Intro to Load Balancing for Developers – The Algorithms
If you’re new to this series, you can find the complete list of articles in the series on my personal page here If you are writing applications to sit behind a Load Balancer, it behooves you to at least have a clue what the algorithm your load balancer uses is about. We’re taking this week’s installment to just chat about the most common algorithms and give a plain- programmer description of how they work. While historically the algorithm chosen is both beyond the developers’ control, you’re the one that has to deal with performance problems, so you should know what is happening in the application’s ecosystem, not just in the application. Anything that can slow your application down or introduce errors is something worth having reviewed. For algorithms supported by the BIG-IP, the text here is paraphrased/modified versions of the help text associated with the Pool Member tab of the BIG-IP UI. If they wrote a good description and all I needed to do was programmer-ize it, then I used it. For algorithms not supported by the BIG-IP I wrote from scratch. Note that there are many, many more algorithms out there, but as you read through here you’ll see why these (or minor variants of them) are the ones you’ll see the most. Plain Programmer Description: Is not intended to say anything about the way any particular dev team at F5 or any other company writes these algorithms, they’re just an attempt to put the process into terms that are easier for someone with a programming background to understand. Hopefully a successful attempt. Interestingly enough, I’ve pared down what BIG-IP supports to a subset. That means that F5 employees and aficionados will be going “But you didn’t mention…!” and non-F5 employees will likely say “But there’s the Chi-Squared Algorithm…!” (no, chi-squared is theoretical distribution method I know of because it was presented as a proof for testing the randomness of a 20 sided die, ages ago in Dragon Magazine). The point being that I tried to stick to a group that builds on each other in some connected fashion. So send me hate mail… I’m good. Unless you can say more than 2-5% of the world’s load balancers are running the algorithm, I won’t consider that I missed something important. The point is to give developers and software architects a familiarity with core algorithms, not to build the worlds most complete lexicon of algorithms. Random: This load balancing method randomly distributes load across the servers available, picking one via random number generation and sending the current connection to it. While it is available on many load balancing products, its usefulness is questionable except where uptime is concerned – and then only if you detect down machines. Plain Programmer Description: The system builds an array of Servers being load balanced, and uses the random number generator to determine who gets the next connection… Far from an elegant solution, and most often found in large software packages that have thrown load balancing in as a feature. Round Robin: Round Robin passes each new connection request to the next server in line, eventually distributing connections evenly across the array of machines being load balanced. Round Robin works well in most configurations, but could be better if the equipment that you are load balancing is not roughly equal in processing speed, connection speed, and/or memory. Plain Programmer Description: The system builds a standard circular queue and walks through it, sending one request to each machine before getting to the start of the queue and doing it again. While I’ve never seen the code (or actual load balancer code for any of these for that matter), we’ve all written this queue with the modulus function before. In school if nowhere else. Weighted Round Robin (called Ratio on the BIG-IP): With this method, the number of connections that each machine receives over time is proportionate to a ratio weight you define for each machine. This is an improvement over Round Robin because you can say “Machine 3 can handle 2x the load of machines 1 and 2”, and the load balancer will send two requests to machine #3 for each request to the others. Plain Programmer Description: The simplest way to explain for this one is that the system makes multiple entries in the Round Robin circular queue for servers with larger ratios. So if you set ratios at 3:2:1:1 for your four servers, that’s what the queue would look like – 3 entries for the first server, two for the second, one each for the third and fourth. In this version, the weights are set when the load balancing is configured for your application and never change, so the system will just keep looping through that circular queue. Different vendors use different weighting systems – whole numbers, decimals that must total 1.0 (100%), etc. but this is an implementation detail, they all end up in a circular queue style layout with more entries for larger ratings. Dynamic Round Robin (Called Dynamic Ratio on the BIG-IP): is similar to Weighted Round Robin, however, weights are based on continuous monitoring of the servers and are therefore continually changing. This is a dynamic load balancing method, distributing connections based on various aspects of real-time server performance analysis, such as the current number of connections per node or the fastest node response time. This Application Delivery Controller method is rarely available in a simple load balancer. Plain Programmer Description: If you think of Weighted Round Robin where the circular queue is rebuilt with new (dynamic) weights whenever it has been fully traversed, you’ll be dead-on. Fastest: The Fastest method passes a new connection based on the fastest response time of all servers. This method may be particularly useful in environments where servers are distributed across different logical networks. On the BIG-IP, only servers that are active will be selected. Plain Programmer Description: The load balancer looks at the response time of each attached server and chooses the one with the best response time. This is pretty straight-forward, but can lead to congestion because response time right now won’t necessarily be response time in 1 second or two seconds. Since connections are generally going through the load balancer, this algorithm is a lot easier to implement than you might think, as long as the numbers are kept up to date whenever a response comes through. These next three I use the BIG-IP name for. They are variants of a generalized algorithm sometimes called Long Term Resource Monitoring. Least Connections: With this method, the system passes a new connection to the server that has the least number of current connections. Least Connections methods work best in environments where the servers or other equipment you are load balancing have similar capabilities. This is a dynamic load balancing method, distributing connections based on various aspects of real-time server performance analysis, such as the current number of connections per node or the fastest node response time. This Application Delivery Controller method is rarely available in a simple load balancer. Plain Programmer Description: This algorithm just keeps track of the number of connections attached to each server, and selects the one with the smallest number to receive the connection. Like fastest, this can cause congestion when the connections are all of different durations – like if one is loading a plain HTML page and another is running a JSP with a ton of database lookups. Connection counting just doesn’t account for that scenario very well. Observed: The Observed method uses a combination of the logic used in the Least Connections and Fastest algorithms to load balance connections to servers being load-balanced. With this method, servers are ranked based on a combination of the number of current connections and the response time. Servers that have a better balance of fewest connections and fastest response time receive a greater proportion of the connections. This Application Delivery Controller method is rarely available in a simple load balancer. Plain Programmer Description: This algorithm tries to merge Fastest and Least Connections, which does make it more appealing than either one of the above than alone. In this case, an array is built with the information indicated (how weighting is done will vary, and I don’t know even for F5, let alone our competitors), and the element with the highest value is chosen to receive the connection. This somewhat counters the weaknesses of both of the original algorithms, but does not account for when a server is about to be overloaded – like when three requests to that query-heavy JSP have just been submitted, but not yet hit the heavy work. Predictive: The Predictive method uses the ranking method used by the Observed method, however, with the Predictive method, the system analyzes the trend of the ranking over time, determining whether a servers performance is currently improving or declining. The servers in the specified pool with better performance rankings that are currently improving, rather than declining, receive a higher proportion of the connections. The Predictive methods work well in any environment. This Application Delivery Controller method is rarely available in a simple load balancer. Plain Programmer Description: This method attempts to fix the one problem with Observed by watching what is happening with the server. If its response time has started going down, it is less likely to receive the packet. Again, no idea what the weightings are, but an array is built and the most desirable is chosen. You can see with some of these algorithms that persistent connections would cause problems. Like Round Robin, if the connections persist to a server for as long as the user session is working, some servers will build a backlog of persistent connections that slow their response time. The Long Term Resource Monitoring algorithms are the best choice if you have a significant number of persistent connections. Fastest works okay in this scenario also if you don’t have access to any of the dynamic solutions. That’s it for this week, next week we’ll start talking specifically about Application Delivery Controllers and what they offer – which is a whole lot – that can help your application in a variety of ways. Until then! Don.
snat vs automap, whats the difference?
I'm trying to see the difference between the snat and automap for the Source Address Translation option. Currently I have traffic coming in to the F5 using automap. What though specifically does that mean? And why wouldn't I use SNAT? All the nodes, (servers in our lan), are not configured to have the F5 as its default gateway. I have a lot of virtual servers configured and I'm not sure how the self-ip plays a role in the nating or snating if at all. From what I understand (but could be wrong) an external client request is directed to the vip ip (since our firewall nats it there) and the destination IP is that of the vip. The F5 then translates the destination IP to that of the IP of the pool member. Then on the way back out the source is translated to the of the vip. But what about the selfip? Can someone please explain all this? Thanks!
X-Forwarded-For Log Filter for Windows Servers
For those that don't know what X-Forwarded-For is, then you might as well close your browser because this post likely will mean nothing to you… A Little Background Now, if you are still reading this, then you likely are having issues with determining the origin client connections to your web servers. When web requests are passed through proxies, load balancers, application delivery controllers, etc, the client no longer has a direct connection with the destination server and all traffic looks like it's coming from the last server in the chain. In the following diagram, Proxy2 is the last hop in the chain before the request hits the destination server. Relying on connection information alone, the server thinks that all connections come from Proxy2, not from the Client that initiated the connection. The only one in the chain here who knows who the client really is (as determined by it's client IP Address, is Proxy1. The problem is that application owners rely on source client information for many reasons ranging from analyzing client demographics to targeting Denial of Service attacks. That's where the X-Forwarded-For header comes in. It is non-RFC standard HTTP request header that is used for identifying the originating IP address of a client connecting to a web server through a proxy. The format of the header is: X-Forwarded-For: client, proxy1, proxy, … X-Forwarded-For header logging is supported in Apache (with mod_proxy) but Microsoft IIS does not have a direct way to support the translation of the X-Forwarded-For value into the client ip (c-ip) header value used in its webserver logging. Back in September, 2005 I wrote an ISAPI filter that can be installed within IIS to perform this transition. This was primarily for F5 customers but I figured that I might as well release it into the wild as others would find value out of it. Recently folks have asked for 64 bit versions (especially with the release of Windows 2008 Server). This gave me the opportunity to brush up on my C skills. In addition to building targets for 64 bit windows, I went ahead and added a few new features that have been asked for. Proxy Chain Support The original implementation did not correctly parse the "client, proxy1, proxy2,…" format and assumed that there was a single IP address following the X-Forwarded-For header. I've added code to tokenize the values and strip out all but the first token in the comma delimited chain for inclusion in the logs. Header Name Override Others have asked to be able to change the header name that the filter looked for from "X-Forwarded-For" to some customized value. In some cases they were using the X-Forwarded-For header for another reason and wanted to use iRules to create a new header that was to be used in the logs. I implemented this by adding a configuration file option for the filter. The filter will look for a file named F5XForwardedFor.ini in the same directory as the filter with the following format: [SETTINGS] HEADER=Alternate-Header-Name The value of "Alternate-Header-Name" can be changed to whatever header you would like to use. Download I've updated the original distribution file so that folks hitting my previous blog post would get the updates. The following zip file includes 32 and 64 bit release versions of the F5XForwardedFor.dll that you can install under IIS6 or IIS7. Installation Follow these steps to install the filter. Download and unzip the F5XForwardedFor.zip distribution. Copy the F5XForwardedFor.dll file from the x86\Release or x64\Release directory (depending on your platform) into a target directory on your system. Let's say C:\ISAPIFilters. Ensure that the containing directory and the F5XForwardedFor.dll file have read permissions by the IIS process. It's easiest to just give full read access to everyone. Open the IIS Admin utility and navigate to the web server you would like to apply it to. For IIS6, Right click on your web server and select Properties. Then select the "ISAPI Filters" tab. From there click the "Add" button and enter "F5XForwardedFor" for the Name and the path to the file "c:\ISAPIFilters\F5XForwardedFor.dll" to the Executable field and click OK enough times to exit the property dialogs. At this point the filter should be working for you. You can go back into the property dialog to determine whether the filter is active or an error occurred. For II7, you'll want to select your website and then double click on the "ISAPI Filters" icon that shows up in the Features View. In the Actions Pane on the right select the "Add" link and enter "F5XForwardedFor" for the name and "C:\ISAPIFilters\F5XForwardedFor.dll" for the Executable. Click OK and you are set to go. I'd love to hear feedback on this and if there are any other feature request, I'm wide open to suggestions. The source code is included in the download distribution so if you make any changes yourself, let me know! Good luck and happy filtering! -Joe
tcpdump command for multiple source hosts and destination hosts
The request that has been given me is to find any SOAP traffic from 2 sets of pools. Pool 1 172.17.30.100 172.17.30.101 172.17.30.102 Pool 2 172.17.31.200 172.17.31.201 172.17.31.202 cany anyone help me with a tcpdump command that will give me all 80 and 443 traffic from pool 1 to pool 2 bidirectionaly?
F5 Automated Backups - The Right Way
Hi all, Often I've been scouring the devcentral fora and codeshares to find that one piece of handywork that will drastically simplify my automated backup needs on F5 devices. Based on the works of Jason Rahm in his post "Third Time's the Charm: BIG-IP Backups Simplified with iCall" on the 26th of June 2013, I went ahead and created my own iApp that pretty much provides the answers for all my backup-needs. Here's a feature list of this iApp: It allows you to choose between both UCS or SCF as backup-types. (whilst providing ample warnings about SCF not being a very good restore-option due to the incompleteness in some cases) It allows you to provide a passphrase for the UCS archives (the standard GUI also does this, so the iApp should too) It allows you to not include the private keys (same thing: standard GUI does it, so the iApp does it too) It allows you to set a Backup Schedule for every X minutes/hours/days/weeks/months or a custom selection of days in the week It allows you to set the exact time, minute of the hour, day of the week or day of the month when the backup should be performed (depending on the usefulness with regards to the schedule type) It allows you to transfer the backup files to external devices using 4 different protocols, next to providing local storage on the device itself SCP (username/private key without password) SFTP (username/private key without password) FTP (username/password) SMB (using smbclient, with username/password) Local Storage (/var/local/ucs or /var/local/scf) It stores all passwords and private keys in a secure fashion: encrypted by the master key of the unit (f5mku), rendering it safe to store the backups, including the credentials off-box It has a configurable automatic pruning function for the Local Storage option, so the disk doesn't fill up (i.e. keep last X backup files) It allows you to configure the filename using the date/time wildcards from the tcl [clock] command, as well as providing a variable to include the hostname It requires only the WebGUI to establish the configuration you desire It allows you to disable the processes for automated backup, without you having to remove the Application Service or losing any previously entered settings For the external shellscripts it automatically generates, the credentials are stored in encrypted form (using the master key) It allows you to no longer be required to make modifications on the linux command line to get your automated backups running after an RMA or restore operation It cleans up after itself, which means there are no extraneous shellscripts or status files lingering around after the scripts execute I wasn't able to upload the iApp template to this article, so I threw it on pastebin: http://pastebin.com/YbDj3eMN Enjoy! Thomas Schockaert
Priority Group Activation, why use it?
If you have 3 members that are active within a pool and you select round robin LB method and set the priority group activation for less than 2, the virtual server is only going to use two of three nodes to round robin, why on earth would you configure this? this is an example in the f5 university. Wouldn't the goal be to use all active nodes within the pool and not limit it to use two of the three?
