Skip to main content

Flume 1.2.0 released

By Anonymous

The Apache Flume Team released yesterday the next large release with number 1.2.0. Here a overview about the fixes and additions (thanks Mike, I copy your overview):

Apache Flume 1.2.0 is the third release under the auspices of Apache of the so-called "NG" codeline, and our first release as a top-level Apache project! Flume 1.2.0 has been put through many stress and regression tests, is stable, production-ready software, and is backwards-compatible with Flume 1.1.0. Four months of very active development went into this release: a whopping 192 patches were committed since 1.1.0, representing many features, enhancements, and bug fixes. While the full change log can be found in the link below, here are a few new feature highlights:

* New durable file channel 
* New client API 
* New HBase sinks (two different implementations) 
* New Interceptor interface (a plugin processing API) 
* New JMX-based monitoring support

With this release - the first after evolving into a tier 1 Apache project - we've updated the website and firstly have a well written UserGuide (again thanks to Mike and Ralph for their great effort).

User-Guide: http://flume.apache.org/FlumeUserGuide.html
Api-Documention:  http://flume.apache.org/releases/content/1.2.0/apidocs/

What's the next?
Now, we got a increasing interest into a Windows version. I don't know why, but that's happen. I try to port some of the sinks into a Windows Platform - if you're a Windows Developer and you've time to spent into the project, all hands are welcome.







Related guides:




If you need help with distributed systems, backend engineering, or data platforms, check my Services.













Labels:







































Most read articles





















Why Is Customer Obsession Disappearing?












By
























    Many companies trade real customer-obsession for automated, low-empathy support. Through examples from Coinbase, PayPal, GO Telecommunications and AT&T, this article shows how reliance on AI chatbots, outsourced call centers, and KPI-driven workflows erodes trust, NPS and customer retention.     It argues that human-centric support—treating support as strategic investment instead of cost—is still a core growth engine in competitive markets.   It's wild that even with all the cool tech we've got these days, like AI solving complex equations and doing business across time zones in a flash, so many companies are still struggling with the basics: taking care of their customers. The drama around Coinbase's customer support is a prime example of even tech giants messing up. And it's not just Coinbase — it's a big-picture issue for the whole industry. At some point, the idea of "customer obsession" got replaced with "customer automation," and no...

























Read more




























What the Heck is Superposition and Entanglement?












By
























   This post is about superposition and interference in simple, intuitive terms. It describes how quantum states combine, how probability amplitudes add, and why interference patterns appear in systems such as electrons, photons and waves. The goal is to give a clear, non mathematical understanding of how quantum behavior emerges from the rules of wave functions and measurement.  If you’ve ever heard the words superposition or entanglement thrown around in conversations about quantum physics, you may have nodded politely while your brain quietly filed them away in the "too confusing to deal with" folder.  These aren't just theoretical quirks; they're the foundation of mind-bending tech like Google's latest quantum chip, the Willow  with its 105 qubits. Superposition challenges our understanding of reality, suggesting that particles don't have definite states until observed. This principle is crucial in quantum technologies, enabling phenomena like quantum comp...

























Read more




























SynthLink Compared to Google’s Natural Questions: A Practical Evaluation












By
























SynthLink evaluates reasoning, synthesis and internal consistency across diverse question types. Google’s Natural Questions evaluates extractive QA: finding short text spans inside structured documents. Because real workloads require interpretation, abstraction and multi-step logic, SynthLink exposes capabilities and failure modes that NQ cannot measure. The two benchmarks are complementary, but SynthLink is more aligned with production tasks.   Benchmarks such as Google’s Natural Questions (NQ) dominate model evaluation. They provide a reliable, academically stable test for extractive question answering: short queries, grounded answers, and constrained context ranges. But real workloads rarely look like NQ. Production systems must handle ambiguous inputs, multi-step reasoning, poorly structured prompts, and cases where no canonical answer exists. SynthLink was designed for this broader landscape. It focuses on evaluating reasoning, synthesis and internal consistency rather than snippe...

























Read more