5 Years Later: OpenAJAX Who?
Five years ago the OpenAjax Alliance was founded with the intention of providing interoperability between what was quickly becoming a morass of AJAX-based libraries and APIs. Where is it today, and why has it failed to achieve more prominence? I stumbled recently over a nearly five year old article I wrote in 2006 for Network Computing on the OpenAjax initiative. Remember, AJAX and Web 2.0 were just coming of age then, and mentions of Web 2.0 or AJAX were much like that of “cloud” today. You couldn’t turn around without hearing someone promoting their solution by associating with Web 2.0 or AJAX. After reading the opening paragraph I remembered clearly writing the article and being skeptical, even then, of what impact such an alliance would have on the industry. Being a developer by trade I’m well aware of how impactful “standards” and “specifications” really are in the real world, but the problem – interoperability across a growing field of JavaScript libraries – seemed at the time real and imminent, so there was a need for someone to address it before it completely got out of hand. With the OpenAjax Alliance comes the possibility for a unified language, as well as a set of APIs, on which developers could easily implement dynamic Web applications. A unified toolkit would offer consistency in a market that has myriad Ajax-based technologies in play, providing the enterprise with a broader pool of developers able to offer long term support for applications and a stable base on which to build applications. As is the case with many fledgling technologies, one toolkit will become the standard—whether through a standards body or by de facto adoption—and Dojo is one of the favored entrants in the race to become that standard. -- AJAX-based Dojo Toolkit , Network Computing, Oct 2006 The goal was simple: interoperability. The way in which the alliance went about achieving that goal, however, may have something to do with its lackluster performance lo these past five years and its descent into obscurity. 5 YEAR ACCOMPLISHMENTS of the OPENAJAX ALLIANCE The OpenAjax Alliance members have not been idle. They have published several very complete and well-defined specifications including one “industry standard”: OpenAjax Metadata. OpenAjax Hub The OpenAjax Hub is a set of standard JavaScript functionality defined by the OpenAjax Alliance that addresses key interoperability and security issues that arise when multiple Ajax libraries and/or components are used within the same web page. (OpenAjax Hub 2.0 Specification) OpenAjax Metadata OpenAjax Metadata represents a set of industry-standard metadata defined by the OpenAjax Alliance that enhances interoperability across Ajax toolkits and Ajax products (OpenAjax Metadata 1.0 Specification) OpenAjax Metadata defines Ajax industry standards for an XML format that describes the JavaScript APIs and widgets found within Ajax toolkits. (OpenAjax Alliance Recent News) It is interesting to see the calling out of XML as the format of choice on the OpenAjax Metadata (OAM) specification given the recent rise to ascendancy of JSON as the preferred format for developers for APIs. Granted, when the alliance was formed XML was all the rage and it was believed it would be the dominant format for quite some time given the popularity of similar technological models such as SOA, but still – the reliance on XML while the plurality of developers race to JSON may provide some insight on why OpenAjax has received very little notice since its inception. Ignoring the XML factor (which undoubtedly is a fairly impactful one) there is still the matter of how the alliance chose to address run-time interoperability with OpenAjax Hub (OAH) – a hub. A publish-subscribe hub, to be more precise, in which OAH mediates for various toolkits on the same page. Don summed it up nicely during a discussion on the topic: it’s page-level integration. This is a very different approach to the problem than it first appeared the alliance would take. The article on the alliance and its intended purpose five years ago clearly indicate where I thought this was going – and where it should go: an industry standard model and/or set of APIs to which other toolkit developers would design and write such that the interface (the method calls) would be unified across all toolkits while the implementation would remain whatever the toolkit designers desired. I was clearly under the influence of SOA and its decouple everything premise. Come to think of it, I still am, because interoperability assumes such a model – always has, likely always will. Even in the network, at the IP layer, we have standardized interfaces with vendor implementation being decoupled and completely different at the code base. An Ethernet header is always in a specified format, and it is that standardized interface that makes the Net go over, under, around and through the various routers and switches and components that make up the Internets with alacrity. Routing problems today are caused by human error in configuration or failure – never incompatibility in form or function. Neither specification has really taken that direction. OAM – as previously noted – standardizes on XML and is primarily used to describe APIs and components - it isn’t an API or model itself. The Alliance wiki describes the specification: “The primary target consumers of OpenAjax Metadata 1.0 are software products, particularly Web page developer tools targeting Ajax developers.” Very few software products have implemented support for OAM. IBM, a key player in the Alliance, leverages the OpenAjax Hub for secure mashup development and also implements OAM in several of its products, including Rational Application Developer (RAD) and IBM Mashup Center. Eclipse also includes support for OAM, as does Adobe Dreamweaver CS4. The IDE working group has developed an open source set of tools based on OAM, but what appears to be missing is adoption of OAM by producers of favored toolkits such as jQuery, Prototype and MooTools. Doing so would certainly make development of AJAX-based applications within development environments much simpler and more consistent, but it does not appear to gaining widespread support or mindshare despite IBM’s efforts. The focus of the OpenAjax interoperability efforts appears to be on a hub / integration method of interoperability, one that is certainly not in line with reality. While certainly developers may at times combine JavaScript libraries to build the rich, interactive interfaces demanded by consumers of a Web 2.0 application, this is the exception and not the rule and the pub/sub basis of OpenAjax which implements a secondary event-driven framework seems overkill. Conflicts between libraries, performance issues with load-times dragged down by the inclusion of multiple files and simplicity tend to drive developers to a single library when possible (which is most of the time). It appears, simply, that the OpenAJAX Alliance – driven perhaps by active members for whom solutions providing integration and hub-based interoperability is typical (IBM, BEA (now Oracle), Microsoft and other enterprise heavyweights – has chosen a target in another field; one on which developers today are just not playing. It appears OpenAjax tried to bring an enterprise application integration (EAI) solution to a problem that didn’t – and likely won’t ever – exist. So it’s no surprise to discover that references to and activity from OpenAjax are nearly zero since 2009. Given the statistics showing the rise of JQuery – both as a percentage of site usage and developer usage – to the top of the JavaScript library heap, it appears that at least the prediction that “one toolkit will become the standard—whether through a standards body or by de facto adoption” was accurate. Of course, since that’s always the way it works in technology, it was kind of a sure bet, wasn’t it? WHY INFRASTRUCTURE SERVICE PROVIDERS and VENDORS CARE ABOUT DEVELOPER STANDARDS You might notice in the list of members of the OpenAJAX alliance several infrastructure vendors. Folks who produce application delivery controllers, switches and routers and security-focused solutions. This is not uncommon nor should it seem odd to the casual observer. All data flows, ultimately, through the network and thus, every component that might need to act in some way upon that data needs to be aware of and knowledgeable regarding the methods used by developers to perform such data exchanges. In the age of hyper-scalability and über security, it behooves infrastructure vendors – and increasingly cloud computing providers that offer infrastructure services – to be very aware of the methods and toolkits being used by developers to build applications. Applying security policies to JSON-encoded data, for example, requires very different techniques and skills than would be the case for XML-formatted data. AJAX-based applications, a.k.a. Web 2.0, requires different scalability patterns to achieve maximum performance and utilization of resources than is the case for traditional form-based, HTML applications. The type of content as well as the usage patterns for applications can dramatically impact the application delivery policies necessary to achieve operational and business objectives for that application. As developers standardize through selection and implementation of toolkits, vendors and providers can then begin to focus solutions specifically for those choices. Templates and policies geared toward optimizing and accelerating JQuery, for example, is possible and probable. Being able to provide pre-developed and tested security profiles specifically for JQuery, for example, reduces the time to deploy such applications in a production environment by eliminating the test and tweak cycle that occurs when applications are tossed over the wall to operations by developers. For example, the jQuery.ajax() documentation states: By default, Ajax requests are sent using the GET HTTP method. If the POST method is required, the method can be specified by setting a value for the type option. This option affects how the contents of the data option are sent to the server. POST data will always be transmitted to the server using UTF-8 charset, per the W3C XMLHTTPRequest standard. The data option can contain either a query string of the form key1=value1&key2=value2 , or a map of the form {key1: 'value1', key2: 'value2'} . If the latter form is used, the data is converted into a query string using jQuery.param() before it is sent. This processing can be circumvented by setting processData to false . The processing might be undesirable if you wish to send an XML object to the server; in this case, change the contentType option from application/x-www-form-urlencoded to a more appropriate MIME type. Web application firewalls that may be configured to detect exploitation of such data – attempts at SQL injection, for example – must be able to parse this data in order to make a determination regarding the legitimacy of the input. Similarly, application delivery controllers and load balancing services configured to perform application layer switching based on data values or submission URI will also need to be able to parse and act upon that data. That requires an understanding of how jQuery formats its data and what to expect, such that it can be parsed, interpreted and processed. By understanding jQuery – and other developer toolkits and standards used to exchange data – infrastructure service providers and vendors can more readily provide security and delivery policies tailored to those formats natively, which greatly reduces the impact of intermediate processing on performance while ensuring the secure, healthy delivery of applications. API Jabberwocky: You Say Tomay-to and I Say Potah-to OpenAjax Metadata 1.0 and the Adobe Dreamweaver Widget Browser OpenAjax Alliance AJAX-based Dojo Toolkit The Stealthy Ascendancy of JSON JSON Continues its Winning Streak Over XML JSON versus XML: Your Choice Matters More Than You Think I am in your HTTP headers, attacking your application The Web 2.0 API: From collaborating to compromised IT as a Service: A Stateless Infrastructure Architecture Model JSON Activity Streams and the Other Consumerization of ITXML Threat Prevention
Where should security live? The divide between operations and application developers is pretty wide, especially when it comes to defining who should be ultimately responsible for application security. Mike Fratto and I have often had lively discussions (read: arguments) about whether security is the responsibility of the developer or the network and security administrators. It's wholly inappropriate to recreate any of these discussions here, as they often devolve to including the words your mother said not to use in public. 'Nuff said. The truth is that when XML enters the picture then the responsibility for securing that traffic has to be borne by both the network/security administrators and the developers. While there is certainly good reason to expect that developers are doing simply security checks for buffer overflows, length restrictions on incoming data, and strong typing, the fact is that there are some attacks in XML that make it completely impractical to check for in the code. Let's take a couple of attack types as examples. XML Entity Expansion This attack is a million laughs, or at least a million or more bytes of memory. Applications need to parse XML in order to manipulate it, so the first thing that happens when XML hits an application is that it is parsed - before the developer even has a chance to check it. In an application server this is generally done before the arguments to the specific operation being invoked are marshaled - meaning it is the application server, not the developer that is responsible for handling this type of attack. These messages can be used to force recursive entity expansion or other repeated processing that exhausts server resources. The most common example of this type of attack is the "billion laughs" attack, which is widely available. The CPU is monopolized while the entities are being expanded, and each entity takes up X amount of memory - eventually consuming all available resources and effectively preventing legitimate traffic from being processed. It's essentially a DoS (Denial of Service) attack. ... ]> &ha128; It is accepted that almost all traditional DoS attacks (ping of death, teardrop, etc...) should be handled by a perimeter security device - a firewall oran application delivery controller - so why should a DoS attack that is perpetrated through XML be any different? It shouldn't. This isn't a developer problem, it's a parser problem and for the most part developers have little or no control over the behavior of the parser used by the application server. The application admin, however, can configure most modern parsers to prevent this type of attack, but that's assuming that their parser is modern and can be configured to handle it. Of course then you have to wonder what happens if that arbitrary limit inhibits processing of valid traffic? Yeah, it's a serious problem. SQL Injection SQL Injection is one of the most commonly perpetrated attacks via web-based applications. It consists basically of inserting SQL code into string-based fields which the attacks thinks (or knows) will be passed to a database as part of an SQL query. This type of attack can easily be accomplished via XML as well simply by inserting the appropriate SQL code into a string element. Aha! The developer can stop this one, you're thinking. After all, the developer has the string and builds the SQL that will be executed, so he can just check for it before he builds the string and sends it off for execution. While this is certainly true, there are myriad combinations of SQL commands that might induce the database to return more data than it should, or to return sensitive data not authorized to the user. This extensive list of commands and combinations of commands would need to be searched for in each and every parameter used to create an SQL query and on every call to the database. That's a lot of extra code and a lot of extra processing - which is going to slow down the application and impede performance. And when a new attack is discovered, each and every function and application needs to be updated, tested, and re-deployed. I'm fairly certain developers have better ways to spend their time than updating parameter checking in every function in every application they have in production. And we won't even talk about third-party applications and the dangers inherent in that scenario. One of the goals of SOA is engendering reuse, and this is one of the best examples of taking advantage of reuse in order to ensure consistent behavior between applications and to reduce the lengthy development cycle required to update, test, and redeploy whenever a new attack is discovered. By placing the onus for keeping this kind of attack from reaching the server on an edge device such as an application firewall like F5's application firewall, updates to address new attacks are immediately applied to all applications and there is no need to recode and redeploy applications. Although there are some aspects of security that are certainly best left to the developer, there are other aspects of security that are better deployed in the network. It's the most effective plan in terms of effort, cost, and consistent behavior where applications are concerned. Imbibing: Mountain Dew Technorati tags: security, application security, application firewall, XML, developers, networking, application deliveryDevops Proverb: Process Practice Makes Perfect
#devops Tools for automating – and optimizing – processes are a must-have for enabling continuous delivery of application deployments Some idioms are cross-cultural and cross-temporal. They transcend cultures and time, remaining relevant no matter where or when they are spoken. These idioms are often referred to as proverbs, which carries with it a sense of enduring wisdom. One such idiom, “practice makes perfect”, can be found in just about every culture in some form. In Chinese, for example, the idiom is apparently properly read as “familiarity through doing creates high proficiency”, i.e. practice makes perfect. This is a central tenet of devops, particularly where optimization of operational processes is concerned. The more often you execute a process, the more likely you are to get better at it and discover what activities (steps) within that process may need tweaking or changes or improvements. Ergo, optimization. This tenet grows out of the agile methodology adopted by devops: application release cycles should be nearly continuous, with both developers and operations iterating over the same process – develop, test, deploy – with a high level of frequency. Eventually (one hopes) we achieve process perfection – or at least what we might call process perfection: repeatable, consistent deployment success. It is implied that in order to achieve this many processes will be automated, once we have discovered and defined them in such a way as to enable them to be automated. But how does one automate a process such as an application release cycle? Business Process Management (BPM) works well for automating business workflows; such systems include adapters and plug-ins that allow communication between systems as well as people. But these systems are not designed for operations; there are no web servers or databases or Load balancer adapters for even the most widely adopted BPM systems. One such solution can be found in Electric Cloud with its recently announced ElectricDeploy. Process Automation for Operations ElectricDeploy is built upon a more well known product from Electric Cloud (well, more well-known in developer circles, at least) known as ElectricCommander, a build-test-deploy application deployment system. Its interface presents applications in terms of tiers – but extends beyond the traditional three-tiers associated with development to include infrastructure services such as – you guessed it – load balancers (yes, including BIG-IP) and virtual infrastructure. The view enables operators to create the tiers appropriate to applications and then orchestrate deployment processes through fairly predictable phases – test, QA, pre-production and production. What’s hawesome about the tools is the ability to control the process – to rollback, to restore, and even debug. The debugging capabilities enable operators to stop at specified tasks in order to examine output from systems, check log files, etc..to ensure the process is executing properly. While it’s not able to perform “step into” debugging (stepping into the configuration of the load balancer, for example, and manually executing line by line changes) it can perform what developers know as “step over” debugging, which means you can step through a process at the highest layer and pause at break points, but you can’t yet dive into the actual task. Still, the ability to pause an executing process and examine output, as well as rollback or restore specific process versions (yes, it versions the processes as well, just as you’d expect) would certainly be a boon to operations in the quest to adopt tools and methodologies from development that can aid them in improving time and consistency of deployments. The tool also enables operations to determine what is failure during a deployment. For example, you may want to stop and rollback the deployment when a server fails to launch if your deployment only comprises 2 or 3 servers, but when it comprises 1000s it may be acceptable that a few fail to launch. Success and failure of individual tasks as well as the overall process are defined by the organization and allow for flexibility. This is more than just automation, it’s managed automation; it’s agile in action; it’s focusing on the processes, not the plumbing. MANUAL still RULES Electric Cloud recently (June 2012) conducted a survey on the “state of application deployments today” and found some not unexpected but still frustrating results including that 75% of application deployments are still performed manually or with little to no automation. While automation may not be the goal of devops, but it is a tool enabling operations to achieve its goals and thus it should be more broadly considered as standard operating procedure to automate as much of the deployment process as possible. This is particularly true when operations fully adopts not only the premise of devops but the conclusion resulting from its agile roots. Tighter, faster, more frequent release cycles necessarily puts an additional burden on operations to execute the same processes over and over again. Trying to manually accomplish this may be setting operations up for failure and leave operations focused more on simply going through the motions and getting the application into production successfully than on streamlining and optimizing the processes they are executing. Electric Cloud’s ElectricDeploy is one of the ways in which process optimization can be achieved, and justifies its purchase by operations by promising to enable better control over application deployment processes across development and infrastructure. Devops is a Verb 1024 Words: The Devops Butterfly Effect Devops is Not All About Automation Application Security is a Stack Capacity in the Cloud: Concurrency versus Connections Ecosystems are Always in Flux The Pythagorean Theorem of Operational Risk
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.Inside 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:Programmability 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?DNSSEC: Is Your Infrastructure Ready?
A few months ago, we teamed with Infoblox for a DNSSEC webinar. Jonathan George, F5 Product Marketing Manager, leads with myself and Cricket Liu of Infoblox as background noise. He’s a blast as always and certainly knows his DNS. So, learn how F5 enables you to deploy DNSSEC quickly and easily into an existing GSLB environment with BIG-IP Global Traffic Manager (GTM). BIG-IP GTM streamlines encryption key generation and distribution by dynamically signing DNS responses in real-time. Running time: 49:20 </p> <p>ps</p> <p>Resources:</p> <ul> <li><a href="http://www.f5.com/news-press-events/web-media/" _fcksavedurl="http://www.f5.com/news-press-events/web-media/">F5 Web Media</a></li> <li><a href="http://www.youtube.com/user/f5networksinc" _fcksavedurl="http://www.youtube.com/user/f5networksinc">F5 YouTube Channel</a></li> <li><a href="http://www.f5.com/products/big-ip/global-traffic-manager.html" _fcksavedurl="http://www.f5.com/products/big-ip/global-traffic-manager.html">BIG-IP GTM</a></li> <li><a href="http://www.f5.com/pdf/white-papers/dnssec-wp.pdf" _fcksavedurl="http://www.f5.com/pdf/white-papers/dnssec-wp.pdf">DNSSEC: The Antidote to DNS Cache Poisoning and Other DNS Attacks (whitepaper)</a> | <a href="http://devcentral.f5.com/s/weblogs/interviews/archive/2009/12/04/audio-tech-brief-dnssec-the-antidote-to-dns.aspx" _fcksavedurl="http://devcentral.f5.com/s/weblogs/interviews/archive/2009/12/04/audio-tech-brief-dnssec-the-antidote-to-dns.aspx">Audio</a></li> <li><a href="http://www.cricketondns.com" _fcksavedurl="http://www.cricketondns.com">Cricket on DNS</a></li> <li><a href="http://www.youtube.com/user/InfobloxInc" _fcksavedurl="http://www.youtube.com/user/InfobloxInc">Infoblox YouTube Channel</a></li> </ul> <p>Technorati Tags: <a href="http://devcentral.f5.com/s/weblogs/psilva/psilva/psilva/archive/2011/05/09/" _fcksavedurl="http://devcentral.f5.com/s/weblogs/psilva/psilva/psilva/archive/2011/05/09/">F5</a>, <a href="http://technorati.com/tags/webinar" _fcksavedurl="http://technorati.com/tags/webinar">webinar</a>, <a href="http://technorati.com/tags/Pete+Silva" _fcksavedurl="http://technorati.com/tags/Pete+Silva">Pete Silva</a>, <a href="http://technorati.com/tags/security" _fcksavedurl="http://technorati.com/tags/security">security</a>, <a href="http://technorati.com/tag/business" _fcksavedurl="http://technorati.com/tag/business">business</a>, <a href="http://technorati.com/tag/education" _fcksavedurl="http://technorati.com/tag/education">education</a>, <a href="http://technorati.com/tag/technology" _fcksavedurl="http://technorati.com/tag/technology">technology</a>, <a href="http://technorati.com/tags/internet" _fcksavedurl="http://technorati.com/tags/internet">internet, </a><a href="http://technorati.com/tags/big-ip" _fcksavedurl="http://technorati.com/tags/big-ip">big-ip</a>, <a href="http://technorati.com/tag/dnssec" _fcksavedurl="http://technorati.com/tag/dnssec">dnssec</a>, <a href="http://technorati.com/tags/infoblox" _fcksavedurl="http://technorati.com/tags/infoblox">infoblox</a> <a href="http://technorati.com/tags/dns" _fcksavedurl="http://technorati.com/tags/dns">dns</a></p> <table border="0" cellspacing="0" cellpadding="2" width="378"><tbody> <tr> <td valign="top" width="200">Connect with Peter: </td> <td valign="top" width="176">Connect with F5: </td> </tr> <tr> <td valign="top" width="200"><a href="http://www.linkedin.com/pub/peter-silva/0/412/77a" _fcksavedurl="http://www.linkedin.com/pub/peter-silva/0/412/77a"><img style="border-bottom: 0px; 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For those who of you that are having problems with logging client addresses in their server logs because you are running your web servers behind a proxy of some sort, never fear, your solution is here. For those that don't, I already discussed in my previous posts about what the X-Forwarded-For header is so feel free to click back into those to read about it. History Back in September, 2005 I wrote and posted a 32-bit ISAPI filter that extracted the X-Forwarded-For header value and replaced the c-ip value (client ip) that is stored in the server logs. Lots of folks have found this useful over time and I was eventually asked for a 64-bit version which I posted about in August, 2009. The Question Well, it looks like it's time for the next generation for this filter… I received an email from a colleague here at F5 telling me that his customer didn't want to deploy any more ISAPI filters in their IIS7 infrastructure. IIS7 introduced the concept of IIS Modules that are more integrated into the whole pipeline and was told that Microsoft is recommending folks move in that direction. I was asked if I had plans to port my ISAPI filter into a HTTP Module. The Answer Well, the answer was "probably not", but now it's changed to a "yes"! The Solution In reading about IIS Module, I found that you can develop in managed (C#/VB) or Native (C++) code. I loaded up the test C# project to see if I could get it working. In a matter of minutes I had a working module that intercepted the event when logging occurs. The only problem was that from managed code, I could find no way to actually modify the values that were passed to the logging processor. This was a problem so I scrapped that and moved to a native C++ module. After a little while of jumping through the documentation, I found the things I needed and pretty soon I had a working HTTP module that implemented the same functionality as the ISAPI filter. Download The new Http Module hasn't had much testing done so please test it out before you roll it out into production. I've made the source available as well if you find an issue and care to fix it. Just make sure you pass back the fixes to me B-). X-Forwarded-For Http Module Binary Distribution X-Forwarded-For Http Module Source Distribution The filter will require installation into IIS in order for you to be able to add it to your applications. Both distributions include a readme.txt file with an example installation procedure. Make sure you use the Release builds for the appropriate platform (x86 or x64) unless you are in need of some troubleshooting as the Debug build will dump a lot of data to a log file. The module supports customizable headers if you are using something other than X-Forwarded-For. Instructions for using that are in the readme.txt file as well. If you have any issues with using this, please let me know on this blog. Keep in mind that this is an unsupported product, but I'll do my best to fix any issues that come up. I'm even open to enhancements if you can think of any. Enjoy! -JoeX-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
