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Cut time to resolution for app errors from five hours to five minutes.

What is 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.
Sentry is a tool in the Exception Monitoring category of a tech stack.
Sentry is an open source tool with 21.3K GitHub stars and 2.4K GitHub forks. Here’s a link to Sentry's open source repository on GitHub

Who uses Sentry?

Companies
1327 companies use Sentry in their tech stacks, including Airbnb, Uber, and Instagram.

Developers
425 developers use Sentry.

Sentry Integrations

JavaScript, GitHub, Node.js, Slack, and Python are some of the popular tools that integrate with Sentry. Here's a list of all 73 tools that integrate with Sentry.

Why developers like Sentry?

Here’s a list of reasons why companies and developers use Sentry
Sentry Reviews

Here are some stack decisions, common use cases and reviews by companies and developers who chose Sentry in their tech stack.

Jeyabalaji Subramanian
Jeyabalaji Subramanian
CTO at FundsCorner · | 12 upvotes · 51.3K views
atFundsCorner
Amazon SQS
Sentry
GitLab CI
Slack
Google Compute Engine
Netlify
AWS Lambda
Zappa
vuex
Vuetify
Vue.js
Swagger UI
MongoDB
Flask
Python

At FundsCorner, we are on a mission to enable fast accessible credit to India’s Kirana Stores. We are an early stage startup with an ultra small Engineering team. All the tech decisions we have made until now are based on our core philosophy: "Build usable products fast".

Based on the above fundamentals, we chose Python as our base language for all our APIs and micro-services. It is ultra easy to start with, yet provides great libraries even for the most complex of use cases. Our entire backend stack runs on Python and we cannot be more happy with it! If you are looking to deploy your API as server-less, Python provides one of the least cold start times.

We build our APIs with Flask. For backend database, our natural choice was MongoDB. It frees up our time from complex database specifications - we instead use our time in doing sensible data modelling & once we finalize the data model, we integrate it into Flask using Swagger UI. Mongo supports complex queries to cull out difficult data through aggregation framework & we have even built an internal framework called "Poetry", for aggregation queries.

Our web apps are built on Vue.js , Vuetify and vuex. Initially we debated a lot around choosing Vue.js or React , but finally settled with Vue.js, mainly because of the ease of use, fast development cycles & awesome set of libraries and utilities backing Vue.

You simply cannot go wrong with Vue.js . Great documentation, the library is ultra compact & is blazing fast. Choosing Vue.js was one of the critical decisions made, which enabled us to launch our web app in under a month (which otherwise would have taken 3 months easily). For those folks who are looking for big names, Adobe, and Alibaba and Gitlab are using Vue.

By choosing Vuetify, we saved thousands of person hours in designing the CSS files. Vuetify contains all key material components for designing a smooth User experience & it just works! It's an awesome framework. All of us at FundsCorner are now lifelong fanboys of Vue.js and Vuetify.

On the infrastructure side, all our API services and backend services are deployed as server less micro-services through Zappa. Zappa makes your life super easy by packaging everything that is required to deploy your code as AWS Lambda. We are now addicted to the single - click deploys / updates through Zappa. Try it out & you will convert!

Also, if you are using Zappa, you can greatly simplify your CI / CD pipelines. Do try it! It's just awesome! and... you will be astonished by the savings you have made on AWS bills at end of the month.

Our CI / CD pipelines are built using GitLab CI. The documentation is very good & it enables you to go from from concept to production in minimal time frame.

We use Sentry for all crash reporting and resolution. Pro tip, they do have handlers for AWS Lambda , which made our integration super easy.

All our micro-services including APIs are event-driven. Our background micro-services are message oriented & we use Amazon SQS as our message pipe. We have our own in-house workflow manager to orchestrate across micro - services.

We host our static websites on Netlify. One of the cool things about Netlify is the automated CI / CD on git push. You just do a git push to deploy! Again, it is super simple to use and it just works. We were dogmatic about going server less even on static web sites & you can go server less on Netlify in a few minutes. It's just a few clicks away.

We use Google Compute Engine, especially Google Vision for our AI experiments.

For Ops automation, we use Slack. Slack provides a super-rich API (through Slack App) through which you can weave magical automation on boring ops tasks.

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Yonas Beshawred
Yonas Beshawred
CEO at StackShare · | 10 upvotes · 10.7K views
atStackShare
Segment
Rails
FullStory
Sentry
#Bug-squashing
#Sessionrecording
#Reproducing-bugs
#UserFeedbackAsAService

One of the challenges we've had to deal with as our product surface area has grown, is identifying and reproducing bugs. We use Sentry for exception monitoring, however, it's usually difficult to try to reproduce bugs. I first heard about FullStory from our friends over at Flexport (check out the Stack Story and you'll hear them mention it: https://stackshare.io/posts/how-flexport-builds-software-to-move-over-1-billion-dollars-in-merchandise). FullStory let's you record user sessions, and play them back to help you identify bugs and UX issues. You're even able to view the console errors live as they happen during the sessions!

We were pretty blown away at how comprehensive the product was at first, and it seems to be getting better every time I use it. Only complaint is that it's super expensive once you're in the hundreds of thousands of sessions so we had to stop trying to record logged out sessions, we only use it for auth'd sessions. We also started out using it via Segment but once we needed to watch out for the number of sessions we were recording we realized that it was impossible to restrict FullStory recordings on a per-page basis without ripping it out of Segment, so we ended up just using their JS snippet and putting that in the Rails views that we wanted to monitor closely.

The ability to share specific portions of sessions, speed them up, skip inactivity, and all sorts of other little features all add up to a really solid product that helps both our PMs and engineers improve our own product much quicker. I officially requested a Sentry + FullStory integration a while back https://twitter.com/yonasbe/status/871987738777616384, still waiting on this! #UserFeedbackAsAService #reproducing-bugs #sessionrecording #bug-squashing

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Johnny Bell
Johnny Bell
Sr. Software Engineer at StackShare · | 7 upvotes · 20.4K views
Redux
Bugsnag
Sentry
LogRocket
JavaScript
React
#ErrorBoundry
#OpenSorce
#Chrome
#OpenSource

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.

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Sebastian Gębski
Sebastian Gębski
CTO at Shedul/Fresha · | 4 upvotes · 23.8K views
atFresha Engineering
Logentries
Sentry
AppSignal
New Relic
GitHub
Git
Jenkins
CircleCI

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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Joshua Dean Küpper
Joshua Dean Küpper
CEO at Scrayos UG (haftungsbeschränkt) · | 4 upvotes · 12.8K views
atScrayos UG (haftungsbeschränkt)
Sentry
GitLab
PostgreSQL
MariaDB

We primarily use MariaDB but use PostgreSQL as a part of GitLab , Sentry and @Nextcloud , which (initially) forced us to use it anyways. While this isn't much of a decision – because we didn't have one (ha ha) – we learned to love the perks and advantages of PostgreSQL anyways. PostgreSQLs extension system makes it even more flexible than a lot of the other SQL-based DBs (that only offer stored procedures) and the additional JOIN options, the enhanced role management and the different authentication options came in really handy, when doing manual maintenance on the databases.

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Sentry

Sentry has been very useful for me and my team. I caught a bug in staging — just as one example — which I wouldn't have caught before deploying to production. That's the sort of thing that happens on a regular basis with Sentry.

I didn't personally make the decision to use Sentry since I'm part of a very large organization that chose it before I joined company. But we've been more than happy enough with Sentry that we use it across most of our teams, regardless of their stack.

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Sentry's features

  • Real-Time Updates: For the first time, developers can fix code-level issues anywhere in the stack well before users even encounter an error.
  • Complete Context: Spend more time where it matters, rather than investing in low-impact issues.
  • Integrate Everywhere: Drop-in integration for every major platform, framework, and language -- JavaScript, Python, PHP, Ruby, Node, Java, .NET, mobile.
  • Root Cause: See the events that lead to errors so you always debug the right thing the first time.
  • Private & Secure: Sentry is compliant with GDPR, PCI DSS, HIPAA, and Privacy Shield by default.
  • Open Source: Sentry is 100% open source and available on GitHub.

Sentry Alternatives & Comparisons

What are some alternatives to Sentry?
Rollbar
Rollbar helps development teams find and fix errors faster. Quickly pinpoint what’s broken and why. View exceptions from all of your languages, frameworks, platforms & environments in one place. Get context & insights to defeat all errors.
Crashlytics
Instead of just showing you the stack trace, Crashlytics performs deep analysis of each and every thread. We de-prioritize lines that don't matter while highlighting the interesting ones. This makes reading stack traces easier, faster, and far more useful! Crashlytics' intelligent grouping can take 50,000 crashes, distill them down to 20 unique issues, and then tell you which 3 are the most important to fix.
Bugsnag
Bugsnag captures errors from your web, mobile and back-end applications, providing instant visibility into user impact. Diagnostic data and tools are included to help your team prioritize, debug and fix exceptions fast.
TrackJS
Production error monitoring and reporting for web applications. TrackJS provides deep insights into real user errors. See the user, network, and application events that tell the story of an error so you can actually fix them.
Airbrake
Airbrake collects errors for your applications in all major languages and frameworks. We alert you to new errors and give you critical context, trends and details needed to find and fix errors fast.
See all alternatives

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