Visa Interview Questions (12+ Questions)

Learn how to diagnose and restore outbound SMTP connectivity using Linux Bash commands and firewall management. This guide covers identifying active firewalls, inspecting outbound rules, allowing SMTP port 25, testing connectivity, and verifying fixes, essential for troubleshooting email delivery issues and managing host-level firewall policies in production systems.

Kubernetes NGINX Ingress Canary: 10% app-v2 Auto-Rollback hashicorp/http-echo. Production-grade canary deployment in canary namespace with NGINX Ingress traffic splitting: 90% app-v1 (3 replicas) vs 10% app-v2 (1 replica) using hashicorp/http-echo containers. Dual Ingress app-ingress + app-ingress-canary with canary-weight: 10, header routing X-Canary: true, and auto-rollback script on >5 v2 pod restarts. Perfect for progressive delivery, A/B testing infrastructure, golden path releases, SRE automation, and zero-risk production deployments.

We need to build a Docker image once for staging, extract its unique fingerprint, which is called as a digest, and promote that exact image to production without rebuilding. The key principle is immutability. We never rebuild for production because rebuilding could pull in newer dependencies that we...

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We need to run integration tests against a real PostgreSQL database. GitHub Actions lets us spin up a database as a service container right alongside our job. The container starts before the steps run. It is available throughout the job and is automatically cleaned up when the job finishes. Service ...

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def subsets(nums: list[int]) -> list[list[int]]:
res = []

def dfs(i, current_subset):
    res.append(current_subset.copy())
    
    for j in range(i, len(nums)):
        current_subset.append(nums[j])
        dfs(j + 1, current_subset)
        current_subset.pop()
        
dfs(0, [])
return res

We'll insert new records into database from CSV file using SQLite and Pandas. We have one CSV file that is called New Customers. It contains customer records that need to be imported in a SQLite database. The problem is that some of these customers might already exist in the database file. SQLite is a lightweight database that stores everything in a single file. Our job here is to read the CSV file, check which records already exist, and make sure we only include the new ones. We will use the connect function where we define the path to the file. Then within this object, we implement cursor. We read the given CSV file into a DataFrame that will be called df. Using cursor execute will run the SQL query. In the query itself, we select ID column from customers table. Fetchall function will retrieve all the results as a list of tuples. The tilde symbol is used here to flip true to false and false to true. Cursor execute will run the insert statement. Instead of putting the values directly in the SQL string, we will use the question mark and pass the actual values as a separate tuple. We do it for security reasons to protect the data from SQL injection. We will use the commit function within our database to finalize and save all changes. Finally, we close the database.

WITH combined AS (
SELECT
i.investment_id,
COALESCE(fd.fund_id, i.fund_id) AS fund_id,
COALESCE(f.firm_id, fd.firm_id) AS firm_id,
f.firm_name,
f.founded_year,
f.location,
fd.fund_name,
fd.fund_size,
fd.fund_start_year,
fd.fund_end_year,
i.company_name,
i.investment_amount,
i.investment_date
FROM {{ ref("firms") }} f
FULL OUTER JOIN {{ ref("funds") }} fd
ON f.firm_id = fd.firm_id
FULL OUTER JOIN {{ ref("investments") }} i
ON fd.fund_id = i.fund_id
)
SELECT *
FROM combined
WHERE NOT (
investment_id IS NULL
AND fund_id IS NULL
AND firm_id IS NULL
AND firm_name IS NULL
AND founded_year IS NULL
AND location IS NULL
AND fund_name IS NULL
AND fund_size IS NULL
AND fund_start_year IS NULL
AND fund_end_year IS NULL
AND company_name IS NULL
AND investment_amount IS NULL
AND investment_date IS NULL
)

Master data aggregation in PySpark. Learn how to join tables, perform multi-column GroupBy operations, and cast aggregated sums to specific data types.

Interview Question: SQL Query for Employee Performance and Bonus Status

Objective:

Crafting an SQL query to showcase employees' names, performance scores, annual salaries, and bonus statuses is an essential exercise in database management. This query will help in evaluating and rewarding ...

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def trap(height: list[int]) -> int:
if not height:
return 0

l, r = 0, len(height) - 1
left_max, right_max = height[l], height[r]
res = 0

while l < r:
    if left_max < right_max:
        l += 1
        left_max = max(left_max, height[l])
        res += left_max - height[l]
    else:
        r -= 1
        right_max = max(right_max, height[r])
        res += right_max - height[r]
        
return res

def find_itinerary(tickets: list[list[str]]) -> list[str]:
adj = defaultdict(list)

tickets.sort(reverse=True)

for src, dst in tickets:
    adj[src].append(dst)
    
res = []

def dfs(src):
    while adj[src]:
        dst = adj[src].pop()
        dfs(dst)
    res.append(src)
    
dfs("JFK")
res.reverse()

return res

How to Identify Customers with Multiple Orders on the Same Date in SQL

Interview Question Objective

Write an SQL query to identify customers who have placed multiple orders on the same date. The query should return distinct pairs of customer names and order dates, sorted by the order date...

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