High CPU utilization (100%).
I observed high CPU utilization (100%) on F5 device, resource provision ASM nominal. I checked the client-side throughput and server-side throughput both are normal but found management interface throughput is very high and what i noticed this is happening in same time period for last 30 days. What could be the reason for this spike. Many thanks in advanced for your time and consideration.
Whitelisting access to URLs based on specific IPs
Dear Community, I have a requrirment to allow access to a specific URI path from few public IPs & all private IPs; remaining public IPs should not be able to access this specific URI path. All other URI paths should be abe to be accessed by any IP whether private or public. Requirement Example: "https://abc.com/good/evening/happy/life" should be able to be accessed by four public IPs only & private IPs. and all other URIs paths than above should be accessable by all public IPs & private IPs. https://abc.com/*
2.5 bad ways to implement a server load balancing architecture
I'm in a bit of mood after reading a Javaworld article on server load balancing that presents some fairly poor ideas on architectural implementations. It's not the concepts that are necessarily wrong; they will work. It's the architectures offered as a method of load balancing made me do a double-take and say "What?" I started reading this article because it was part 2 of a series on load balancing and this installment focused on application layer load balancing. You know, layer 7 load balancing. Something we at F5 just might know a thing or two about. But you never know where and from whom you'll learn something new, so I was eager to dive in and learn something. I learned something alright. I learned a couple of bad ways to implement a server load balancing architecture. TWO LOAD BALANCERS? The first indication I wasn't going to be pleased with these suggestions came with the description of a "popular" load-balancing architecture that included two load balancers: one for the transport layer (layer 4) and another for the application layer (layer 7). In contrast to low-level load balancing solutions, application-level server load balancing operates with application knowledge. One popular load-balancing architecture, shown in Figure 1, includes both an application-level load balancer and a transport-level load balancer. Even the most rudimentary, entry level load balancers on the market today - software and hardware, free and commercial - can handle both transport and application layer load balancing. There is absolutely no need to deploy two separate load balancers to handle two different layers in the stack. This is a poor architecture introducing unnecessary management and architectural complexity as well as additional points of failure into the network architecture. It's bad for performance because it introduces additional hops and points of inspection through which application messages must flow. To give the author credit he does recognize this and offers up a second option to counter the negative impact of the "additional network hops." One way to avoid additional network hops is to make use of the HTTP redirect directive. With the help of the redirect directive, the server reroutes a client to another location. Instead of returning the requested object, the server returns a redirect response such as 303. I found it interesting that the author cited an HTTP response code of 303, which is rarely returned in conjunction with redirects. More often a 302 is used. But it is valid, if not a bit odd. That's not the real problem with this one, anyway. The author claims "The HTTP redirect approach has two weaknesses." That's true, it has two weaknesses - and a few more as well. He correctly identifies that this approach does nothing for availability and exposes the infrastructure, which is a security risk. But he fails to mention that using HTTP redirects introduces additional latency because it requires additional requests that must be made by the client (increasing network traffic), and that it is further incapable of providing any other advanced functionality at the load balancing point because it essentially turns the architecture into a variation of a DSR (direct server return) configuration. THAT"S ONLY 2 BAD WAYS, WHERE'S THE .5? The half bad way comes from the fact that the solutions are presented as a Java based solution. They will work in the sense that they do what the author says they'll do, but they won't scale. Consider this: the reason you're implementing load balancing is to scale, because one server can't handle the load. A solution that involves putting a single server - with the same limitations on connections and session tables - in front of two servers with essentially the twice the capacity of the load balancer gains you nothing. The single server may be able to handle 1.5 times (if you're lucky) what the servers serving applications may be capable of due to the fact that the burden of processing application requests has been offloaded to the application servers, but you're still limited in the number of concurrent users and connections you can handle because it's limited by the platform on which you are deploying the solution. An application server acting as a cluster controller or load balancer simply doesn't scale as well as a purpose-built load balancing solution because it isn't optimized to be a load balancer and its resource management is limited to that of a typical application server. That's true whether you're using a software solution like Apache mod_proxy_balancer or hardware solution. So if you're implementing this type of a solution to scale an application, you aren't going to see the benefits you think you are, and in fact you may see a degradation of performance due to the introduction of additional hops, additional processing, and poorly designed network architectures. I'm all for load balancing, obviously, but I'm also all for doing it the right way. And these solutions are just not the right way to implement a load balancing solution unless you're trying to learn the concepts involved or are in a computer science class in college. If you're going to do something, do it right. And doing it right means taking into consideration the goals of the solution you're trying to implement. The goals of a load balancing solution are to provide availability and scale, neither of which the solutions presented in this article will truly achieve.iControl with Java - Retrieve List of Virtual Servers does not include Applications
Hi, i connect to the F5 using the Java Wrapper API; Now, when i get the list of Virtual-Servers via iControlInterfaces.getLocalLBVirtualServer().get_list() it only returns the virtual servers that are not created with an application (i.e. with the f5.microsoft_exchange_2010_2013_cas template). I could not find any way to further "open" the list; How can i retrieve these too? Many thanks in advance! ReneBlock requests from web browser and only allow from clients application in ASM
Dear Community, I have a requirment to allow email application traffic initialated from email clinets i.e outlook, boxer only and block all traffic initiated from web browsers. Please inform how we can accomplish this using ASM. Best RegardsInside Look - PCoIP Proxy for VMware Horizon View
I sit down with F5 Solution Architect Paul Pindell to get an inside look at BIG-IP's native support for VMware's PCoIP protocol. He reviews the architecture, business value and gives a great demo on how to configure BIG-IP. BIG-IP APM offers full proxy support for PC-over-IP (PCoIP), a leading virtual desktop infrastructure (VDI) protocol. F5 is the first to provide this functionality which allows organizations to simplify their VMware Horizon View architectures. Combining PCoIP proxy with the power of the BIG-IP platform delivers hardened security and increased scalability for end-user computing. In addition to PCoIP, F5 supports a number of other VDI solutions, giving customers flexibility in designing and deploying their network infrastructure. ps Related: F5 Friday: Simple, Scalable and Secure PCoIP for VMware Horizon View Solutions for VMware applications F5's YouTube Channel In 5 Minutes or Less Series (24 videos – over 2 hours of In 5 Fun) Inside Look Series Life@F5 Series Technorati Tags: vdi,PCoIP,VMware,Access,Applications,Infrastructure,Performance,Security,Virtualization,silva,video,inside look,big-ip,apm Connect with Peter: Connect with F5:The Concise Guide to Proxies
We often mention that the benefits derived from some application delivery controllers are due to the nature of being a full proxy. And in the same breath we might mention reverse, half, and forward proxies, which makes the technology sound more like a description of the positions on a sports team than an application delivery solution. So what does these terms really mean? Here's the lowdown on the different kinds of proxies in one concise guide. PROXIES Proxies (often called intermediaries in the SOA world) are hardware or software solutions that sit between the client and the server and do something to requests and sometimes responses. The most often heard use of the term proxy is in conjunction with anonymizing Web surfing. That's because proxies sit between your browser and your desired destination and proxy the connection; that is you talk to the proxy while the proxy talks to the web server and neither you nor the web server know about each other. Proxies are not all the same. Some are half proxies, some are full proxies; some are forward and some are reverse. Yes, that came excruciatingly close to sounding like a Dr. Seuss book. (Go ahead, you know you want to. You may even remember this from .. .well, when it was first circulated.) FORWARD PROXIES Forward proxies are probably the most well known of all proxies, primarily because most folks have dealt with them either directly or indirectly. Forward proxies are those proxies that sit between two networks, usually a private internal network and the public Internet. Forward proxies have also traditionally been employed by large service providers as a bridge between their isolated network of subscribers and the public Internet, such as CompuServe and AOL in days gone by. These are often referred to as "mega-proxies" because they managed such high volumes of traffic. Forward proxies are generally HTTP (Web) proxies that provide a number of services but primarily focus on web content filtering and caching services. These forward proxies often include authentication and authorization as a part of their product to provide more control over access to public content. If you've ever gotten a web page that says "Your request has been denied by blah blah blah. If you think this is an error please contact the help desk/your administrator" then you've probably used a forward proxy. REVERSE PROXIES A reverse proxy is less well known, generally because we don't use the term anymore to describe products used as such. Load balancers (application delivery controllers) and caches are good examples of reverse proxies. Reverse proxies sit in front of web and application servers and process requests for applications and content coming in from the public Internet to the internal, private network. This is the primary reason for the appellation "reverse" proxy - to differentiate it from a proxy that handles outbound requests. Reverse proxies are also generally focused on HTTP but in recent years have expanded to include a number of other protocols commonly used on the web such as streaming audio (RTSP), file transfers (FTP), and generally any application protocol capable of being delivered via UDP or TCP. HALF PROXIES Half-proxy is a description of the way in which a proxy, reverse or forward, handles connections. There are two uses of the term half-proxy: one describing a deployment configuration that affects the way connections are handled and one that describes simply the difference between a first and subsequent connections. The deployment focused definition of half-proxy is associated with a direct server return (DSR) configuration. Requests are proxied by the device, but the responses do not return through the device, but rather are sent directly to the client. For some types of data - particularly streaming protocols - this configuration results in improved performance. This configuration is known as a half-proxy because only half the connection (incoming) is proxied while the other half, the response, is not. The second use of the term "half-proxy" describes a solution in which the proxy performs what is known as delayed binding in order to provide additional functionality. This allows the proxy to examine the request before determining where to send it. Once the proxy determines where to route the request, the connection between the client and the server are "stitched" together. This is referred to as a half-proxy because the initial TCP handshaking and first requests are proxied by the solution, but subsequently forwarded without interception. Half proxies can look at incoming requests in order to determine where the connection should be sent and can even use techniques to perform layer 7 inspection, but they are rarely capable of examining the responses. Almost all half-proxies fall into the category of reverse proxies. FULL PROXIES Full proxy is also a description of the way in which a proxy, reverse or forward, handles connections. A full proxy maintains two separate connections - one between itself and the client and one between itself and the destination server. A full proxy completely understands the protocols, and is itself an endpoint and an originator for the protocols. Full proxies are named because they completely proxy connections - incoming and outgoing. Because the full proxy is an actual protocol endpoint, it must fully implement the protocols as both a client and a server (a packet-based design does not). This also means the full proxy can have its own TCP connection behavior, such as buffering, retransmits, and TCP options. With a full proxy, each connection is unique; each can have its own TCP connection behavior. This means that a client connecting to the full proxy device would likely have different connection behavior than the full proxy might use for communicating with servers. Full proxies can look at incoming requests and outbound responses and can manipulate both if the solution allows it. Many reverse and forward proxies use a full proxy model today. There is no guarantee that a given solution is a full proxy, so you should always ask your solution provider if it is important to you that the solution is a full proxy.
F5 and its gateway
Hi I made basic F5 configuration based on F5 protocol. But I notice there is not gateway config towards outside connection. For example, the virtual server in F5 send message out via its neighbor device. We do not need to define the neighbor device’s ip address at the F5. If so, F5 find the gateway through the incoming traffic, Is this correct? ThanksProgrammability in the Network: Canary Deployments
#devops The canary deployment pattern is another means of enabling continuous delivery. Deployment patterns (or as I like to call them of late, devops patterns) are good examples of how devops can put into place systems and tools that enable continuous delivery to be, well, continuous. The goal of these patterns is, for the most part, to make sure operations can smoothly move features, functions, releases or applications into production. We've previously looked at the Blue Green deployment pattern and today we're going to look at a variation: Canary deployments. Canary deployments are applicable when you're running a cluster of servers. In other words, you've got lots and lots of (probably active right now while you're considering pushing that next release) users. What you don't want is to do the traditional "we're sorry, we're down for maintenance, here's a picture of a funny squirrel to amuse you while you wait" maintenance page. You want to be able to roll out the new release without disruption. Yeah, that's quite the ask, isn't it? The Canary deployment pattern is an incremental upgrade methodology. First, the build is pushed to a small set of servers to which only a select group of users are directed. If that goes well, the release is pushed to a larger set of servers with a limited set of users. Finally, if that goes well, then the release is pushed out to all servers and all users. If issues occur at any stage, the release is halted - it goes no further. Hence the naming of the pattern - after the miner's canary, used because "its demise provided a warning of dangerous levels of toxic gases". The trick to implementing this pattern is two fold: first, being able to group the servers used in each step into discrete pools and second, the ability to direct specific sets of users to the appropriate pools. Both capabilities requires the ability to execute some logic to perform user-based load balancing. Nolio, in its first Devops Best Practices video, implements Canary deployments by manipulating the pools of servers at the load balancing tier, removing them to upgrade and then reinserting them for testing before moving onto the next phase. If your load balancing solution is programmable, there's no need to actually remove them as you can simply insert logic to remove them from being selected until they've been upgraded. You can also then insert the logic to determine which users are directed to which pool of servers. If the load balancing platform is really programmable, you can even extend that to determination to querying a database to determine user inclusion in certain groups, such as those you might use to perform AB testing. Such logic might base the decision on IP address (not the best option but an option) or later, when you're actually rolling out to a percentage of users you can write logic that randomly selects users based on location or their user name - like sharding, only in reverse - or pretty much anything you can think of. You can even split that further if you're rolling out an update to an API that's used by both mobile and traditional clients, to catch both or neither or specific types in an orderly fashion so you can test methodically - because you want to test methodically when you're using live users as test subjects. The beauty of this pattern is that allows continuous delivery. Users are never disrupted (if you do it right) and the upgrade occurs in a safely staged, incremental fashion. That enables you to back out quickly if necessary, because you do have a back button plan, right? Right?
