Datadog vs New Relic vs Skylight

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Datadog
Datadog

2.2K
1.5K
+ 1
696
New Relic
New Relic

14.5K
3K
+ 1
1.9K
Skylight
Skylight

84
43
+ 1
51
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- No public GitHub repository available -
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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!

What is 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.

What is Skylight?

Skylight is a smart profiler for your Rails apps that visualizes request performance across all of your servers.
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Why do developers choose Datadog?
Why do developers choose New Relic?
Why do developers choose Skylight?

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What tools integrate with Datadog?
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    What are some alternatives to Datadog, New Relic, and Skylight?
    Splunk
    Splunk Inc. provides the leading platform for Operational Intelligence. Customers use Splunk 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.
    Sentry
    Sentry is an open-source platform for workflow productivity, aggregating errors from across the stack in real time. 500K developers use Sentry to get the code-level context they need to resolve issues at every stage of the app lifecycle.
    See all alternatives
    Decisions about Datadog, New Relic, and Skylight
    Julien DeFrance
    Julien DeFrance
    Principal Software Engineer at Tophatter · | 3 upvotes · 74.8K views
    atStessaStessa
    New Relic
    New Relic
    Datadog
    Datadog
    #APM

    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.

    See more
    Jerome Dalbert
    Jerome Dalbert
    Senior Backend Engineer at StackShare · | 3 upvotes · 47K views
    atStackShareStackShare
    Heroku
    Heroku
    New Relic
    New Relic
    Skylight
    Skylight
    Rails
    Rails
    Pingdom
    Pingdom
    Slack
    Slack

    We currently monitor performance with the following tools:

    1. Heroku Metrics: our main app is Hosted on Heroku, so it is the best place to get quick server metrics like memory usage, load averages, or response times.
    2. Good old New Relic for detailed general metrics, including transaction times.
    3. Skylight for more specific Rails Controller#action transaction times. Navigating those timings is much better than with New Relic, as you get a clear full breakdown of everything that happens for a given request.

    Skylight offers better Rails performance insights, so why use New Relic? Because it does frontend monitoring, while Skylight doesn't. Now that we have a separate frontend app though, our frontend engineers are looking into more specialized frontend monitoring solutions.

    Finally, if one of our apps go down, Pingdom alerts us on Slack and texts some of us.

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    Sebastian Gębski
    Sebastian Gębski
    CTO at Shedul/Fresha · | 4 upvotes · 258.3K views
    atFresha EngineeringFresha Engineering
    CircleCI
    CircleCI
    Jenkins
    Jenkins
    Git
    Git
    GitHub
    GitHub
    New Relic
    New Relic
    AppSignal
    AppSignal
    Sentry
    Sentry
    Logentries
    Logentries

    Regarding Continuous Integration - we've started with something very easy to set up - CircleCI , but with time we're adding more & more complex pipelines - we use Jenkins to configure & run those. It's much more effort, but at some point we had to pay for the flexibility we expected. Our source code version control is Git (which probably doesn't require a rationale these days) and we keep repos in GitHub - since the very beginning & we never considered moving out. Our primary monitoring these days is in New Relic (Ruby & SPA apps) and AppSignal (Elixir apps) - we're considering unifying it in New Relic , but this will require some improvements in Elixir app observability. For error reporting we use Sentry (a very popular choice in this class) & we collect our distributed logs using Logentries (to avoid semi-manual handling here).

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    Robert Zuber
    Robert Zuber
    CTO at CircleCI · | 8 upvotes · 139.9K views
    atCircleCICircleCI
    Datadog
    Datadog
    PagerDuty
    PagerDuty
    Honeycomb
    Honeycomb
    Rollbar
    Rollbar
    Segment
    Segment
    Amplitude
    Amplitude
    PostgreSQL
    PostgreSQL
    Looker
    Looker

    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.

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    Interest over time
    Reviews of Datadog, New Relic, and Skylight
    Review ofDatadogDatadog

    Background

    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.

    Experience

    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.

    Continuous evolution

    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.

    Other points

    • 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.

    Review ofDatadogDatadog

    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.

    Review ofSkylightSkylight

    If you follow the registration flow you end up with running analytics virtually in a minute. Awesome first experience.

    I don't have my application in production so I needed to enable skylight in development, but Skylight navigated me nicely to the exact paragraph of a documentation, which helped.

    Review ofDatadogDatadog

    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.

    Highly recommended.

    Review ofDatadogDatadog

    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.

    How developers use Datadog, New Relic, and Skylight
    Avatar of StackShare
    StackShare uses SkylightSkylight

    When we were facing performance issues with the new StackShare app. We originally thought it was a server issue. So we did quite a bit of research to see how many dynos we should be using for the sort of application we have and traffic profile. We couldn’t find anything useful online so I ended up asking my buddy Alain over at BlockScore. After a quick convo with him, I knew we should be totally fine with just 2 dynos.

    We also tested the theory by increasing the number of dynos and running the load tests. They had little to no effect on error rate, so this also confirmed that it wasn’t a server issue.

    So that meant it was an application issue. New Relic wasn’t any help. I spoke with another friend who suggested we use a profiler. We totally should have been using one all along. We added mini-profiler, which was great for identifying slow queries and overall page load times. We also had the Rails Chrome extension so we could see how long view rendering was taking. So we cleaned up the slowest queries.

    We tried to use mini-profiler in production on the new StackShare app and for some reason, we couldn’t get it to work. We were in a time crunch so I asked Alain what they used and he said that they use Skylight in production. Funny enough, I remembered the name Skylight because we listed it on the site a while back. So we did that, and at first we couldn’t really see how it was useful. Then we realized what we were seeing were a ton of repeat queries on some of the pages we load tested.

    Skylight is cool because it sort of gives you the full MVC profile. We were able to pinpoint specific db queries that being repeated. So we cleaned those up pretty quickly. But then we noticed the views were taking up all the load time, so we start implementing caching more aggressively. After we cleaned up the db queries and added more caching, our pages went from this: skylight1 to this: skylight2

    Skylight ended up being super useful. We use it in production now.

    Avatar of StackShare
    StackShare uses New RelicNew Relic

    Free Heroku add-on. Not particularly useful for us. Rails profilers tend to do a better job at the app level. And I can never really figure out what’s going on with Heroku by looking at New Relic. I don’t know if we’re just not using New Relic correctly or if it really does just suck for our use case. But I guess some insight is better than none.

    Avatar of MaxCDN
    MaxCDN uses New RelicNew Relic

    How do you know what parts of the workflow need improvement? Measure it. With New Relic in place, we have graphs of our API performance and can directly see if a server or zone is causing trouble, and the impact of our changes. There’s no comparison between a real-time performance graph and “Strange, the site seems slow, I should tail the logs”.

    Avatar of DigitalPermits
    DigitalPermits uses DatadogDatadog

    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.

    Avatar of Kalibrr
    Kalibrr uses New RelicNew Relic

    We monitor and troubleshoot our app's performance using New Relic, which gives us a great view into each type of request that hits our servers. It also gives us a nice weekly summary of error rates and response times so that we know how well we've done in the past week.

    Avatar of Sail Tactics
    Sail Tactics uses DatadogDatadog

    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.

    Avatar of AngeloR
    AngeloR uses DatadogDatadog

    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.

    Avatar of Steve Paulo
    Steve Paulo uses New RelicNew Relic

    I'm trying to wring more instrumentation out of New Relic as it pertains to Rack, but for the time being, New Relic is monitoring/alerting uptime and some basic performance metrics.

    Avatar of Jeff Flynn
    Jeff Flynn uses New RelicNew Relic

    Just like we care about errors, we care about metrics - especially around performance. You'd be crazy not to use it - and not surprisingly, it's a one-click add-on in Heroku.

    Avatar of Hund
    Hund uses