Alternatives to Airbrake

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!

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.

For my portfolio websites and my personal OpenSource projects I had started exclusively using React and JavaScript so I needed a way to track any errors that we're happening for my users that I didn't uncover during my personal UAT.

I had narrowed it down to two tools LogRocket and Sentry (I also tried Bugsnag but it did not make the final two). Before I get into this I want to say that both of these tools are amazing and whichever you choose will suit your needs well.

I firstly decided to go with LogRocket the fact that they had a recorded screen capture of what the user was doing when the bug happened was amazing... I could go back and rewatch what the user did to replicate that error, this was fantastic. It was also very easy to setup and get going. They had options for React and Redux.js so you can track all your Redux.js actions. I had a fairly large Redux.js store, this was ended up being a issue, it killed the processing power on my machine, Chrome ended up using 2-4gb of ram, so I quickly disabled the Redux.js option.

After using LogRocket for a month or so I decided to switch to Sentry. I noticed that Sentry was openSorce and everyone was talking about Sentry so I thought I may as well give it a test drive. Setting it up was so easy, I had everything up and running within seconds. It also gives you the option to wrap an errorBoundry in React so get more specific errors. The simplicity of Sentry was a breath of fresh air, it allowed me find the bug that was shown to the user and fix that very simply. The UI for Sentry is beautiful and just really clean to look at, and their emails are also just perfect.

I have decided to stick with Sentry for the long run, I tested pretty much all the JS error loggers and I find Sentry the best.

Need advice on this.

Which one should I use for logging and error monitoring ( Datadog / Sentry / Stackdriver )?

Open to any other solutions.

For my portfolio websites and my personal OpenSource projects I had started exclusively using React and JavaScript so I needed a way to track any errors that we're happening for my users that I didn't uncover during my personal UAT.

I had narrowed it down to two tools LogRocket and Sentry (I also tried Bugsnag but it did not make the final two). Before I get into this I want to say that both of these tools are amazing and whichever you choose will suit your needs well.

I firstly decided to go with LogRocket the fact that they had a recorded screen capture of what the user was doing when the bug happened was amazing... I could go back and rewatch what the user did to replicate that error, this was fantastic. It was also very easy to setup and get going. They had options for React and Redux.js so you can track all your Redux.js actions. I had a fairly large Redux.js store, this was ended up being a issue, it killed the processing power on my machine, Chrome ended up using 2-4gb of ram, so I quickly disabled the Redux.js option.

After using LogRocket for a month or so I decided to switch to Sentry. I noticed that Sentry was openSorce and everyone was talking about Sentry so I thought I may as well give it a test drive. Setting it up was so easy, I had everything up and running within seconds. It also gives you the option to wrap an errorBoundry in React so get more specific errors. The simplicity of Sentry was a breath of fresh air, it allowed me find the bug that was shown to the user and fix that very simply. The UI for Sentry is beautiful and just really clean to look at, and their emails are also just perfect.

I have decided to stick with Sentry for the long run, I tested pretty much all the JS error loggers and I find Sentry the best.

There’s a tool called LeakCanary that was built by the team at Square. It detects memory allocations and can spot when this scenario is occurring. LeakCanary has been billed as a memory leak detection library for #Android (and you’ll be happy to know there’s a Bugsnag integration for it as well!).

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.