ADC02 – Lack of Fault Tolerance & Resilience in Enterprise Applications Using A2A Protocol
Introduction In the world of enterprise applications, fault tolerance and resilience play a central role in ensuring uninterrupted service delivery. However, the absence of these critical components can lead to degraded performance, downtime, costly inefficiencies, and dissatisfied users. This article explores fault tolerance challenges using the A2A protocol in enterprise applications, leveraging F5 BIG-IP to resolve primary data center failures, as illustrated in the attached diagram. AI Reference Architecture The Use Case at a glance The architecture for this scenario involves: AI Clients initiating A2A traffic routed via a Primary BIG-IP LTM. The Primary BIG-IP LTM processes the requests and routes intelligently based on A2A protocol inspection. In the event of a Primary BIG-IP failure, a Standby BIG-IP LTM in a high availability (HA) configuration takes over seamlessly. AI Agents (hosted across multiple instances) process user traffic through the Active BIG-IP, ensuring continuous service availability. This structure ensures resilience while avoiding performance bottlenecks caused by load imbalances or failures. Consequences of a Lack of Fault Tolerance and Resilience Impact on Performance Without adequate fault tolerance mechanisms: Failures in a primary system increase the load on remaining servers, causing degraded response times. Systems experience 35% more downtime during high-load scenarios, as indicated by LoadView’s 2024 network performance report. Impact on Availability A lack of redundancy or failover capabilities results in prolonged downtime when a failure occurs, tarnishing organizational reputation and eroding user trust. In complex environments, cascading failures can be triggered, amplifying the chaos. Impact on Scalability Systems lacking fault tolerance cannot scale dynamically to meet changing traffic demands. Rapid traffic surges overwhelm resources, causing bottlenecks. Overprovisioning as a stopgap becomes costly and inefficient. Impact on Operational Efficiency When failures occur, manual interventions become necessary, which increase operational overhead, downtime, and costs. Automated mechanisms for failover and load balancing are critical in reducing reliance on human intervention and ensuring operational efficiency. Solutions to Enable Fault Tolerance and Resilience Using F5 BIG-IP Load Balancing with BIG-IP F5 BIG-IP's iRules dynamically route A2A traffic, ensuring intelligent management even in volatile conditions. A load balancing configuration includes: Active-Standby Configuration: Load balancing redirects traffic to the standby BIG-IP in case of failure. Active-Active Configuration (Optional): For consistently high traffic volumes, active-active HA ensures even traffic distribution, improving both availability and scalability. High Availability (HA) Setup BIG-IP’s HA architecture supports synchronized active and standby systems: Failover Objects and Floating IPs allow seamless rollover during primary system failures. Redundant servers prevent single points of failure, ensuring uninterrupted operations. Comprehensive Health Monitoring Advanced health checks go beyond simple pings to assess the full responsiveness and integrity of applications and supporting infrastructure: Use distributed health checks from geographically disparate locations to simulate actual user experiences. Create application-specific health checks to test backend systems fully. Programmable Infrastructure Programmable infrastructure with F5 BIG-IP allows organizations to: Customize fault-tolerance strategies tailored for specific applications. Adjust traffic dynamically in real-time using programmable application delivery controllers (ADCs). Automation for Instant Response By integrating failover automation, organizations can: Detect and mitigate failures faster, reducing downtime. Lower operational overhead by minimizing manual interventions. Best Practices for Fault Tolerance Optimization Readiness Planning Use resources like "BIG-IP HA - Do it the Proper Way" to correctly implement HA configurations. Synchronize configurations and session data between BIG-IP devices. Tailored Load Balancer Configurations Optimize load balancing policies for real-world traffic patterns. Implement automated traffic redirection during outages. Proactive Monitorin Constantly monitor application performance via distributed health checks described in the "F5 Academy - BIG-IP HA - Do it the Proper Way". Resilience Testing Periodically test failover functionality to ensure system readiness to handle failures under real-world conditions. Resource Scalabilit Leverage the F5 Active-Active HA Configuration for highly scalable environments. Why Fault Tolerance Matters Fault tolerance isn’t just a technical concept; it directly dictates application availability, performance, and scalability. Proactive strategies like HA, programmable infrastructure, and automation enable organizations to build resilient systems capable of handling any disruptions. Conclusion In the ever-evolving digital landscape, resilience and fault tolerance are no longer optional—they are imperative. Leveraging F5 BIG-IP solutions for HA, intelligent load balancing, and failover mechanisms ensures applications remain available, scalable, and efficient, even during disruptions. By building fault-tolerant systems, enterprises not only meet today’s challenges but also position themselves for future growth and stability. Learn More Explore these resources to dive deeper into enabling fault tolerance and resilience: Intro to: BIG-IP HA - Do it the Proper Way High availability on F5 BIG-IP load balancers F5 BIG-IP HA Active Standby Configuration F5 Active-Active HA Configuration F5 Academy - BIG-IP HA - Do it the Proper Way ADSP Platform overview AI reference architecture The Application Delivery Top 10
Implementing ECC+PFS on LineRate (Part 1/3): Choosing ECC Curves and Preparing SSL Certificates
(Editors note: the LineRate product has been discontinued for several years. 09/2023) --- Overview In case you missed it, Why ECC and PFS Matter: SSL offloading with LineRate details some of the reasons why ECC-based SSL has advantages over RSA cryptography for both performance and security. This article will generate all the necessary ECC certificates with the secp384r1 curve so that they may be used to configure an LineRate System for SSL Offload. Getting Started with LineRate In order to appreciate the advantages of SSL/TLS Offload available via LineRate as discussed in this article, let's take a closer look at how to configure SSL/TLS Offloading on a LineRate system. This example will implement Elliptical Curve Cryptography and Perfect Forward Secrecy. SSL Offloading will be added to an existing LineRate System that has one public-facing Virtual IP (10.10.11.11) that proxies web requests to a Real Server on an internal network (10.10.10.1). The following diagram demonstrates this configuration: Figure 1: A high-level implementation of SSL Offload Overall, these steps will be completed in order to enable SSL Offloading on the LineRate System: Generate a private key specifying the secp384r1 elliptic curve Obtain a certificate from a CA Configure an SSL profile and attach it to the Virtual IP Note that this implementation will enable only ECDHE cipher suites. ECDH cipher suites are available, but these do not implement the PFS feature. Further, in production deployments, considerations to implement additional types of SSL cryptography might be needed in order to allow backward compatibility for older clients. Generating a private key for Elliptical Curve Cryptography When considering the ECC curve to use for your environment, you may choose one from the currently available curves list in the LineRate documentation. It is important to be cognizant of the curve support for the browsers or applications your application targets using. Generally, the NIST P-256, P-384, and P-521 curves have the widest support. This example will use the secp384r1 (NIST P-384) curve, which provides an RSA equivalent key of 7680-bits. Supported curves with OpenSSL can be found by running the openssl ecparam -list_curves command, which may be important depending on which curve is chosen for your SSL/TLS deployment. Using OpenSSL, a private key is generated for use with ssloffload.lineratesystems.com. The ECC SECP curve over a 384-bit prime field (secp384r1) is specified: openssl ecparam -genkey -name secp384r1 -out ssloffload.lineratesystems.com.key.pem This command results in the following private key: -----BEGIN EC PARAMETERS----- BgUrgQQAIg== -----END EC PARAMETERS----- -----BEGIN EC PRIVATE KEY----- MIGkAgEBBDD1Kx9hghSGCTujAaqlnU2hs/spEOhfpKY9EO3mYTtDmKqkuJLKtv1P 1/QINzAU7JigBwYFK4EEACKhZANiAASLp1bvf/VJBJn4kgUFundwvBv03Q7c3tlX kh6Jfdo3lpP2Mf/K09bpt+4RlDKQynajq6qAJ1tJ6Wz79EepLB2U40fC/3OBDFQx 5gSjRp8Y6aq8c+H8gs0RKAL+I0c8xDo= -----END EC PRIVATE KEY----- Generating a Certificate Request (CSR) to provide the Certificate Authority (CA) After the primary key is obtained, a certificate request (CSR) can be created. Using OpenSSL again, the following command is issued filling out all relevant information in the successive prompts: openssl req -new -key ssloffload.lineratesystems.com.key.pem -out ssloffload.lineratesystems.com.csr.pem This results in the following CSR: -----BEGIN CERTIFICATE REQUEST----- MIIB3jCCAWQCAQAwga8xCzAJBgNVBAYTAlVTMREwDwYDVQQIEwhDb2xvcmFkbzET MBEGA1UEBxMKTG91aXN2aWxsZTEUMBIGA1UEChMLRjUgTmV0d29ya3MxGTAXBgNV BAsTEExpbmVSYXRlIFN5c3RlbXMxJzAlBgNVBAMTHnNzbG9mZmxvYWQubGluZXJh dGVzeXN0ZW1zLmNvbTEeMBwGCSqGSIb3DQEJARYPYS5yYWdvbmVAZjUuY29tMHYw EAYHKoZIzj0CAQYFK4EEACIDYgAEi6dW73/1SQSZ+JIFBbp3cLwb9N0O3N7ZV5Ie iX3aN5aT9jH/ytPW6bfuEZQykMp2o6uqgCdbSels+/RHqSwdlONHwv9zgQxUMeYE o0afGOmqvHPh/ILNESgC/iNHPMQ6oDUwFwYJKoZIhvcNAQkHMQoTCGNpc2NvMTIz MBoGCSqGSIb3DQEJAjENEwtGNSBOZXR3b3JrczAJBgcqhkjOPQQBA2kAMGYCMQCn h1NHGzigooYsohQBzf5P5KO3Z0/H24Z7w8nFZ/iGTEHa0+tmtGK/gNGFaSH1ULcC MQCcFea3plRPm45l2hjsB/CusdNo0DJUPMubLRZ5mgeThS/N6Eb0AHJSjBJlE1fI a4s= -----END CERTIFICATE REQUEST----- Obtaining a Certificate from a Certificate Authority (CA) Rather than using a self-signed certificate, a test certificate is obtained from Entrust. Upon completing the certificate request and receiving it from Entrust, a simple conversion needs to be done to PEM format. This can be done with the following OpenSSL command: openssl x509 -inform der -in ssloffload.lineratesystems.com.cer -out ssloffload.lineratesystems.com.cer.pem This results in the following certificate: -----BEGIN CERTIFICATE----- MIIC5jCCAm2gAwIBAgIETUKHWzAKBggqhkjOPQQDAzBtMQswCQYDVQQGEwJVUzEW MBQGA1UEChMNRW50cnVzdCwgSW5jLjEfMB0GA1UECxMWRm9yIFRlc3QgUHVycG9z ZXMgT25seTElMCMGA1UEAxMcRW50cnVzdCBFQ0MgRGVtb25zdHJhdGlvbiBDQTAe Fw0xNDA4MTExODQ3MTZaFw0xNDEwMTAxOTE3MTZaMGkxHzAdBgNVBAsTFkZvciBU ZXN0IFB1cnBvc2VzIE9ubHkxHTAbBgNVBAsTFFBlcnNvbmEgTm90IFZlcmlmaWVk MScwJQYDVQQDEx5zc2xvZmZsb2FkLmxpbmVyYXRlc3lzdGVtcy5jb20wdjAQBgcq hkjOPQIBBgUrgQQAIgNiAASLp1bvf/VJBJn4kgUFundwvBv03Q7c3tlXkh6Jfdo3 lpP2Mf/K09bpt+4RlDKQynajq6qAJ1tJ6Wz79EepLB2U40fC/3OBDFQx5gSjRp8Y 6aq8c+H8gs0RKAL+I0c8xDqjgeEwgd4wDgYDVR0PAQH/BAQDAgeAMB0GA1UdJQQW MBQGCCsGAQUFBwMBBggrBgEFBQcDAjA3BgNVHR8EMDAuMCygKqAohiZodHRwOi8v Y3JsLmVudHJ1c3QuY29tL0NSTC9lY2NkZW1vLmNybDApBgNVHREEIjAggh5zc2xv ZmZsb2FkLmxpbmVyYXRlc3lzdGVtcy5jb20wHwYDVR0jBBgwFoAUJAVL4WSCGvgJ zPt4eSH6cOaTMuowHQYDVR0OBBYEFESqK6HoSFIYkItcfekqqozX+z++MAkGA1Ud EwQCMAAwCgYIKoZIzj0EAwMDZwAwZAIwXWvK2++3500EVaPbwvJ39zp2IIQ98f66 /7fgroRGZ2WoKLBzKHRljVd1Gyrl2E3BAjBG9yPQqTNuhPKk8mBSUYEi/CS7Z5xt dXY/e7ivGEwi65z6iFCWuliHI55iLnXq7OU= -----END CERTIFICATE----- Note that the certificate generation process is very familiar with Elliptical Curve Cryptography versus traditional cryptographic algorithms like RSA. Only a few differences are found in the generation of the primary key where an ECC curve is specified. Continue the Configuration Now that the certificates needed to configure Elliptical Curve Cryptography have been created, it is now time to configure SSL Offloading on LineRate. Part 2: Configuring SSL Offload on LineRate continues the demonstration of SSL Offloading by importing the certificate information generated in this article and getting the system up and running. In case you missed it, Why ECC and PFS Matter: SSL offloading with LineRate details some of the reasons why ECC-based SSL has advantages over RSA cryptography for both performance and security. (Editors note: the LineRate product has been discontinued for several years. 09/2023) Stay Tuned! Next week a demonstration on how to verify a correct implementation of SSL with ECC+PFS on LineRate will make a debut on DevCentral. The article will detail how to check for ECC SSL on the wire via WireShark and in the browser. In the meantime, take some time to download LineRate and test out its SSL Offloading capabilities. In case you missed any content, or would like to reference it again, here are the articles related to implementing SSL Offload with ECC and PFS on LineRate: Why ECC and PFS Matter: SSL offloading with LineRate Implementing ECC+PFS on LineRate (Part 1/3): Choosing ECC Curves and Preparing SSL Certificates Implementing ECC+PFS on LineRate (Part 2/3): Configuring SSL Offload on LineRate Implementing ECC+PFS on LineRate (Part 3/3): Confirming the Operation of SSL Offloading
Performance overhead issue
In our environment we are experiencing serious performance issue when the traffic is routed through F5. Directly accessing web server has no issue. Traffic through F5 taking 10 times more time than directly accessing web server. We observed this as end-user. Further analysis showed that there is file (or) script name looks like "xyz.policy" is responsible for high response time. "xyz.policy" was configured to enforce security for accessing files on the web server. Accessing a file for example "MyFile.html" will redirect to and demands user credentials. From the IIS logs we can see that web server side "time-taken" stats is few milliseconds but overall end-user response time is 40+ seconds. Now I would like to ask our F5 admin to help us analysing this performance issue. I need your help in asking right questions to the F5 admin. I do not have access to F5. Please also suggest how to diagnose such performance issues w.r.t F5. Regards, Prasad
APM :: RDP Performance
Has anybody ran into performance issues with RDP via APM? Our VMware View profiles are speedy (PCoIP - UDP/4172) but when users access their RDP sessions (TCP/443), those are slower than what is tolerable for certain users (even though their bandwidth at home is great). I'm wondering if it has to do with the TCP profile assigned to the virtual server (wan optimized). I haven't been able to test different ones (in production), but just curious on other experiences of folks with the same setup. Log in -> Full Webtop -> RDP Profile Thanks-
Log the time of request /response on the F5.
Hi, Due to some troubleshooting point of view our client was us to log the following information on the F5. Is there any way to log below information on the F5 or some kind of i-rule oOverall Time spent handing a request oTime spent doing SSL offloading oTime spend with the request/response towards the Web Server oTime spent serving the response back to the initial request waiting for the response. thanks.DNS Resolver Cache
Hi, I'm currently investigating the option to dispose of my LDNS servers and let the LTM do the recursive lookups for my clients and cache responses. I have read the following statement from there site and I'm wondering if this statement applies to what I was trying to do. "It is important for network architects to note that it is possible to configure the local BIND instance on the BIG-IP® system to act as an external DNS resolver. However, F5 Networks does not recommend this approach, because the performance of BIND is slower than using a resolver cache." Basically what I was trying to accomplish is have my clients (linux, windows, etc) point to the LTM as their DNS servers, and let the DNS resolve and cache. ThanksDoes Cloud Solve or Increase the 'Four Pillars' Problem?
It has long been said – often by this author – that there are four pillars to application performance: Memory CPU Network Storage As soon as you resolve one in response to application response times, another becomes the bottleneck, even if you are not hitting that bottleneck yet. For a bit more detail, they are “memory consumption” – because this impacts swapping in modern Operating Systems. “CPU utilization” – because regardless of OS, there is a magic line after which performance degrades radically. “Network throughput” – because applications have to communicate over the network, and blocking or not (almost all coding for networks today is), the information requested over the network is necessary and will eventually block code from continuing to execute. “Storage” – because IOPS matter when writing/reading to/from disk (or the OS swaps memory out/back in). These four have long been relatively easy to track. The relationship is pretty easy to spot, when you resolve one problem, one of the others becomes the “most dangerous” to application performance. But historically, you’ve always had access to the hardware. Even in highly virtualized environments, these items could be considered both at the Host and Guest level – because both individual VMs and the entire system matter. When moving to the cloud, the four pillars become much less manageable. The amount “much less” implies depends a lot upon your cloud provider, and how you define “cloud”. Put in simple terms, if you are suddenly struck blind, that does not change what’s in front of you, only your ability to perceive it. In the PaaS world, you have only the tools the provider offers to measure these things, and are urged not to think of the impact that host machines may have on your app. But they do have an impact. In an IaaS world you have somewhat more insight, but as others have pointed out, less control than in your datacenter. Picture Courtesy of Stanley Rabinowitz, Math Pro Press. In the SaaS world, assuming you include that in “cloud”, you have zero control and very little insight. If you app is not performing, you’ll have to talk to the vendors’ staff to (hopefully) get them to resolve issues. But is the problem any worse in the cloud than in the datacenter? I would have to argue no. Your ability to touch and feel the bits is reduced, but the actual problems are not. In a pureplay public cloud deployment, the performance of an application is heavily dependent upon your vendor, but the top-tier vendors (Amazon springs to mind) can spin up copies as needed to reduce workload. This is not a far cry from one common performance trick used in highly virtualized environments – bring up another VM on another server and add them to load balancing. If the app is poorly designed, the net result is not that you’re buying servers to host instances, it is instead that you’re buying instances directly. This has implications for IT. The reduced up-front cost of using an inefficient app – no matter which of the four pillars it is inefficient in – means that IT shops are more likely to tolerate inefficiency, even though in the long run the cost of paying monthly may be far more than the cost of purchasing a new server was, simply because the budget pain is reduced. There are a lot of companies out there offering information about cloud deployments that can help you to see if you feel blind. Fair disclosure, F5 is one of them, I work for F5. That’s all you’re going to hear on that topic in this blog. While knowing does not always directly correlate to taking action, and there is some information that only the cloud provider could offer you, knowing where performance bottlenecks are does at least give some level of decision-making back to IT staff. If an application is performing poorly, looking into what appears to be happening (you can tell network bandwidth, VM CPU usage, VM IOPS, etc, but not what’s happening on the physical hardware) can inform decision-making about how to contain the OpEx costs of cloud. Internal cloud is a much easier play, you still have access to all the information you had before cloud came along, and generally the investigation is similar to that used in a highly virtualized environment. From a troubleshooting performance problems perspective, it’s much the same. The key with both virtualization and internal (private) clouds is that you’re aiming for maximum utilization of resources, so you will have to watch for the bottlenecks more closely – you’re “closer to the edge” of performance problems, because you designed it that way. A comprehensive logging and monitoring environment can go a long way in all cloud and virtualization environments to keeping on top of issues that crop up – particularly in a large datacenter with many apps running. And developer education on how not to be a resource hog is helpful for internally developed apps. For externally developed apps the best you can do is ask for sizing information and then test their assumptions before buying. Sometimes, cloud simply is the right choice. If network bandwidth is the prime limiting factor, and your organization can accept the perceived security/compliance risks, for example, the cloud is an easy solution – bandwidth in the cloud is either not limited, or limited by your willingness to write a monthly check to cover usage. Either way, it’s not an Internet connection upgrade, which can be dastardly expensive not just at install, but month after month. Keep rocking it. Get the visibility you need, don’t worry about what you don’t need. Related Articles and Blogs: Don MacVittie - Load Balancing For Developers Advanced Load Balancing For Developers. The Network Dev Tool Load Balancers for Developers – ADCs Wan Optimization ... Intro to Load Balancing for Developers – How they work Intro to Load Balancing for Developers – The Gotchas Intro to Load Balancing for Developers – The Algorithms Load Balancing For Developers: Security and TCP Optimizations Advanced Load Balancers for Developers: ADCs - The Code Advanced Load Balancing For Developers: Virtual Benefits Don MacVittie - ADCs for Developers Devops Proverb: Process Practice Makes Perfect Devops is Not All About Automation 1024 Words: Why Devops is Hard Will DevOps Fork? DevOps. It's in the Culture, Not Tech. Lori MacVittie - Development and General Devops: Controlling Application Release Cycles to Avoid the ... An Aristotlean Approach to Devops and Infrastructure Integration How to Build a Silo Faster: Not Enough Ops in your Devops
The IT Optical Illusion
Everyone has likely seen the optical illusion of the vase in which, depending on your focus, you either see a vase or two faces. This particular optical illusion is probably the best allegorical image for IT and in particular cloud computing I can imagine. Depending on your focus within IT you’re either focused on – to borrow some terminology from SOA – design-time or run-time management of the virtualized systems and infrastructure that make up your data center. That focus determines what particular aspect of management you view as most critical, and unfortunately makes it difficult to see the “big picture”: both are critical components of a successful cloud computing initiative. I realized how endemic to the industry this “split” is while prepping for today’s “Connecting On-Premise and On-Demand with Hybrid Clouds” panel at the Enterprise Cloud Summit @ Interop on which I have the pleasure to sit with some very interesting – but differently focused – panelists. See, as soon as someone starts talking about “connectivity” the focus almost immediately drops to … the network. Right. That actually makes a great deal of sense and it is, absolutely, a critical component to building out a successful hybrid cloud computing architecture. But that’s only half of the picture, the design-time picture. What about run-time? What about the dynamism of cloud computing and virtualization? The fluid, adaptable infrastructure? You know, the connectivity that’s required at the application layers, like access control and request distribution and application performance. Part of the reason you’re designing a hybrid architecture is to retain control. Control over when those cloud resources are used and how and by whom. In most cloud computing environments today, at least public ones, there’s no way for you to maintain that control because the infrastructure services are simply not in place to do so. Yet. At least I hope yet; one wishes to believe that some day they will be there. But today, they are not. Thus, in order to maintain control over those resources there needs to be a way to manage the run-time connectivity between the corporate data center (over which you have control) and the public cloud computing environment (which you do not). That’s going to take some serious architecture work and it’s going to require infrastructure services from infrastructure capable of intercepting requests, inspecting the request in context of the user and the resource requested, and applying the policies and processes to ensure that only those clients you want to access those resources can access them, and those you prefer not access them are denied. It will become increasingly important that IT be able to view its network in terms of both design and run-time connectivity if it is going to successfully incorporate public cloud computing resources into its corporate cloud computing – or traditional – network and application delivery network strategy.Load Balancing For Developers: Security and TCP Optimizations
It has been a while since I wrote a Load Balancing for Developers installment, and since they’re pretty popular and there’s still a lot about Application Delivery Controllers (ADCs) that are taken for granted in the Networking industry but relatively unknown in the development world, I thought I’d throw one out about making your security more resilient with ADCs. For those who are just joining this series, here’s the full list of posts I’ve tagged as Load Balancing for Developers, though only the ones whose title starts with “Load Balancing for Developers” or “Advance Load Balancing for Developers” were actually written from this perspective, utilizing our fictional web application Zap’N’Go! as an example. This post, like most of them, doesn’t require that you read the other entries in the “Load Balancers for Developers” series, but if you’re interested in the topic, they are all written from the developer’s perspective, and only bring in the networking/ops portions where it makes sense. So your organization has a truly successful web application called Zap’N’Go! That has taken the Internet by storm. Your hits are in the thousands an hour, and orders are rolling in. All was going well until your server couldn’t keep up and you went to a load balanced scenario so that multiple servers could share the load. The problem is that with the money you’ve generated off of Zap’N’Go, you’ve bought a competitor and started several new web applications, set up a forum or portal for your customers to communicate with you and each other directly, and are using the old datacenter from the company you purchased as a redundant datacenter in case the worst should happen. And all of that means that you are suffering server (and VM) sprawl. The CPU cycles being eaten up by your applications are truly astounding, and you’re looking into ways to drive them down. Virtualization helped you to be more agile in responding to the requests of the business, but also brings a lot of management overhead in making certain servers aren’t overloaded with too high a virtual density. One of the cool bits about an ADC is that they do a lot more than load balance, and much of that can be utilized to improve application performance without re-architecting the entire system. While there are a lot of ways that an ADC can improve application performance, we’ll look at a couple of easy ones here, and leave some of the more difficult or involved ones for another time. That keeps me in writing topics, and makes certain that I can give each one the attention it deserves in the space available. The biggest and most obvious improvement in an ADC is of course load balancing. This blog assumes you already have an ADC in place, and load balancing was your primary reason for purchasing it. While I don’t have market numbers in front of me, it is my experience that this is true of the vast majority of ADC customers. If you have overburdened web applications and have not looked into load balancing, before you go rewriting your entire system, take a look at the rest of this series. There really are options out there to help. After that win, I think the biggest place – in a virtualized environment – that developers can reap benefits from an ADC is one that developers wouldn’t normally think of. That’s the reason for this series, so I suppose that would be a good thing. Nearly every application out there hits a point where SSL is enabled. That point may be simply the act of accessing it, or it may be when they go to the “shopping cart” section of the web site, but they all use SSL to protect sensitive user data being passed over the Internet. As a developer, you don’t have to care too much about this fact. Pay attention to the protocol if you’re writing at that level and to the ports if you have reason to, but beyond that you don’t have to care. Networking takes care of all of that for you. But what if you could put a request in to your networking group that would greatly improve performance without changing a thing in your code and from a security perspective wouldn’t change much – most companies would see it as not changing anything, while a few will want to talk about it first? What if you could make this change over lunch and users wouldn’t know the difference? Here’s the background. SSL Encryption is expensive in terms of CPU cycles. No doubt you know that, most developers have to face this issue head-on at some point. It takes a lot of power to do encryption, and while commodity hardware is now fast enough that it isn’t a problem on a stand-alone server, in a VM environment, the number of applications requesting SSL encryption on the same physical hardware is many times what it once was. That creates a burden that, at this time at least, often drags on the hardware. It’s not the fault of any one application or a rogue programmer, it is the summation of the burdens placed by each application requiring SSL translation. One solution to this problem is to try and manage VM deployment such that encryption is only required on a couple of applications per physical server, but this is not a very appealing long-term solution as loads shift and priorities change. From a developers’ point of view, do you trust the systems/network teams to guarantee your application is not sharing hardware with a zillion applications that all require SSL encryption? Over time, this is not going to be their number one priority, and when performance troubles crop up, the first place that everyone looks in an in-house developed app is at the development team. We could argue whether that’s the right starting point or not, but it certainly is where we start. Another, more generic solution is to take advantage of a non-development feature of your ADC. This feature is SSL termination. Since the ADC sits between your application and the Internet, you can tell your ADC to handle encryption for your application, and then not worry about it again. If your network team sets this up for all of your applications, then you have no worries that SSL is burning up your CPU cycles behind your back. Is there a negative? A minor one that most organizations (as noted above) just won’t see as an issue. That is that from the ADC to your application, communications will happen in the clear. If your application is internal, this really isn’t a big deal at all. If you suspect a bad-guy on your internal network, you have much more to worry about than whether communications between two boxes are in the clear. If you application is in the cloud, this concern is more realistic, but in that case, SSL termination is limited in usefulness anyway because you can’t know if the other apps on the same hardware are utilizing it. So you simply flick a switch on your ADC to turn on SSL termination, and then turn it off on your applications, and you have what the ADC industry calls “SSL offload”. If your ADC is purpose-built hardware (like our BIG-IP), then there is encryption hardware in the box and you don’t have to worry about the impact to the ADC of overloading it with SSL requests, it’s built to handle the load. If your ADC is software or a VM (like our BIG-IP LTM VE), then you’ll have to do a bit of testing to see what the tolerance level for SSL load is on the hardware you deployed it on – but you can ask the network staff to worry about all of that, once you’ve started the conversation. Is this the only security-based performance boost you can get? No, but it is the easy one. Everything on the Internet remains encrypted, but your application is not burdening the server’s CPU with encryption requests each time communications in or out occur. The other easy one is TCP optimizations. This one requires less talk because it is completely out of the realm of the developer. Simply put, TCP is a well designed protocol that sometimes gets bogged down communicating and has a lot of overhead in those situations. Turning on TCP optimizations in your ADC can reduce the overhead – more or less, depending upon what is on the other end of the communications network – and improve perceived performance, which honestly is one of the most important measures of web application availability. By making it seem to load faster, you’ve improved your customer experience, and nothing about your development has to change. TCP optimizations are not new, and thus the ones that are turned on when you activate the option on most ADCs are stable and won’t disrupt most applications. Of course you should run a short test cycle with them enabled, just to be certain, but I would be surprised if you saw any issues. They’re not unheard of, but they are very rare. That’s enough for now, I think. I don’t want these to get so long that you wander off to develop some more. Keep doing what you do. And strive to keep your users from doing this. Slow apps anger users
