Skip to main content

Performance Counter Setup on Windows Azure

Cand avem o aplicatie in cloud avem nevoie de a monitoriza diferiti parametrii. Acest lucru il facem asa cum il facem si pe un server normal folosindune de performance counter.
Intrebarea ar putea sa fie usor diferita: Ce facem cu aceste valori odata ce le avem?
Daca intram remote pe masina, puten sa ne folosim perfmon.exe pentru a monitoriza toti acest parametrii. Dar daca vrem mai mult de atata, daca vrem ca aceste valori sa le putem accesa remote sau sa le persistam in Azure Storage.
In ajutor ne-a venit in ajutor Microsoft si ne-a oferit DiagnosticMonitor pentru Azure. Acesta poate sa fie configurat destul de usor in momentul in care aplicatia porneste si ne va permite sa scriem orice valoare in Azure Tables. In exemplul de mai jos o sa prezint cum se configureaza pentru a putea vedea load-ul la procesor:
var config = DiagnosticMonitor.GetDefaultInitialConfiguration();
config.PerformanceCounters.ScheduledTransferPeriod = TimeSpan.FromMinutes(30);
config.PerformanceCounters.DataSources.Add
new PerformanceCounterConfiguration() {
CounterSpecifier = @"\Processor(_Total)\% Processor Time",
SampleRate = TimeSpan.FromSeconds(30)
};
Deoarece fiecare tranzactie se contorizeaza la sfarsit de luna, am setat ca flush-ul la date sa se faca odata la 30 de minute. Odata ce am facut aceasta configurare ajunge sa pornim diagnosticarea pentru noua configuratie:
DiagnosticMonitor.Start("Microsoft.WindowsAzure.Plugins.Diagnostics.ConnectionString", config);
Am vazut ca la unele persoane nu este foarte clar ce valoare reprezinta "\Processor(_Total)\% Processor Time". Aceasta reprezinta CPU usage in momentul in care s-a facut requestul. Valoare este media la CPU usage pentru toate procesoarele masinii noastre.
Aceasta setare este nevoie sa o adaugati in entry point-ul aplicatiei voastre din cloud. Clasa care reprezinta entry-point-ul pentru o aplicatie in cloud are ca si clasa de baza RoleEntryPoint.
Mai jos gasiti o implementare cap coada a unui performance counter.
public class WebRole : RoleEntryPoint
{
public override bool OnStart()
{
var config = DiagnosticMonitor.GetDefaultInitialConfiguration();
config.OverallQuotaInMB = 4080;
config.ConfigurationChangePollInterval = TimeSpan.FromHours(1);
config.PerformanceCounters.BufferQuotaInMB = 128;
config.PerformanceCounters.ScheduledTransferPeriod = TimeSpan.FromSeconds(60);

config.PerformanceCounters.DataSources.
Add(new PerformanceCounterConfiguration
{
CounterSpecifier = @"\Processor(_Total)\% Processor Time",
SampleRate = TimeSpan.FromSeconds(30)
});

DiagnosticMonitor.Start("Microsoft.WindowsAzure.Plugins.Diagnostics.ConnectionString", config);

return true;
}
}
Odata ce am facut aceste configurari si am facut un deploy (sau am rulat aplicatia local) o sa puteti observa ca apare o noua table in Windows Azure Tables. Aceasta poata numele de "WADPerformanceCountersTable" si o sa contina toate valorile de la toti performance counters pe care ii monitorizati. In acest tabel o sa gasiti toate datele despre performance counters pe care voi ii monitorizati.
Pentru a putea vizualiza aceste valori mai usor, va recomand sa folositi Cloud Monitoring Studio. Este un tool gratis de pe codeplex care iti permite sa vizualizezi toate datele sub forma unui grafic.

Comments

Popular posts from this blog

Windows Docker Containers can make WIN32 API calls, use COM and ASP.NET WebForms

After the last post , I received two interesting questions related to Docker and Windows. People were interested if we do Win32 API calls from a Docker container and if there is support for COM. WIN32 Support To test calls to WIN32 API, let’s try to populate SYSTEM_INFO class. [StructLayout(LayoutKind.Sequential)] public struct SYSTEM_INFO { public uint dwOemId; public uint dwPageSize; public uint lpMinimumApplicationAddress; public uint lpMaximumApplicationAddress; public uint dwActiveProcessorMask; public uint dwNumberOfProcessors; public uint dwProcessorType; public uint dwAllocationGranularity; public uint dwProcessorLevel; public uint dwProcessorRevision; } ... [DllImport("kernel32")] static extern void GetSystemInfo(ref SYSTEM_INFO pSI); ... SYSTEM_INFO pSI = new SYSTEM_INFO(

Azure AD and AWS Cognito side-by-side

In the last few weeks, I was involved in multiple opportunities on Microsoft Azure and Amazon, where we had to analyse AWS Cognito, Azure AD and other solutions that are available on the market. I decided to consolidate in one post all features and differences that I identified for both of them that we should need to take into account. Take into account that Azure AD is an identity and access management services well integrated with Microsoft stack. In comparison, AWS Cognito is just a user sign-up, sign-in and access control and nothing more. The focus is not on the main features, is more on small things that can make a difference when you want to decide where we want to store and manage our users.  This information might be useful in the future when we need to decide where we want to keep and manage our users.  Feature Azure AD (B2C, B2C) AWS Cognito Access token lifetime Default 1h – the value is configurable 1h – cannot be modified

What to do when you hit the throughput limits of Azure Storage (Blobs)

In this post we will talk about how we can detect when we hit a throughput limit of Azure Storage and what we can do in that moment. Context If we take a look on Scalability Targets of Azure Storage ( https://azure.microsoft.com/en-us/documentation/articles/storage-scalability-targets/ ) we will observe that the limits are prety high. But, based on our business logic we can end up at this limits. If you create a system that is hitted by a high number of device, you can hit easily the total number of requests rate that can be done on a Storage Account. This limits on Azure is 20.000 IOPS (entities or messages per second) where (and this is very important) the size of the request is 1KB. Normally, if you make a load tests where 20.000 clients will hit different blobs storages from the same Azure Storage Account, this limits can be reached. How we can detect this problem? From client, we can detect that this limits was reached based on the HTTP error code that is returned by HTTP