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
F5 Friday: Load Balancing MySQL with F5 BIG-IP
Scaling MySQL just got a whole lot easier load balancing MySQL – any database, really – is not a trivial task. Generally speaking one does not simply round robin your way through a cluster of MySQL databases as a means to achieve scalability. It is databases, in fact, that have driven a wide variety of scalability patterns such as sharding and partitioning to achieve the ultimate goal of high-performance and scalability simultaneously. Unfortunately, most folks don’t architect their applications with scalability in mind. A single database is all that’s necessary at first, and because of the way in which the application interacts with the database, it doesn’t make sense to code in support for multiple database instances, such as is often implemented with a MySQL master-slave cluster. That’s because the application has to actually open a connection to the database in question. If you’re only starting with one database, you really can’t code in a connection to a separate instance. Eventually that application’s usage grows and the demands upon the database require a more scalable approach. Enter the MySQL master/slave relationship. A typical configuration is to maintain the master as the “write” database, i.e. all updates and/or inserts must use the master, while the slave instance is used as a “read only” instance. Obviously this means the application code must be changed to support this kind of functional sharding. Unless you leverage network server virtualization from a load balancing service capable of acting as a full-proxy at layer 7 (application) like BIG-IP. This solution leverages iRules to implement database load balancing. While this specific example is designed to perform the common functional sharding pattern of read-write separation for a master-slave MySQL cluster, the flexibility of iRules is such that other architectural solutions can easily be designed using the same basic functions. Location based sharding is another popular means of scaling databases, and using the GeoLocation capabilities of BIG-IP along with iRules to inspect and route database requests, it should be a fairly trivial architectural task to implement. The ability to further extend sharding or other distribution methodologies for scaling databases without modifying the application itself is a huge bonus for both developers and operations. By decoupling the application from the database, it provides a more flexibility set of scalability domains in which technology targeted scalability strategies can be leveraged independent of the other layers. This is an important facet of agile infrastructure architecture and should not be underestimated as a benefit of network server virtualization. MySQL Load Balancing Resources: MySQL Proxy iRule MySQL Proxy iApp (deployment package for BIG-IP v11) The Full-Proxy Data Center Architecture Infrastructure Scalability Pattern: Sharding Streams Infrastructure Scalability Pattern: Sharding Sessions Infrastructure Scalability Pattern: Partition by Function or Type IT as a Service: A Stateless Infrastructure Architecture Model F5 Friday: Platform versus Product At the Intersection of Cloud and Control… What is a Strategic Point of Control Anyway? All F5 Friday Posts on DevCentral Why Single-Stack Infrastructure SucksThe Challenges of SQL Load Balancing
#infosec #iam load balancing databases is fraught with many operational and business challenges. While cloud computing has brought to the forefront of our attention the ability to scale through duplication, i.e. horizontal scaling or “scale out” strategies, this strategy tends to run into challenges the deeper into the application architecture you go. Working well at the web and application tiers, a duplicative strategy tends to fall on its face when applied to the database tier. Concerns over consistency abound, with many simply choosing to throw out the concept of consistency and adopting instead an “eventually consistent” stance in which it is assumed that data in a distributed database system will eventually become consistent and cause minimal disruption to application and business processes. Some argue that eventual consistency is not “good enough” and cite additional concerns with respect to the failure of such strategies to adequately address failures. Thus there are a number of vendors, open source groups, and pundits who spend time attempting to address both components. The result is database load balancing solutions. For the most part such solutions are effective. They leverage master-slave deployments – typically used to address failure and which can automatically replicate data between instances (with varying levels of success when distributed across the Internet) – and attempt to intelligently distribute SQL-bound queries across two or more database systems. The most successful of these architectures is the read-write separation strategy, in which all SQL transactions deemed “read-only” are routed to one database while all “write” focused transactions are distributed to another. Such foundational separation allows for higher-layer architectures to be implemented, such as geographic based read distribution, in which read-only transactions are further distributed by geographically dispersed database instances, all of which act ultimately as “slaves” to the single, master database which processes all write-focused transactions. This results in an eventually consistent architecture, but one which manages to mitigate the disruptive aspects of eventually consistent architectures by ensuring the most important transactions – write operations – are, in fact, consistent. Even so, there are issues, particularly with respect to security. MEDIATION inside the APPLICATION TIERS Generally speaking mediating solutions are a good thing – when they’re external to the application infrastructure itself, i.e. the traditional three tiers of an application. The problem with mediation inside the application tiers, particularly at the data layer, is the same for infrastructure as it is for software solutions: credential management. See, databases maintain their own set of users, roles, and permissions. Even as applications have been able to move toward a more shared set of identity stores, databases have not. This is in part due to the nature of data security and the need for granular permission structures down to the cell, in some cases, and including transactional security that allows some to update, delete, or insert while others may be granted a different subset of permissions. But more difficult to overcome is the tight-coupling of identity to connection for databases. With web protocols like HTTP, identity is carried along at the protocol level. This means it can be transient across connections because it is often stuffed into an HTTP header via a cookie or stored server-side in a session – again, not tied to connection but to identifying information. At the database layer, identity is tightly-coupled to the connection. The connection itself carries along the credentials with which it was opened. This gives rise to problems for mediating solutions. Not just load balancers but software solutions such as ESB (enterprise service bus) and EII (enterprise information integration) styled solutions. Any device or software which attempts to aggregate database access for any purpose eventually runs into the same problem: credential management. This is particularly challenging for load balancing when applied to databases. LOAD BALANCING SQL To understand the challenges with load balancing SQL you need to remember that there are essentially two models of load balancing: transport and application layer. At the transport layer, i.e. TCP, connections are only temporarily managed by the load balancing device. The initial connection is “caught” by the Load balancer and a decision is made based on transport layer variables where it should be directed. Thereafter, for the most part, there is no interaction at the load balancer with the connection, other than to forward it on to the previously selected node. At the application layer the load balancing device terminates the connection and interacts with every exchange. This affords the load balancing device the opportunity to inspect the actual data or application layer protocol metadata in order to determine where the request should be sent. Load balancing SQL at the transport layer is less problematic than at the application layer, yet it is at the application layer that the most value is derived from database load balancing implementations. That’s because it is at the application layer where distribution based on “read” or “write” operations can be made. But to accomplish this requires that the SQL be inline, that is that the SQL being executed is actually included in the code and then executed via a connection to the database. If your application uses stored procedures, then this method will not work for you. It is important to note that many packaged enterprise applications rely upon stored procedures, and are thus not able to leverage load balancing as a scaling option. Depending on your app or how your organization has agreed to protect your data will determine which of these methods are used to access your databases. The use of inline SQL affords the developer greater freedom at the cost of security, increased programming(to prevent the inherent security risks), difficulty in optimizing data and indices to adapt to changes in volume of data, and deployment burdens. However there is lively debate on the values of both access methods and how to overcome the inherent risks. The OWASP group has identified the injection attacks as the easiest exploitation with the most damaging impact. This also requires that the load balancing service parse MySQL or T-SQL (the Microsoft Transact Structured Query Language). Databases, of course, are designed to parse these string-based commands and are optimized to do so. Load balancing services are generally not designed to parse these languages and depending on the implementation of their underlying parsing capabilities, may actually incur significant performance penalties to do so. Regardless of those issues, still there are an increasing number of organizations who view SQL load balancing as a means to achieve a more scalable data tier. Which brings us back to the challenge of managing credentials. MANAGING CREDENTIALS Many solutions attempt to address the issue of credential management by simply duplicating credentials locally; that is, they create a local identity store that can be used to authenticate requests against the database. Ostensibly the credentials match those in the database (or identity store used by the database such as can be configured for MSSQL) and are kept in sync. This obviously poses an operational challenge similar to that of any distributed system: synchronization and replication. Such processes are not easily (if at all) automated, and rarely is the same level of security and permissions available on the local identity store as are available in the database. What you generally end up with is a very loose “allow/deny” set of permissions on the load balancing device that actually open the door for exploitation as well as caching of credentials that can lead to unauthorized access to the data source. This also leads to potential security risks from attempting to apply some of the same optimization techniques to SQL connections as is offered by application delivery solutions for TCP connections. For example, TCP multiplexing (sharing connections) is a common means of reusing web and application server connections to reduce latency (by eliminating the overhead associated with opening and closing TCP connections). Similar techniques at the database layer have been used by application servers for many years; connection pooling is not uncommon and is essentially duplicated at the application delivery tier through features like SQL multiplexing. Both connection pooling and SQL multiplexing incur security risks, as shared connections require shared credentials. So either every access to the database uses the same credentials (a significant negative when considering the loss of an audit trail) or we return to managing duplicate sets of credentials – one set at the application delivery tier and another at the database, which as noted earlier incurs additional management and security risks. YOU CAN’T WIN FOR LOSING Ultimately the decision to load balance SQL must be a combination of business and operational requirements. Many organizations successfully leverage load balancing of SQL as a means to achieve very high scale. Generally speaking the resulting solutions – such as those often touted by e-Bay - are based on sound architectural principles such as sharding and are designed as a strategic solution, not a tactical response to operational failures and they rarely involve inspection of inline SQL commands. Rather they are based on the ability to discern which database should be accessed given the function being invoked or type of data being accessed and then use a traditional database connection to connect to the appropriate database. This does not preclude the use of application delivery solutions as part of such an architecture, but rather indicates a need to collaborate across the various application delivery and infrastructure tiers to determine a strategy most likely to maintain high-availability, scalability, and security across the entire architecture. Load balancing SQL can be an effective means of addressing database scalability, but it should be approached with an eye toward its potential impact on security and operational management. What are the pros and cons to keeping SQL in Stored Procs versus Code Mission Impossible: Stateful Cloud Failover Infrastructure Scalability Pattern: Sharding Streams The Real News is Not that Facebook Serves Up 1 Trillion Pages a Month… SQL injection – past, present and future True DDoS Stories: SSL Connection Flood Why Layer 7 Load Balancing Doesn’t Suck Web App Performance: Think 1990s.
Logging the request coming to a Virtual Server
Hi Everyone, I want to record each and every hit on my Virtual Server. It want the hit log to be sent to my Syslog server. I have configured the Syslog IP under the "Remote Logging" configuration in the GUI. But I am not getting the logs of Remote IP addresses connecting to my Virtual Servers. Have I missed any configuration? Do I need to configure anything under the virtual server configuration?? Need some quick response pls.. Regards,b
Expand disk or add new disk to big-ip VE
Hey We have a VMWare 5.1 environment with big-ip VE and I want to expand the disk its running on due to new apps I want to run on it but dont have the diskspace. Have tried to expand the disk with adding disk space and expanding the disk with basic linux commands, we cannot get that to work and I cannot really find much information about this. I would appreciate if someone could point me to a solution. Thank youWhat is a Strategic Point of Control Anyway?
From mammoth hunting to military maneuvers to the datacenter, the key to success is control Recalling your elementary school lessons, you’ll probably remember that mammoths were large and dangerous creatures and like most animals they were quite deadly to primitive man. But yet man found a way to hunt them effectively and, we assume, with more than a small degree of success as we are still here and, well, the mammoths aren’t. Marx Cavemen PHOTO AND ART WORK : Fred R Hinojosa. The theory of how man successfully hunted ginormous creatures like the mammoth goes something like this: a group of hunters would single out a mammoth and herd it toward a point at which the hunters would have an advantage – a narrow mountain pass, a clearing enclosed by large rock, etc… The qualifying criteria for the place in which the hunters would finally confront their next meal was that it afforded the hunters a strategic point of control over the mammoth’s movement. The mammoth could not move away without either (a) climbing sheer rock walls or (b) being attacked by the hunters. By forcing mammoths into a confined space, the hunters controlled the environment and the mammoth’s ability to flee, thus a successful hunt was had by all. At least by all the hunters; the mammoths probably didn’t find it successful at all. Whether you consider mammoth hunting or military maneuvers or strategy-based games (chess, checkers) one thing remains the same: a winning strategy almost always involves forcing the opposition into a situation over which you have control. That might be a mountain pass, or a densely wooded forest, or a bridge. The key is to force the entire complement of the opposition through an easily and tightly controlled path. Once they’re on that path – and can’t turn back – you can execute your plan of attack. These easily and highly constrained paths are “strategic points of control.” They are strategic because they are the points at which you are empowered to perform some action with a high degree of assurance of success. In data center architecture there are several “strategic points of control” at which security, optimization, and acceleration policies can be applied to inbound and outbound data. These strategic points of control are important to recognize as they are the most efficient – and effective – points at which control can be exerted over the use of data center resources. DATA CENTER STRATEGIC POINTS of CONTROL In every data center architecture there are aggregation points. These are points (one or more components) through which all traffic is forced to flow, for one reason or another. For example, the most obvious strategic point of control within a data center is at its perimeter – the router and firewalls that control inbound access to resources and in some cases control outbound access as well. All data flows through this strategic point of control and because it’s at the perimeter of the data center it makes sense to implement broad resource access policies at this point. Similarly, strategic points of control occur internal to the data center at several “tiers” within the architecture. Several of these tiers are: Storage virtualization provides a unified view of storage resources by virtualizing storage solutions (NAS, SAN, etc…). Because the storage virtualization tier manages all access to the resources it is managing, it is a strategic point of control at which optimization and security policies can be easily applied. Application Delivery / load balancing virtualizes application instances and ensures availability and scalability of an application. Because it is virtualizing the application it therefore becomes a point of aggregation through which all requests and responses for an application must flow. It is a strategic point of control for application security, optimization, and acceleration. Network virtualization is emerging internal to the data center architecture as a means to provide inter-virtual machine connectivity more efficiently than perhaps can be achieved through traditional network connectivity. Virtual switches often reside on a server on which multiple applications have been deployed within virtual machines. Traditionally it might be necessary for communication between those applications to physically exit and re-enter the server’s network card. But by virtualizing the network at this tier the physical traversal path is eliminated (and the associated latency, by the way) and more efficient inter-vm communication can be achieved. This is a strategic point of control at which access to applications at the network layer should be applied, especially in a public cloud environment where inter-organizational residency on the same physical machine is highly likely. OLD SKOOL VIRTUALIZATION EVOLVES You might have begun noticing a central theme to these strategic points of control: they are all points at which some kind of virtualization – and thus aggregation – occur naturally in a data center architecture. This is the original (first) kind of virtualization: the presentation of many resources as a single resources, a la load balancing and other proxy-based solutions. When there is a one —> many (1:M) virtualization solution employed, it naturally becomes a strategic point of control by virtue of the fact that all “X” traffic must flow through that solution and thus policies regarding access, security, logging, etc… can be applied in a single, centrally managed location. The key here is “strategic” and “control”. The former relates to the ability to apply the latter over data at a single point in the data path. This kind of 1:M virtualization has been a part of datacenter architectures since the mid 1990s. It’s evolved to provide ever broader and deeper control over the data that must traverse these points of control by nature of network design. These points have become, over time, strategic in terms of the ability to consistently apply policies to data in as operationally efficient manner as possible. Thus have these virtualization layers become “strategic points of control”. And you thought the term was just another square on the buzz-word bingo card, didn’t you?
http and https monitors
Hello guys, My first question is what is the difference between http and https monitor? And can I use these monitors for any port or are there specific ports I need to use? For example- for many of tasks for 8443 monitor I use https monitor, so does that mean when the port is 8080 then I need to use http monitor? But I haven't seen anybody using http monitor so far. Please put some light on my question guys, I am sorry for silly question like this. Thank you in advance.. RASM Event log with local storage
Hi all, May you help me the way to extend local data storage volume for ASM Event logs? I have been using default profile named "Log illegal requests" in TMOS 11.6, and I don't have remote storage now. Because I want to view event logs more than 01 day period, during auditing time, but the older event logs were deleted. I have researched more information about the local data storage for ASM event log, but I can't find the solution. Could anyone help me? and please correct to me if I have any wrong knowledge. Hope your response. Best regards, Loan.
F5 Predicts: Education gets personal
The topic of education is taking centre stage today like never before. I think we can all agree that education has come a long way from the days where students and teachers were confined to a classroom with a chalkboard. Technology now underpins virtually every sector and education is no exception. The Internet is now the principal enabling mechanism by which students assemble, spread ideas and sow economic opportunities. Education data has become a hot topic in a quest to transform the manner in which students learn. According to Steven Ross, a professor at the Centre for Research and Reform in Education at Johns Hopkins University, the use of data to customise education for students will be the key driver for learning in the future[1].This technological revolution has resulted in a surge of online learning courses accessible to anyone with a smart device. A two-year assessment of the massive open online courses (MOOCs) created by HarvardX and MITxrevealed that there were 1.7 million course entries in the 68 MOOC [2].This translates to about 1 million unique participants, who on average engage with 1.7 courses each. This equity of education is undoubtedly providing vast opportunities for students around the globe and improving their access to education. With more than half a million apps to choose from on different platforms such as the iOS and Android, both teachers and students can obtain digital resources on any subject. As education progresses in the digital era, here are some considerations for educational institutions to consider: Scale and security The emergence of a smogasborad of MOOC providers, such as Coursera and edX, have challenged the traditional, geographical and technological boundaries of education today. Digital learning will continue to grow driving the demand for seamless and user friendly learning environments. In addition, technological advancements in education offers new opportunities for government and enterprises. It will be most effective if provided these organisations have the ability to rapidly scale and adapt to an all new digital world – having information services easily available, accessible and secured. Many educational institutions have just as many users as those in large multinational corporations and are faced with the issue of scale when delivering applications. The aim now is no longer about how to get fast connection for students, but how quickly content can be provisioned and served and how seamless the user experience can be. No longer can traditional methods provide our customers with the horizontal scaling needed. They require an intelligent and flexible framework to deploy and manage applications and resources. Hence, having an application-centric infrastructure in place to accelerate the roll-out of curriculum to its user base, is critical in addition to securing user access and traffic in the overall environment. Ensuring connectivity We live in a Gen-Y world that demands a high level of convenience and speed from practically everyone and anything. This demand for convenience has brought about reform and revolutionised the way education is delivered to students. Furthermore, the Internet of things (IoT), has introduced a whole new raft of ways in which teachers can educate their students. Whether teaching and learning is via connected devices such as a Smart Board or iPad, seamless access to data and content have never been more pertinent than now. With the increasing reliance on Internet bandwidth, textbooks are no longer the primary means of educating, given that students are becoming more web oriented. The shift helps educational institutes to better personalise the curriculum based on data garnered from students and their work. Duty of care As the cloud continues to test and transform the realms of education around the world, educational institutions are opting for a centralised services model, where they can easily select the services they want delivered to students to enhance their learning experience. Hence, educational institutions have a duty of care around the type of content accessed and how it is obtained by students. They can enforce acceptable use policies by only delivering content that is useful to the curriculum, with strong user identification and access policies in place. By securing the app, malware and viruses can be mitigated from the institute’s environment. From an outbound perspective, educators can be assured that students are only getting the content they are meant to get access to. F5 has the answer BIG-IP LTM acts as the bedrock for educational organisations to provision, optimise and deliver its services. It provides the ability to publish applications out to the Internet in a quickly and timely manner within a controlled and secured environment. F5 crucially provides both the performance and the horizontal scaling required to meet the highest levels of throughput. At the same time, BIG-IP APM provides schools with the ability to leverage virtual desktop infrastructure (VDI) applications downstream, scale up and down and not have to install costly VDI gateways on site, whilst centralising the security decisions that come with it. As part of this, custom iApps can be developed to rapidly and consistently deliver, as well as reconfigure the applications that are published out to the Internet in a secure, seamless and manageable way. BIG-IP Application Security Manager (ASM) provides an application layer security to protect vital educational assets, as well as the applications and content being continuously published. ASM allows educational institutes to tailor security profiles that fit like a glove to wrap seamlessly around every application. It also gives a level of assurance that all applications are delivered in a secure manner. Education tomorrow It is hard not to feel the profound impact that technology has on education. Technology in the digital era has created a new level of personalised learning. The time is ripe for the digitisation of education, but the integrity of the process demands the presence of technology being at the forefront, so as to ensure the security, scalability and delivery of content and data. The equity of education that technology offers, helps with addressing factors such as access to education, language, affordability, distance, and equality. Furthermore, it eliminates geographical boundaries by enabling the mass delivery of quality education with the right policies in place. [1] http://www.wsj.com/articles/SB10001424052702304756104579451241225610478 [2] http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2586847
