Performance analysis with pyArango: Part III Measuring possible capacity with usage Scenarios

00General, how to, PerformanceTags: , , , , ,

So you measured and tuned your system like described in the Part I and Part II of these blog post series. Now you want to get some figures how many end users your system will be able to serve. Therefore you define “scenarios” which will be typical for what your users do.
One such a user scenario could i.e. be:

  • log in
  • do something
  • log out

Since your users won’t nicely queue up and wait for other users to finish their business, the pace you need to test your defined system is “starting n scenarios every second”. Many scenarios simulating different users may be running in parallel. If your scenario would require 10 seconds to finish, and you’d start 1 per second, that means that your system needs to be capable to process 10 users in parallel. If it can’t handle that, you will see that more than 10 sessions are running in parallel, and the time required to handle such a scenario will lengthen. You will see the server resource usage go up and up, and finally have it burst in flames.
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Setting up Datacenter to Datacenter Replication in ArangoDB

00Architecture, cluster, General, how to, Releases, ReplicationTags: , ,

Please note that this tutorial is valid for the ArangoDB 3.3 milestone 1 version of DC to DC replication!

This milestone release contains data-center to data-center replication as an enterprise feature. The is a preview of the upcoming 3.3 release and is not considered production ready.

In order to prepare for a major disaster, you can setup a backup data center that will take over operations if the primary data center goes down. For a server failure, the resilience features of ArangoDB can be used. Data center to data center is used to handle the failure of a complete data center.

Data is transported between data-centers using a message queue. The current implementation uses Apache Kafka as message queue. Apache Kafka is a commonly used open source message queue which is capable of handling multiple data-centers. However, the ArangoDB replication is not tied to Apache Kafka. We plan to support different message queues systems in the future.

The following contains a high-level description how to setup data-center to data-center replication. Detailed instructions for specific operating systems will follow shortly. Read more

A geo demonstration using Foxx

01Foxx, how toTags: ,

Geo data is getting more and more important for today’s applications. The growing number of location-aware services, IoT applications and other solutions using latitude and longitude ask for precise and fast processing of geo data.

Let me show you in this quick demonstration how you can use geo functions and visualize your data using Foxx and leaflet.js. Read more

How to put ArangoDB to Spartan-Mode

00Foxx, General, how toTags:

Most of us saw the fantastic movie 300 (I did it last night…again) or at least read the comics. 300 spartans barely wearing anything but achieving a lot. This little how-to will show you how to put ArangoDB into Spartan-Mode and thereby reduce memory-footprint and CPU usage.

Big thanks to Conrad from L.A. for his time and for giving us the impulse for this little how-to!
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Read the latest NoSQL Performance Benchmark 2018: MongoDB, PostgreSQL, OrientDB, Neo4j and ArangoDB