VIPTest: Rapid Application Testing for F5 Environments
VIPTest is a Python-based tool for efficiently testing multiple URLs in F5 environments, allowing quick assessment of application behavior before and after configuration changes. It supports concurrent processing, handles various URL formats, and provides detailed reports on HTTP responses, TLS versions, and connectivity status, making it useful for migrations and routine maintenance.
Intermediate iRules: Nested Conditionals
Conditionals are a pretty standard tool in every programmer's toolbox. They are the functions that allow us to decided when we want certain actions to happen, based on, well, conditions that can be determined within our code. This concept is as old as compilers. Chances are, if you're writing code, you're going to be using a slew of these things, even in an Event based language like iRules. iRules is no different than any other programming/scripting language when it comes to conditionals; we have them. Sure how they're implemented and what they look like change from language to language, but most of the same basic tools are there: if, else, switch, elseif, etc. Just about any example that you might run across on DevCentral is going to contain some example of these being put to use. Learning which conditional to use in each situation is an integral part to learning how to code effectively. Once you have that under control, however, there's still plenty more to learn. Now that you're comfortable using a single conditional, what about starting to combine them? There are many times when it makes more sense to use a pair or more of conditionals in place of a single conditional along with logical operators. For example: if { [HTTP::host] eq "bob.com" and [HTTP::uri] starts_with "/uri1" } { pool pool1 } elseif { [HTTP::host] eq "bob.com" and [HTTP::uri] starts_with "/uri2" } { pool pool2 } elseif { [HTTP::host] eq "bob.com" and [HTTP::uri] starts_with "/uri3" } { pool pool3 } Can be re-written to use a pair of conditionals instead, making it far more efficient. To do this, you take the common case shared among the example strings and only perform that comparison once, and only perform the other comparisons if that result returns as desired. This is more easily described as nested conditionals, and it looks like this: if { [HTTP::host] eq "bob.com" } { if {[HTTP::uri] starts_with "/uri1" } { pool pool1 } elseif {[HTTP::uri] starts_with "/uri2" } { pool pool2 } elseif {[HTTP::uri] starts_with "/uri3" } { pool pool3 } } These two examples are logically equivalent, but the latter example is far more efficient. This is because in all the cases where the host is not equal to "bob.com", no other inspection needs to be done, whereas in the first example, you must perform the host check three times, as well as the uri check every single time, regardless of the fact that you could have stopped the process earlier. While basic, this concept is important in general when coding. It becomes exponentially more important, as do almost all optimizations, when talking about programming in iRules. A script being executed on a server firing perhaps once per minute benefits from small optimizations. An iRule being executed somewhere in the order of 100,000 times per second benefits that much more. A slightly more interesting example, perhaps, is performing the same logical nesting while using different operators. In this example we'll look at a series of if/elseif statements that are already using nesting, and take a look at how we might use the switch command to even further optimize things. I've seen multiple examples of people shying away from switch when nesting their logic because it looks odd to them or they're not quite sure how it should be structured. Hopefully this will help clear things up. First, the example using if statements: when HTTP_REQUEST { if { [HTTP::host] eq "secure.domain.com" } { HTTP::header insert "Client-IP:[IP::client_addr]" pool sslServers } elseif { [HTTP::host] eq "www.domain.com" } { HTTP::header insert "Client-IP:[IP::client_addr]" pool httpServers } elseif { [HTTP::host] ends_with "domain.com" and [HTTP::uri] starts_with "/secure"} { HTTP::header insert "Client-IP:[IP::client_addr]" pool sslServers } elseif {[HTTP::host] ends_with "domain.com" and [HTTP::uri] starts_with "/login"} { HTTP::header insert "Client-IP:[IP::client_addr]" pool httpServers } elseif { [HTTP::host] eq "intranet.myhost.com" } { HTTP::header insert "Client-IP:[IP::client_addr]" pool internal } } As you can see, this is completely functional and would do the job just fine. There are definitely some improvements that can be made, though. Let's try using a switch statement instead of several if comparisons for improved performance. To do that, we're going to have to use an if nested inside a switch comparison. While this might be new to some or look a bit odd if you're not used to it, it's completely valid and often times the most efficient you’re going to get. This is what the above code would look like cleaned up and put into a switch: when HTTP_REQUEST { HTTP::header insert "Client-IP:[IP::client_addr]" switch -glob [HTTP::host] { "secure.domain.com" { pool sslServers } "www.domain.com" { pool httpServers } "*.domain.com" { if { [HTTP::uri] starts_with "/secure" } { pool sslServers } else { pool httpServers } } "intranet.myhost.com" { pool internal } } } As you can see this is not only easier to read and maintain, but it will also prove to be more efficient. We've moved to the more efficient switch structure, we've gotten rid of the repeat host comparisons that were happening above with the /secure vs /login uris, and while I was at it I got rid of all those examples of inserting a header, since that was happening in every case anyway. Hopefully the benefit this technique can offer is clear, and these examples did the topic some justice. With any luck, you'll nest those conditionals with confidence now.How to get a F5 BIG-IP VE Developer Lab License
(applies to BIG-IP TMOS Edition) To assist DevOps teams improve their development for the BIG-IP platform, F5 offers a low cost developer lab license.This license can be purchased from your authorized F5 vendor. If you do not have an F5 vendor, you can purchase a lab license online: CDW BIG-IP Virtual Edition Lab License CDW Canada BIG-IP Virtual Edition Lab License Once completed, the order is sent to F5 for fulfillment and your license will be delivered shortly after via e-mail. F5 is investigating ways to improve this process. To download the BIG-IP Virtual Edition, please log into downloads.f5.com (separate login from DevCentral), and navigate to your appropriate virtual edition, example: For VMware Fusion or Workstation or ESX/i:BIGIP-16.1.2-0.0.18.ALL-vmware.ova For Microsoft HyperV:BIGIP-16.1.2-0.0.18.ALL.vhd.zip KVM RHEL/CentoOS: BIGIP-16.1.2-0.0.18.ALL.qcow2.zip Note: There are also 1 Slot versions of the above images where a 2nd boot partition is not needed for in-place upgrades. These images include_1SLOT- to the image name instead of ALL. The below guides will help get you started with F5 BIG-IP Virtual Edition to develop for VMWare Fusion, AWS, Azure, VMware, or Microsoft Hyper-V. These guides follow standard practices for installing in production environments and performance recommendations change based on lower use/non-critical needs fo Dev/Lab environments. Similar to driving a tank, use your best judgement. DeployingF5 BIG-IP Virtual Edition on VMware Fusion Deploying F5 BIG-IP in Microsoft Azure for Developers Deploying F5 BIG-IP in AWS for Developers Deploying F5 BIG-IP in Windows Server Hyper-V for Developers Deploying F5 BIG-IP in VMware vCloud Director and ESX for Developers Note: F5 Support maintains authoritativeAzure, AWS, Hyper-V, and ESX/vCloud installation documentation. VMware Fusion is not an official F5-supported hypervisor so DevCentral publishes the Fusion guide with the help of our Field Systems Engineering teams.Streamlining BIG-IP Next Deployments: Automate with CI/CD Pipelines Using Terraform Cloud and GitHub
Automation is key to maintaining efficiency and consistency in today's fast-paced IT environment. In this article, I will demonstrate how to automate the deployment of BIG-IP Next configurations using Terraform Cloud and GitHub. By integrating AS3 JSON and Terraform configuration code, you can ensure that any changes made in your GitHub repository automatically trigger Terraform Cloud to deploy the updated configurations to your BIG-IP Next instance via the BIG-IP Next Central Manager. Key Players: BIG-IP Next:Your powerful application delivery controller, offers advanced features for load balancing, security, and more. BIG-IP Next Central Manager: The brain of your BIG-IP Next deployment, orchestrating and managing all your BIG-IP instances. BIG-IP Next Terraform resources:A powerful interface allowing programmatic control over your BIG-IP configuration, simplifying automation. Terraform Cloud:A robust platform for infrastructure-as-code, providing version control, collaboration, and powerful automation tools. GitHub:A popular version control system for collaborative software development, where your Terraform configuration files will reside. Terraform Agent: A local agent installed on a dedicated VM in your private data center as a bridge between Terraform Cloud and your BIG-IP Next instances. The Workflow: Define your Infrastructure in GitHub:Using the Terraform resources documented athttps://clouddocs.f5.com/products/orchestration/terraform/latest/BIG-IP-Next/big-ip-next-index.html#release-notes, you describe your desired BIG-IP Next configuration in code (e.g., creating virtual servers, pools, monitors, and other application services). Store your Terraform code in a GitHub repository. Configure Terraform Cloud: Set up a workspace in Terraform Cloud and link it to your GitHub repository. Configure a VCS trigger to automatically initiate a Terraform plan and apply it when changes are made to your code in GitHub. Install and Configure Terraform Agent: Set up a VM in your private data center, run Ubuntu, and install the Terraform Agent. Configure the agent to connect to your Terraform Cloud workspace. Automatic Configuration: When you push changes to your Terraform code in GitHub, Terraform Cloud detects the update, triggers a Terraform plan, and sends it to the Terraform Agent. The agent then communicates with your BIG-IP Next Central Manager, to implement the necessary changes to your BIG-IP Next instances. Benefits: Simplified Management: No more manual configuration and tedious updates! Terraform Cloud automates deployment, reducing errors and ensuring consistency across your BIG-IP Next environment. Increased Efficiency: Spend less time on repetitive tasks and focus on building and deploying applications faster. Collaboration and Version Control:Work collaboratively with your team, track changes, and easily revert to previous configurations using GitHub's robust version control capabilities. Scalability and Flexibility:Terraform Cloud seamlessly scales to manage large and complex environments, providing flexibility and adaptability for your growing needs. Getting Started: Set up GitHub Repository: Create a repository in GitHub and store your Terraform configuration files there. You can clone the GitHub repository from https://github.com/f5bdscs/example-AS3.git and begin working on it. terraform { required_providers { bigipnext = { source = "F5Networks/bigipnext" version = "1.2.0" } } cloud { organization = "39nX-example" workspaces { name = "39nX-example" } } } variable "host" {} variable "username" {} variable "password" {} provider "bigipnext" { username = var.username password = var.password host = var.host } resource "bigipnext_cm_as3_deploy" "test" { target_address = "10.1.1.10" as3_json = file("as3.json") } Explanation: Terraform Block: Defines the required provider bigipnext with source and version. Specifies cloud organization and workspace name. Variable Declarations: host, username, and password are declared as input variables. Provider Configuration: Uses the input variables for username, password, and host. Resource Definition: bigipnext_cm_as3_deploy resource with target_address and as3_json file. Make sure to create and populate the as3.json file with the necessary AS3 declarations. Also, ensure you provide values for host, username, and password when running the Terraform commands. { "class": "ADC", "schemaVersion": "3.45.0", "id": "example-declaration-01", "label": "Sample 1", "remark": "Simple HTTP application with round robin pool", "next-cm-tenant01": { "class": "Tenant", "EXAMPLE_APP": { "class": "Application", "template": "http", "serviceMain": { "class": "Service_HTTP", "virtualAddresses": [ "10.1.20.10" ], "pool": "next-cm-pool01" }, "next-cm-pool01": { "class": "Pool", "monitors": [ "http" ], "members": [ { "servicePort": 8080, "serverAddresses": [ "10.1.20.4" ] } ] } } } } Configure Terraform Cloud:Create a workspace, link it to your GitHub repository, and set up a VCS trigger to activate plans and apply changes. Please follow the guide at https://developer.hashicorp.com/terraform/tutorials/cloud-get-started/cloud-vcs-changeto integrate Terraform Cloud with your GitHub repository. Install and Configure Terraform Agent:Set up a VM in your private data center, install the Terraform Agent, and configure it to connect to your Terraform Cloud workspace. Please follow the guide at https://developer.hashicorp.com/terraform/tutorials/cloud/cloud-agents to install Terraform Cloud agent Deploy your configuration: Push your code to GitHub and watch as Terraform Cloud automatically updates your BIG-IP Next instances. You can watch the Demonstration Video here https://youtu.be/0xEtj-jAepEUsing BIG-IP GTM to Integrate with Amazon Web Services
This is the latest in a series of DNS articles that I've been writing over the past couple of months. This article is taken from a fantastic solution that Joe Cassidy developed. So, thanks to Joe for developing this solution, and thanks for the opportunity to write about it here on DevCentral. As a quick reminder, my first six articles are: Let's Talk DNS on DevCentral DNS The F5 Way: A Paradigm Shift DNS Express and Zone Transfers The BIG-IP GTM: Configuring DNSSEC DNS on the BIG-IP: IPv6 to IPv4 Translation DNS Caching The Scenario Let's say you are an F5 customer who has external GTMs and LTMs in your environment, but you are not leveraging them for your main website (example.com). Your website is a zone sitting on your windows DNS servers in your DMZ that round robin load balance to some backend webservers. You've heard all about the benefits of the cloud (and rightfully so), and you want to move your web content to the Amazon Cloud. Nice choice! As you were making the move to Amazon, you were given instructions by Amazon to just CNAME your domain to two unique Amazon Elastic Load Balanced (ELB) domains. Amazon’s requests were not feasible for a few reasons...one of which is that it breaks the RFC. So, you engage in a series of architecture meetings to figure all this stuff out. Amazon told your Active Directory/DNS team to CNAME www.example.com and example.com to two AWS clusters: us-east.elb.amazonaws.com and us-west.elb.amazonaws.com. You couldn't use Microsoft DNS to perform a basic CNAME of these records because of the BIND limitation of CNAME'ing a single A record to multiple aliases. Additionally, you couldn't point to IPs because Amazon said they will be using dynamic IPs for your platform. So, what to do, right? The Solution The good news is that you can use the functionality and flexibility of your F5 technology to easily solve this problem. Here are a few steps that will guide you through this specific scenario: Redirect requests for http://example.com to http://www.example.com and apply it to your Virtual Server (1.2.3.4:80). You can redirect using HTTP Class profiles (v11.3 and prior) or using a policy with Centralized Policy Matching (v11.4 and newer) or you can always write an iRule to redirect! Make www.example.com a CNAME record to example.lb.example.com; where *.lb.example.com is a sub-delegated zone of example.com that resides on your BIG-IP GTM. Create a global traffic pool “aws_us_east” that contains no members but rather a CNAME to us-east.elb.amazonaws.com. Create another global traffic pool “aws_us_west” that contains no members but rather a CNAME to us-west.elb.amazonaws.com. The following screenshot shows the details of creating the global traffic pools (using v11.5). Notice you have to select the "Advanced" configuration to add the CNAME. Create a global traffic Wide IP example.lb.example.com with two pool members “aws_us_east” and “aws_us_west”. The following screenshot shows the details. Create two global traffic regions: “eastern” and “western”. The screenshot below shows the details of creating the traffic regions. Create global traffic topology records using "Request Source: Region is eastern" and "Destination Pool is aws_us_east". Repeat this for the western region using the aws_us_west pool. The screenshot below shows the details of creating these records. Modify Pool settings under Wide IP www.example.com to use "Topology" as load balancing method. See the screenshot below for details. How it all works... Here's the flow of events that take place as a user types in the web address and ultimately receives the correct IP address. External client types http://example.com into their web browser Internet DNS resolution takes place and maps example.com to your Virtual Server address: IN A 1.2.3.4 An HTTP request is directed to 1.2.3.4:80 Your LTM checks for a profile, the HTTP profile is enabled, the redirect request is applied, and redirect user request with 301 response code is executed External client receives 301 response code and their browser makes a new request to http://www.example.com Internet DNS resolution takes place and maps www.example.com to IN CNAME example.lb.example.com Internet DNS resolution continues mapping example.lb.example.com to your GTM configured Wide IP The Wide IP load balances the request to one of the pools based on the configured logic: Round Robin, Global Availability, Topology or Ratio (we chose "Topology" for our solution) The GTM-configured pool contains a CNAME to either us_east or us_west AWS data centers Internet DNS resolution takes place mapping the request to the ELB hostname (i.e. us-west.elb.amazonaws.com) and gives two A records External client http request is mapped to one of the returned IP addresses And, there you have it. With this solution, you can integrate AWS using your existing LTM and GTM technology! I hope this helps, and I hope you can implement this and other solutions using all the flexibility and power of your F5 technology.F5 BIG-IP deployment with Red Hat OpenShift - keeping client IP addresses and egress flows
Controlling the egress traffic in OpenShift allows to use the BIG-IPfor several use cases: Keeping the source IP of the ingress clients Providing highly scalable SNAT for egress flows Providing security functionalities for egress flowsBIG-IP Next Central Manager API with Postman
In my last article I dove into the Central Manager AS3 endpoints with thecURL command. As I was preparing for this one, I thought it would work better as a live stream than a traditional article. Here's the stream you can watch in the replay, and the resources I mentioned on the stream are posted below. Show description: I've been working with the BIG-IP Next API from the API reference and with curl on the command line, and I gotta tell you, as much as I don't love Postman, it's super handy when learning an API. In this episode of DevCentral Connects, I'll download the collection from the Next documentation, get the environment variables set up, and walk through some of the tasks available in the collection to start working with the BIG-IP Next API. Resources BIG-IP Next Articles on DevCentral BIG-IP Next Academy group on DevCentral Embracing AS3: Foundations BIG-IP Next automation: AS3 basics BIG-IP Next automation: Working with the AS3 endpoints 20.0 Postman collection 20.1 Postman collection 20.2 Postman collection
