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Sentry

Cut time to resolution for app errors from five hours to five minutes.
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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 23.2K GitHub stars and 2.6K GitHub forks. Here’s a link to Sentry's open source repository on GitHub

Who uses Sentry?

Companies
2339 companies reportedly use Sentry in their tech stacks, including Airbnb, Uber, and Instagram.

Developers
2405 developers on StackShare have stated that they use Sentry.

Sentry Integrations

GitHub, PHP, Node.js, Python, and Slack are some of the popular tools that integrate with Sentry. Here's a list of all 111 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 · 358.7K views
atFundsCornerFundsCorner
Amazon SQS
Amazon SQS
Python
Python
Flask
Flask
MongoDB
MongoDB
Swagger UI
Swagger UI
Vue.js
Vue.js
Vuetify
Vuetify
vuex
vuex
Zappa
Zappa
AWS Lambda
AWS Lambda
Netlify
Netlify
Google Compute Engine
Google Compute Engine
Slack
Slack
GitLab CI
GitLab CI
Sentry
Sentry

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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Johnny Bell
Johnny Bell
Senior Software Engineer at StackShare · | 10 upvotes · 241.9K views
React
React
JavaScript
JavaScript
LogRocket
LogRocket
Sentry
Sentry
Bugsnag
Bugsnag
Redux
Redux
#OpenSource
#Chrome
#OpenSorce
#ErrorBoundry

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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Yonas Beshawred
Yonas Beshawred
CEO at StackShare · | 10 upvotes · 236.8K views
atStackShareStackShare
Segment
Segment
Sentry
Sentry
FullStory
FullStory
Rails
Rails
#UserFeedbackAsAService
#Reproducing-bugs
#Sessionrecording
#Bug-squashing

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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Tassanai Singprom
Tassanai Singprom
Web Developer · | 9 upvotes · 291.3K views
JavaScript
JavaScript
PHP
PHP
HTML5
HTML5
jQuery
jQuery
Redis
Redis
Amazon EC2
Amazon EC2
Ubuntu
Ubuntu
Sass
Sass
Vue.js
Vue.js
Firebase
Firebase
Laravel
Laravel
Lumen
Lumen
Amazon RDS
Amazon RDS
GraphQL
GraphQL
MariaDB
MariaDB
Google Analytics
Google Analytics
Postman
Postman
Elasticsearch
Elasticsearch
Git
Git
GitHub
GitHub
GitLab
GitLab
npm
npm
Visual Studio Code
Visual Studio Code
Kibana
Kibana
Sentry
Sentry
BrowserStack
BrowserStack
Slack
Slack

This is my stack in Application & Data

JavaScript PHP HTML5 jQuery Redis Amazon EC2 Ubuntu Sass Vue.js Firebase Laravel Lumen Amazon RDS GraphQL MariaDB

My Utilities Tools

Google Analytics Postman Elasticsearch

My Devops Tools

Git GitHub GitLab npm Visual Studio Code Kibana Sentry BrowserStack

My Business Tools

Slack

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Trey Tacon
Trey Tacon
Sentry
Sentry
StatsD
StatsD
Graphite
Graphite
Grafana
Grafana
PagerDuty
PagerDuty
Amazon CloudWatch
Amazon CloudWatch

A huge part of our continuous deployment practices is to have granular alerting and monitoring across the platform. To do this, we run Sentry on-premise, inside our VPCs, for our event alerting, and we run an awesome observability and monitoring system consisting of StatsD, Graphite and Grafana. We have dashboards using this system to monitor our core subsystems so that we can know the health of any given subsystem at any moment. This system ties into our PagerDuty rotation, as well as alerts from some of our Amazon CloudWatch alarms (we’re looking to migrate all of these to our internal monitoring system soon).

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Joshua Dean KĂĽpper
Joshua Dean KĂĽpper
CEO at Scrayos UG (haftungsbeschränkt) · | 5 upvotes · 48.6K views
atScrayos UG (haftungsbeschränkt)Scrayos UG (haftungsbeschränkt)
MariaDB
MariaDB
PostgreSQL
PostgreSQL
GitLab
GitLab
Sentry
Sentry

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'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

Sentry's Followers
2383 developers follow Sentry to keep up with related blogs and decisions.
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