Datadog Interview Questions

Are you looking for a Datadog job? Are you ready to attend an interview for your next dream job? Do you want to ace your interview by coming prepared? This article will cover frequently asked Datadog interview questions and how to respond to them. With this knowledge, you'll be able to confidently walk into your interview and land the job you want. We will help you summarize all the important questions and answers, making it much easier to score good marks in the interview.

Datadog is a data monitoring analytics tool based on the SaaS platform. It is designed for DevOps teams and can be used to evaluate event monitoring and performance metrics for infrastructure and cloud services. 

Some things to know about Datadog

  • Datadog is compatible with many programming languages, tools, and services and can be installed locally or in a cloud environment. Datadog uses PostgreSQL, Kafka, and other Agents created with the Go framework.
  • Datadog, a company specializing in cloud-based monitoring and analytics, is always looking for skilled engineers to join their team and contribute to developing the best product for their clientele.

We'll look at some often-asked Datadog interview questions, split into the two sections below.

Top 10 Datadog Questions

  1. What are the Datadog Features?
  2. What companies compete with Datadog?
  3. How Datadog collects data?
  4. What are the primary advantages of using Datadog?
  5. What characteristics does Datadog have?
  6. What is a Datadog span?
  7. Which Scalable Systems are monitored by Datadog?
  8. What is a tool for APM?
  9. What exactly does Datadog do?
  10. How does a Datadog help?

Top Datadog Interview Questions  for Freshers

1. What is a Datadog?

Datadog is a SaaS-based monitoring and data analytics tool. It's made for IT and DevOps groups and can be used to monitor infrastructure and cloud services for performance metrics and events. The software allows for monitoring tools, servers, and data stores.

Datadog Platform

2. Who makes use of Datadog?

Examples of businesses using Datadog

  • Zendesk Inc
  • Lorven Technologies
If you want to gain more knowledge on Datadog, then enroll your name in the Datadog Training Program Course.

3. What is a Datadog agent?

Datadog Agent is software that will be installed on your hosts. Datadog receives host-generated metrics and events for performance and monitoring analysis. 

The code for the Datadog Agent can be found at DataDog/datadog-agent on GitHub.

Datadog Agent

4. How does Datadog store data?

Datadog data is stored in various places, but a centralized query system compiles relevant information from all of them and provides it to the user in various formats, such as APIs, dashboards, and monitoring and alerting tools.

5. What are the Datadog Features?

Some of the Features of Datadog are

  • Datadog makes use of flexible dashboards.
  • Datadog alerts people to critical issues that need their attention.
  • Datadog can monitor and analyze things like logs, latency, and error rates.
  • Datadog helps because it lets people use the API.
  • Apps written in PHP, Python, Node, Go, and Java can all be monitored and managed with Datadog.
  • Datadog gives DevOps or IT Teams a single view of a company's infrastructure.

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6. Why would you like to work for Datadog?

Datadog is looking for people who are interested in software technology, are curious, and have much drive. They want people who can talk to people well and analyze problems analytically. Datadog wants to hire people who like to look into things and aren't afraid to challenge themselves.

7. What companies compete with Datadog?

Datadog has competitors and other options.

  • Instana.
  • New Relic One.
  • Dynatrace.
  • Amazon CloudWatch.
  • AppDynamics.
  • ManageEngine Applications Manager.
  • SolarWinds Server & Application Monitor.
  • Microsoft Azure Application Insights.

8. How Datadog collects data?

Datadog retrieves information from AWS Lambda. This is something that can be achieved through the use of serverless monitoring. Integrations with log gathering and Datadog are inextricably linked to one another. Data Dog's specialized parsing, processors, and faces can be activated with the help of an integration default configuration file.

9. Can the log be sent to Datadog without the Datadog agent?

Yes, without using the Datadog agent, we can send server logs to Datadog using most of the familiar open-source log shippers, such as the HTTP API and fluent. However, there are many advantages to using the Datadog agent to collect server logs.

10. How do we use exometry to transmit Datadog tags?

We can use Exometer in conjunction with the exometer_report _statsd reporter to determine the response time of the endpoints.


exometer.update [:app_name, :webapp, :resp_time]

11. What are the primary advantages of using Datadog?

  • Datadog correlates metrics from cloud providers, SaaS tools, web servers, StatsID databases, and other services.
  • Using real-time dashboards, Datadog can quickly analyze, alert, and graph our vast data.
  • So that we can concentrate on those issues, Datadog can filter performance metrics.
  • By updating and adding comments to annotations for our production data, Datadog promotes team collaboration.

12. Does Datadog have a way to determine the duration between logs?

We can use the transaction command in Splunk, which can show the time between logs in the following ways

2020-01-01 12:12 event=START id=5
2020-01-01 12:13 event=STOP id=5

13. What types of problems does Datadog resolve?

Many businesses of varying sizes worldwide use Datadog because it simplifies the process of migrating to the cloud and undergoing digital transformation while also enhancing communication between the teams responsible for network operations, software development, and business management.

Top Datadog Interview Questions for Experienced

1. How do we use JQ to stringify JSON in Datadog?

Using JQ, we can stringify JSON by using the derivation shown below

      "title": "456789-accesslogs",
      "text": "{\"region\": \"CA\",\"waf_rule_tags\": \"{\\\"RULEID:942100\\\":[\\\"application-multi\\\",\\\"language-multi\\\",\\\"
      "priority": "normal",
      "tags": ["environment: test"],
      "alert_type": "info"


2. What makes a Cliff AI different from a Datadog?

  • is a business reliability tool that lets you keep an eye on your key operational and business metrics without requiring you to build any dashboards or complex data pipelines. 
  • You can access this functionality by simply logging into the platform. This is since using does not necessitate the construction of either. 
  • Cliff offers support for the activities you monitor for your company in a manner that is analogous to how you monitor the company's operations.

3. What distinguishes Datadog?

Fundamentally speaking, Datadog is more concerned with cloud monitoring and security. In addition, it gives users access to any location, at any scale, and within any stack or application.

4. Where are the Datadog files stored?

All of the data that goes back and forth between Datadog and its users is encrypted and protected by Transport Layer Security (TLS) and HTTP Strict Transport Security (HSTS).

5. Is Datadog involved in cybersecurity?

Monitors can identify online threats across your applications, networks, and infrastructure when using Datadog.

Related Article: What is Cyber Security?

6. Is Datadog hosted on Azure?

Datadog is a unified service hosted on Azure. Utilizing the Azure portal allows for effective management of the integration as well as the provisioning of Datadog.

7. What characteristics does Datadog have?

The characteristics of using Datadog are outlined below.

  • The primary goal of Datadog is to provide IT and other DevOps teams with a comprehensive view of their infrastructure.
  • Datadog is also utilized using its flexible dashboards.
  • Datadog is also used to send out urgent problem alerts.

8. Is Datadog used by Amazon?

Datadog is an AWS Advanced Technology Partner and has the DevOps, Microsoft Workloads, AWS Migration, and Containers Competencies.

9. What are the most important reasons to use Datadog?

Datadog is also used to correlate metrics from our SaaS, cloud providers, web servers, tools, stats, SQL, and NoSQL databases, as well as our apps, tools, and other services.

The vast amount of data we have can be quickly analyzed, alerted on, and graphed by Datadog thanks to real-time dashboards.

10. What is a Datadog span?

A service entry span is a span that is used as the starting point for a request for a service. When a flame graph's color deviates from its direct parent's, you can see this in Datadog APM. When viewed, the list of services is displayed to the right of a flame graph.

Datadog Span

11. Which Scalable Systems are monitored by Datadog?

Datadog is a platform that functions effectively in the cloud and is primarily aware of the challenges businesses face when attempting to scale their applications.

12. How will you calculate the interval between Datadog logs?

Splunk, which has some of the transactions that command and can help produce duration between the logs, is easy to use. Splunk also has some of the transactions that command.

13. Describe what makes you want to work for Datadog.

Datadog is a highly inquisitive company backed by a sizable community of people passionate about software and technology. People who can quickly and analytically solve problems and those who possess excellent communication skills are always in high demand.

14. How big or small is Datadog?

Along with retirement planning, employer-paid health insurance, and a host of other benefits, the company has provided eligible workers with various remote and work-from-anywhere positions.

Related Article: Datadog Tutorial

15. What is a tool for APM?

  • Performance monitoring is the process of keeping tabs on critical and software application performance metrics (APM) through telemetry data and monitoring software. 
  • Performance monitoring is also known as application metrics tracking.

Frequently Asked Datadog Interview Questions

1. What are the main differences between Grafana and Datadog?

Datadog is primarily a subscription-based software as a service platform that provides various products to monitor technological infrastructure and applications. 

At the same time, Grafana is an open-source web visualization tool that makes it simple to create dashboards by combining data from many different sources.

2. How did you think the name Datadog got started?

When they established Datadog in the early 2010s, cloud migration was starting. The DevOps movement is essential to the cloud migration that was starting. … Because it was the real name of something that caused pain and fear, we decided to use Data dog 17 as a code name when we first started the company. But we always planned to come up with more 

3. Can Datadog be run locally?

Developing on your own with the help of DataDog. You can do that by creating a personal account on our website. Hosting your own local DataDog agent and sending metrics to your DataDog environment are covered.

4. Can Datadog be used on-site?

No matter where or how teams deploy their services, Datadog gives teams complete visibility into every layer of an on-premise environment.

5. What programming language is used to write the Datadog Agent?

The Datadog agent is written or scripted in Go.

6. How does Datadog store its data?

Datadog uses a database called Kafka for its operations to store its data.

7. What exactly does Datadog do?

The Datadog Agent is a piece of software that operates on your server(s). It also collects host metrics and events and sends them to Datadog so you can quickly analyze monitoring and performance data.

8. Does Datadog use Python?

Datadog lets you quickly start monitoring Python applications and lower your compute costs with machine learning-based alerts, automatic code instrumentation, out-of-the-box dashboards, and seamless telemetry data correlation.

Related Article: Python Tutorial

9. What software is used by Datadog?

Datadog employs a Go-based agent and a backend composed of PostgreSQL, Apache Cassandra, and Kafka. A Rest application program interface (API) integrates Datadog with various programming languages. For example, Chef, Ubuntu, Kubernetes, Ansible, Puppet, and Bitbucket integrations.

10. How does a Datadog help?

With the assistance of Datadog's insightful analysis, technology companies can make decisions based on the data gathered and accomplish particular goals in enhancing their products.


During interviews, candidates are frequently questioned with variations of the Datadog Interview questions that have been mentioned above. If you want to be successful in an interview, look over these questions and ensure that you are well-prepared for the interview to pass the exam. Candidates who are interested in acing the interview on their very first try will undoubtedly benefit from all of these kinds of questions.

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Last updated: 03 Apr 2023
About Author


Madhuri is a Senior Content Creator at MindMajix. She has written about a range of different topics on various technologies, which include, Splunk, Tensorflow, Selenium, and CEH. She spends most of her time researching on technology, and startups. Connect with her via LinkedIn and Twitter .

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