Tag Archives: scylla

Evaluating ScyllaDB for production 1/2

I have recently been conducting a quite deep evaluation of ScyllaDB to find out if we could benefit from this database in some of our intensive and latency critical data streams and jobs.

I’ll try to share this great experience within two posts:

  1. The first one (you’re reading) will walk through how to prepare yourself for a successful Proof Of Concept based evaluation with the help of the ScyllaDB team.
  2. The second post will cover the technical aspects and details of the POC I’ve conducted with the various approaches I’ve followed to find the most optimal solution.

But let’s start with how I got into this in the first place…


Selecting ScyllaDB

I got interested in ScyllaDB because of its philosophy and engagement and I quickly got into it by being a modest contributor and its Gentoo Linux packager (not in portage yet).

Of course, I didn’t pick an interest in that technology by chance:

We’ve been using MongoDB in (mass) production at work for a very very long time now. I can easily say we were early MongoDB adopters. But there’s no wisdom in saying that MongoDB is not suited for every use case and the Hadoop stack has come very strong in our data centers since then, with a predominance of Hive for the heavy duty and data hungry workflows.

One thing I was never satisfied with MongoDB was its primary/secondary architecture which makes you lose write throughput and is even more horrible when you want to set up what they call a “cluster” which is in fact some mediocre abstraction they add on top of replica-sets. To say the least, it is inefficient and cumbersome to operate and maintain.

So I obviously had Cassandra on my radar for a long time, but I was pushed back by its Java stack, heap size and silly tuning… Also, coming from the versatile MongoDB world, Cassandra’s CQL limitations looked dreadful at that time…

The day I found myself on ScyllaDB’s webpage and read their promises, I was sure to be challenging our current use cases with this interesting sea monster.


Setting up a POC with the people at ScyllaDB

Through my contributions around my packaging of ScyllaDB for Gentoo Linux, I got to know a bit about the people behind the technology. They got interested in why I was packaging this in the first place and when I explained my not-so-secret goal of challenging our production data workflows using Scylla, they told me that they would love to help!

I was a bit surprised at first because this was the first time I ever saw a real engagement of the people behind a technology into someone else’s POC.

Their pitch is simple, they will help (for free) anyone conducting a serious POC to make sure that the outcome and the comprehension behind it is the best possible. It is a very mature reasoning to me because it is easy to make false assumptions and conclude badly when testing a technology you don’t know, even more when your use cases are complex and your expectations are very high like us.

Still, to my current knowledge, they’re the only ones in the data industry to have this kind of logic in place since the start. So I wanted to take this chance to thank them again for this!

The POC includes:

  • no bullshit, simple tech-to-tech relationship
  • a private slack channel with multiple ScyllaDB’s engineers
  • video calls to introduce ourselves and discuss our progress later on
  • help in schema design and logic
  • fast answers to every question you have
  • detailed explanations on the internals of the technology
  • hardware sizing help and validation
  • funny comments and French jokes (ok, not suitable for everyone)

 

 

 

 

 

 

 

 

 


Lessons for a successful POC

As I said before, you’ve got to be serious in your approach to make sure your POC will be efficient and will lead to an unbiased and fair conclusion.

This is a list of the main things I consider important to have prepared before you start.

Have some background

Make sure to read some literature to have the key concepts and words in mind before you go. It is even more important if like me you do not come from the Cassandra world.

I found that the Cassandra: The Definitive Guide book at O’Reilly is a great read. Also, make sure to go around ScyllaDB’s documentation.

Work with a shared reference document

Make sure you share with the ScyllaDB guys a clear and detailed document explaining exactly what you’re trying to achieve and how you are doing it today (if you plan on migrating like we did).

I made a google document for this because it felt the easiest. This document will be updated as you go and will serve as a reference for everyone participating in the POC.

This shared reference document is very important, so if you don’t know how to construct it or what to put in it, here is how I structured it:

  1. Who’s participating at <your company>
    • photo + name + speciality
  2. Who’s participating at ScyllaDB
  3. POC hardware
    • if you have your own bare metal machines you want to run your POC on, give every detail about their number and specs
    • if not, explain how you plan to setup and run your scylla cluster
  4. Reference infrastructure
    • give every details on the technologies and on the hardware of the servers that are currently responsible for running your workflows
    • explain your clusters and their speciality
  5. Use case #1 : <name>
    • Context
      • give context about your use case by explaining it without tech words, think from the business / user point of view
    • Current implementations
      • that’s where you get technical
      • technology names and where they come into play in your current stack
      • insightful data volumes and cardinality
      • current schema models
    • Workload related to this use case
      • queries per second per data source / type
      • peek hours or no peek hours?
      • criticality
    • Questions we want to answer to
      • remember, the NoSQL world is lead by query-based-modeling schema design logic, cassandra/scylla is no exception
      • write down the real questions you want your data model(s) to be able to answer to
      • group them and rate them by importance
    • Validated models
      • this one comes during the POC when you have settled on the data models
      • write them down, explain them or relate them to the questions they answer to
      • copy/paste some code showcasing how to work with them
    • Code examples
      • depending on the complexity of your use case, you may have multiple constraints or ways to compare your current implementation with your POC
      • try to explain what you test and copy/paste the best code you came up with to validate each point

Have monitoring in place

ScyllaDB provides a monitoring platform based on Docker, Prometheus and Grafana that is efficient and simple to set up. I strongly recommend that you set it up, as it provides valuable insights almost immediately, and on an ongoing basis.

Also you should strive to give access to your monitoring to the ScyllaDB guys, if that’s possible for you. They will provide with a fixed IP which you can authorize to access your grafana dashboards so they can have a look at the performances of your POC cluster as you go. You’ll learn a great deal about ScyllaDB’s internals by sharing with them.

Know when to stop

The main trap in a POC is to work without boundaries. Since you’re looking for the best of what you can get out of a technology, you’ll get tempted to refine indefinitely.

So this is good to have at least an idea on the minimal figures you’d like to reach to get satisfied with your tests. You can always push a bit further but not for too long!

Plan some high availability tests

Even if you first came to ScyllaDB for its speed, make sure to test its high availability capabilities based on your experience.

Most importantly, make sure you test it within your code base and guidelines. How will your code react and handle a failure, partial and total? I was very surprised and saddened to discover so little literature on the subject in the Cassandra community.

POC != production

Remember that even when everything is right on paper, production load will have its share of surprises and unexpected behaviours. So keep a good deal of flexibility in your design and your capacity planning to absorb them.

Make time

Our POC lasted almost 5 months instead of estimated 3, mostly because of my agenda’s unwillingness to cooperate…

As you can imagine this interruption was not always optimal, for either me or the ScyllaDB guys, but they were kind not to complain about it. So depending on how thorough you plan to be, make sure you make time matching your degree of demands. The reference document is also helpful to get back to speed.


Feedback for the ScyllaDB guys

Here are the main points I noted during the POC that the guys from ScyllaDB could improve on.

They are subjective of course but it’s important to give feedback so here it goes. I’m fully aware that everyone is trying to improve, so I’m not pointing any fingers at all.

I shared those comments already with them and they acknowledged them very well.

More video meetings on start

When starting the POC, try to have some pre-scheduled video meetings to set it right in motion. This will provide a good pace as well as making sure that everyone is on the same page.

Make a POC kick starter questionnaire

Having a minimal plan to follow with some key points to set up just like the ones I explained before would help. Maybe also a minimal questionnaire to make sure that the key aspects and figures have been given some thought since the start. This will raise awareness on the real answers the POC aims to answer.

To put it simpler: some minimal formalism helps to check out the key aspects and questions.

Develop a higher client driver expertise

This one was the most painful to me, and is likely to be painful for anyone who, like me, is not coming from the Cassandra world.

Finding good and strong code examples and guidelines on the client side was hard and that’s where I felt the most alone. This was not pleasant because a technology is definitely validated through its usage which means on the client side.

Most of my tests were using python and the python-cassandra driver so I had tons of questions about it with no sticking answers. Same thing went with the spark-cassandra-connector when using scala where some key configuration options (not documented) can change the shape of your results drastically (more details on the next post).

High Availability guidelines and examples

This one still strikes me as the most awkward on the Cassandra community. I literally struggled with finding clear and detailed explanations about how to handle failure more or less gracefully with the python driver (or any other driver).

This is kind of a disappointment to me for a technology that position itself as highly available… I’ll get into more details about it on the next post.

A clearer sizing documentation

Even if there will never be a magic formula, there are some rules of thumb that exist for sizing your hardware for ScyllaDB. They should be written down more clearly in a maybe dedicated documentation (sizing guide is labeled as admin guide at time of writing).

Some examples:

  • RAM per core ? what is a core ? relation to shard ?
  • Disk / RAM maximal ratio ?
  • Multiple SSDs vs one NMVe ?
  • Hardware RAID vs software RAID ? need a RAID controller at all ?

Maybe even provide a bare metal complete example from two different vendors such as DELL and HP.

What’s next?

In the next post, I’ll get into more details on the POC itself and the technical learnings we found along the way. This will lead to the final conclusion and the next move we engaged ourselves with.

ScyllaDB meets Gentoo Linux

I am happy to announce that my work on packaging ScyllaDB for Gentoo Linux is complete!

Happy or curious users are very welcome to share their thoughts and ping me to get it into portage (which will very likely happen).

Why Scylla?

Ever heard of the Cassandra NoSQL database and Java GC/Heap space problems?… if you do, you already get it 😉

I will not go into the details as their website does this way better than me but I got interested into Scylla because it fits the Gentoo Linux philosophy very well. If you remember my writing about packaging Rethinkdb for Gentoo Linux, I think that we have a great match with Scylla as well!

  • it is written in C++ so it plays very well with emerge
  • the code quality is so great that building it does not require heavy patching on the ebuild (feels good to be a packager)
  • the code relies on system libs instead of bundling them in the sources (hurrah!)
  • performance tuning is handled by smart scripting and automation, allowing the relationship between the project and the hardware is strong

I believe that these are good enough points to go further and that such a project can benefit from a source based distribution like Gentoo Linux. Of course compiling on multiple systems is a challenge for such a database but one does not improve by staying in their comfort zone.

Upstream & contributions

Packaging is a great excuse to get to know the source code of a project but more importantly the people behind it.

So here I got to my first contributions to Scylla to get Gentoo Linux as a detected and supported Linux distribution in the different scripts and tools used to automatically setup the machine it will run upon (fear not, I contributed bash & python, not C++)…

Even if I expected to contribute using Github PRs and got to change my habits to a git-patch+mailing list combo, I got warmly welcomed and received positive and genuine interest in the contributions. They got merged quickly and thanks to them you can install and experience Scylla in Gentoo Linux without heavy patching on our side.

Special shout out to Pekka, Avi and Vlad for their welcoming and insightful code reviews!

I’ve some open contributions about pushing further on the python code QA side to get the tools to a higher level of coding standards. Seeing how upstream is serious about this I have faith that it will get merged and a good base for other contributions.

Last note about reaching them is that I am a bit sad that they’re not using IRC freenode to communicate (I instinctively joined #scylla and found myself alone) but they’re on Slack (those “modern folks”) and pretty responsive to the mailing lists 😉

Java & Scylla

Even if scylla is a rewrite of Cassandra in C++, the project still relies on some external tools used by the Cassandra community which are written in Java.

When you install the scylla package on Gentoo, you will see that those two packages are Java based dependencies:

  • app-admin/scylla-tools
  • app-admin/scylla-jmx

It pained me a lot to package those (thanks to help of @monsieurp) but they are building and working as expected so this gets the packaging of the whole Scylla project pretty solid.

emerge dev-db/scylla

The scylla packages are located in the ultrabug overlay for now until I test them even more and ultimately put them in production. Then they’ll surely reach the portage tree with the approval of the Gentoo java team for the app-admin/ packages listed above.

I provide a live ebuild (scylla-9999 with no keywords) and ebuilds for the latest major version (2.0_rc1 at time of writing).

It’s as simple as:

$ sudo layman -a ultrabug
$ sudo emerge -a dev-db/scylla
$ sudo emerge --config dev-db/scylla

Try it out and tell me what you think, I hope you’ll start considering and using this awesome database!