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December 07, 2020
Datadog is used by couple of departments within the organization. We are using it to monitor our infrastructure such as the servers, containers, processes, storage health as well as to load and look into the metrics.
- Single stop for monitoring various database types and their infrastructure.
- Easier to look into metrics history.
- Managing downtime for various resources is simple.
- It would be good if there were a way to remove resources from Datadog faster.
September 12, 2020
Datadog is an excellent infrastructure management tool. It provides a variety of tools for monitoring infrastructure and applications. It's APM tool offers a unique insight into application errors, while it's tracing can help with identifying hotspots and predicting growth in a variety of ways. It also provides an integrated log solution that aggregates and can map logs across applications and back to traces. It's up to date, with libraries and integrations for many tools and languages.
- Application Monitoring
- Log Management
- Events Tracking
- Infrastructure flow visualization
November 20, 2020
It is used to monitor multiple hosts for networking, compute, and memory along with application-level metrics (errors, performance, etc). This allows for site reliability engineers to determine the cause of errors and gain other data for root cause analysis (RCA).
- Visualization
- Network mapping
- Error finding
- Navigation to new areas can be counterintuitive.
March 09, 2020
We are testing and using Datadog in the e-commerce applications we are creating in a project to re-engineer our existing legacy applications, and transform them into a micro services based architecture hosted on several different cloud platforms. Datadog is helping us to monitor all the applications and the logging within a single pane of glass.
- APM monitoring.
- Logging.
- Alerts.
- Cost.
- Training.
- Documentation.
November 12, 2019
We use Datadog to monitor all kinds of application metrics: errors, network stats, response times, queues, and a bunch of application-specific metrics. We also have alerts set up that notify us of changes in production application performance. We also get a lot of metrics "for free" from all kinds of third-party tools (e.g. ElasticSearch, GitHub, Heroku, Cloudflare, etc).
- Thanks to the tool's versatility and a huge ecosystem around it, you can use it to track virtually anything.
- Powerful alert and warning configuration let you drastically reduce false positives.
- Runbooks give your team members guidance on how to act on alerts.
- Powerful data analysis features: you can slice and dice your data, almost the same way you can do it in a behavioral analytics tool. This means you can efficiently refine your metrics as your business grows.
- Overwhelming to use for newcomers.
- Even when you're familiar with the tool, finding the right metric or dashboard can be challenging unless you know exactly what you're looking for.
October 16, 2019
Our IT department uses Data Dog to monitor critical server uptime as well as switches and routers over SNMP. We also use the Data Dog API to write critical events for alerting and monitoring. We don’t currently use the application monitoring features, but I could see us using them in the future.
- Price.
- Functionality/extensibility.
- Support.
- Community.
- Documentation is lacking in some places.
- Some features could be easier to set-up.
- Favors customization over simplicity.
September 20, 2019
We had very complex monitoring requirements for APIs related to IoT and mobile app users. There were several different tools, no reliable results and we were losing credibility in the stability and reliability of our infrastructure. Also, all tools were very difficult to manage, implement and support, not to mention expensive.
- API monitoring
- End-user experience
- Easy to implement
- Agent-based
- Initial learning curve
- Azure integration could be easier
February 05, 2019
The engineering/dev-ops teams use DataDog as the tool of choice for monitoring our applications/servers, and for aggregating logs. All of our applications and micro-services use the DataDog Rest API to send metrics to, so that we can monitor performance and CPU usage, and setup alerts in case any issues arise.
- Great UX. Good looking dashboards and advanced graphs.
- Simple Rest API allowing integration with basically any service/application. Allows for the creation of a centralized source of data.
- Good API documentation and very responsive customer service.
- Good pricing model for micro-services. Can handle getting data from many sources without having to pay as much as alternatives.
- Limitation on what you can do with reporting and analytics. If you need to do very advanced mathematical/graphing operations, might need to use data in another BI Tool to accomplish.
- Good amount of upfront work to install and configure across your entire application/software stack. Heavy learning curve.
- Logging capabilities not as robust as alternatives like Splunk.
June 24, 2019
Our DevOps team utilizes DataDog to be aware of any abnormalities across our infrastructure, whether hosted or local. We can look in one place to see stats and alarms across all infrastructure, independent of hosting provider's console. Being a software company, we can also send events to DataDog via their API to generate alerts for certain activity within our applications.
- Server resource usage
- Multi-stage alerts based on configurable thresholds
- Custom Dashboards of all accumulated data
- We had a couple "integrations" that had some issues during setup, but Support addressed them very quickly
- Unnecessary alerts about DataDog components...by the time I see them, they're almost always also fixed
- I wish there was a DataDog mobile app that would have dedicated alerts (configurable per alert to override Do Not Disturb setting) instead of relying on emails notifications that could be overlooked in the midst of many incoming emails around the same time.
We use Datadog on almost all of our production systems to give us granularity into how systems are running, and additionally, use Datadog's logging feature to aggregate all of our logs across systems in real time. Datadog's simple dashboards enable visibility from different providers to be displayed all in one place, even if systems are not from the same vendor.
- Does a good job at log management with full search, live-access, and automatic archiving to S3 is also simple.
- APM is fantastic and gives great insights into production machines, but is not cheap.
- Because APM is billed by instance, it can be very expensive -- perhaps even more than the cost of the underlying instances depending on the kinds of systems you are running.
- While it's not difficult to deploy, it certainly has quirks owing to the limits of cloud platforms -- we wish it was easier to set up for some services.
DataDog is currently being used by Wayfair's Monitoring, Network Ops, and Critical Incident teams to provide a variety of data to provision, manage and maintain the existing infrastructure for internal and external sites and applications. It is a critical input to how these teams identify, tag, and respond to alerts within the company. We use Datadog for the current day to day provisioning tasks and well as prior/after any maintenance.
It has a key plug-in with ServiceNow and this is a key integration at Wayfair. ServiceNow is used as the reporting platform to store and index all DataDog alerting. Further, we have built several notification systems to piggy back off DataDog alerts for clear and wide-spread notifications to all stakeholders of a particular stack of technology.
The visuals and simple interface provides a clean and ready-made application in which to address the business and technical needs, for a rapidly evolving infrastructure. Wayfair has a tremendous amount of growth and we rely on this tool to grow and adapt alongside us. The Platform as a Service approach has proven to provide what we need, without the dependencies to support the infrastructure, which is a big bonus for our teams.
- APIs, the ability to interact with the data we pull into data dog is key. We port the information over to Servicenow, so the ability to pull everything into DataDog, then Servicenow, is a key component of our success here at Wayfair.
- Simple Interface - clean, useful, effective. Allows users to use DataDog for one reason, get work done.
- Lightweight agent on hosts
- Reducing the delays in monitoring agent response time
- Configuration of aggregate metrics, allow us to compile / aggregate data faster and with more ease
- Improvements in Security policies
Datadog is currently used by the Operations departments (DevOps and ProdOps) to monitor application performance, create dashboards to analyze the performance in real time when trying to debug issues, and trigger alerts in situations where manual intervention is needed. As a cloud-centric product, Datadog fits well into the organization and has very low operational overhead.
- Monitoring application performance
- Easy to read and modify dashboards
- Lightweight agent on machines
- Speed/performance of monitoring agents (reducing delays)
- Easier configuration of alerts (including moving averages, etc. so that the math becomes easier)
- Improved security (custom certificates, pinning, etc.)
Datadog is implemented as APM of choice for our organization at the platform level. Any team across the company opting to use the platform gets Datadog to gain insights into the platform with metrics like ELB, container & network stats, memory usage etc. This integration comes out of the box for the clients which they can use for monitoring their services
- Easy to setup and use
- offers wide variety of integrations with third-party services and systems
- Cheaper than competitors
- No custom query language which can be handy
- Initial setup and configuration can be painful at the start
- Additional reporting capabilities missing
August 04, 2018
We are Premium MSP partner for AWS so our DevOps engineers, Managers user them, We also have a product for Cloud Management Platform where we are working on parsing information from Datadog to our SaaS platform to present monitoring data much graphically.
- Monitors resource metrics well
- always prompt
- simple UI
- customizations available for metric visualization
- no Oracle integration
- increased data retention of metrics
- Support for more custom intergrations like Kubernetes etc.
- go easy on pricing a bit!
March 23, 2018
Datadog is being used in the whole company to monitor all the instances we have.
Used to be in private cloud and now it is used in AWS instances also.
Used to be in private cloud and now it is used in AWS instances also.
- Datadog is great for monitoring CPU, memory and all the resources
- Combined with New Relic and OpsGenie you have all the alerts you need
- Datadog has a long time history to compare over time
- Sometimes the graphics are a little bit confusing
August 01, 2017
Datadog provides great visibility into how our server infrastructure is performing. There is support for a huge variety of integrations, pretty much any service you can think of has a supported integration. Our organization uses the dashboard functionality to get a quick view as to the current state of our environment. If there's a server or website issue, everyone hops onto Datadog to get a view as to what's happening.
- The dashboard is easy to customize and understand for our organization to consume various site metrics.
- The integration support is very strong, pretty much any service you can think of is supported. Also can create custom metrics.
- Datadog customer support is helpful and responsive. Can generally help with workarounds to any issues.
- User interface could be improved in some areas, looking for host information and the agent install link takes a bit of time.
- Configuration of the agent is generally done via a config file which is a pro and a con. It would be nice to have some UI to configure various agent options.
- Billing isn't entirely straightforward, they could use more reports to figure out the source of your monthly costs.
Datadog helps us monitor our applications and ensure uptime. It is widely adopted by the entire engineering organization. When it comes to gathering performance metrics and tuning of our software applications, Datadog is just what we need. It ensures our infrastructure is highly available with fast and reliable services to our customers.
- Metric and time series data collection
- Integrations with other tools like PagerDuty, Slack and AWS
- Creation of monitors to trigger alarms and notify teams
- Easier way to create new dashboards and a way to implement them as code
- Datadog needs to be woven into application's code which creates dependencies
- Make the datadog agent more robust and reliable
April 13, 2018
It's being used by all engineers. We have scaled our e-commerce, and Datadog makes easier to look at each cluster. One great point of Datadog is how easy it is to identify an unhealthy box. Also, another great one, is to watch important metrics like CPU and memory. It's way easier to watch it on Datadog rather than AWS itself.
- Monitoring unhealthy box instances
- Watch CPU usage
- Watch Memory Usage
- Monitoring logging issue. To do that, we need other kinds of tool, such as Splunk.
- It takes a time to create a dashboard from scratch. It's easy to set up by a senior user, but it is not for beginners.
August 18, 2017
We use Datadog for monitoring our public cloud. We integrate it with some of the AWS components and monitor our instances on the cloud. It's a great solution for cloud-based monitoring with APIs.
- Dashboards are so great.
- Rest API functionality makes this one of the best monitoring tools on the market.
- With the integration it provides with cloud watch, there is an option to monitor even without the agent installation.
- We need to automate the agent installation, otherwise, it's a tedious job to do manually.
- The integration with AWS had some issues in the past, but that seems better now.
- This product has a steep learning curve at the beginning.
Datadog is being used to pull variable information from an agent on each of our servers and sent to a centralized location so we have a one stop place to understand how well our servers and services are doing. It is being used by the operations team as well as developers. It addresses getting having to go many places to get the same information.
- Centralized data.
- Quick easy graphs.
- Customization.
- Many other products out there like it.
- Not as dynamic as some other open source tools.
- Pricey compared to open source tools.
Datadog Scorecard Summary
What is Datadog?
Datadog is a monitoring, security and analytics platform for developers, IT operations teams, security engineers and business users in the cloud age. Datadog's SaaS platform integrates and automates infrastructure monitoring, application performance monitoring and log management to provide unified, real-time observability of their customers' entire technology stack. Datadog is used by organizations of all sizes and across a wide range of industries to enable digital transformation and cloud migration, drive collaboration among development, operations, security and business teams, accelerate time to market for applications, reduce time to problem resolution, secure applications and infrastructure, understand user behavior and track key business metrics.
Datadog Screenshots
Datadog Videos (3)
Datadog Integrations
Amazon Web Services, Docker, Kubernetes, Microsoft Azure, Microsoft Azure Active Directory, Adobe Experience Manager, Aerospike Database, Akamai, MPulse, Alibaba Cloud IoT Platform, Amazon API Gateway, Amazon Athena, Vertica, Amazon CloudFront, Amazon CloudSearch, AWS CloudTrail, xMatters, AWS CodeDeploy, Amazon Cognito, AWS Database Migration Service, Amazon DynamoDB, Amazon EC2 Auto Scaling, Zendesk, Apache Hadoop, AWS CodeBuild, VNS3, VictorOps, AWS Auto Scaling, HashiCorp Vault, Twistlock, Travis CI, Apache Tomcat, TeamCity, Sumo Logic, Statuspage, Stardog, Apache Spark, Splunk Cloud, Microsoft SQL Server, Squadcast, Apache Solr, Slack, Signal Sciences, Sentry, SAP HANA, Scylla, Riak, Redis, Redmine, Pivotal RabbitMQ, Prometheus, PostgreSQL, Pivotal CRM, SolarWinds Pingdom, PaperTrail, PagerDuty, OpsGenie, Mirantis OpenStack, OpenShift, New Relic, NGINX, MySQL, MongoDB, mParticle, MapR, Logz.io, Logstash, Jira Software, Apache HBase, Apache Hive, Apache Cassandra, Apache CloudStack, Apache Druid, HAProxy, Google Cloud Datastore, Google Cloud Dataflow, Gitlab, GitHub, Enterprise Fluentd, Flowdock, Apache Flink, Fastly, Amazon Elasticsearch Service, Elasticsearch, Apache CouchDB, Couchbase, Confluent Platform, ConfigCat, CockroachDB, Cloudflare, Apptio Cloudability, Chef, from Progress, CircleCI, Bitbucket, BigPanda, Apollo, Red Hat Ansible Automation Platform, LaunchDarkly, Opsmatic, Amazon DocumentDB (with MongoDB compatibility), Amazon Elastic Container Service (Amazon ECS), StatsD, Squid, ServiceNow, Ruby, Python, Puppet, php, Oracle, NodeJS, Nagios, Linux, HiveMQ, Puppet Enterprise (formerly Puppet Data Center Automation)
Datadog Competitors
Splunk Cloud, Dynatrace, SolarWinds Log Analyzer (LA)
Datadog Pricing
- Has featureFree Trial Available?Yes
- Does not have featureFree or Freemium Version Available?No
- Does not have featurePremium Consulting/Integration Services Available?No
- Entry-level set up fee?Optional
| Edition | Pricing Details | Terms |
|---|---|---|
| Free | $0 | Up to 5 hosts |
| Standard | $15/host | Up to 500 hosts |
| Enterprise | Custom | 500+ hosts |
Datadog Support Options
| Free Version | Paid Version | |
|---|---|---|
| Live Chat | ||
| Forum/Community | ||
| FAQ/Knowledgebase | ||
| Social Media | ||
| Video Tutorials / Webinar | ||
| Phone |
Datadog Technical Details
| Deployment Types: | On-premise, SaaS |
|---|---|
| Operating Systems: | Windows, Linux, Mac, Debian, Ubuntu, CentOS/RedHat, Fedora, CoreOS, Docker, Kubernetes, Openshift, SmartOS, Chef, Puppet, Ansible |
| Mobile Application: | Apple iOS, Android |
| Supported Languages: | English |