RG System and DataStax Enterprise Offer an All-Inclusive SaaS Infrastructure Management SolutionApril 24, 2017
This post is one in a series of quick-hit interviews with companies using DataStax Enterprise (DSE) for key parts of their business. In this interview, we talked with Benoit Balzola, System DevOps at RG System.
DataStax: Hello Benoit, thanks a lot for your time today. Could you please tell us a bit about RG System and your role at the company?
RG System: RG System is the software editor of an all-in-one SaaS infrastructure management solution that gathers on one unique Dashboard IT monitoring, antimalware security and online data backup. Therefore, we enable CTOs and MSPs to keep an eye on their IT resources and to be alerted if something goes wrong.
I am RG’s System DevOps so my job is to make sure our infrastructure is always up in order to guarantee our customers the highest uptime possible. And Cassandra’s fault tolerance is definitely a huge help for that!
DataStax: What differentiates RG System from other companies offering SaaS infrastructure management solutions?
RG System: We are the only company to offer such a comprehensive Dashboard that enables its users to monitor their infrastructure, backup their data and secure their IT resources from the same web interface.
Moreover, since we developed the monitoring solution from scratch, we decided to collaborate on the security and backup sides with companies that are known to be the best in their markets. This is how our Dashboard embeds Bitdefender Gravity Zone V6 and Dell EMC Avamar technologies, which is also unique in our market.
Finally, I would say that our customer oriented approach stands out from the competition. We are and Agile company, we follow SCRUM guidelines when it comes to development and thanks to our participative roadmap, our customers can express themselves, let us know which feature is important for them and vote on the community ideas to prioritize their development.
DataStax: Did you use a different technology before you started using DataStax Enterprise (DSE)?
RG System: We used to work with SQL before switching to Cassandra, but we reached its limits: 48 CPU, 128 GB RAM, 10000 I/OPS SSD backed storage. We needed to scale, that’s why we decided to switch to Apache Cassandra™ Open Source first, before switching definitely to DSE.
DataStax: Why did you decide to use DataStax Enterprise?
RG System: As I said, we reached the limits of SQL and we had to reach many more query/sec. We switched from SQL to DSE when we reached about 3000 write/s and 3000 read/s. As we’re storing everything related to monitoring into DSE, we really needed a more powerful technology to sustain our development.
DataStax: How would you sum up the benefits you’ve achieved with DataStax Enterprise?
RG System: I think it holds in 4 words: scale, fault tolerance, DSE Search and OpsCenter. And the online documentation is definitely useful!
DataStax: What caused you to use DataStax Enterprise over open source Apache Cassandra™?
RG System: We needed to have a global overview of our infrastructure, and that’s what we achieved with OpsCenter. Plus it was really important for us to be able to search for the precise info we needed in the whole big data, and that’s where DSE Search could definitely come handy.
DataStax: What features from the DataStax Enterprise stack are you using at the moment?
RG System: We are mainly using OpsCenter and DSE Search that provide us real time analysis on loads of data, massive indexation, and faster queries.
DataStax: Tell us about the future of your project(s), do you intend to leverage other parts of DSE to make it a reality?
RG System: At the moment we are keeping an eye on DSE Graph. Our Dashboard is based on a treeview research so it would make sense to use this complementary technology offered by DataStax.
DataStax: What advice would you give to other startups that are thinking about using Cassandra and DSE for the first time in their solutions?
RG System: Start with it from the very beginning. We didn’t, and we had to migrate from a relational model to a denormalized one, an experience you definitely want to avoid!
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