Pick the wrong log collector and you pay for it on every node you deploy. A heavier agent multiplied across a thousand hosts is real memory and CPU you can’t get back, and a pipeline wired tightly to one vendor’s backend is hard to unwind later. So the Fluentd vs Logstash decision usually comes down to two questions: how much processing do you need at the collection point, and how committed are you to the Elastic Stack?

Most telemetry pipelines treat every newline as the end of an event. That assumption holds for a tidy syslog stream but breaks the moment a Java stack trace, a Python traceback, or a pretty-printed JSON payload lands in the file. One event becomes forty lines, and your SIEM ingests forty fragments instead of one record. For a SecOps team, the cost is operational. Detection rules match on fragments or miss the event entirely, correlation loses the context that made the event worth alerting on, and the event count balloons against a volume-based license.

We are happy to announce the latest release of NXLog Platform, version 1.13. This update adds NXLog Platform operating system support for Debian 13 and NXLog Agent support for legacy 32-bit Windows. Plus, you can now use NXLog Agent with the native macOS Keychain for secure certificate storage on Apple systems. Read on for more details about these updates. Deploy NXLog Platform on Debian 13 NXLog Platform 1.13 adds support for installation on Debian 13, the latest stable release of the Debian operating system.

At NXLog, we’ve been in the log collection space long enough to know that the toughest challenges aren’t technical but political. There’s always that Windows XP machine running the ATM firmware that no one can touch. Or the Windows Server 2003 box that keeps the conveyor belt running 24/7. Then there’s the industrial SCADA system installed before smartphones existed, quietly humming along in a corner of the plant floor.

Agentic AI is now embedded across the enterprise: summarizing customer records, pulling from data warehouses, drafting on top of internal documents, calling production APIs on behalf of staff. The pitch is compelling. The reality is that you have deployed a non-deterministic process with read access to PII, trade secrets, and the business intelligence your competitors would pay for. It is a black box that reasons differently on each run, and a single misrouted tool call can move sensitive data into a context where it does not belong.

Fluent Bit wins on footprint. Logstash wins on parsing depth. The choice isn’t which tool is "better" — it’s where in your pipeline each one earns its keep, and what your detection tier silently misses when you put one in the wrong tier. Pick wrong and the cost shows up in three places: detection latency when batches stall, audit evidence when collectors stop shipping, and MTTR when responders can’t tell whether a quiet endpoint is an attack indicator or a broken agent.