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Jaeger vs Zipkin - OpenTracing Distributed Tracers

In the previous three parts of our OpenTracing series, we provided an Overview of OpenTracing, explaining what OpenTracing is and does, how it works and what it aims to achieve, we looked at Zipkin – a popular open-source distributed tracer and then at Jaeger – a newer open-source distributed tracer developed under the CNCF umbrella. In this blog post – the last part of the OpenTracing series – we will compare Jaeger vs. Zipkin side by side!

Garbage Collection Settings for Elasticsearch Master Nodes

Elasticsearch comes with good out-of-the-box Garbage Collection settings. So good in fact that the Definitive Guide recommends not changing them. While we agree that most use-cases wouldn’t benefit from GC tuning, especially when it turns out there simply isn’t enough heap, there are exceptions. We found that G1 GC, for example, works well on big heaps. This allows you to have less, bigger nodes, which in turn means less network traffic in a large cluster.

OpenTracing: Jaeger as Distributed Tracer

In the previous two parts of OpenTracing series, we provided a good OpenTracing overview, explaining what OpenTracing is and does, how it works and what it aims to achieve and looked at Zipkin – a popular open-source distributed tracer. In this blog post, we will look at Jaeger, a newer open-source distributed tracer developed under the CNCF umbrella.

GDPR: Top 5 Logging Best Practices

The rather broad definition of personal data in the GDPR requires paying special attention to log data. GDPR and personal data in web server logs is a popular topic in many GDPR fora. For example, IP addresses or cookies might be considered personal data. Consequently, such data must be stored only with the consent of customers for a limited time. It is highly recommended to anonymize personal data before you hand over the logs to any 3rd party to minimize risk.

OpenTracing: Zipkin as Distributed Tracer

In part one of the OpenTracing blog series we provided a good OpenTracing overview, explaining what OpenTracing is and does, how it works and what it aims to achieve. One of the key aspects of OpenTracing is that it is vendor neutral, and also that OpenTracing is just a specification. In order to instrument an application via OpenTracing API, it’s necessary to have an OpenTracing-compatible tracer correctly deployed and listening for incoming span requests.

Solr on Docker: The Good, the Bad and the Ugly

This talk was given during Lucene Revolution 2017 and has two goals: first, to discuss the tradeoffs for running Solr on Docker. For example, you get dynamic allocation of operating system caches, but you also get some CPU overhead. We'll keep in mind that Solr nodes tend to be different than your average container: Solr is usually long running, takes quite some RSS and a lot of virtual memory. This will imply, for example, that it makes more sense to use Docker on big physical boxes than on configurable-size VMs (like Amazon EC2).

Solr: Optimize Is Not Bad For You Deep Dive Into The Segment Merge Abyss

They say optimize is bad for you, they say you shouldn't do it, they say it will invalidate operating system caches and make your system suffer. This is all true, but is it true in all cases? In this presentation we will look closer on what optimize or better called force merge does to your Solr search engine. You will learn what segments are, how they are built and how they are used by Lucene and Solr for searching.

Elasticsearch for logs and metrics: A deep dive - Velocity 2016, O'REILLY CONFERENCES

We are known worldwide for our Elasticsearch, ELK stack and Solr consulting services, and we are always happy to help others improve their skills in these technologies, not only through Solr & Elastic Stack trainings, but also by sharing our knowledge in meetups and conferences. On 7-9 November 2016, we joined O’REILLY Velocity 2016 conference, discussing the latest tech in Elasticsearch.