FortiSIEM Sizing Information
This document provides information about the following:
Minimum Requirements
Browser Display
FortiSIEM, like most monitoring, SIEM and analytics tools, shows a lot of information on the screen at once. FortiSIEM HTML GUI has chosen a bigger font for legibility reasons. Hence, we recommend that users have a minimum 1680x1050 desktop display resolution.
Hardware
Minimum hardware requirements for FortiSIEM nodes are as follows.
| Node | CPU | RAM | Local Disk |
|---|---|---|---|
| Supervisor | 8 vCPU | 24 GB (32 GB is using Elasticsearch) | 200 GB (80 GB for OS and App, 60 GB for CMDB and 60 GB for SVN) |
| Worker | 4 vCPU | 16 GB | 200 GB (80 GB for OS and App; rest for used) |
| Collector | 2 vCPU | 4 GB | 40 GB |
- Supervisor VA needs more memory since it hosts many heavy-duty components such as Application Server (Java), PostGreSQL Database Server and Rule Master.
- With Elasticsearch, Supervisor VA also hosts the Java Query Server component for communicating with Elasticsearch – hence the need for additional 8 GB memory.
Note that these are only the minimum requirements. The performance may improve by increasing vCPUs and RAM in certain situations. External storage depends on your EPS mix and the number of days of log storage needs. To provide more meaningful guidance, scalability tests were conducted as described below.
Internal Scalability Tests
FortiSIEM team performed several scalability tests described below.
Test Setup
- A specific set of events were sent repeatedly to achieve the target EPS.
- The target EPS was constant over time.
- A set of Linux servers were monitored via SNMP and performance monitoring data was collected.
- Events triggered many incidents.
Test Success Criteria
The following success criteria should be met on testing:
- Incoming EPS must be sustained without any event loss.
- Summary dashboards should be up to date and not fall behind.
- Widget dashboards should show data indicating that inline reporting is keeping up.
- Incidents should be up to date.
- Real-time search should show current data and trend chart should reflect incoming EPS.
- GUI navigation should be smooth.
- CPU, memory and IOPS are not maxed out. Load average must be less than the number of cores.
The tests were run for three cases:
- All-in-one FSM Hardware Appliance: FSM-2000F and FSM-3500F with collectors FSM-500F sending events.
- FSM Virtual Appliance with FortiSIEM EventDB as the data store.
- FSM Virtual Appliance with Elasticsearch as the data store.
Hardware Appliance EPS Test
The test beds were as follows:
The results are shown below:
| Event Sender | ||||
|---|---|---|---|---|
| FortiSIEM HW Appliance | Collector Model | Count | EPS/Collector | Sustained EPS without Loss |
| FSM-2000F | FSM-500F | 3 | 5K | 15K |
| FSM-3500F | FSM-500F | 4 | 8K | 30K |
Virtual Appliance EPS Test with FortiSIEM Event Database
All tests were done in AWS. The following hardware was used.
| Type | AWS Instance Type | Hardware Spec |
|---|---|---|
| Collector | c4.xlarge | 4vCPU, 7 GB RAM |
| Worker | c4.2xlarge | 8vCPU, 15 GB RAM |
| Super | m4.4xlarge | 16vCPU, 64 GB RAM, CMDB Disk 10K IOPS |
| NFS Server | c4.2xlarge | 8vCPU, 16 GB RAM, 10K IOPS |
The test bed is as follows:
The following result shows 10K EPS sustained per Worker with over 20K CMDB Devices.
| Event Sender | Event Handler | ||||||
|---|---|---|---|---|---|---|---|
| Collector Count | EPS/Collector | Monitored Device/Collector | Super | Workers | Orgs | CMDB Device | Sustained EPS without Loss |
| 150 | 200 | 150 | 1 | 3 | 150 | 22,500 | 30K |
Virtual Appliance EPS Test with Elasticsearch Database
All tests were done in AWS. The following hardware was used.
| Type | AWS Instance Type | Hardware Spec |
|---|---|---|
| Collector | c4.xlarge | 4vCPU, 7 GB RAM |
| Worker | c4.2xlarge | 8vCPU, 15 GB RAM |
| Super | m4.4xlarge | 16vCPU, 64 GB RAM, CMDB Disk 10K IOPS |
| Elastic Search Master Node | c3.2xlarge | 8vCPU, 16 GB RAM with 8 GB JVM |
| Elastic Search Coordinating Node | m5.4xlarge | 16vCPU, 64 GB RAM with 30 GB JVM allocation |
| Elastic Search Data Node | i3.4xlarge | 16vCPU, 122 GB RAM, 1.9TBx2 NVMe SSD Instance-store Volumes, 30 GB JVM |
The test bed was as follows:
The following result shows 5K EPS sustained per Data Node with over 20K CMDB Devices.
| Event Sender | Event Handler | |||||||
|---|---|---|---|---|---|---|---|---|
| Collector Count | EPS/ Collector | Monitored Device/ Collector | Super | Workers | Elastic (M/CO/DN/ Shards)* | Orgs | CMDB Device | Sustained EPS without Loss |
| 150 | 200 | 150 | 1 | 3 | 1/1/5/10 | 150 | 22,500 | 30K |
Recommended Sizing for FortiSIEM Event DB Based Deployment
Processing Requirement
| Requirement | Recommendation | ||||
|---|---|---|---|---|---|
| EPS | Deployment | HW Model | SW Configuration | ||
| Nodes | HW Per Node (vCPU, RAM) | NFS IOPS | |||
| Up to 5K | Hardware | FSM-2000F | |||
| Up to 5K | Software | All-in-one | 16,24GB | ||
| 5K – 10K | Hardware | FSM-2000F | |||
| 5K – 10K | Software | Supervisor | 16,24GB | ||
| 1 Worker | 8,16GB | 2000 | |||
| 10K – 15K | Hardware | FSM-3500F | |||
| 10K – 15K | Software | Supervisor | 16,24GB | ||
| 2 Workers | 8,16GB | 3000 | |||
| 15K – 25K | Hardware | FSM-3500F | |||
| 15K – 25K | Software | Supervisor | 16,24GB | ||
| 3 Workers | 16,16GB | 5000 | |||
| 25K – 35K | Software | Supervisor | 16,24GB | ||
| 4 Workers | 16,16GB | 7000 | |||
| Add 10K EPS | Software | Add 1 Worker | 16,16GB | Add 2000 IOPS | |
Storage Requirement for FortiSIEM EventDB
FortiSIEM storage requirement depends on three factors:
- EPS
- Bytes/log mix in your environment
- Compression ratio (8:1)
You are likely licensed for Peak EPS. Typically, EPS peaks during morning hours on weekdays and goes down dramatically after 2 pm on weekdays and also remains low on weekends. So the average EPS should be used to calculate storage needs.
For calculating Bytes/log, consider the following aspects:
- Network devices and Linux servers tend to send shorter logs (150-200 bytes/log) while Windows Security logs tend to be much larger (500-1000 bytes/log).
- Busy corporate firewalls and domain controllers tend to send much higher log volumes (higher EPS) than other systems, assuming they are sending all logs.
- Database indices built on logs for efficient searching consumes significant storage as well.
- ASCII text (syslog) compresses much better than binary (for example, Netflow)
Therefore, it is difficult to properly assume a specific Bytes/log mix in your environment without measurement. Our experience from sampling of 5 large customers has shown that Bytes/log is between 100-150 including all factors – device mix, log mix, indexing cost and compression. We calculated this by dividing the total FortiSIEM event file size (in \data) over one day by the total number of events on that day, and then averaging over a few days.
The table below shows two scenarios – Worst case and Average case for NFS storage. In Worst case, Peak EPS and 150 Bytes/log is used. In the Average case, 0.5 Peak EPS and 100 Bytes/log is used.
Peak EPS |
Storage (Months) |
NFS Storage (TB)* |
|
|---|---|---|---|
| Worst case | Average case | ||
1000 |
12 |
5 |
1.66 |
1000 |
24 |
9 |
3 |
1000 |
36 |
14 |
4.66 |
2000 |
12 |
9 |
3 |
2000 |
24 |
19 |
6.33 |
2000 |
36 |
28 |
9.33 |
5000 |
12 |
23 |
7.66 |
5000 |
24 |
47 |
15.66 |
5000 |
36 |
70 |
23.33 |
10000 |
12 |
47 |
15.66 |
10000 |
24 |
93 |
31 |
10000 |
36 |
140 |
46.66 |
NFS Storage (TB):
- Worst case = (Peak EPS*150*86400*30*Storage(Months))/10^12
- Average case = (0.5*Peak EPS*100*86400*30*Storage(Months))/10^12
Recommended Sizing for Elasticsearch Based Deployment
 |
Adding or moving shards is easy but splitting is not possible. Plan ahead for shard sizing is very important. |
Processing Requirement
Requirement |
Recommendation |
||||
|---|---|---|---|---|---|
EPS |
ES Configuration |
Hardware per node (vCPU, RAM) |
Elastic JVM RAM |
Shards |
Replica |
Up to 1K - without Replica |
All-in-one |
(8,16GB) |
8GB |
5 |
0 |
Up to 1K - with Replica |
3 node cluster |
(8,16GB) |
8GB |
5 |
1 |
1K-5K - with Replica |
3 node cluster |
(8,64GB) |
30GB |
5 |
1 |
5K-10K - with Replica |
Coordinating and Master Node |
(8,32GB) |
16GB |
|
|
|
3 Data Nodes |
(8,64GB) |
30GB |
5 |
1 |
10K-15K - with Replica |
Coordinating Node |
(16,32GB) |
16GB |
|
|
|
Master Node |
(8,16GB) |
8GB |
|
|
|
3 Data Nodes |
(16,64GB) |
30GB |
10 |
1 |
15K-25K - with Replica |
Coordinating Node |
(16,64GB) |
30GB |
|
|
|
Master Node |
(8,16GB) |
8GB |
|
|
|
5 Data Nodes |
(16,64GB) |
30GB |
15 |
1 |
25K-35K - with Replica |
Coordinating Node |
(16,64GB) |
30GB |
|
|
|
Master Node |
(8,16GB) |
8GB |
|
|
|
7 Data Nodes |
(16,64GB) |
30GB |
20 |
1 |
35K-45K - with Replica |
Coordinating Node |
(16,64GB) |
30GB |
|
|
|
Master Node |
(8,16GB) |
8GB |
|
|
|
9 Data Nodes |
(16,64GB) |
30GB |
25 |
1 |
Add 5K EPS - with Replica |
Add 1 Data Node |
(16,64GB) |
30GB |
Add 3 Shards |
1 |
Storage Requirement for Elasticsearch
Elasticsearch consumes more storage than NFS because it indexes the data more heavily than FortiSIEM event database.
FortiSIEM Elasticsearch storage requirement depends on two factors:
- EPS
- Bytes/log mix in your environment
You are likely licensed for Peak EPS. Typically, EPS peaks during morning hours on weekdays and goes down dramatically after 2 pm on weekdays and also remains low on weekends. So the average EPS should be used to calculate storage needs.
For calculating Bytes/log, consider the following aspects:
- Network devices and Linux servers tend to send shorter logs (150-200 bytes/log) while Windows Security logs tend to be much larger (500-1000 bytes/log).
- Busy corporate firewalls and domain controllers tend to send much higher log volumes (higher EPS) than other systems, assuming they are sending all logs.
- Database indices built on logs for efficient searching consumes significant storage as well.
- ASCII text (syslog) compresses much better than binary (for example, Netflow)
Therefore, it is difficult to properly assume a specific Bytes/log mix in your environment without measurement. Our internal scalability test environment shows Bytes/log is around 1000 including all factors – device mix, log mix, indexing cost and compression. We calculated this by dividing the total Elasticsearch database file size (in \data) over one day by the total number of events on that day, and then averaging over a few days.
The table below shows two scenarios – Worst case and Average case for Storage/Cluster. In Worst case, Peak EPS and 1000 Bytes/log is used. In the average case, 0.5 Peak EPS is used. As we gather experience with more customers, we will publish average Bytes/log and update the Average storage requirements.
| Peak EPS | Replica | Storage (Months) | Storage/Cluster (TB) | |
|---|---|---|---|---|
| Worst case | Average case | |||
| 1000 | 0 | 12 | 31 | 15.5 |
| 1000 | 1 | 12 | 62 | 31 |
| 2000 | 1 | 12 | 124 | 62 |
| 5000 | 1 | 12 | 311 | 155.5 |
| 10000 | 1 | 6 | 311 | 155.5 |
| 15000 | 1 | 6 | 467 | 233.5 |
| 25000 | 1 | 3 | 389 | 194.5 |
| 50000 | 1 | 3 | 778 | 389 |
Storage per Cluster (TB):
- Worst case = (Peak EPS*1000*86400*Storage(Month)*30*(Replica+1))/10^12
- Average case = (0.5*Peak EPS*1000*86400*Storage(Month)*30*(Replica+1))/10^12