Find Interview Questions for Pantheon inc

Right Answer:
Synchronous API calls wait for the response before moving on to the next task, while asynchronous API calls allow the program to continue executing other tasks while waiting for the response.

Right Answer:
An API (Application Programming Interface) is a set of rules and protocols that allows different software applications to communicate with each other. It defines the methods and data formats that applications can use to request and exchange information. APIs work by sending requests from one application to another, which then processes the request and sends back a response.

Right Answer:
API documentation is a technical manual that explains how to use an API, including its endpoints, request and response formats, authentication methods, and examples. It is necessary because it helps developers understand how to integrate and interact with the API effectively, ensuring proper usage and reducing errors.

Right Answer:
The different types of APIs are:

1. **Open APIs (Public APIs)** - Available to developers and third parties.
2. **Internal APIs (Private APIs)** - Used within an organization.
3. **Partner APIs** - Shared with specific business partners.
4. **Composite APIs** - Combine multiple endpoints into a single call.
5. **Web APIs** - Accessible over the internet using HTTP/HTTPS.

Right Answer:
The common status codes in HTTP responses are:

- **200**: OK
- **201**: Created
- **204**: No Content
- **400**: Bad Request
- **401**: Unauthorized
- **403**: Forbidden
- **404**: Not Found
- **500**: Internal Server Error
- **502**: Bad Gateway
- **503**: Service Unavailable

Right Answer:
The purpose of feature engineering in data analysis is to create, modify, or select variables (features) that improve the performance of machine learning models by making the data more relevant and informative for the analysis.

Right Answer:
The different types of data analysis are:

1. Descriptive Analysis
2. Diagnostic Analysis
3. Predictive Analysis
4. Prescriptive Analysis
5. Exploratory Analysis

Right Answer:
Data normalization is the process of organizing data in a database to reduce redundancy and improve data integrity. It involves structuring the data into tables and defining relationships between them. Normalization is important because it helps eliminate duplicate data, ensures data consistency, and makes it easier to maintain and update the database.

Right Answer:
1. Remove duplicates
2. Handle missing values
3. Correct inconsistencies
4. Standardize formats
5. Filter out irrelevant data
6. Validate data accuracy
7. Normalize data if necessary

Right Answer:
Correlation is a statistical measure that indicates the extent to which two variables fluctuate together, while causation implies that one variable directly affects or causes a change in another variable.

Right Answer:
1. Relevant and compelling headline
2. Clear and concise content
3. Strong call-to-action (CTA)
4. Fast loading speed
5. Mobile-friendly design
6. Trust signals (e.g., testimonials, reviews)
7. Minimal distractions (e.g., limited navigation)
8. Consistent messaging with the ad
9. High-quality images or videos
10. Easy-to-fill forms

Right Answer:
A responsive website is designed to automatically adjust its layout and content to fit different screen sizes and devices, providing an optimal viewing experience on desktops, tablets, and smartphones.

Right Answer:
White Hat SEO practices are ethical techniques that follow search engine guidelines to improve website ranking, focusing on quality content and user experience. Black Hat SEO practices involve unethical techniques that violate search engine guidelines, such as keyword stuffing and link farming, aiming for quick results but risking penalties.

Right Answer:
On-Page SEO refers to the optimization of elements on a website, such as content, HTML tags, and internal links, to improve its visibility in search engines. Off-Page SEO involves activities outside the website, like building backlinks, social media marketing, and online reputation management, to enhance its authority and ranking.

Right Answer:

To set up an alerting escalation policy, follow these steps:

1. **Define Alert Criteria**: Identify the conditions that trigger alerts (e.g., CPU usage, downtime).
2. **Set Alert Severity Levels**: Classify alerts by severity (e.g., critical, warning, info).
3. **Establish Notification Channels**: Decide how alerts will be communicated (e.g., email, SMS, chat).
4. **Create Escalation Paths**: Outline who gets notified first and who to escalate to if the issue isn’t resolved within a set timeframe.
5. **Set Response Timeframes**: Define how quickly each level of escalation should respond.
6. **Document the Process**: Ensure all team members understand the escalation policy.
7. **Test the Policy**: Regularly test the alerting system to ensure it works as intended.
8. **Review and Adjust**: Periodically review the policy for effectiveness and make adjustments as necessary.

Right Answer:

The components of IT infrastructure that should be monitored include:

1. Servers
2. Network devices (routers, switches, firewalls)
3. Storage systems
4. Applications and services
5. Databases
6. Virtual machines and containers
7. Cloud resources
8. End-user devices (desktops, laptops, mobile devices)
9. Power and cooling systems
10. Security systems and logs

Right Answer:

False positives in monitoring occur when an alert is triggered for an issue that isn't actually present, while false negatives happen when a real issue exists but no alert is triggered. To reduce them, you can fine-tune alert thresholds, implement better anomaly detection algorithms, use correlation rules to filter out noise, and regularly review and adjust monitoring configurations based on historical data and trends.

Right Answer:

The ELK stack consists of Elasticsearch, Logstash, and Kibana. It is used in infrastructure monitoring to collect, store, analyze, and visualize log data from various sources. Elasticsearch indexes the data, Logstash processes and ingests it, and Kibana provides a user-friendly interface for visualizing and querying the data, helping to identify issues and monitor system performance.

Right Answer:

Proactive monitoring involves actively checking systems and applications to identify and resolve potential issues before they affect performance, while reactive monitoring occurs after an issue has been detected, focusing on responding to and fixing problems as they arise.