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Datadog

Unify logs, metrics, and traces from across your distributed infrastructure.

What is Datadog?

Datadog is the leading service for cloud-scale monitoring. It is used by IT, operations, and development teams who build and operate applications that run on dynamic or hybrid cloud infrastructure. Start monitoring in minutes with Datadog!
Datadog is a tool in the Performance Monitoring category of a tech stack.

Who uses Datadog?

Companies
960 companies reportedly use Datadog in their tech stacks, including Airbnb, Facebook, and Spotify.

Developers
4230 developers on StackShare have stated that they use Datadog.

Datadog Integrations

GitHub, Python, Git, Node.js, and Docker are some of the popular tools that integrate with Datadog. Here's a list of all 161 tools that integrate with Datadog.
Pros of Datadog
130
Monitoring for many apps (databases, web servers, etc)
103
Easy setup
83
Powerful ui
80
Powerful integrations
66
Great value
50
Great visualization
41
Events + metrics = clarity
39
Custom metrics
38
Notifications
36
Flexibility
16
Free & paid plans
13
Great customer support
12
Makes my life easier
7
Adapts automatically as i scale up
7
Easy setup and plugins
5
Super easy and powerful
4
In-context collaboration
4
AWS support
3
Rich in features
2
Cost
2
Docker support
2
Best than others
1
Full visibility of applications
1
Automation tools
1
Monitor almost everything
1
Free setup
1
Simple, powerful, great for infra
1
Easy to Analyze
1
Expensive
1
Cute logo
1
Source control and bug tracking
Decisions about Datadog

Here are some stack decisions, common use cases and reviews by companies and developers who chose Datadog in their tech stack.

Shared insights
on
DatadogDatadog
at

We use Datadog to centralise our log outputs, monitor our hosts and set alerts for our tools.

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Farzeem Diamond Jiwani
Software Engineer at IVP | 5 upvotes 路 459K views

Hey there! We are looking at Datadog, Dynatrace, AppDynamics, and New Relic as options for our web application monitoring.

Current Environment: .NET Core Web app hosted on Microsoft IIS

Future Environment: Web app will be hosted on Microsoft Azure

Tech Stacks: IIS, RabbitMQ, Redis, Microsoft SQL Server

Requirement: Infra Monitoring, APM, Real - User Monitoring (User activity monitoring i.e., time spent on a page, most active page, etc.), Service Tracing, Root Cause Analysis, and Centralized Log Management.

Please advise on the above. Thanks!

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Shared insights
on
DatadogDatadogZabbixZabbixCentreonCentreon

My team is divided on using Centreon or Zabbix for enterprise monitoring and alert automation. Can someone let us know which one is better? There is one more tool called Datadog that we are using for cloud assets. Of course, Datadog presents us with huge bills. So we want to have a comparative study. Suggestions and advice are welcome. Thanks!

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We are looking for a centralised monitoring solution for our application deployed on Amazon EKS. We would like to monitor using metrics from Kubernetes, AWS services (NeptuneDB, AWS Elastic Load Balancing (ELB), Amazon EBS, Amazon S3, etc) and application microservice's custom metrics.

We are expected to use around 80 microservices (not replicas). I think a total of 200-250 microservices will be there in the system with 10-12 slave nodes.

We tried Prometheus but it looks like maintenance is a big issue. We need to manage scaling, maintaining the storage, and dealing with multiple exporters and Grafana. I felt this itself needs few dedicated resources (at least 2-3 people) to manage. Not sure if I am thinking in the correct direction. Please confirm.

You mentioned Datadog and Sysdig charges per host. Does it charge per slave node?

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Greg Smethells
CTO and Software Architect at Medstrat | 3 upvotes 路 32.6K views

We use AppOptics. I am curious what are the current leaders for APM for small companies (50 employees) that use Python, MariaDB, RabbitMQ, and Google Cloud Storage. We run both Celery and Gunicorn services. We are considering Datadog or some other deep code profiling tool that can spot I/O, DB, or other response time/request rate issues

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Dewald Swanepoel
Shared insights
on
DatadogDatadogStatsDStatsD

I see StatsD is commonly used in conjunction with Datadog. In fact, Datadog even has their own StatsD daemon (called DogStatsD) embedded in the DataDog agent. Can someone explain to me what it is that StatsD gives you which you don't already have with Datadog's APM and distributed tracing functionality?

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Blog Posts

GitHubPythonGit+22
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GitHubGitDocker+34
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GitHubPythonNode.js+26
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GitHubSlackMySQL+44
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Datadog's Features

  • 14-day Free Trial for an unlimited number of hosts
  • 200+ turn-key integrations for data aggregation
  • Clean graphs of StatsD and other integrations
  • Slice and dice graphs and alerts by tags, roles, and more
  • Easy-to-use search for hosts, metrics, and tags
  • Alert notifications via e-mail and PagerDuty
  • Receive alerts on any metric, for a single host or an entire cluster
  • Full API access in more than 15 languages
  • Overlay metrics and events across disparate sources
  • Out-of-the-box and customizable monitoring dashboards
  • Easy way to compute rates, ratios, averages, or integrals
  • Sampling intervals of 10 seconds
  • Mute all alerts with 1 click during upgrades and maintenance
  • Tools for team collaboration

Datadog Alternatives & Comparisons

What are some alternatives to Datadog?
New Relic
New Relic is the all-in-one web application performance tool that lets you see performance from the end user experience, through servers, and down to the line of application code.
Splunk
It provides the leading platform for Operational Intelligence. Customers use it to search, monitor, analyze and visualize machine data.
Prometheus
Prometheus is a systems and service monitoring system. It collects metrics from configured targets at given intervals, evaluates rule expressions, displays the results, and can trigger alerts if some condition is observed to be true.
Grafana
Grafana is a general purpose dashboard and graph composer. It's focused on providing rich ways to visualize time series metrics, mainly though graphs but supports other ways to visualize data through a pluggable panel architecture. It currently has rich support for for Graphite, InfluxDB and OpenTSDB. But supports other data sources via plugins.
AppDynamics
AppDynamics develops application performance management (APM) solutions that deliver problem resolution for highly distributed applications through transaction flow monitoring and deep diagnostics.
See all alternatives

Datadog's Followers
4558 developers follow Datadog to keep up with related blogs and decisions.