Tuning nProbe Performance¶
As nProbe can be deployed on very different environments, it is necessary to tune it according to the network where is active. In order to achieve a good probe setup, it is necessary to understand how nProbe is working internally. Each captured packet is analyzed, associated to a flow, and stored onto a hash. Periodically, the hash is analyzed and expired flows are emitted. The hash size is static (-w flag) as this allows nProbe to: Allocate all the needed memory at startup (this is compulsory on embedded systems where memory is limited and it is necessary to know at startup whether a certain application can operate with the available resources). Avoid exhausting all the available memory in case of attacks that can produce several flows. Selecting the hash size is a matter of trade-off between efficiency (an efficient hash is at least 1/3 empty) and memory usage. This statement does not mean that a huge hash is always the solution as the flow export process can be slower (and more CPU cycles are needed) as a large hash needs to be explored.
On the other hand, the hash size is just a part of the problem. In fact, the hash fill percentage can be also controlled by other factors such as:
- Reducing the flow lifetime (-t)
- Reducing the maximum flow idle time (-d)
- Increasing how often the hash is walked searching expired flows (-s)
nProbe allows users to ease the tuning process by printing the status of internal hashes using the –b flag. Users who experience severe nProbe performance problems, packet loss or high CPU usage, should start nProbe with –b in order to find out whether their probe setup is optimal.
High-Speed Flow Collection¶
Since nProbe 9.2 we have introduced a new command line option
--collector-passthrough that is suitable when you want collect flows and send them unchanged to a temote collector. As the flow cache is completely bypassed, the collection speed is greatly enhanced, so this is the best option you can choose for instance when delivering flows to ntopng.
When you need to collect flows at high speed with minimum CPU and memory requirements (this is the case whe collected flows are not stored into the cache but exported immediately), you should consider cache bypassing. In particular this is achieved with the –collector-passthrough option. Please refer to the “nProbe Case Study” section of this manual for further information about this topic.
Expected Collection Performance¶
nProbe has been enhacend with a new command line option
--simulate-collection that allows to simulate infinite flow ingress to measure the top collection speed. The current performance numbers have been reported on this blog post and can be as high as 300 Kfps (collection only) or 183 Kfps when speaking with ntopng via ZMQ.
Collecting Flows from Many Routers¶
When nProbe is used to colelct flows from many routers, it is important to label the flow according to the location it originates from. In particular in large networks, locations are spread across multiple sites, so identifying the flow source using the IP address of the probe is not often possible. For this reason nProbe implements the observation point concept.
It allows you to mark flows according to their source regardless of the IP address of the probe originating them. You can read more about this topic on this blog post
Handling Trillion Flows: Dumping Flows into ClickHouse¶
nProbe Enterprise M/L can natively dump flows into the ClickHouse open source database. Due to the nature of ClickHouse, data import happens in batches using a syntax similar to MySQL dump, namely
--clickhouse=<host[@port]>:<dbname>:<prefix>:<user>:<pw> You can read more about this topic on this blog post
There are many reasons for which the information we collect cam be duplicated, including routing, redundant paths, backup devices. nProbe provides you advanced features for data deduplication:
- When you have duplicated packets you can use the option
--enable-ipv4-deduplicationto discard consecutive duplicated IPv4 packets. Note that retransmissions might be exchanged (if consecutive) for duplications
- During collection you can use
--flow-deduplicationto specify and interval (example –flow-deduplication 15) in seconds during which if a flow is seen two or more times, only the first flow is considered