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· 4 min read
Dominik Lohmann

We're thrilled to announce the release of Tenzir v4.9, enhancing the Explorer further to empower you with the capability of rendering your data as a chart.

· 2 min read
Dominik Lohmann

Did you ever want to get a sneak peek behind the scenes at Tenzir? Now you can!

· 3 min read
Dominik Lohmann
Jannis Christopher Köhl

Hot off the press: Tenzir v4.8. This release is filled with goodness.

· 3 min read
Matthias Vallentin

We re-wired Tenzir's fluent-bit operator and introduced a significant performance boost as a side effect: A 3–5x gain for throughput in events per second (EPS) and 4–8x improvement of latency in terms of processing time.

· 4 min read
Dominik Lohmann

Tenzir v4.7 brings a new context type, two parsers, four new operators, improvements to existing parsers, and a sizable under-the-hood performance improvement.

· 9 min read
Matthias Vallentin

How would you create a contextualization engine? What are the essential building blocks? We asked ourselves these questions after studying what's out there and built from scratch a high-performance contextualization framework in Tenzir. This blog post introduces this brand-new framework, provides usage examples, and describes how you can build your own context plugin.

· 6 min read
Dominik Lohmann

Tenzir v4.6 is here, and it is our biggest release yet. The headlining feature is the all-new context feature, powered by the context and enrich operators and the new context plugin type.

· 6 min read
Matthias Vallentin

Enrichment is a major part of a security data lifecycle and can take on many forms: adding GeoIP locations for all IP addresses in a log, attaching asset inventory data via user or hostname lookups, or extending alerts with magic score to bump it up the triaging queue. The goal is always to make the data more actionable by providing a better ground for decision making.

This is the first part of series of blog posts on contextualization. We kick things off by looking at how existing systems do enrichment. In the next blog post, we introduce how we address this use case with pipeline-first mindset in the Tenzir stack.