Datadog vs Scout: What are the differences?
Developers describe Datadog as "Unify logs, metrics, and traces from across your distributed infrastructure". 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!. On the other hand, Scout is detailed as "Application Monitoring that Developers Love". Scout is application monitoring that points developers right to the source of problems: N+1 database queries, memory bloat, performance trends, and more Scout eliminates much of the investigation part when performance woes occur. .
Datadog and Scout belong to "Performance Monitoring" category of the tech stack.
Some of the features offered by Datadog are:
- 14-day Free Trial for an unlimited number of hosts
- 200+ turn-key integrations for data aggregation
- Clean graphs of StatsD and other integrations
On the other hand, Scout provides the following key features:
- Monitors Ruby & Elixir apps with more languages to come
- Easy install
- Detailed transaction traces
"Monitoring for many apps (databases, web servers, etc)" is the top reason why over 118 developers like Datadog, while over 9 developers mention "Easy setup" as the leading cause for choosing Scout.
According to the StackShare community, Datadog has a broader approval, being mentioned in 540 company stacks & 223 developers stacks; compared to Scout, which is listed in 29 company stacks and 7 developer stacks.
What is Datadog?
What is Scout?
Need advice about which tool to choose?Ask the StackShare community!
Sign up to add, upvote and see more prosMake informed product decisions
What are the cons of using Scout?
Sign up to get full access to all the companiesMake informed product decisions
Sign up to get full access to all the tool integrationsMake informed product decisions
Which #APM / #Infrastructure #Monitoring solution to use?
The 2 major players in that space are New Relic and Datadog Both are very comparable in terms of pricing, capabilities (Datadog recently introduced APM as well).
In our use case, keeping the number of tools minimal was a major selection criteria.
As we were already using #NewRelic, my recommendation was to move to the pro tier so we would benefit from advanced APM features, synthetics, mobile & infrastructure monitoring. And gain 360 degree view of our infrastructure.
Few things I liked about New Relic: - Mobile App and push notificatin - Ease of setting up new alerts - Being notified via email and push notifications without requiring another alerting 3rd party solution
I've certainly seen use cases where NewRelic can also be used as an input data source for Datadog. Therefore depending on your use case, it might also be worth evaluating a joint usage of both solutions.
Our primary source of monitoring and alerting is Datadog. We’ve got prebuilt dashboards for every scenario and integration with PagerDuty to manage routing any alerts. We’ve definitely scaled past the point where managing dashboards is easy, but we haven’t had time to invest in using features like Anomaly Detection. We’ve started using Honeycomb for some targeted debugging of complex production issues and we are liking what we’ve seen. We capture any unhandled exceptions with Rollbar and, if we realize one will keep happening, we quickly convert the metrics to point back to Datadog, to keep Rollbar as clean as possible.
We use Segment to consolidate all of our trackers, the most important of which goes to Amplitude to analyze user patterns. However, if we need a more consolidated view, we push all of our data to our own data warehouse running PostgreSQL; this is available for analytics and dashboard creation through Looker.
We're a real-time financial services messaging company, so being able to monitor our servers and applications in real-time is important to us. We also like a good deal, so $15/server seemed a bargain.
What were we looking for?
We wanted to monitor our MS infrastructure (servers, SQL) and apps (C#) to understand performance issues and be able to rectify. We also want to be able to do long-term trending. And we wanted to go from nothing to live in a short time.
Installing the Datadog agent on the servers was a breeze and enabling the integrations for SQL and Windows trivial.
Using the StatsD based API was also very easy - no worrying about JSON or UDP calls. The ability to add tags to all metrics is also a key benefit. We run multiple (100+) instances of a single application and being able to distinguish events from each one via tagging, or to see aggregates, is extremely useful.
In all it took 2 days R&D to instrument our key applications sufficiently for production deployment. Deploying the agent to our production servers took 30 mins, giving our Ops team complete visibility for the 1st time.
What have we learned
Since we've been live Datadog has given us numerous insights into the way our system behaves, from uneven server loadings and sporadic memory usage to performance tuning a key application that resulted in a 50% increase in throughput. Knowing what's taking the time has been a boon.
The other nice surprise has been the evolving nature of Datadog. It seems like every couple of weeks there's a new feature on the site.
- I like the transparent pricing. Services that won't show me the price without having to talk to a sales person are really annoying.
- Support has been good. We've contacted them several times with questions and always had a quick response (time zone considered...we're in London) and a helpful answer.
So What's bad?
Probably the weakest aspect at the moment is the long term trending of data. Whilst you can wind the time bar back to see what happened last week you can't ask questions like "show me the peak period each day for the last x months". The "get data" API is also fairly weak. Neither are concerns at the moment, and I'm sure they're on the to-do list.
We love Scout at Rollbar. Here's how we use it.
Zero configuration monitoring for new hosts
We have added Scout to our Ansible configuration for new host setup. So, when we provision a new machine, we get basic monitoring without any extra configuration. Once the host is up and running, we add it to the appropriate role in Scout and all of our monitoring plugins are magically deployed and enabled on the new host.
Monitoring HTTP response codes
One of the best things about Scout is how beautiful and therefore usable their graphs are. We have a Scout dashboard which shows all of our response codes which allows us to quickly see connections between different hosts when problems occur.
Scout's plugin model makes it really easy to extend. We have implemented our own log monitoring plugin which reports metrics like the 90th percentile of slow queries on our site. These types of plugins allow us to see issues at a glance during deploys, maintenance and load spikes.
Slowly taking over Nagios
Nagios is amazing, but let's be real... Anyone who has used it knows how painful it is to set up, administer and extend. We are in the process of cutting over from Nagios to Scout to handle more of our infrastructure monitoring and soon, alerting.
I've been a systems administrator most of my career. Everywhere I went, I'd have to rebuild the same monitoring + graphing system. And then make sure that every machine wrote to that system and every application handed up the proper metrics through whatever mechanism seemed good at the time.
Then, as CTO of SimpleReach, single-handedly managing over 200 servers in addition to everything else, I found Datadog. We were already using statsd to instrument our applications, now it was just a matter of getting that data to Datadog. We use Chef, so I installed the Datadog agent on every machine in about 10 minutes and we were up and running.
The best part was that we had a deploy problem the next day with one of our main applications and troubleshooting took minutes instead of hours (and Datadog immediately paid for itself). Now no new features go out without instrumentation and no machine gets created without being monitored.
Datadog just scales with us. Great service and I highly recommend it to anyone not looking to reinvent the wheel with monitoring and instrumentation.
I'm a freelance developer with a handful of servers that needed insightful monitoring and alerts. I searched high and low across both hosted and self hosted solutions... paid and open source. While many are quite capable the self-hosted solutions were clunky and overkill. The few self-hosted for pay solutions costs structure were completely outside of a freelances budget. ScoutApp is the first that had the easy to use setup, amazing plugins for specific app monitoring and the price was actually affordable. Setup couldn't be easier. Plugins are handled amazingly with a single click that initiates the agent to install remotely. The interface is minimal and easy to read. Triggers are so well done and easy to setup with clear human language detailing the alert criteria. Real-time graphing is just icing on the cake.
ScoutApp is great for not just small but enterprise level infrastructures as well. Added features such as roles, multi-user accounts, environments and even an API make growing with it a no brainer.
Very well done and highly recommended.
I used to have NewRelic on https://doorbell.io for my monitoring. It worked pretty well for the basic things, and the basic plan is free.
However, as https://doorbell.io's stack got increasingly complicated, the plugins of NewRelic didn't work as well as I needed, in order to reliably monitor all aspects of the platform.
I decided to try out Scout as an alternative, since even though it doesn't have a free plan, the basic plan is only $8/month (compared to $149 for NewRelic).
I found the interface to be really good, and they have great documentation. I found plugins for every single part of my stack, and they all worked very easily "out of the box". And best of all, added practically no overhead to the server!
So overall, I'd say it's a service that's well worth paying for. It's a steal at $8/month!
We migrated our infrastructure monitoring to Scout about six months ago when our previous monitoring solution became unreliable and cumbersome to maintain. We were pleasantly surprised at the ease of implementation and the library of plugins already available.
The fine grain polling frequency and long term metric logging helped us maintain the high level of uptime our application requires. Moreover, due to the nature of the Scout protocol, changes to our specific application monitoring can be configured at a high level in their interface with a few clicks.
For the few times we have been in communication with their support team to help sort our questions or clarify details, we have been thoroughly impressed at their response time and personalized attention to our needs.
We highly recommend using Scout.
We are a very small non profit with a very simple server setup. Our two developers do not have any special training as sys admins. But it was very easy to get setup with Scout and start some simple monitoring of our servers. Most of what we do is check that some key processes are running and that our URLs are up. It was easy to do all of that with Scout. That said: we're interested in learning more about Scout's capabilities and doing more sophisticated server monitoring down the line.
Datadog makes running a service with 800,000 unique users a month possible as a single developer/maintainer. I bought a separate monitor just to keep my datadog dashboards always visible and rely on triggers to keep watch over 20+ servers.
We use datadog to monitor our servers and some application metrics. Easy to get started and scale to many servers. Datadog support engineers are always quick to respond to bugs and other challenges.
We are a very small non profit with a very simple server setup. Our two developers do not have any special training as sys admins. That said, it was very simple to get setup with Scout and start some simple monitoring of our servers. Most of what we do is check that some key processes are running and that our URLs are up. But we're interested in learning more aboutS Scout's capabilities/ doing more sophisticated server monitoring down the line.
We just started looking into Datadog, but from what we see, it's like New Relic meets Loggly. It's really easy to plugin different services (like the one on this list) and get detailed analysis of what is happening on your servers and services. It makes tracking down sparse and difficult to understand problems possible.
Monitoring day-to-day operations of multiple high-performance computing assets distributed across several networks. Monitoring vendor provided data and setting up alerts when things do not show up on time.
Datadog was used as an agent for monitoring and as for the statsd daemon included. This way we are able to have automated system stats and include whatever other metrics we want to track.
Datadog is used because it has a great free tier and it provides us with great insights and integrations into our infrastructure and tools.