Archive for 29th February 2016

Amazon AWS Tips and Gotchas – Part 2 – AWS EBS & RDS MS SQL

Continuing in this series of blog posts taking a bit of a “warts and all” view of a few Amazon AWS features, below are a handful more tips and gotchas when designing and implementing solutions on Amazon AWS, including EBS and MS SQL on RDS.

For the first post in this series with a bit of background on where it all originated from, see here:
http://tekhead.it/blog/2016/02/amazon-aws-tips-and-gotchas-part-1/

For more posts in this series, see here:
Index of AWS Tips and Gotchas

AWS Tips and Gotchas – Part 2 – EBS & RDS
  1. You cannot increase the size of EBS volumes without stopping the instance. If you are designing scale-out / high availability solution then this is not a big issue as you should be able to take some downtime on any individual node, but that downtime is going to be fairly significant, and the larger the volume, the more downtime you will incur. The actual process looks like this (summary below):
    • Stop the instance
    • Snapshot the volume
    • Create a new volume from the snapshot, with your new larger size
    • Detach the old volume
    • Attach the new volume and start the instance back up

    This is one of those features which is bread and butter for a vSphere or Hyper-V admin, and could be done online in seconds with the vast majority of guest operating systems.

    I think it really highlights the key difference between designing for AWS Cloud, and a traditional enterprise virtual infrastructure. In a solution where most of your hosts are ephemeral, this should not be a big issue. If you try to take a traditional enterprise approach, you may find yourself in hot water, having to take service downtime to make simple changes.

    I suggest where possible / appropriate, avoid using EBS and use alternative options such as S3 which can scale on demand.

  2. Similar to resizing EBS volumes, you cannot hot-resize an instance, or indeed resize them / change their type in place. In order to change instance type you need to detach any EBS volumes (including root volumes if you wish to maintain them too), terminate the instance, create a new one and re-attach your volumes.
    Obviously you cannot re-attach a root volume if you are using instance storage (ephemeral) for this, so make sure you use EBS backed volumes if you want to maintain your root volumes for any scale-up elements of your solutions which cannot simply be re-created from a bootstrap script.
  3. If your application depends on Microsoft SQL, you are going to be in for a fairly unpleasant surprise! It is not currently possible to resize MS SQL volumes on Amazon RDS once they have been deployed! At all. Full stop. Nada.AWS MS SQL - say what nowThe recommendation from AWS is to deploy your estimated future capacity requirement from day one! Not very cloudy at all…Your only growth option when you hit your initial capacity limit is to migrate all the data to a new RDS instance and take some application downtime to fail over.This can be minimised by using things like log shipping from the source instance to get the target as close to up-to-date as possible, but you will still need to shut down and swing your applications, and frankly it’s a risky headache which would be better avoided if possible, and certainly not something you want to be doing on a regular basis.Probably best to design for your estimated growth, and add a percentage on top.

Find more posts in this series here:
Index of AWS Tips and Gotchas

Amazon AWS Tips and Gotchas – Part 3 – S3, Tags and ASG

Domain Migration to http://tekhead.it is Now Complete!

Tekhead Logo

This is just an uber quick reminder that as per my previous post, I have now updated the domain for the blog from http://www.tekhead.org to http://tekhead.it.

The changes went live tonight (27/02/2016) around midnight, and all previous blog paths are now 301 redirected to the equivalent address on the new site. Hopefully I won’t lose too much Google juice with the new address!

So, if you have any difficulties whatsoever accessing paths or content, please let me know via Twitter, and I would be very grateful!

Amazon AWS Tips and Gotchas – Part 1 – AWS Intro, EBS and EC2

Although I have been very much aware of AWS for many years and understood it at a high level, I have never had the time to get deep down and dirty with the AWS platform… that is until now!

I have spent the past three weeks immersing myself in AWS via the most excellent ACloud.Guru Solution Architect Associate training course, followed by a one week intensive AWS instructor-led class from QA on AWS SA Associate and Professional.

While the 100 hours or so I have spent labbing and interacting with AWS is certainly not 10,000, it has given me some valuable insights on both how absolutely AWSome (sorry – had to be done!) the platform is, as well as experiencing a few eye openers which I felt were worth sharing.

It would be very easy for me to extoll the virtues of AWS, but I don’t think there would be much benefit to that. Everyone knows it is a great platform (but maybe I’ll do it later anyway)! In the meantime, I thought it would be worthwhile taking a bit more of a “warts and all” view of a few features. Hopefully, this will avoid others stepping into the potential traps which have come up directly or indirectly through my recent training materials, as well as being a memory aid to myself!

pretty cloud AWS EC2 EBS

The key thing is with all of these “gotchas”, they are not irreparable, and can generally be worked around by tweaking your infrastructure design. In addition, with the rate that AWS develop and update features on their platforms, it is likely that many of them will improve over the coming months / years anyway.

The general feeling around many of these “features” is that AWS are indirectly and gently encouraging you to avoid building your solutions on EC2 and other IaaS services, Instead, pushing you more towards using their more managed services such as RDS, Lambda, Elastic Beanstalk etc.

This did originally start off as a single “Top 10” post but realised quickly that there are a lot more than 10 items and some of them are pretty deep dive! As such, I have split the content into easily consumable chunks, with a few lightweight ones to get us started… keep your eyes open for a few whoppers later in the series!

The full list of posts will be available here:
Index of AWS Tips and Gotchas

AWS Tips and Gotchas – Part 1
  1. Storage for any single instance may not exceed 20,000 IOPS and 320MB/sec per EBS volume. This is really only something which will impact very significant workloads. The current “recommended” workaround for this is to do some pretty scary things such as in-guest RAID / striping!

    Doing this with RAID0 means you then immediately risk loss of the entire datastore if a single EBS volume in the set goes offline for even a few seconds. Alternatively, you can buy twice as much storage and waste compute resources doing RAID calculations. In addition, you then have to do some really kludgy things to get consistent snapshots from your volume, such as taking your service offline. 
    In reality, only the most extreme workloads hit this kind of scale up. The real answer (which is probably better in the long term) is to refactor your application or database for scale-out, a far more cloudy design.
    amazon AWS EBS
  2. The internet gateway service does not provide a native method for capping of outbound bandwidth. It doesn’t take a genius to work out that when outbound bandwidth is chargeable, you could walk away with a pretty significant bandwidth bill should something decide to attack your platform with a high volume of traffic. One potential method to work around this would be to use NAT instances. You can then control the bandwidth using 3rd party software in the NAT instance OS.
  3. There is no SLA for EC2 instances unless you run them across multiple Availability Zones. Of course with typical RTTs of a few milliseconds at most, there is very little reason not to stretch your solutions across multiple AZs. The only time you might keep in one AZ is if you have highly latency sensitive applications, or potentially the type of app which requires a serialised string of DB queries to generate a response to the end user.

    In a way I actually quite like this SLA requirement as it pushes customers who might otherwise have accepted the risk of a single DC, into designing something more robust and accepting the (often minor) additional costs. With the use of Auto Scaling and Elastic Load Balancing there is often no reason you can’t have a very highly available application split across two or more AZs, whilst using roughly the same number of servers as a single site solution.

    For example the following solution would be resilient to a single AZ failure, whilst using no more infrastructure than a typical resilient on-premises single site solution:Teahead AWS Simple HA Web Configuration
    No DR replication required, no crazy metro clustering setup, nothing; just a cost effective, scalable, highly resilient and simple setup capable of withstanding the loss of an entire data centre (though not a region, obviously).

Find more posts in this series here:
Index of AWS Tips and Gotchas

Amazon AWS Tips and Gotchas – Part 2 – AWS EBS & RDS MS SQL

 

Docker Part 3 – HOWTO Create a Simple Python Web App in Docker

Docker Logo

If you’ve been following this series (last part here), we now have docker installed, but what do we do next? Create our first containers of course!

I think we need to make it a bit more interesting though as just creating containers is a bit meaningless, in real life we’re actually going to do something with them. The scenario is that we want a few copies of our simple python web application. To achieve this we need to use a few simple docker commands:

  • Create a new container
  • Install an application inside of it
  • Store it as an image
  • Duplicate it more than once and make these available to other clients
  • Test each instance to ensure they are unique and accessible

The good thing here is that all of the above steps are repeatable with whatever application you wish to install inside your containers. This is just a simple way to help get your head around the concepts and commands.

We start by creating our first empty Ubuntu container. The –i connects us to the shell of the container (interactive).

$ sudo docker run -i -t --name="firstcontainer" ubuntu:14.04 /bin/bash


Then in this case we need to install the python and web.py dependencies INSIDE of the container. This could be modified for any required dependencies or apps.

$ apt-get update
$ apt-get install -y python python-webpy


Within the container, create a new python script:

$ sudo mkdir /home/test1
$ sudo vi /home/test1/app.py


The contents of the script are:

#!/usr/bin/python
import web,sys
urls = (
 '/', 'index'
 )
app = web.application(urls, globals())
class index:
 def GET(self):
 argumentone = sys.argv[2]
 greeting = "Hello World, the test message is " + argumentone
 return greeting
if __name__ == '__main__' :
 app = web.application(urls, globals())
 app.run()


Exit the container, back to the Native OS:

$ exit


Confirm the name of your container (the last container run):

$ sudo docker ps –l
 CONTAINER ID IMAGE COMMAND CREATED STATUS PORTS NAMES
 f711ff0fd695 ubuntu:14.04 /bin/bash 32 minutes ago Exit 0 firstcontainer


Create a new image from your docker called testpython1

$ sudo docker commit firstcontainer testpython:0.1


Confirm you can see the image and get the image ID:

$ sudo docker images
 REPOSITORY TAG IMAGE ID CREATED VIRTUAL SIZE
 testpython 0.1 fcb365f7591b 2 minutes ago 247.8 MB


Finally, start up 3 instances of your web application:

$ sudo docker run -d -p 8081:8081 fcb365f7591b python /home/test1/app.py 8081 "instance1"
$ sudo docker run -d -p 8082:8082 fcb365f7591b python /home/test1/app.py 8082 "instance2"
$ sudo docker run -d -p 8083:8083 fcb365f7591b python /home/test1/app.py 8083 "instance3"


Open a browser on your network and connect to http://dockerserverip:8081
Try the same for the other two port numbers. Note we now have a system running 3 separate containers which could then be load balanced using a third party tool, or even run completely different content. Cool huh?

Next, how to mount a drive into your container…

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