Kibana vs Sentry: What are the differences?
Kibana: Explore & Visualize Your Data. Kibana is an open source (Apache Licensed), browser based analytics and search dashboard for Elasticsearch. Kibana is a snap to setup and start using. Kibana strives to be easy to get started with, while also being flexible and powerful, just like Elasticsearch; Sentry: Cut time to resolution for app errors from five hours to five minutes. 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.
Kibana belongs to "Monitoring Tools" category of the tech stack, while Sentry can be primarily classified under "Exception Monitoring".
Some of the features offered by Kibana are:
- Flexible analytics and visualization platform
- Real-time summary and charting of streaming data
- Intuitive interface for a variety of users
On the other hand, Sentry provides the following key 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.
"Easy to setup" is the primary reason why developers consider Kibana over the competitors, whereas "Consolidates similar errors and makes resolution easy" was stated as the key factor in picking Sentry.
Kibana and Sentry are both open source tools. Sentry with 21.4K GitHub stars and 2.45K forks on GitHub appears to be more popular than Kibana with 12.4K GitHub stars and 4.8K GitHub forks.
Airbnb, Uber Technologies, and Instagram are some of the popular companies that use Sentry, whereas Kibana is used by Airbnb, DigitalOcean, and 9GAG. Sentry has a broader approval, being mentioned in 1341 company stacks & 434 developers stacks; compared to Kibana, which is listed in 907 company stacks and 479 developer stacks.
What is Kibana?
What is Sentry?
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One size definitely doesn’t fit all when it comes to open source monitoring solutions, and executing generally understood best practices in the context of unique distributed systems presents all sorts of problems. Megan Anctil, a senior engineer on the Technical Operations team at Slack gave a talk at an O’Reilly Velocity Conference sharing pain points and lessons learned at wrangling known technologies such as Icinga, Graphite, Grafana, and the Elastic Stack to best fit the company’s use cases.
At the time, Slack used a few well-known monitoring tools since it’s Technical Operations team wasn’t large enough to build an in-house solution for all of these. Nor did the team think it’s sustainable to throw money at the problem, given the volume of information processed and the not-insignificant price and rigidity of many vendor solutions. With thousands of servers across multiple regions and millions of metrics and documents being processed and indexed per second, the team had to figure out how to scale these technologies to fit Slack’s needs.
On the backend, they experimented with multiple clusters in both Graphite and ELK, distributed Icinga nodes, and more. At the same time, they’ve tried to build usability into Grafana that reflects the team’s mental models of the system and have found ways to make alerts from Icinga more insightful and actionable.
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.
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.
I use Kibana because it ships with the ELK stack. I don't find it as powerful as Splunk however it is light years above grepping through log files. We previously used Grafana but found it to be annoying to maintain a separate tool outside of the ELK stack. We were able to get everything we needed from Kibana.
I use both Kibana and Grafana on my workplace: Kibana for logging and Grafana for monitoring. Since you already work with Elasticsearch, I think Kibana is the safest choice in terms of ease of use and variety of messages it can manage, while Grafana has still (in my opinion) a strong link to metrics
For our Predictive Analytics platform, we have used both Grafana and Kibana
- Grafana based demo video: https://www.youtube.com/watch?v=tdTB2AcU4Sg
- Kibana based reporting screenshot: https://imgur.com/vuVvZKN
predictions and ML algorithms support, so if you need them, you may be better off with Kibana . The multi-variate analysis features it provide are very unique (not available in Grafana).
For everything else, definitely Grafana . Especially the number of supported data sources, and plugins clearly makes Grafana a winner (in just visualization and reporting sense). Creating your own plugin is also very easy. The top pros of Grafana (which it does better than Kibana ) are:
- Creating and organizing visualization panels
- Templating the panels on dashboards for repetetive tasks
- Realtime monitoring, filtering of charts based on conditions and variables
- Export / Import in JSON format (that allows you to version and save your dashboard as part of git)
This is my stack in Application & Data
My Utilities Tools
Google Analytics Postman Elasticsearch
My Devops Tools
Git GitHub GitLab npm Visual Studio Code Kibana Sentry BrowserStack
My Business Tools
Lots of companies I respect were using it + open-source + great features and UI. Went for the hosted version, since it plays nice with Heroku. I like how they group together similar errors, give you the ability to mute events or mark them as solved. P.S. check out the Founder Stories feature we did on Sentry if you want to know how they started, its an awesome story.
The error and event tracking in Sentry is superb. Being able to assign the raw error to people along with all information at the time the event occurred means that we're tracking and fixing problems before they become apparent to customers. We use the self-hosted instance of Sentry.
Sentry is a very powerful error reporting tool. We use it both on front-end and back-end of Ataccama One. It proved to be invaluable in providing insights on our errors - what caused it, what user did before the error occured, stack trace, release tracking and more.
We use Sentry to gather our thrown non-checked exceptions in one place, so we don't have to crawl through all our logs manually. All standalone-applications, our website aswell as our game-servers are linked into sentry.
Sentry is amazing, most of our systems send their exceptions to sentry. We couldn't live without it and get a much better understanding of how our code is behaving in the wild. Plus it integrates with Github.
Used for graphing internal logging data; including metrics related to how fast we serve pages and execute MySQL/ElasticSearch queries.
Our Kibana instances uses our ElasticSearch search data to help answer any complicated questions we have about our data.
Kibana is our tools to query data in Elasticsearch clusters set up as catalog search engine.