrity to restore service stability.

Troubleshoot volume mounting failures by aligning volumeMode settings between PersistentVolume and PersistentVolumeClaim. Fix db-pod volumeMode mismatch, mount storage at /var/lib/data, and resolve Pending pod state. Essential for persistent storage configuration, volume management, storage class alignment, and ensuring pods can successfully claim and mount volumes.

Fix a failing Kubernetes Job by correcting the command entrypoint, mounting a ConfigMap volume to the required path, and setting the appropriate restart policy. Edit the manifest file, replace the broken Job, and verify successful completion with exit code 0.

We have a deployment script that runs on every push. The problem is that when someone pushes multiple commits in quick succession, multiple workflows will start running at the same time. These overlapping deployments cause resource conflicts and can leave the production environment in an inconsisten...

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We have a deployment workflow that needs to be triggered manually. The operator should be able to choose which environment to deploy, either staging or production, at trigger time, without modifying any code. We need to set up a workflow_dispatch trigger with input parameters for staging and prod. W...

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We need to harden a GitHub Actions workflow by following the principle of least privilege. By default, the GitHub token that workflows use has a read/write access to the repository, thus more access than most jobs need. We need to lock everything down to read-only by default and only grant write acc...

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Here we will be working with Pandas. Pandas is a library that was specifically designed for data analysis and manipulation. We have one CSV file that is called Stock Data. It contains daily price information within multiple companies. Each row has a date, ticker, and closing price. Our job here is to calculate rolling statistics, mean, sum, and standard deviation for the period of 7, 14, and 30 days separately for each ticker. In the output, we should have three original columns, plus nine new columns that we'll build. Rolling method in Pandas provides window calculation and allows us to perform aggregate operations. In order to start doing any operations on the file, we need to read it into DataFrame. Using for loop, we go through three window sizes, 7, 14, and 30 days. Then we group by ticker so that all the calculations run separately for each of them. We implement the rolling method and set that window equals to window. Mean will calculate the average of all values in each window. We need to save that DataFrame to a new CSV file using to_csv function.

SELECT
c.industry,
SUM(i.amount) AS total_investment
FROM {{ ref("companies") }} c
INNER JOIN {{ ref("investments") }} i
ON c.company_id = i.company_id
GROUP BY c.industry
ORDER BY total_investment DESC

def merge_triplets(triplets: list[list[int]], target: list[int]) -> bool:
good_indices = set()

for t in triplets:
    if t[0] > target[0] or t[1] > target[1] or t[2] > target[2]:
        continue
        
    for i, val in enumerate(t):
        if val == target[i]:
            good_indices.add(i)
            
    if len(good_indices) == 3:
        return True
        
return len(good_indices) == 3

SQL Query to Determine Supplier Performance Based on On-Time Deliveries

Objective

To determine the performance of suppliers by calculating the percentage of orders delivered on or before the expected date, you'll need to write an SQL query. The output should list each supplier's name, thei...

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