Looking for a way to mask your sensitive data? Newly contributed "Sanitizer plugin" for Fluentd might be able to help you.

In this blog, we will talk about 3 of the most common architectures that users leverage when deploying Fluent Bit and Fluentd: Forwarder's and Aggregators, Side car / Agent deployment, and Network device aggregator.

Reducing log volume sent to a single location, performing calculations before sending data to a back end, and time-series predictions for when an application may consume too much memory. This blog walks through these use cases and how to leverage Fluent Bit's new stream processing features with a standard data pipeline.

The use of containers in production has reached to 92%+ in the CNCF survey. Check this post if you're using Fluentd with k8s. Next up is fluentbit, ConfigMap and Forwarder/Aggregator discussion. Stay tuned.

Need some tips for multiline log parsing? We will walk through multiline log collection challenges and how to use Fluent Bit to collect these critical logs.

In the previous post, we discussed key use cases and approach regarding Fluentd and Kafka. Now, we will be reviewing the step-by-step instruction of how to configure Fluentd and Kafka with some security features.

In enterprise, processing streaming data in real time sometimes gets critical. A good example is “SecOps“. If you are an operator of SecOps, you need to capture the events which may cause security incidents in order to take actions, such as blocking suspicious access by changing security configuration, once you get event triggers. “Event-driven” system addresses this by getting those data in real time basis and responding quickly to the events happening.

Diagtool is a simple, yet powerful tool to simplify troubleshooting process and also make it more secure. Diagtool delivers the functions you need to automate your process and accelerate the problem determination :

The code has been contributed in the Fluentd community. You can download instructions for Diagtool here.

Running operations is much more challenging than just plugging in new software.Troubleshooting is a constant nightmare for anyone operating even minimal software. When the software is implemented in production, it is even more challenging for the ops team.