Find Interview Questions for Netlight

Right Answer:
Kanban focuses on visualizing workflow, limiting work in progress (WIP), and continuous flow. Scrum uses time-boxed iterations (sprints) with specific roles (Scrum Master, Product Owner, Development Team) and events (sprint planning, daily scrum, sprint review, sprint retrospective).

Use Kanban when you need continuous delivery, have evolving priorities, and want to improve workflow incrementally. Use Scrum when you need structured development with fixed-length iterations, have clear goals for each iteration, and benefit from team collaboration with defined roles.

Right Answer:
I would assess the organization's context, choose a suitable scaling framework like SAFe or LeSS based on needs, implement it incrementally with training and coaching, focusing on value delivery, and continuously inspect and adapt the implementation based on feedback and results.

Right Answer:
Agile ceremonies are recurring meetings within a sprint to facilitate communication, planning, and continuous improvement.

* **Sprint Planning:** The team decides what work to complete in the upcoming sprint. They discuss user stories, estimate effort, and define the sprint goal.

* **Daily Stand-up:** A brief daily meeting where the team shares progress, identifies roadblocks, and coordinates efforts. Each member typically answers: What did I do yesterday? What will I do today? Are there any impediments?

* **Sprint Review:** The team demonstrates the completed work to stakeholders, gathering feedback and ensuring alignment with expectations.

* **Sprint Retrospective:** The team reflects on the past sprint, identifying what went well, what could be improved, and defining action items to enhance future performance.

Right Answer:
The Agile Manifesto values:

* **Individuals and interactions** over processes and tools.
* **Working software** over comprehensive documentation.
* **Customer collaboration** over contract negotiation.
* **Responding to change** over following a plan.

That is, while the items on the right have value, we value the items on the left more.

Right Answer:
I've used tools like Jira, Azure DevOps, and Trello for Agile project management. I choose them based on project needs; Jira for complex workflows and robust reporting, Azure DevOps for integrated development environments, and Trello for simpler, visually-oriented task management.

Right Answer:
API versioning is the practice of managing changes to an API by assigning version numbers to different iterations of the API. It is important because it allows developers to introduce new features or make changes without breaking existing client applications that rely on older versions, ensuring backward compatibility and a smoother transition for users.

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 testing is the process of verifying that an application programming interface (API) functions as expected, ensuring it meets the requirements for functionality, reliability, performance, and security. Tools that can be used for API testing include Postman, SoapUI, JMeter, RestAssured, and Swagger.

Right Answer:
API authentication is the process of verifying the identity of a user or application trying to access an API. Common methods include:

1. **API Keys**: Unique keys provided to users to access the API.
2. **Basic Authentication**: Uses a username and password encoded in Base64.
3. **OAuth**: A token-based authentication method that allows users to grant limited access to their resources without sharing credentials.
4. **JWT (JSON Web Tokens)**: A compact, URL-safe means of representing claims to be transferred between two parties, often used for stateless authentication.
5. **HMAC (Hash-based Message Authentication Code)**: Uses a secret key to create a hash of the request, ensuring data integrity and authenticity.

Right Answer:
HTTP methods are standardized request types used in APIs to perform actions on resources. The main methods are:

1. **GET**: Retrieve data from a server.
2. **POST**: Send data to a server to create a new resource.
3. **PUT**: Update an existing resource on the server.
4. **DELETE**: Remove a resource from the server.
5. **PATCH**: Apply partial modifications to a resource.

These methods define the action to be performed on the specified resource in the API.

Right Answer:
To develop a healthy camp environment, ensure clear communication, promote teamwork, establish safety protocols, encourage respect and inclusivity, provide adequate resources, and foster a positive atmosphere through activities and support.

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:
Regression analysis is a statistical method used to examine the relationship between one dependent variable and one or more independent variables. It is used to predict outcomes, identify trends, and understand the strength of relationships in data.

Right Answer:
Data analysis is the process of inspecting, cleaning, and modeling data to discover useful information, draw conclusions, and support decision-making. It is important because it helps organizations make informed decisions, identify trends, improve efficiency, and solve problems based on data-driven insights.

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:
Classification analysis is a data analysis technique used to categorize data into predefined classes or groups. It works by using algorithms to learn from a training dataset, where the outcomes are known, and then applying this learned model to classify new, unseen data based on its features. Common algorithms include decision trees, logistic regression, and support vector machines.