This is a story of an excursion to the bottom of a deep rabbit hole, where I discovered a foot gun in `gcc`’s `libgcc`. The investigation has cost me several days and I hope that by writing this up I can entertain others and save them the journey.

TL;DR

If a C++ application is compiled with GCC on Linux and statically linked against a non-GLibC C-library (like `libmusl`), then there is a danger of a data race which leads to a busy loop happening after `main()` and all static destructors have finished. The race happens, if the application does not use `pthread_cancel` explicitly and if the..

This post uses the new `.tar.gz` binary distribution of ArangoDB to run multiple versions of ArangoDB alongside each other on the same machines. We will do a production-ready deployment on 3 cloud instances with authentication, TLS encryption, (self-signed) certificates and `systemd` service. In the end, we show how to perform a rolling upgrade for one of the clusters to a new version.

Interested in trying out ArangoDB? Fire up your cluster in just a few clicks with ArangoDB ArangoGraph: the Cloud Service for ArangoDB. Start your free 14-day trial here

The new `.tar.gz` binary archive

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It has been a few months since we first released the Kubernetes operator for ArangoDB and started to brag about it. Since then, quite a few things have happened.

For example, we have done a lot of testing, fixed bugs, and by now the operator is declared to be production ready for three popular public Kubernetes offerings, namely Google Kubernetes Engine (GKE), Amazon Elastic Kubernetes Service (EKS) and Pivotal Kubernetes Service (PKS) (see here for the current state of affairs).

To investigate the impact of the Meltdown and Spectre patches on the performance of ArangoDB, we ran benchmark tests with the two storage engines available in ArangoDB (MMFiles & RocksDB). We used the arangobench benchmark and test tool for these tests.

The tests include 10 different test cases with changing test parameters like concurrency, batch requests and asynchronous execution.

I have varying levels of familiarity with Google’s original leveldb and three of its derivatives. RocksDB is one of the three. In each of the four leveldb offerings, the code is optimized for a given environment. Google’s leveldb is optimized for a cell phone, which has much more limited resources than a server. RocksDB is optimized for flash arrays on a large servers (per various Rocksdb wiki pages). Note that a flash array is a device of much higher throughput than a SATA or SSD drive or array. It is a device that sits on the processor’s bus. RocksDB’s performance benchmark page details a..

Every company needs a disaster recovery plan for all important systems. This is true from small units like single processes running in some container to the largest distributed architectures. For databases in particular this usually involves a mixture of fault-tolerance, redundancy, regular backups and emergency plans. The larger a data store, the more difficult is it to come up with a good strategy.

Recently I gave a talk about ArangoDB in front of a community of mathematicians. I advertised that nearly arbitrary data can “easily” be stored in a JSON based document store. The moment I had uttered the word “easily”, one of them asked about long integers. And if a mathematician says “long integer” they do not mean 64bit but “properly long”. He actually wanted to store orders of finite groups. I said one should use a JSON UTF-8 string for this but I should have seen the next question coming because he then wanted that a sorted index would actually sort the documents by the numerical value..

With the new Version 3.2 we have introduced a new feature called SatelliteCollections. This post explains what this is all about, how it can help you, and explains a concrete use case for which it is essential.

Recently, we have got a lot of feedback about the fact that standing up an ArangoDB cluster “manually” is an awkward and error-prone affair. We have been aware of this for some time, but always expected that most users running ArangoDB clusters would do so on Apache Mesos or DC/OS, where deployment is a breeze due to our ArangoDB framework.

However, for various valid reasons people do not want to use Apache Mesos and thus are back to square one with the problem of deploying an ArangoDB cluster without Apache Mesos.