Friday, 22 September 2017

A PRTG Sensor for the Pure Storage FlashArray






 


Why A PRTG Sensor?


I was in a meeting with a good customer of Pure Storage when I noticed that their operational panel on the floor was showing a PRTG dashboard. The PRTG Network Monitor tool from Paessler is a very nice agentless monitoring solution that is able to utilise a wide range of methods to monitor any accessible system or application on your network. It is a Windows based solution but supports all required methods to gain remote insights into your services such as SNMP, SSH, Scripts, REST, WMI, packaet sniffing, etc.


I am familiar with PRTG as I use it at home to monitor my home network and various components. This is possible due to the fact that you can run 100 sensors on a free license. The wonderful world of home automation and online media have made my network as critical to my household as it is for corporatations own services. Plus it is also fun to work with solutions like this, not to mention that it provides some interesting insights into your home network when combined with a Ubiquiti setup. 

Anyway back to the task in hand, I thought that looking at how we could monitor Pure FlashArray's with PRTG could both help me to familiarise myself with the Purity API. It turns out we do have a couple of options at the Pure OpenSource community Pure/Code within the  Python and PowerShell script packs written by some clever dudes in Pure (nod to Barkz). The only consideration for these was that they are focused on the array level performance metrics, where I wanted to see what else we can keep an eye on. Also, as a new Pure employee, as stated prior, it also gives me the chance to work with the Restful API of Purity.

I can say that writing this sensor was a bit of fun and the Restful API of Purity has to be one of the most logical I have worked with. Very simple in structure, versioned to allow for supportability across a range of Purity versions, and a rich capability around those supporting actions such as filtering. It took no time at all to get comfortable with the structure, limits were only my own and those discovered within PRTG.




video



So What Does It Do?

I wanted to provide a good overview of the current operational health of the arrays monitored while ensuring that the reporting was not overly complicated. As a first release my focus is on array level conditions covering:
  • Array capacity status
  • Array performance metrics
  • General hardware status of Controllers, Shelves and Chassis
  • General drive health
Array object sensor summary page
I have plans to add further granularity to cover 'volume performance', 'host performance' and 'protection compliance' in upcoming releases, but with the current method there is a limit of 50 channels to one sensor so still determining the best way to meet the number of instances required to monitor at that level and how to cater for lifecycle of objects that are subjected to CRUD operations (well create, update, delete anyway.

With the current script, the sensor reads the metrics from the array via a PowerShell script that directly queries each arrays Restful API. Although there is only a single script, it supports the multiple sensors through the 'Scope' parameter provided within the arguments section of each sensor (more details in installation instructions).

Each sensor can contain one or more channels, a channel can be thought of as a single value aligned to the sensor such as 'capacity consumed' within the 'capacity' sensor. Then as appropriate limits are assigned to the channel that define the thresholds that a channels value goes either above (maxlimit) or under (minlimit) to raise a warning or error condition for the sensor. Some channels have explicit limits set such as those related to capacity and health but others, such as the performance metrics, are left to self determine when an exceptional condition occurs based on operational patterns already recorded. For example latency may stay steady under a millisecond for normal operations but if suddenly it increases to 20 milliseconds for multiple recordings, PRTG will determine this to be an exception and raise a warning condition.

Array capacity sensor

Because each channel needs to provide a value that supports numeric comparisons to determine if limits are met, textual values returned from the array had to be converted to a representative numeric value. The textual values such as for Hardware components status to be reported as 'healthy', is enabled through the use of lookup tables included in the pack. Currently there are two included which provide lookup values for the channels in the 'Drive Health' and 'Hardware Health' sensor status values

Array Hardware Sensor
Where the Array performance and capacity sensors provide a collection of metrics related to the sensors scope of the whole array, the health sensor for hardware provides summary graphs for each major component (Chassis, Controller, Shelf) and for the Drive Health sensor, a status for each drive.

Hardware Health Sensor


For the Hardware Health sensor, summary values were required as reporting each individual hardware component that can be monitored exceeds the 50 channel to a sensor limit (not enforced but supportability and reliability can be compromised). I open to looking at alternative methods that can allow for all components to be individually reported in the future.


Drive Health Sensor


Installation


Requirements

  • First, get the scripts and associated lookup files from GitHub at Pure Storage Sensor Module. This will provide a Zip file of the required files but you can also download it directly from the GHitHub site  at 'https://github.com/davlloyd/purestorage-prtg' 
    • This set contains 4 files including:
      • Get-PureFA-Sensor.ps1 - The main PowerShell script
      • prtg.standardlookups.purestorage.drivestatus.ovl - Drive status lookup file
      • prtg.standardlookups.purestorage.hardwarestatus.ovl - Hardware status lookup file
      • readme.md - Markdown file with Installation instructions 
    • The Powershell script and lookup files need to be copied onto the PRTG server and then associated sensors created accordingly.
  • Ensure the PRTG server (or PRTG probe if running sensor from a probe)is running PowerShell 4.0

Script Installation

  1. Copy the script Get-PureFA-Sensor.ps1 to the directory 'C:\Program Files (x86)\PRTG Network Monitor\Custom Sensors\EXEXML' 
  2. Copy the two lookup files prtg.standardlookups.purestorage.drivestatus.ovl and prtg.standardlookups.purestorage.hardwarestatus.ovl to the directory 'C:\Program Files (x86)\PRTG Network Monitor\lookups\custom'
  3. Restart the Windows service 'PRTG Core Server Service'. This step is required to have PRTG read in the new custom lookup files

Sensor Creation


  1. Create a new device in PRTG with the address (IP or FQDN of the FlashArray you want to monitor
  2. Now, select <Add Sensor>. On the search field, type "Script Advanced" and then select the sensor type <EXE/Script Advanced Sensor> from the result list. 
  3. On the Add Sensor to Device screen, enter the following: 
    1. The sensor's name and tags (optional): There are currently four sensors to create. I have been naming them as follows:
      1. Capacity
      2. Performance
      3. Drive Health
      4. Hardware Health
    2. Under Exe/Script, use the Drop-down to select the script 'Get-PureFA-Sensor.ps1' from the list.
    3. Set the parameters for Array access and sensor scope as follows
      1. [ArrayAddress] (use the PRTG variable '%host' to inherit from device entry
      2. Either of the following combinations for security authentication:
        1. [username] and [password]  - This is ok for testing purposes but as password is stored in clear text not recommended for production. This will generate or read the APIKey for the account
        2. [apikey] - preferred access method. The APIKey is generated from within the Purity Console for the preferred account. You do not need to enter account details if specifying an APIKey
      3. [Scope] to set what is monitored for this sensor. Scope option values are:
        • capacity
        • performance
        • hardware
        • drive
      4. By default the sensors will be run every 60 seconds, adjust accordingly. You can get a view of time for execution by running the scripts in debug mode but ensure that it is disabled when running the script as a sensor.
-arrayaddress '%host' -scope 'hardware' -apikey '3bdf3b60-f0c0-fa8a-83c1-b794ba8f562c'
Sensor Setup

You are now ready to go. For a look at how to set a sensor up watch the video on this blog.



Sensor Screen

Performance Chart








Tuesday, 24 May 2016

VMware Photon Platform, Notes from the Field - Entry Two

Time to Build The Cluster Services

Is it a bird,  plane or the Photon Platform? In the early days of Photon Platforms announcements, in my own mind, I had it pegged as a purpose built platform alternative to 'vSphere Integrated Containers (VIC)'. Keeping in mind that VICs sole purpose in life is to enable Containers in vSphere with a cool concept of a 1:1 alignment of VM to Container. This meant a container can have all the flexibility inherent in a container with all the control and security of a VM. Alright come on down Photon Platform just bigger, better more focused right? Well not really....

So one thing that strikes you with the Photon Platform is the flexibility of choices it provides. From a scheduling cluster manager's perspective you can utilise Swarm, Kubernetes or Mesos out of the box. On the other side, this is ESXi after all (marketing slides aside that keep alluding to the slimmed down hypervisor) so it will happily run Virtual Machines  and Containers side by side (well containers within VMs anyway).

Being able to support both is important as not all workloads are created equal in this new age. Let's be honest, not everyone working in this new 'Cloud Native' world has grown a beard, rides a bicycle and wears skinny jeans, there is a variety of personalities that need to be catered for. What is common is we don't all need the assurance and crutches that come from the more traditional platforms. If I fall over it is ok, I will just get myself back up. In the traditional world I would have crutches, cushions, people watching me, ready to catch me if a stumble, etc. This is because in this traditional world I am seen as needed to be treated like a VIP (i.e. Very Important Process) and require all the care of advanced services to keep me going (and the costs associated with those advanced services). Sometimes a more traditional approach may be preferable to containerising (is that a word?) the workload so Virtual Machines live on even if they are seen as cattle (I'll let Duncan Epping define that for you).



This mixed capability is emphasised by the fact that all the management VMs are hosted out of the hypervisors that are flagged as Management hosts (you designate if a host is 'Management' so participates in the control plane or 'Cloud' which only provide a hosting platform capacity, or both). Anyway myself for one, I'm a big fan as by including the ability to host containers and VMs as this provides that flexible, cost and scale focused platform I want without having to look at alternatives such as Openstack. Add to this the fact that it also includes support for the 3 main container and workload cluster scheduling services out of the box and your covering a lot of bases for possible consumers of Photon Platform.

My personal choice is to go forward with Mesos at this stage as it gives me the open choices I want when paired with Marathon. I have played with all three though on Photon as all it takes is that you import the 3 images and enabled the 3 cluster types. I am not here to tell you how to do this or how to create a cluster as there are plenty of blogs that do that, I just want to give my view and some lessons I learnt on the way that may help someone out there. 

It is important to note that when creating clusters, they align to there traditional model and not some Hybrid like in VIC. What I mean by that is that if you create a Docker Swarm cluster, the slave nodes will be running the containers in a shared multi-node format. The nodes are utilising PhotonOS as there Operating System but we don't have the 1:1 Container to VM alignment of VIC. This is important to consider as your sizing of those nodes should reflect your needs. There are default 'Flavors' (remember Flavors define the resource configuration profiles) aligned to the different clusters but they can be overwritten at the API, CLI level when creating a cluster.

This system is built as a multi-tenant service from the ground up so when you create workloads they need to be placed within a Project assigned to a Tenant. As you would expect, a Tenant gets an allotment of Resources (vCPUS, memory, Disk Capacity, VMs, etc) which are then subdivided into Resource Tickets (think Gold , Silver Bronze classes or whatever). A Project is then assigned a Resource Ticket which it then further carves out a resource reservation /limit out of. All the way down this logical structure you can add Access Controls via the integration with VMware Lightwave



So importantly as a tenant, I can create my own cluster service to host workloads or just create VMs directly based on virtual appliances or virtual disks imported into the system.  I can then control my VM workloads via the CLI and API into Photon Platforms Controller VM as you would of normally via vCenter, or use the cluster manager of choice to control the workloads within them.

As a final statement on the installation of the clusters what I can say is this. I have built all 3 flavours using simple sandbox methods as well as going through the full manual processes (more then once as I like punishment) and there is a highly compelling value proposition here. To be able to create these services as you require them  on a production class platform so simply is huge. There will be challenges with the way it is done now such as how do they stay close to release parity (hence the compelling part of it being Open Source), but this is a new era platform that brings together the traditional on-premise controls to the new cloud native era's service requirements in the one stack. This is great stuff for a version 0.8 release!

Some Notes On Cluster Enablement:


Be Wary Of Resource Stinginess
My nature is to give less then more when allocating resources. This sent my on a dance to the requirements of the various clusters as I did not have enough resources aligned to my Project.  Just be aware of the sizing needs (they vary of course depending on your own configuration requirements) and if you are resource constrained, use custom 'Flavors'. I prefer to bang my head on the wall so got very use to the 'Photon Cluster Create' operation being closely followed by the 'Photon Cluster Delete' operation to delete the failure and started again (side note, it didn't like me trying to recreate deleted clusters with the same name, didn't ping this down but got into the habit of using unique names each attempt) :)

Cluster Creation IP Address Requirements
Within the instructions it is emphasised that DHCP needs to be disabled / not present in the management network which is where the clusters are installed. Ironically, if DHCP is disabled the cluster deployment fails with a 'Unable to Obtain an IP Address' error. To progress forward I re-enabled DHCP in the management network (the one that the Photon Controller is installed into). The more accurate requirement description is to ensure the static IP addresses you provide (i.e. for the 'zookeeper' servers in Mesos and 'etcd' servers in Kubernetes and Swarm) are not also served within the active DHCP scopes.

Those Damn Certificates
Maybe you lucky that your company provides an open network and all traffic is created equal. That is not the case in mine, we trust no-one and inject ourselves into every certificate coming into the network. Any problems with this is mitigated by adding our own certificates into the trusted root but this is difficult for those environments that are created dynamically as these clusters are.

When you create a cluster PhotonOS based VMs are created corresponding to your configurations requirements (i.e. how many slaves, how many provide the interconnect service) and are then configured by templates contained on the Controller. Where the certificates being trusted becomes critical is the fact that the services run as containers within the VMs and as such the images need to be downloaded as part of the initial execution. The end result is the cluster creation operations fail with 'Time Exceeded' errors.

Anyway its an easy fix! I edited the template files contained in the controller directory '/usr/lib/esxcloud/deployer/scripts/clusters' with descriptive names such as 'kubernetes-master-user-data-template' to inject our certificates into the VMs. This at least made that problem go away and you of course could do this to apply any other customisations that may be required. It would be nice to see some option in the future to inject certificates into the process. I also provided this same feedback for 'vSphere Integrated Containers' as had the same problem there!




Sunday, 22 May 2016

VMware Photon Platform, Notes from the Field - Entry One

First, some overview ramblings:


Ok, first of all let me say this, I am excited about the changing landscape in the industry. This shift to containerisation is exciting to me in two ways. Firstly, as an automation focused engineer, this just seems like the natural progression / evolution of the current platform (incoming alert, Unikernels). Secondly, the technology landscape is very exciting, lots of new tools (or is that toys) to play with!



That said I have been fortunate to be working with VMware (shout out to Roman Tarnavski @romant) for a while now on their rapidly evolving 'Cloud Native' program. With this a couple of recent announcements have there two primary offerings 'vSphere Integrated Containers' and 'Photon Platform' are both now Opensource on github so now everyone can have a go. A key point of differentiation between the two is that VIC leverages your existing VMware vSphere platform to host container centric workloads on a 1:1 basis on a Virtual Machine, the other, Photon Controller still leverages ESXi (today anyway) but has it's own control plane.

Photon Controller is a replacement to vCenter focused on the operational requirements of the container workloads, not virtual machines. Why you may ask? An easy way to think about it is the rate of change and scale that us usually associated with a container aligned environment versus the long term service life and different scale models associated with traditional Virtual Machines drives a different model. 

If you are all in for containers, or alternatively, have a substantial container footprint today (or will soon) you have some considerations when assessing VIC versus Photon Platform:

  • Will you be limited by the sizing maximums of vSphere. Think vCenter, is 10,000 VMs enough when 1 VM equals 1 container how about the change rate of those VMs.
  • You also may be questioning the commercials around vSphere in a container world, do you really need those advanced availability services (e.g. HA/DRS) in a container world. I would say no, the idea of containers is pretty simple, let them scale out and have availability controls north of the service such as with NLB (I know it is an over simplification) or south with stateful data services (should be scale out themselves but that is for another day).

Neither of these statements cover the why VMware anyway? Isn't this new world order a shift away from the vendors we typically associated with infrastructure, doesn't the consumer in this new world not care about infrastructure? All I would say there is that there is a world of difference between developing in a sandbox environment and having your workload run in a production class platform with all the controls, monitoring and reporting thats in place within organisations today for traditional workloads. I also do a lot of testing in the Cloud and directly on my laptop, tat is the beauty of containers, you can just shift around. But for it to go production, there are certain requirements that a lot of organisations need to comply to. This may be due to regulatory demands, data sovereignty requirements, cost controls, to name a few.  

The idea of either offering is to be able to provide the application developers, operator, <insert whoever else here> the same user experience, with the same toolsets but aimed at a different platform. This platform then is able to have the same operators (VMware Admins) look after it in the same / similar way that they do there vSphere environment. Everyone wins :)

Anyway, next I will look at the install and configuration stage. There is some great content at github and by other bloggers such as William Lam. But I am finding some differences with my own experiences to what others have documented. 

Some quick notes:


Controller Install VIB Upload fail
I kept getting file upload errors when the installer tried to upload the Photon VIB to the Management ESX host (see these issues in the log /var/log/esxcloud/deployer/deployer.log) . I still have not isolated where the issue is and not been able to isolate it as yet in the source code. What I did do though is simplified my naming convections and the issue went away. I noticed all the blog samples where pushing into default bare ESX hosts where I aligned mine to my own pseudo naming standards. In the end I simplified my environment by taking hyphens out of my port group and datastore naming and was now able to install. 

YAML Install File with CLI
The examples provided and the exported file provide the 'image_datastores' field within the 'deployment' section as an array. I ended up getting errors around the conversion of the field to an array when attempting to deploy through the cli. This occurred regardless if I had or or more values assigned. As such changed the field to a straight string and it worked. Change shown below:



Uploading Images getting HTTP 413 Error
To enable management clusters (schedulers) you need to upload the corresponding dish images into the Controller (Mesos, Kubernetes or Swarm). I found that regardless of the image I was getting a NGINX error of 413 'Request Entity To Large'. You don't have to be a google ninja to identify the error quickly with the reported resolution to set the 'client_max_body_size' value in the 'nginx.conf' file.On the controller VM the NGINX service runs as docker container called 'ManagementUi' so it was easy to then pull the configuration file down with a 'docker cp' command to have a look, low and behold the setting is not there!

OK, now I have just a rat down he drainpipe I can say that I was on the wrong track. NGINX looks after the User Interface but not the API. Looking at the docker containers there is one running HAPROXY which is the loadbalancer service, called you guessed it 'LoadBalancer'. Jumping into this VM and looking att he file 'haproxy.cfg' you can see that the API is served by ports 28080 and 9000.  By switching the photon cli target to either these ports let the images upload successfully (e.g. photon target set http://10.63.251.150:9000).

I took the long way but got there in the end, time to start playing!!!