With application data observability from Neblic, you can monitor the data in your Kafka topic so you can better debug your application
Neblic's Kafka integration samples data from Kafka Topics. The data is sent to a local Neblic collector where data is analyzed in real-time. Data checks and data metrics are created locally and only metrics are sent to the cloud.
Your data is analyzed locally in the Neblic collector. We set specific metrics relevant for each specific field. Checks such as nulls, value distributions, the cardinality of values seen, and more. You can also set custom functions that evaluate for domain-specific data checks.
Once you've identified root cause, you can start testing a solution. With Neblic also deployed in Dev or Stage enviroments, you can even compare results in real time between enviroments. Find, fix, compare, ship.
Data observability allows you to monitor your Kafka application to ensure it functions correctly by analyzing the data in each topic. A set of custom checks and metrics continuously analyze your data in multiple parts of your application, giving you a sense of the application's health in real-time.
Having a single view of your application through a single pane of glass enables anyone to understand each topic's function and gain valuable context, without requiring specialized domain knowledge.
Monitoring the application in real time lets us detect any issues just as they happen, and alert so it can be acted upon before customers need to tell you what is happening.
By looking at the application data and understanding it, Neblic is able to level up any developer to troubleshoot issues on any service, even if they don't have domain expertise in it.
Answering the questions that your APM stack just can't
By monitoring actual application data in real time, you can get precise understanding of what the issue is, and go back in time to where it started.
Deploy Samplers in Points of Interest in your application, and track down the source of the issues.
What events made it fail? an unexpected null value? a change of schema? Easily track it down.
Single point of authentication to all of your services. Query the data using a unified interface, regardless of what the underlying system is.
A generic observability tool that lets you catch errors at runtime without having to hardcode errors or having to re-compile your application.
You can run elaborate, custom data checks with real-world production data, rather than having to rely on ad-hoc tests with synthetic data, and without affecting the production enviroment.