"Tens of thousands of organizations use MongoDB to build high-performance systems at scale, including over 30 of the world’s 100 largest organizations and many of the world’s most successful and innovative web companies. To achieve high performance with any database system requires an understanding of best practices.
Get the guide that will inform you of the best practices and considerations for achieving performance at scale in a MongoDB system."
Find the possibility to download a best practice white paper here.
In a guest post by Asya Kamsky you can find "10 Things You Should Know About Running MongoDB At Scale"
- MongoDB requires DevOps, too.
- Successful MongoDB users monitor everything and prepare for growth.
- The obstacles to scaling performance as your usage grows may not be what you’d expect.
- Lots of MongoDB users succeed with a single replica set.
- You can get great performance out of MongoDB, even if your entire database doesn’t fit in RAM.
- Data written has to be flushed to disk.
- Replication != Backups.
- Replica set health is more than replication lag.
- MongoDB doesn’t know how secure your data needs to be.
- There is no need to tinker under the hood.
Find the complete article here.
The New Way
If you’re looking for a very modern way to check and monitor performance, you should give Performance Analyzer a try.
Monitor and Analyze MongoDB database configuration and performance metrics. Correlate events and metrics from databases, operating system and/or virtualization layer (VMware vSphere, KVM). Troubleshoot bottlenecks and capacity issues in minutes using our efficient data crawler and preconfigured dashboards. Complete setup in minutes instead of hours or days.
Some of our MongoDB Server integration features are:
- Visualize real-time and historical performance metrics of your NoSQL Server
- Set important thresholds for your NoSQL Server based on custom metrics
- Check Database Open Connections and Commands over time
- Plan resources based on Database growth and memory usage
- Full insights into Disk Latency and VM Disk IOps of the underlying operating system