Datadog Reviews

I think that the best features that Datadog has is that you can track and follow logs in real time, something really important to have if your project is live. I like the idea of creating custom views of sets of logs (with custom filters, data parsing and a lot more) and that you can share them with your team.

It is a bit complicated to set for the first time. Is not quite easy to use or know at first about all the available features that Datadog has. Interface is tricky and can be a blocker sometimes. Following that, if your fields are not mapped in the right way, filters are not that useful.

Datadog is probably one of the most notable analytics tool out there for large companies. It's easy to track users' flow in terms of what routes they're hitting, when they hit a snag and 404, or other metrics like how performant certain requests are which allows us to identify bottlenecks and get rid of them immediately.

There is a steep learning curve I will say with this software and needs an expert to help lead tutorials or sessions to get the ball rolling with new tool users. Although there are many built in functionalities and easily customizable features, it can be overwhelming and hard to pinpoint exactly what type of analytics you're looking for. It's one of those softwares where you have to play around with it to get the stars to align and find a model or metric that works best for your customers and use cases.

It´s very useful to use it as TV Dashboards of Apps health. It allows you to use personalized counters for metrics you can set in your code. It' s great to see app performance during product launching.

Theree's no mobile version of the app, would be very useful to carry those dashboards and monitors on your phone.

Looks like it should do the job, less log limits than other products.

Spent days trying to get it working on a pretty vanilla Windows VM but never could get it up and running. Support pretty much just told me to read the documentation which wasn't really helpful after going over it ten times already. Had similar problem with another product and they could tell me the exact lines of the config and registry that needed changing.

As a software tester, I use Datadog for debugging customer issues, when I may not have direct access. I can quickly filter through the logs in order to find the issue and generate reproductions or resolve issues

Sometimes when requesting to see a log in context it is does not return the correct context which makes the debugging process harder.

- The filter functionality is great which lets you filter out errors for quick analysis, can easily create custom dashboards. - Great Visualizations, easy to set up dashboards/monitors with options do maths like ratios, rates, average, interval. - It can be easily integrated with other apps like Slack to set alerts for failed jobs. -

- A slow learning curve, lack of resources on how to get useful functionality from UI or APIs. - UI sometimes be bit slower although not bad if you've integrated with multiple external apps.

The log imports from AWS work really well and are much faster at searching than using AWS Cloudwatch. I find it easy day to day to search for items in logs, especially after implementing a few log transformers

initial setup gets a bit confusing sometimes, and it was easier to change the logging format of our code than to implement lots of parsers to make the log interpretation better

Really simple set up to monitor our full stack environment. Dashboard is very clear and suitable for both technical and non-technical stakeholders.

Nothing really. Migrating to any product can be challenging but setup was pretty simple and no key functionality absent.

Datadog is useful for visualizing and monitoring your cloud applications. If you have agents on you devices, it can analyze a ton of information coming in and show it to you, but that's where it ends, at least, as far as I could figure out in my free trial.

I was very hopeful of this software, but I didn't want to throw agents from a product I've never used before on my servers and instances, so I tried to upload a data pull ( about 500,000 log entries) to Datadog, to see what it could do, but there's no way to upload a csv/txt file to the software. It has to be via agents on your services. I know that metadata would be missing from a csv, but it seems like a major oversight to not be able to accept a csv of logs for a new user to experiment at low risk.

The vast no of integration you can do with your cloud, whether its AWS Azure or Google, is phenomenal. The pre installed dashboards really help to set it up quickly. The notebook feature is quite useful too, if you are not ready to spend much on dashboards. Overall, nice all in one solution to capture logs from cloud and analyze them.

The metric creation process is not very easy. If you want to create metrics from logs, it gets more complicated.

Datadog is a tool that I like for several reasons, because implementing it does not require technical knowledge, has a series of metrics that allow you to read whether the performance of applications or servers is appropriate or not, so if you find a failure or something out of the ordinary in these applications the user immediately receives alerts that notify him of this problem so that it can be resolved in the shortest possible time, these alerts being received at any time since Datadog works continuously 24/7 and the best thing is that it is a software that is very easy to use and implement, in addition to being extremely flexible because it allows you to choose the monitoring parameters that you want to apply.

Datadog is not a perfect tool because it has some drawbacks and is that the more applications are integrated with this software the performance or speed of information delivery tends to slow down which should not be since the integrations are to improve even more the performance of said tool.

Datadog provides a way of having a lot of information about your systems, clusters and infrastructure in only one site, being able to analyze valuable data for your company. It is possible to create alarms and notifications when overpassing some threshold or value, for example, when a service is down in your systems of when the CPU gets a high percentage of usage. It integrates pretty well with tons of services and systems, such as Amazon Web Services, Apache, Nginx, several databases, and a long etcetera. Also, it is possible to send notifications to apps like Slack or Hipchat.

Datadog is not very easy to use at the beginning and it needs a little bit of investigation but it is worth to learn it.

This software allows to monitoring all you need and also can find lots of solutions for a high gama of cases. by using this app i be able to see the problems that me and my team have, so we can solve it by utilizing all the data that datadog provides. Works in differents OS and that make things more easy

The proces to instal and put in march this softwre can be a nightmare if you have not experience, it is really complicated. Though the software have nice tools, the price is not the best in the market, is posible to find something good for lowes price if you know what are you loking for. And finally haved some problem with some data transfer working with this app but i really dont konw what was the razon why

This tool called Datadog I love mainly because it is really efficient and very useful because it allows through it you can carry out a monitoring of the performance of applications in a very simple way, being this through the reading of metrics that are really simple to understand and issue very detailed information that is useful to diagnose the cause and thus be able to solve the problem in the shortest time possible, also is available 24/7 so in case of any fault send immediately a mail informing the same and the best thing is that it has a clean interface, intuitive and easy to use without having technical knowledge to manage it.

One of its drawbacks is that when it is integrated with a large number of tools it can become heavy, which causes the information to be slowed down.

It's got everything that's needed for infrastructure and application monitoring and alerting. It also fits extremely well into our Infrastructure-as-Code paradigm where everything we set up is kept in a git repository as a Terraform project. DataDog is what we recommend and implement for our clients, and provides more useful features than Sensu.

Metrics and monitors don't render correctly on mobile phones. It's totally unusable in portrait mode, and barely usable in landscape mode.

The metrics navigator, you start by picking a metric or server, and it then tells you all the information it is collecting from it, so you can start designing your monitoring dashboards and see the data that will appear as you go

There are times where a chart would omit certain spikes, due to the way they aggregate values. But a quick email to support and they'll give you the settings you need to adjust not to miss such events, even when you look at a chart for the month

For our AWS deployment, we use Datadog for application performance and server monitoring as well as synthetic HTTP tests . DataDog enables real-time information and measuring engineering-specific metrics and allows you to control how you trace and diagnose data. If you are looking to track the time it takes for a web hook to fire after an asynchronous request has been made, you can store the time the request has been sent in your database and when the webhook fires for that request, measure the delta and send it to DataDog. DataDog integrates with Slack, which allows for alerts on average and max thresholds.

Datadog has a mature product but features are limited, the tool feels dated and the UI is very plain.

Datadog has integrations with pretty much every main software service you can think of. It has pretty robust support for Windows machines and the custom metrics support is great, so you can track anything you'd like.

The usability could be improved in some areas, the custom dashboard features are powerful but the syntax can be hard to work with.

Datadog provides a great, easy-to-use and extensible interface for displaying data out of your own systems, providing you the insight to sniff out issues as they arise.

No matter how many integrations Datadog builds in, there will always be gaps, and some of those gaps hit our needs. As such, we need to use several monitoring solutions to cover our whole platform.

Configuring monitoring tools is not always trivial, half of the battle is making sure metrics are flowing. Datadog is very flexible when it comes to sending metrics to their cloud. You can use collectD, statsd, file beats, or the 84523982 other options. Our orchestration software already had an option to enable Datadog collection. Once the data is in place, you need to figure out what metrics are relevant. Datadog has a number of pre-built dashboards tweaked for popular software systems. If you are using something homegrown, they can provide recommendations and optimizations after enough data has been ingested. API and documentation are top notch and we were able to build integrations quite easily.

Datadog is purely cloud-based system so there's no on-prem option, only SaaS. Depending on your company, this may be a deal-breaker since all of your metrics data is hosted in the cloud. Since it's a SaaS based service, it won't be easy to move data to another service. Occasionally web UI will bog down but it's fairly performant for the most part.

Great web monitoring tool if you have the time to dig into all the options and settings. The user interface is really professional and good looking and the charts and graphs are well thought out.

It requires a bit of server tinkering, which I wasn't familiar with. Not really a minus.

Datadog's Windows support is great, the Windows agent supports detailed IIS and MSSQL statistics. Their RabbitMQ support is good as well - providing good insight into queues. Customizable dashboards are very handy as well.

The User interface generally is good but in some instances can be a bit too technical to use.

Feature-rich cloud monitoring solution which works across multiple cloud providers (AWS, Azure, etc)

It takes a bit of time to get familiar with the admin portal user interface.

Easy to monitor and get analytics We can monitor inside any stack, any app, at any scale, anywhere Supports multiple dashboards Notebooks help you to share the data

More options some time confuses Help documentation needs improvement Some times dashboards are very complex to understand

I noticed that this monitoring system is very flexible, you can track pretty much any metric, which is great. Great integration with many services like AWS, Chef, Couchbase, JVM, HAProxy, MySQL etc. Dashboard functionality is easy. Comes with UI, UI is simply designed but supports all the key functionalities that you would expect from a counter services, and to be able to create dashboard based on counters.

Noticed that the more data you have, the slower response Datadog service will become, when you query the service. Query a specific counter, as well as when the counter contains high dimensional data, which is normal, we haven't yet tested what is the upper limit for how much data it can decently handle. But we have been very satisfied using Datadog, and we feel that it should be enough for small to mid size company.