The F5 BIG-IP platform consists of software and hardware that acts as a reverse proxy and distributes network or application traffic across a number of servers. Load balancers are used to increase capacity and reliability of applications. They improve the overall performance of applications by decreasing the burden on servers associated with managing and maintaining application and network sessions, as well as by performing application-specific tasks. As it’s a critical and important part of your network, monitoring F5 BIG-IP health is critical to ensure operations are working as expected. This can be achieved via traditional SNMP polling, but in order to get a detailed view of the performance of F5 network services, you will require a combination of SNMP polling and F5 syslog message analysis.
The best platform to do syslog message analysis is still the Elastic stack. Over the past years I’ve been working on a set of F5 Logstash filters, which can be used to create beautiful Kibana dashboards which can give you detailed insights in the working and processes of your F5 BIG Load Balancer.
Load balancers are generally grouped into two categories: Layer 4 and Layer 7. Layer 4 load balancers act upon data found in network and transport layer protocols (IP, TCP, FTP, UDP). Layer 7 load balancers distribute requests based upon data found in application layer protocols such as HTTP. Requests are received by both types of load balancers and they are distributed to a particular server based on a configured algorithm. Some industry standard algorithms are:
- Round robin
- Weighted round robin
- Least connections
- Least response time
Layer 7 load balancers can further distribute requests based on application specific data such as HTTP headers, cookies, or data within the application message itself, such as the value of a specific parameter. Load balancers ensure reliability and availability by monitoring the “health” of applications and only sending requests to servers and applications that can respond in a timely manner.
Monitoring F5 BIG-IP Platform
Nagios allows you to actively monitor the health of your F5 Load Balancer with SNMP. I’ll add some examples here asap.
You can find the required configuration files on GitHub. The project includes F5 Logstash filters, F5 elasticsearch templates and F5 Logstash patterns.
F5 Logstash input
type => 'syslog-f5'
port => <portnumber>
F5 Logstash filters
dcc => ASM related messages. BIG-IP Application Security Manager (ASM) enables organizations to protect against OWASP top 10 threats, application vulnerabilities, and zero-day attacks. Leading Layer 7 DDoS defenses, detection and mitigation techniques, virtual patching, and granular attack visibility thwart even the most sophisticated threats before they reach your servers.
apd => Access Policy Demon. The apd process runs a BIG-IP APM access policy for a user session.
tmm => The traffic management microkernel is the process running on the BIG-IP host O/S that performs all of the local / global traffic management for the system.
sshd => The ssh daemon provides remote access to the BIG-IP system command line interface
logger => If a BIG-IP high-availability redundant pair has the Detect ConfigSync Status feature enabled, each unit in the pair sends periodic iControl queries to its peer to determine if the redundant pair configuration is synchronized. These iControl requests occur approximately every 30 seconds on each unit. Each inbound request generates an entry in both the local /var/log/httpd/ssl_access_log file and the /var/log/httpd/ssl_request_log file. As I never saw anything useful coming out of it, I asked our F5 engineer to have a look at this F5 article , which describes how to exclude these messages in the F5 syslog configuration.
F5 Logstash custom grok patterns
You will need to add these F5 Logstash custom grok patterns to your Logstash patterns directory. For me it’s located in /etc/logstash/patterns
Included in the GitHub project you can find my f5 elasticsearch template, with the correct mappings for each field. This enables you to use your data more efficiently and allow for advanced ip aggregations. You can find more information about mapping types here. If you have ideas about better mappings (I know they need some work), please let me know on GitHub by making an issue.
The Logstash filters I created allow you do some awesome things in Kibana. I’m working on a set of dashboards with a menu which will allow you to drilldown to interesting stuff, such as apd processors, session, dcc scraping and other violations.
Elastic F5 Home Dashboard
Elastic F5 dcc scraping dashboard
I will open source them when I consider them ready for public. If you are truly interested in helping me develop and expand them, send me an email (willem.dhaeseatgmail), and I’ll consider sending you my Kibana 5 dashboards json exports. The only requirement is that you use f5-* as index pattern.