Your version may be slightly different but for my guests, to uninstall open-vm-tools I needed to run

rpm -e vmware-open-vm-tools-kmod-8.0.4-480973.sles11sp1.x86_64
rpm -e vmware-open-vm-tools-common-8.0.4-480973.sles11sp1.x86_64

in order, ie kmod needed to be removed prior to common.

It was now onto installing the official VMware Tools – which isnt as easy as with Windows guests.

VMware Tools has gcc and the kernel headers as a prerequisite, so the first step is to connect the installation DVD (eg SLES-11-SP1-DVD-x86_64-GM-DVD1.iso) to the guest via the vSphere console.

Mount to your standard location, if you are not sure the below command will create a mount point and mount the DVD in one go;

mkdir /mnt/cdrom && mount /dev/cdrom /mnt/cdrom

From there you can run yast;

yast2

and select Software, then Software Management;

Tab down to the Search Phrase and enter ‘gcc’. The tab over to the right side, highlight it press [ENTER] – this will select it to be installed;

Tab back to the Search Phrase and enter ‘kernel’. Tab over to the right side and highlight kernel-default-devel and press [ENTER] – this will select it and some dependencies to be installed;

Tab back around the page until you get to Accept and hit [ENTER]. You will be presented with a confirmation box, when happy press [ENTER];

Yast will now go ahead and install gcc and the kernel headers, with should only take a minute or so;

Once it is complete you can next / ok your way out and close yast. If you want you can confirm the installations via;

rpm -q gcc
rpm -q kernel-defaullt-dev

With prerequisites done its now onto VMware Tools. First unmount the installation DVD:

umount /mnt/cdrom

Via the vSphere console for that guest select VM, Install VMware Tools this will attach an ISO that has the installation files in it onto the the guest, but it wont mount it so enter;

mount /dev/cdrom /mnt/cdrom

There are two versions of the installation, and RPM package and a .tar.gz which needs to be compiled, which is the way I went. First, extract the .tar.gz into your temp folder via;

cp /mnt/cdrom/VMwareTools-*.tar.gz /tmp
cd /tmp
tar zxpf /mnt/cdrom/VMwareTools-*.tar.gz

After the extraction is complete, go to the created vmware-tools-distrib folder and run the installation script vmware-install.pl;

cd vmware-tools-distrib
/vmware-install.pl

Now its pretty much follow the prompts;

In which directory do you want to install the binary files?
[/usr/bin]

What is the directory that contains the init directories (rc0.d/ to rc6.d/)?
[/etc/init.d]

What is the directory that contains the init scripts?
[/etc/init.d]

In which directory do you want to install the daemon files?
[/usr/sbin]

In which directory do you want to install the library files?
[/usr/lib/vmware-tools]

The path "/usr/lib/vmware-tools" does not exist currently. This program is
going to create it, including needed parent directories. Is this what you want?
[yes]

In which directory do you want to install the documentation files?
[/usr/share/doc/vmware-tools]

The path "/usr/share/doc/vmware-tools" does not exist currently. This program
is going to create it, including needed parent directories. Is this what you
want? [yes]

The path "/usr/share/doc/vmware-tools" does not exist currently. This program
is going to create it, including needed parent directories. Is this what you
want? [yes]

The installation of VMware Tools for Linux completed
successfully. You can decide to remove this software from your system at any
time by invoking the following command: "/usr/bin/vmware-uninstall-tools.pl".

VMware Tools is installed, now it needs to be compiled against your machine (hence the gcc and header prerequisites. The installation will offer to kick this off for you;

Before running VMware Tools for the first time, you need to configure it by
invoking the following command: "/usr/bin/vmware-config-tools.pl". Do you want
this program to invoke the command for you now? [yes]

What is the location of the directory of C header files that match your running
kernel? [/lib/modules/2.6.32.12-0.7-default/build/include]

Stuff will happen;

Building the vmmemctl module.

Using 2.6.x kernel build system.
make: Entering directory `/tmp/vmware-config0/vmmemctl-only'
make -C /lib/modules/2.6.32.12-0.7-default/build/include/..
SUBDIRS=$PWD SRCROOT=$PWD/. \
         MODULEBUILDDIR= modules
make[1]: Entering directory `/usr/src/linux-2.6.32.12-0.7-obj/x86_64/default'
make -C ../../../linux-2.6.32.12-0.7
O=/usr/src/linux-2.6.32.12-0.7-obj/x86_64/default/. modules
...
...

and then it will ask

None of the pre-built vmhgfs modules for VMware Tools is suitable for your
running kernel.  Do you want this program to try to build the vmhgfs module for
your system (you need to have a C compiler installed on your system)? [yes]

There will be four of these for vmhgfs, vmxnet, vmblock and vmci – after confirming each there will be a blurb about the compiling process.

After vmci it prompts;

The communication service is used in addition to the standard communication
between the guest and the host.  The rest of the software provided by VMware
Tools is designed to work independently of this feature.
If you wish to have the VMCI feature, you can install the driver by running
vmware-config-tools.pl again after making sure that gcc, binutils, make and the
kernel sources for your running kernel are installed on your machine. These
packages are available on your distribution's installation CD.
[ Press Enter key to continue ]

After continuing you will be asked to confirm two more compiles for vmxnet3 then pvscsi, and then you pretty much done;

Creating a new initrd boot image for the kernel.

Kernel image:   /boot/vmlinuz-2.6.32.12-0.7-default
Initrd image:   /boot/initrd-2.6.32.12-0.7-default
Root device:    /dev/sda2 (mounted on / as ext3)
Resume device:  /dev/sda1
Kernel Modules: vmxnet hwmon thermal_sys thermal scsi_mod
scsi_transport_spi mptbase mptscsih mptspi libata ata_piix ata_generic
ide-core piix ide-pci-generic processor fan jbd mbcache ext3 edd
crc-t10dif sd_mod
Features:       block resume.userspace resume.kernel
Bootsplash:     SLES (800x600)
28276 blocks
No X install found.

  Checking acpi hot plug                                              done
Starting VMware Tools services in the virtual machine:
  Switching to guest configuration:                                   done
  Paravirtual SCSI module:                                            done
  Guest memory manager:                                               done
  Guest operating system daemon:                                      done

The configuration of VMware Tools for Linux for this running
kernel completed successfully.

You must restart your X session before any mouse or graphics changes take
effect.

You can now run VMware Tools by invoking the following command:
"/usr/bin/vmware-toolbox" during an X server session.

To enable advanced X features (e.g., guest resolution fit, drag and drop, and
file and text copy/paste), you will need to do one (or more) of the following:
1. Manually start /usr/bin/vmware-user
2. Log out and log back into your desktop session; and,
3. Restart your X session.

And that’s it – you’ve swapped out open-vm-tools for the official VMware Tools.

Well it appears Google have made another series of algorithm changes aimed at detecting these type of sites and reduce the ranking in the results.

In January Google announced the Page Layout Algorithm improvement stating;

…we’ve heard complaints from users that if they click on a result and it’s difficult to find the actual content, they aren’t happy with the experience. Rather than scrolling down the page past a slew of ads, users want to see content right away.

The claim given this adjustment, sites with high ads and low content above-the-fold “may not rank as highly going forward”.

Above-the-fold is typically recognized as the first 600pixels deep of a webpage, eg for my one of my pages;

This adjustment apparently detects pages with stacked ads / low content in this “first seen” part of the page. Google claim it won’t affect a lot of sites, but it does appear to be a warning.

There is some great information and research of the impact of Above the Fold by Jakob Nielsen in his post “Scrolling and Attention”. Of course there is the counter view, such as Paddy Donnelly’s “Life Below 600“.

In February Google announced a significant algorithm change known as Panda which by their own calculation affects nearly 12% of all queries. Initially applicable to US queries only, in April it was expanded to include all languages and aims to reduce the ranking of site of low quality, low value, copied content and sites “that are just not very useful”.

Typically not many specifics have been given, Google resist making too many statements to prevent reverse engineering, but it’s interesting to note in their April announcement it specifically gave the example of those hated hot word ads.

So some significant changes which are targeting some of the sites I mentioned in my Grumpy SEO post – I think the layout algorithm will be the most interesting to watch, as a number of sites, even popular ones have this type of design.

Yesterday I wrote about getting started with Google Analytics in C# to get a simple list of visits in the last 7 days;

The type of data you want all depends on the content of your data query, in that example

DataQuery PageViewQuery = new DataQuery(DataFeedUrl)
{
    Ids = ProfileID,
    Dimensions = "ga:date",
    Metrics = "ga:pageviews",
    Sort = "ga:date",
    GAStartDate = (DateTime.Now).AddDays(-7).ToString("yyyy-MM-dd"),
    GAEndDate = (DateTime.Now).ToString("yyyy-MM-dd")
};

I must admit I’m looking at stripping the entire data from Google Analytics to use in some ideas, so I thought I’d list some of the most common data query types to help any others looking to do something similar.

By the way – the output of any times (for instance ga:timeOnSite) I have left as the raw value of number of seconds. If you want to convert that to something more human readable you can user something like;

TimeSpan timeOnSite  = TimeSpan.FromSeconds(value);
Console.WriteLine(String.Format("{0}:{1}", timeOnSite.Hours, timeOnSite.Minutes));

Visits By Country

DataQuery dataquery = new DataQuery(DataFeedUrl)
{
    Ids = ProfileID,
    Dimensions = "ga:country",
    Metrics = "ga:visits",
    Sort = "-ga:visits",
    GAStartDate = (DateTime.Now).AddDays(-7).ToString("yyyy-MM-dd"),
    GAEndDate = (DateTime.Now).ToString("yyyy-MM-dd")
};
...
Console.WriteLine(String.Format("{0}\t{1}",
    Entry.Title.Text.Split('=')[1],
    Entry.Metrics[0].Value));

Visitors and Pageviews Over Time

DataQuery dataquery = new DataQuery(DataFeedUrl)
{
    Ids = ProfileID,
    Metrics = "ga:visits,ga:pageviews",
    Sort = "-ga:visits",
    GAStartDate = (DateTime.Now).AddDays(-7).ToString("yyyy-MM-dd"),
    GAEndDate = (DateTime.Now).ToString("yyyy-MM-dd")
};
...
Console.WriteLine(String.Format("Visits: {0}", Entry.Metrics[0].Value));
Console.WriteLine(String.Format("Pageviews: {0}", Entry.Metrics[1].Value));

New vs Returning Visits

DataQuery dataquery = new DataQuery(DataFeedUrl)
{
    Ids = ProfileID,
    Dimensions = "ga:visitorType",
    Metrics = "ga:visits",
    Sort = "ga:visits",
    GAStartDate = (DateTime.Now).AddDays(-7).ToString("yyyy-MM-dd"),
    GAEndDate = (DateTime.Now).ToString("yyyy-MM-dd")
};
...
Console.WriteLine(String.Format("{0}\t{1}",
    Entry.Title.Text.Split('=')[1],
    Entry.Metrics[0].Value));

Browser and Operating System

DataQuery dataquery = new DataQuery(DataFeedUrl)
{
    Ids = ProfileID,
    Dimensions = "ga:operatingSystem,ga:operatingSystemVersion,ga:browser,ga:browserVersion",
    Metrics = "ga:visits",
    Sort = "-ga:visits",
    GAStartDate = (DateTime.Now).AddDays(-7).ToString("yyyy-MM-dd"),
    GAEndDate = (DateTime.Now).ToString("yyyy-MM-dd")
};
...
Console.WriteLine(String.Format("{0}{1}using {2}{3}\t{4}",
    values[0].Split('=')[1], values[1].Split('=')[1],
    values[2].Split('=')[1], values[3].Split('=')[1],
    Entry.Metrics[0].Value));

Time on Site

DataQuery dataquery = new DataQuery(DataFeedUrl)
{
    Ids = ProfileID,
    Metrics = "ga:visits,ga:timeOnSite",
    GAStartDate = (DateTime.Now).AddDays(-7).ToString("yyyy-MM-dd"),
    GAEndDate = (DateTime.Now).ToString("yyyy-MM-dd")
};
...
Console.WriteLine(String.Format("\tVisits: {0}", Entry.Metrics[0].Value));
Console.WriteLine(String.Format("\tTimeOnSite: {0}", Entry.Metrics[1].Value));

Referring Sites

DataQuery dataquery = new DataQuery(DataFeedUrl)
{
    Ids = ProfileID,
    Dimensions = "ga:source",
    Metrics = "ga:pageviews,ga:timeOnSite,ga:exits",
    Filters = "ga:medium==referral",
    Sort = "-ga:pageviews",
    GAStartDate = (DateTime.Now).AddDays(-7).ToString("yyyy-MM-dd"),
    GAEndDate = (DateTime.Now).ToString("yyyy-MM-dd")
};
...
Console.WriteLine(Entry.Title.Text.Split('=')[1]);
Console.WriteLine(String.Format("\tPageViews: {0}", Entry.Metrics[0].Value));
Console.WriteLine(String.Format("\tTimeOnSite: {0}", Entry.Metrics[1].Value));
Console.WriteLine(String.Format("\texits: {0}", Entry.Metrics[1].Value));

Keywords

DataQuery dataquery = new DataQuery(DataFeedUrl)
{
    Ids = ProfileID,
    Dimensions = "ga:keyword",
    Metrics = "ga:visits",
    Sort = "-ga:visits",
    GAStartDate = (DateTime.Now).AddDays(-7).ToString("yyyy-MM-dd"),
    GAEndDate = (DateTime.Now).ToString("yyyy-MM-dd")
};
...
Console.WriteLine(String.Format("{0}\t{1}",
    Entry.Title.Text.Split('=')[1],
    Entry.Metrics[0].Value));

Search Engines

DataQuery dataquery = new DataQuery(DataFeedUrl)
{
    Ids = ProfileID,
    Dimensions = "ga:source",
    Metrics = "ga:pageviews,ga:timeOnSite,ga:exits",
    Filters = "ga:medium==cpa,ga:medium==cpc,ga:medium==cpm,ga:medium==cpp,ga:medium==cpv,ga:medium==organic,ga:medium==ppc",
    Sort = "-ga:pageviews",
    GAStartDate = (DateTime.Now).AddDays(-7).ToString("yyyy-MM-dd"),
    GAEndDate = (DateTime.Now).ToString("yyyy-MM-dd")
};
...
Console.WriteLine(Entry.Title.Text.Split('=')[1]);
Console.WriteLine(String.Format("\tPageViews: {0}", Entry.Metrics[0].Value));
Console.WriteLine(String.Format("\tTimeOnSite: {0}", Entry.Metrics[1].Value));
Console.WriteLine(String.Format("\texits: {0}", Entry.Metrics[1].Value));

Search Engines – Organic Search

DataQuery dataquery = new DataQuery(DataFeedUrl)
{
    Ids = ProfileID,
    Dimensions = "ga:source",
    Metrics = "ga:pageviews,ga:timeOnSite,ga:exits",
    Filters = "ga:medium==organic",
    Sort = "-ga:pageviews",
    GAStartDate = (DateTime.Now).AddDays(-7).ToString("yyyy-MM-dd"),
    GAEndDate = (DateTime.Now).ToString("yyyy-MM-dd")
};
...
Console.WriteLine(Entry.Title.Text.Split('=')[1]);
Console.WriteLine(String.Format("\tPageViews: {0}", Entry.Metrics[0].Value));
Console.WriteLine(String.Format("\tTimeOnSite: {0}", Entry.Metrics[1].Value));
Console.WriteLine(String.Format("\texits: {0}", Entry.Metrics[1].Value));

Search Engines – Paid Search

DataQuery dataquery = new DataQuery(DataFeedUrl)
{
    Ids = ProfileID,
    Dimensions = "ga:source",
    Metrics = "ga:pageviews,ga:timeOnSite,ga:exits",
    Filters = "ga:medium==cpa,ga:medium==cpc,ga:medium==cpm,ga:medium==cpp,ga:medium==cpv,ga:medium==ppc",
    Sort = "-ga:pageviews",
    GAStartDate = (DateTime.Now).AddDays(-7).ToString("yyyy-MM-dd"),
    GAEndDate = (DateTime.Now).ToString("yyyy-MM-dd")
};
Console.WriteLine(Entry.Title.Text.Split('=')[1]);
Console.WriteLine(String.Format("\tPageViews: {0}", Entry.Metrics[0].Value));
Console.WriteLine(String.Format("\tTimeOnSite: {0}", Entry.Metrics[1].Value));
Console.WriteLine(String.Format("\texits: {0}", Entry.Metrics[1].Value));

Top Content

DataQuery dataquery = new DataQuery(DataFeedUrl)
{
    Ids = ProfileID,
    Dimensions = "ga:pagePath",
    Metrics = "ga:pageviews,ga:uniquePageviews,ga:timeOnPage,ga:bounces,ga:entrances,ga:exits",
    Sort = "-ga:pageviews",
    GAStartDate = (DateTime.Now).AddDays(-7).ToString("yyyy-MM-dd"),
    GAEndDate = (DateTime.Now).ToString("yyyy-MM-dd")
};
...
Console.WriteLine(String.Format("{0}\t{1}",
    Entry.Title.Text.Split('=')[1],
    Entry.Metrics[0].Value));

Top Landing Pages

DataQuery dataquery = new DataQuery(DataFeedUrl)
{
    Ids = ProfileID,
    Dimensions = "ga:landingPagePath",
    Metrics = "ga:entrances,ga:bounces",
    Sort = "-ga:entrances",
    GAStartDate = (DateTime.Now).AddDays(-7).ToString("yyyy-MM-dd"),
    GAEndDate = (DateTime.Now).ToString("yyyy-MM-dd")
};
...
Console.WriteLine(Entry.Title.Text.Split('=')[1]);
Console.WriteLine(String.Format("\tEntrances: {0}", Entry.Metrics[0].Value));
Console.WriteLine(String.Format("\tBounces: {0}", Entry.Metrics[1].Value));

Top Exit Pages

DataQuery dataquery = new DataQuery(DataFeedUrl)
{
    Ids = ProfileID,
    Dimensions = "ga:exitPagePath",
    Metrics = "ga:exits,ga:pageviews",
    Sort = "-ga:exits",
    GAStartDate = (DateTime.Now).AddDays(-7).ToString("yyyy-MM-dd"),
    GAEndDate = (DateTime.Now).ToString("yyyy-MM-dd")
};
...
Console.WriteLine(Entry.Title.Text.Split('=')[1]);
Console.WriteLine(String.Format("\tExits: {0}", Entry.Metrics[0].Value));
Console.WriteLine(String.Format("\tPageViews: {0}", Entry.Metrics[1].Value));

Site Search – Search Terms

DataQuery dataquery = new DataQuery(DataFeedUrl)
{
    Ids = ProfileID,
    Dimensions = "ga:searchKeyword",
    Metrics = "ga:searchUniques",
    Sort = "-ga:earchUniques",
    GAStartDate = (DateTime.Now).AddDays(-7).ToString("yyyy-MM-dd"),
    GAEndDate = (DateTime.Now).ToString("yyyy-MM-dd")
};
...
Console.WriteLine(String.Format("{0}\t{1}",
    Entry.Title.Text.Split('=')[1],
    Entry.Metrics[0].Value));

Mobile Traffic

DataQuery dataquery = new DataQuery(DataFeedUrl)
{
    Ids = ProfileID,
    Dimensions = "ga:browser,ga:operatingSystem,ga:source",
    Metrics = "ga:visits,ga:pageviews,ga:timeOnSite",
    Segment = "gaid::-11",
    Sort = "ga:operatingSystem",
    GAStartDate = (DateTime.Now).AddDays(-7).ToString("yyyy-MM-dd"),
    GAEndDate = (DateTime.Now).ToString("yyyy-MM-dd")
};
...
Console.WriteLine(Entry.Title.Text);
Console.WriteLine(String.Format("\tVisits: {0}", Entry.Metrics[0].Value));
Console.WriteLine(String.Format("\tPageviews: {0}", Entry.Metrics[1].Value));
Console.WriteLine(String.Format("\tTimeOnSite: {0}", Entry.Metrics[1].Value));

Everyone uses Google Analytics it has amazingly valuable information that you not only want to analyse but often publish on your website or application – and it isnt that hard to tap into it via C#.

The first thing you need are Google Analytics C# libraries. Id like to say they are available at the project site (http://google-gdata.googlecode.com) but unfortunately the links are broken. After a bit of hunting I found them in the SVN repository at http://google-gdata.googlecode.com/svn/trunk/clients/cs/lib/Release/.

You want to get all the dll’s;

Google.GData.AccessControl.dll, Google.GData.Analytics.dll, Google.GData.Apps.dll, Google.GData.Blogger.dll, Google.GData.Calendar.dll, Google.GData.Client.dll, Google.GData.Contacts.dll, Google.GData.ContentForShopping.dll, Google.GData.Documents.dll, Google.GData.Extensions.dll, Google.GData.Photos.dll, Google.GData.Spreadsheets.dll, Google.GData.WebmasterTools.dll, Google.GData.YouTube.dll

- I have also zipped them and included them at the bottom of the page.

Depending on what you want to do later you may also want to get NewtonSoft.Json.dll which is an amazing Json to C# serializer by Jason Newton-King (http://james.newtonking.com/pages/json-net.aspx) which I use for bf3mobile.com – if you have a ton of json data it is honey from heaven.

This simple project is also going to use Google.GData.Client.dll and Google.GData.Analytics.dll – and its a little console app to find your pageview count per day for the last seven days.

Firstly lets declare the properties;

public static string username { get; set; }

public static string password { get; set;}

public static AnalyticsService Service { get; set; }

public static string AccountsFeedUrl { get; set; }

public static string DataFeedUrl { get; set; }

Now normally when you want to interigate the Analytics data for a specific website you need three things – your username, password and the profile ID of the website – which looks something like ga:12345678 – not something you often have handy – so the first part of the code is going to search all your websites by name.

You get to your list of websites via the accounts feed url “https://www.google.com/analytics/feeds/accounts/default”;

//set your username and password
username = "JohnCitizen@gmail.com";
password = "Password123";

//set the accounts feed url
AccountsFeedUrl = "https://www.google.com/analytics/feeds/accounts/default";

//bind to the google analytics service
Service = new AnalyticsService("AnalyticsSampleApp");
Service.setUserCredentials(username, password);

Now that you have bound to Google Analytics you create an open search;

AccountQuery AccountsQuery = new AccountQuery(AccountsFeedUrl);
AccountFeed AccountsFeed = Service.Query(AccountsQuery);

The results come back a series of AtomEntry entries, so you can simply roll through them looking for your website;

List<AtomEntry> Accounts = AccountsFeed.Entries.ToList();
foreach(AtomEntry Account in Accounts)
    if(Account.Title.Text.Equals("www.arboundy.com"))
    {
        GetPageViews(Account);
    }

and call your method, in this example GetPageViews.

To get data about your site you use the data feed url “https://www.google.com/analytics/feeds/data” and this is where you need the site’s profile ID, which you can get from your now found AtomEntry;

string ProfileID = Account.Id.AbsoluteUri.Substring(47);
DataFeedUrl = "https://www.google.com/analytics/feeds/data";

Next you have to create a DataQuery with the parameters defining your search;

DataQuery PageViewQuery = new DataQuery(DataFeedUrl)
{
    Ids = ProfileID,
    Dimensions = "ga:date",
    Metrics = "ga:pageviews",
    Sort = "ga:date",
    GAStartDate = (DateTime.Now).AddDays(-7).ToString("yyyy-MM-dd"),
    GAEndDate = (DateTime.Now).ToString("yyyy-MM-dd")
};

All fairly readable – we are look for ga:pageviews sorted by ga:date from GAStartDate to the GAEndDate (both in yyyy-MM-dd). Naturally your could sort by ga:pageviews instead. (Note the sort is by default ascending, if you want to sort descending you put a minus in front, ie: Sort = “-ga:date”)

Armed with your query you get the results;

DataFeed Results = Service.Query(PageViewQuery);

The results come back one per dimension, which we defined as ga:date – so there will be seven entries. If we didnt define the dimension, there would be only one result – the sum of all the results – ie the sum of all seven days.

Each result comes back as an AtomEntry – and they are fairly complicated. Ends out to make easy sense of them you cast the as a DataEntry;

foreach (AtomEntry Result in Results.Entries)
{
    DataEntry Entry = (DataEntry)Result;

Your title is your Entry.Title.Text which will come our something like ga:date=20120421 and your value will be Entry.Metrics[0].Value – so with a simple loop;

foreach (AtomEntry Result in Results.Entries)
{
    DataEntry Entry = (DataEntry)Result;
    Console.WriteLine(String.Format("{0}\t{1}",
        Entry.Title.Text.Split('=')[1],
        Entry.Metrics[0].Value));
};

you get

Not bad. As said a copy of the libraries is below plus the full code.

.

.

using System;
using System.Collections.Generic;
using System.Linq;
using System.Text;
using Google.GData.Analytics;
using Google.GData.Client;

namespace Google.Analytics
{
    class Program
    {
        public static string username { get; set; }

        public static string password { get; set;}

        public static AnalyticsService Service { get; set; }

        public static string AccountsFeedUrl { get; set; }

        public static string DataFeedUrl { get; set; }

        static void Main(string[] args)
        {
            username = "JohnCitizen@gmail.com";
            password = "Password123";
            AccountsFeedUrl =
               "https://www.google.com/analytics/feeds/accounts/default";

            Service = new AnalyticsService("AnalyticsSampleApp");
            Service.setUserCredentials(username, password);

            AccountQuery AccountsQuery = new AccountQuery(AccountsFeedUrl);
            AccountFeed AccountsFeed = Service.Query(AccountsQuery);

            List<AtomEntry> Accounts = AccountsFeed.Entries.ToList();
            foreach (AtomEntry Account in Accounts)
                if (Account.Title.Text.Equals("www.arboundy.com"))
                {
                    GetPageViews(Account);
                }
        }

        private static void GetPageViews(AtomEntry Account)
        {
            string ProfileID = Account.Id.AbsoluteUri.Substring(47);
            DataFeedUrl = "https://www.google.com/analytics/feeds/data";

            DataQuery PageViewQuery = new DataQuery(DataFeedUrl)
            {
                Ids = ProfileID,
                Dimensions = "ga:date",
                Metrics = "ga:pageviews",
                Sort = "ga:date",
                GAStartDate = (DateTime.Now).AddDays(-7).ToString("yyyy-MM-dd"),
                GAEndDate = (DateTime.Now).ToString("yyyy-MM-dd")
            };

            DataFeed Results = Service.Query(PageViewQuery);

            foreach (AtomEntry Result in Results.Entries)
            {
                DataEntry Entry = (DataEntry)Result;

                Console.WriteLine(String.Format("{0}\t{1}",
                    Entry.Title.Text.Split('=')[1],
                    Entry.Metrics[0].Value));
            }
        }
    }
}

I have been working on the project of transitioning from the old ESX infrastructure to the new infrastructure, a project which includes everything from replacing the SAN’s, Hosts, upgrading ESX, changing from a Fibre to a Ethernet fabric – the works.

We had a plan, and no this isn’t a story of how bad that plan went. Every issue we have experienced was during nominated maintenance windows and we had the ultimate fail-over of restoring – this isn’t an incompetence story.

Anyway, we had a plan, a series of tasks and test that would see us transition from the old to the new, with a period of running both at the same time as the guests were migrated;

This forecast and acknowledged risks during the migration stage. But due to factors including the Global Financial Crisis and hardware incompatibilities we had to extend the life of the legacy infrastructure much further than we liked and had delays in commissioning the new infrastructure, thus extending our risk period;

I can tell you that due to issues we have bashed our ESX Cluster like an old shoe. We have had hardware black screen of deaths, hard reboots, crashed LUN’s, filled LUN’s, disappearing LUN’s, disappearing fibre cards, disappearing NIC’s – the lot. The servers have been opened and reopened, components on the desk like an server massacre and people wearing three anti static straps just for luck.

And VMware has pulled through every time.

Every time something went pop Im there with my recovery plan thinking “the Windows guests are toast”, we get it together and VMware just says “Cheers!” and everything comes online.

Ive become a broken record in the server room, constantly say how I cant believe it pulled it back together. Im almost willing to claim that I could abuse its parents and chuck a cup of water at it and VMware will just recover with a smile.

Sure VMware creates a new capacity, performance and management style – but if you treat it with respect – Im at the point of saying it can do anything.

The other night I was doing some research of load balancers and http accelerators which let me to to HAProxy (http://haproxy.1wt.eu) which led me to the cluster monitoring solution Ganglia (http://ganglia.sourceforge.net) which led me to Wikimedia’s Live Grid Report (don’t you just love the internet?).

Its available for anyone too look at and shows the utilisation of their cluster. At the time of writing they had 748 hosts with 10,382 CPU’s and 15 Terrabytes of RAM while serving a few Gigabytes per second of outgoing data and a couple Gigabytes of incoming data…

and it reminded me how there is a whole different world out there most of us don’t get to see.

I mean I get happy walking around 60+ soloed but 750 clustered – that would be impressive.

If you hunt around you can even see the individual hosts and sure they have got some 24×2.66 GHz 11Gb RAM 250Gb HD units but the majority appear to be nice little 8×2.XX GHz 8Gb RAM 72Gb HD ones – that Google type of many small low cost units clustered together …

meaning individual failures, even many individual failures have minimal impact to the overall environment.

Looking through the cluster stats and configs made me quite jealous – I want one!

Extracting this list via C# is pretty easy these days.

First you need to connect to the domain, and to do this you need to add a reference to System.DirectoryServices. From there you create a DirectoryEntry to the root of your domain;

DirectoryEntry root = new DirectoryEntry("LDAP://example.com");

From there you can recursively go through domain tree in a number of ways, including a DomainSearcher. For this we will keep it simple with a recursive loop;

ListEmailAddress(root);

private static void ListEmailAddress(DirectoryEntry Root)
{
    try
    {
        foreach(DirectoryEntry Child in Root.Children)
        {
            if (Child.SchemaClassName.Equals("user"))
            {
                ListSMTPAddresses(Child);
            }
            ListEmailAddress(Child);
        }
    }
    catch
    {}
}

Quite simply; for each node in the tree (starting with root) for each child node it checks if it is a user, if so it calls the ListSMTPAddresses(Child) method, then it chucks the child back into the method again. This recursively goes through all the OU’s in the tree finding each user.

The ListSMTPAddresses(Child) method is simply;

private static void ListSMTPAddresses(DirectoryEntry Child)
{
    try
    {
        foreach(string SMTPAddress in Child.Properties["proxyaddresses"])
        {
            if (SMTPAddress.ToLower().Contains("smtp:"))
            {
                string Address = SMTPAddress.ToLower().Substring(5);
                if (Address.Contains("systemmailbox"))
                {
                    if (!EmailAddresses.Contains(Address))
                         EmailAddresses.Add(Address);
                }
            }
        }
    }
    catch
    {}
}

Child.Properties["proxyaddresses"] is a little different than some of the property values as it is an list of all the email addresses associated with an acount – so we have to do the foreach loop. However most other values can be read by a simple;

string x = Child.Properties["propertyname"].Value;

Once done the the results are written to a file;

private static void WriteFile()
{
    ///sort and clean
    EmailAddresses.Sort();

    StringBuilder txt = new StringBuilder();
    foreach(string EmailAddress in EmailAddresses)
        txt.AppendLine(EmailAddress);

    //write
    TextWriter writer = new StreamWriter("SMTPAddresses.txt");
    writer.Write(txt.ToString());
    writer.Close();
    writer.Dispose();
}

By modifying this code you can get to nearly every property for a user oject in Active Directory by changing the property name.

Richard Mueller of rlmueller.net has spreadsheet of property names and the definitions at http://www.rlmueller.net/UserAttributes.htm.

.

I’m yet to start learning Objective-C so I went the standard website way, and with the iphone interface and some tricks you can achieve a fairly impressive look quote quickly.

Making it look like an app was important, and if you get the javascript / css just right you can get pretty close;

As you can see from the logon screen above. The site remembers soldiers you have previously looked up and places the in the drop down list, and with the iphone / safari rendering it comes out clean;

The trickiest part was getting the stats, screen scraping may have been possible but would have been too time consuming. Luckily after a bit of sleuthing I found a json feed and was able to convert it to a stats page;

To keep the source guessing I punch the stats request through a series of randomised proxies with fake spoofed user agents – but don’t tell any one.

I’ve probably missed the boat with this one, there are a number of iphone and andriod apps out there which do similar things, and EA/Dice have been claiming an official app will be out soon (though they have been saying that for months) – but it still was a fun exercise on how to get the data and how to render it.

If you are a Battlefield 3 fan be sure to check it out on your mobile at bf3mobile.com, if not you can always test it using one of my retired soldier’s name – arb_anikan.

I want to add a lot more features, but I’ll probably get too tempted to rebuild it in Objective-C and see what its like to publish your own app.