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  • Microsoft MVP Award

    - by EltonStoneman
    [Source: http://geekswithblogs.net/EltonStoneman] I learned over Easter that I have been awarded a BizTalk MVP by Microsoft for 2010, which is great news. It's all a bit shadowy, but I suspect Michael Stephenson had a hand in it – so thanks Mike.

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  • Passthrough Objects – Duck Typing++

    - by EltonStoneman
    [Source: http://geekswithblogs.net/EltonStoneman] Can't see a genuine use for this, but I got the idea in my head and wanted to work it through. It's an extension to the idea of duck typing, for scenarios where types have similar behaviour, but implemented in differently-named members. So you may have a set of objects you want to treat as an interface, which don't implement the interface explicitly, and don't have the same member names so they can't be duck-typed into implicitly implementing the interface. In a fictitious example, I want to call Get on whichever ICache implementation is current, and have the call passed through to the relevant method – whether it's called Read, Retrieve or whatever: A sample implementation is up on github here: PassthroughSample. This uses Castle's DynamicProxy behind the scenes in the same way as my duck typing sample, but allows you to configure the passthrough to specify how the inner (implementation) and outer (interface) members are mapped:       var setup = new Passthrough();     var cache = setup.Create("PassthroughSample.Tests.Stubs.AspNetCache, PassthroughSample.Tests")                             .WithPassthrough("Name", "CacheName")                             .WithPassthrough("Get", "Retrieve")                             .WithPassthrough("Set", "Insert")                             .As<ICache>(); - or using some ugly Lambdas to avoid the strings :     Expression<Func<ICache, string, object>> get = (o, s) => o.Get(s);     Expression<Func<Memcached, string, object>> read = (i, s) => i.Read(s);     Expression<Action<ICache, string, object>> set = (o, s, obj) => o.Set(s, obj);     Expression<Action<Memcached, string, object>> insert = (i, s, obj) => i.Put(s, obj);       ICache cache = new Passthrough<ICache, Memcached>()                     .Create()                     .WithPassthrough(o => o.Name, i => i.InstanceName)                     .WithPassthrough(get, read)                     .WithPassthrough(set, insert)                     .As();   - or even in config:   ICache cache = Passthrough.GetConfigured<ICache>(); ...  <passthrough>     <types>       <typename="PassthroughSample.Tests.Stubs.ICache, PassthroughSample.Tests"             passesThroughTo="PassthroughSample.Tests.Stubs.AppFabricCache, PassthroughSample.Tests">         <members>           <membername="Name"passesThroughTo="RegionName"/>           <membername="Get"passesThroughTo="Out"/>           <membername="Set"passesThroughTo="In"/>         </members>       </type>   Possibly useful for injecting stubs for dependencies in tests, when your application code isn't using an IoC container. Possibly it also has an alternative implementation using .NET 4.0 dynamic objects, rather than the dynamic proxy.

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  • SBUG Session: The Enterprise Cache

    - by EltonStoneman
    [Source: http://geekswithblogs.net/EltonStoneman] I did a session on "The Enterprise Cache" at the UK SOA/BPM User Group yesterday which generated some useful discussion. The proposal was for a dedicated caching layer which all app servers and service providers can hook into, sharing resources and common data. The architecture might end up like this: I'll update this post with a link to the slide deck once it's available. The next session will have Udi Dahan walking through nServiceBus, register on EventBrite if you want to come along. Synopsis Looked at the benefits and drawbacks of app-centric isolated caches, compared to an enterprise-wide shared cache running on dedicated nodes; Suggested issues and risks around caching including staleness of data, resource usage, performance and testing; Walked through a generic service cache implemented as a WCF behaviour – suitable for IIS- or BizTalk-hosted services - which I'll be releasing on CodePlex shortly; Listed common options for cache providers and their offerings. Discussion Cache usage. Different value propositions for utilising the cache: improved performance, isolation from underlying systems (e.g. service output caching can have a TTL large enough to cover downtime), reduced resource impact – CPU, memory, SQL and cost (e.g. caching results of paid-for services). Dedicated cache nodes. Preferred over in-host caching provided latency is acceptable. Depending on cache provider, can offer easy scalability and global replication so cache clients always use local nodes. Restriction of AppFabric Caching to Windows Server 2008 not viewed as a concern. Security. Limited security model in most cache providers. Options for securing cache content suggested as custom implementations. Obfuscating keys and serialized values may mean additional security is not needed. Depending on security requirements and architecture, can ensure cache servers only accessible to cache clients via IPsec. Staleness. Generally thought to be an overrated problem. Thinking in line with eventual consistency, that serving up stale data may not be a significant issue. Good technical arguments support this, although I suspect business users will be harder to persuade. Providers. Positive feedback for AppFabric Caching – speed, configurability and richness of the distributed model making it a good enterprise choice. .NET port of memcached well thought of for performance but lack of replication makes it less suitable for these shared scenarios. Replicated fork – repcached – untried and less active than memcached. NCache also well thought of, but Express version too limited for enterprise scenarios, and commercial versions look costly compared to AppFabric.

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  • Use Expressions with LINQ to Entities

    - by EltonStoneman
    [Source: http://geekswithblogs.net/EltonStoneman] Recently I've been putting together a generic approach for paging the response from a WCF service. Paging changes the service signature, so it's not as simple as adding a behavior to an existing service in config, but the complexity of the paging is isolated in a generic base class. We're using the Entity Framework talking to SQL Server, so when we ask for a page using LINQ's .Take() method we get a nice efficient SQL query for just the rows we want, with minimal impact on SQL Server and network traffic. We use the maximum ID of the record returned as a high-water mark (rather than using .Skip() to go to the next record), so the approach caters for records being deleted between page requests. In the paged response we include a HasMorePages indicator, computed by comparing the max ID in the page of results to the max ID for the whole resultset - if the latter is bigger, then there are more pages. In some quick performance testing, the paged version of the service performed much more slowly than the unpaged version, which was unexpected. We narrowed it down to the code which gets the max ID for the full resultset - instead of building an efficient MAX() SQL query, EF was returning the whole resultset and then computing the max ID in the service layer. It's easy to reproduce - take this AdventureWorks query:             var context = new AdventureWorksEntities();             var query = from od in context.SalesOrderDetail                         where od.ModifiedDate >= modified                          && od.SalesOrderDetailID.CompareTo(id) > 0                         orderby od.SalesOrderDetailID                         select od;   We can find the maximum SalesOrderDetailID like this:             var maxIdEfficiently = query.Max(od => od.SalesOrderDetailID);   which produces our efficient MAX() SQL query. If we're doing this generically and we already have the ID function in a Func:             Func<SalesOrderDetail, int> idFunc = od => od.SalesOrderDetailID;             var maxIdInefficiently = query.Max(idFunc);   This fetches all the results from the query and then runs the Max() function in code. If you look at the difference in Reflector, the first call passes an Expression to the Max(), while the second call passes a Func. So it's an easy fix - wrap the Func in an Expression:             Expression<Func<SalesOrderDetail, int>> idExpression = od => od.SalesOrderDetailID;             var maxIdEfficientlyAgain = query.Max(idExpression);   - and we're back to running an efficient MAX() statement. Evidently the EF provider can dissect an Expression and build its equivalent in SQL, but it can't do that with Funcs.

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  • Using C# 4.0’s DynamicObject as a Stored Procedure Wrapper

    - by EltonStoneman
    [Source: http://geekswithblogs.net/EltonStoneman] Overview Ignoring the fashion, I still make a lot of use of DALs – typically when inheriting a codebase with an established database schema which is full of tried and trusted stored procedures. In the DAL a collection of base classes have all the scaffolding, so the usual pattern is to create a wrapper class for each stored procedure, giving typesafe access to parameter values and output. DAL calls then looks like instantiate wrapper-populate parameters-execute call:       using (var sp = new uspGetManagerEmployees())     {         sp.ManagerID = 16;         using (var reader = sp.Execute())         {             //map entities from the output         }     }   Or rolling it all into a fluent DAL call – which is nicer to read and implicitly disposes the resources:   This is fine, the wrapper classes are very simple to handwrite or generate. But as the codebase grows, you end up with a proliferation of very small wrapper classes: The wrappers don't add much other than encapsulating the stored procedure call and giving you typesafety for the parameters. With the dynamic extension in .NET 4.0 you have the option to build a single wrapper class, and get rid of the one-to-one stored procedure to wrapper class mapping. In the dynamic version, the call looks like this:       dynamic getUser = new DynamicSqlStoredProcedure("uspGetManagerEmployees", Database.AdventureWorks);     getUser.ManagerID = 16;       var employees = Fluently.Load<List<Employee>>()                             .With<EmployeeMap>()                             .From(getUser);   The important difference is that the ManagerId property doesn't exist in the DynamicSqlStoredProcedure class. Declaring the getUser object with the dynamic keyword allows you to dynamically add properties, and the DynamicSqlStoredProcedure class intercepts when properties are added and builds them as stored procedure parameters. When getUser.ManagerId = 16 is executed, the base class adds a parameter call (using the convention that parameter name is the property name prefixed by "@"), specifying the correct SQL Server data type (mapping it from the type of the value the property is set to), and setting the parameter value. Code Sample This is worked through in a sample project on github – Dynamic Stored Procedure Sample – which also includes a static version of the wrapper for comparison. (I'll upload this to the MSDN Code Gallery once my account has been resurrected). Points worth noting are: DynamicSP.Data – database-independent DAL that has all the data plumbing code. DynamicSP.Data.SqlServer – SQL Server DAL, thin layer on top of the generic DAL which adds SQL Server specific classes. Includes the DynamicSqlStoredProcedure base class. DynamicSqlStoredProcedure.TrySetMember. Invoked when a dynamic member is added. Assumes the property is a parameter named after the SP parameter name and infers the SqlDbType from the framework type. Adds a parameter to the internal stored procedure wrapper and sets its value. uspGetManagerEmployees – the static version of the wrapper. uspGetManagerEmployeesTest – test fixture which shows usage of the static and dynamic stored procedure wrappers. The sample uses stored procedures from the AdventureWorks database in the SQL Server 2008 Sample Databases. Discussion For this scenario, the dynamic option is very favourable. Assuming your DAL is itself wrapped by a higher layer, the stored procedure wrapper classes have very little reuse. Even if you're codegening the classes and test fixtures, it's still additional effort for very little value. The main consideration with dynamic classes is that the compiler ignores all the members you use, and evaluation only happens at runtime. In this case where scope is strictly limited that's not an issue – but you're relying on automated tests rather than the compiler to find errors, but that should just encourage better test coverage. Also you can codegen the dynamic calls at a higher level. Performance may be a consideration, as there is a first-time-use overhead when the dynamic members of an object are bound. For a single run, the dynamic wrapper took 0.2 seconds longer than the static wrapper. The framework does a good job of caching the effort though, so for 1,000 calls the dynamc version still only takes 0.2 seconds longer than the static: You don't get IntelliSense on dynamic objects, even for the declared members of the base class, and if you've been using class names as keys for configuration settings, you'll lose that option if you move to dynamics. The approach may make code more difficult to read, as you can't navigate through dynamic members, but you do still get full debugging support.     var employees = Fluently.Load<List<Employee>>()                             .With<EmployeeMap>()                             .From<uspGetManagerEmployees>                             (                                 i => i.ManagerID = 16,                                 x => x.Execute()                             );

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  • Moving DataSets through BizTalk

    - by EltonStoneman
    [Source: http://geekswithblogs.net/EltonStoneman] Yuck. But sometimes you have to, so here are a couple of things to bear in mind: Schemas Point a codegen tool at a WCF endpoint which exposes a DataSet and it will generate an XSD which describes the DataSet like this: <xs:elementminOccurs="0"name="GetDataSetResult"nillable="true">  <xs:complexType>     <xs:annotation>       <xs:appinfo>         <ActualTypeName="DataSet"                     Namespace="http://schemas.datacontract.org/2004/07/System.Data"                     xmlns="http://schemas.microsoft.com/2003/10/Serialization/" />       </xs:appinfo>     </xs:annotation>     <xs:sequence>       <xs:elementref="xs:schema" />       <xs:any />     </xs:sequence>  </xs:complexType> </xs:element>  In a serialized instance, the element of type xs:schema contains a full schema which describes the structure of the DataSet – tables, columns etc. The second element, of type xs:any, contains the actual content of the DataSet, expressed as DiffGrams: <GetDataSetResult>  <xs:schemaid="NewDataSet"xmlns:xs="http://www.w3.org/2001/XMLSchema"xmlns=""xmlns:msdata="urn:schemas-microsoft-com:xml-msdata">     <xs:elementname="NewDataSet"msdata:IsDataSet="true"msdata:UseCurrentLocale="true">       <xs:complexType>         <xs:choiceminOccurs="0"maxOccurs="unbounded">           <xs:elementname="Table1">             <xs:complexType>               <xs:sequence>                 <xs:elementname="Id"type="xs:string"minOccurs="0" />                 <xs:elementname="Name"type="xs:string"minOccurs="0" />                 <xs:elementname="Date"type="xs:string"minOccurs="0" />               </xs:sequence>             </xs:complexType>           </xs:element>         </xs:choice>       </xs:complexType>     </xs:element>  </xs:schema>  <diffgr:diffgramxmlns:diffgr="urn:schemas-microsoft-com:xml-diffgram-v1"xmlns:msdata="urn:schemas-microsoft-com:xml-msdata">     <NewDataSetxmlns="">       <Table1diffgr:id="Table11"msdata:rowOrder="0"diffgr:hasChanges="inserted">         <Id>377fdf8d-cfd1-4975-a167-2ddb41265def</Id>         <Name>157bc287-f09b-435f-a81f-2a3b23aff8c4</Name>         <Date>a5d78d83-6c9a-46ca-8277-f2be8d4658bf</Date>       </Table1>     </NewDataSet>  </diffgr:diffgram> </GetDataSetResult> Put the XSD into a BizTalk schema and it will fail to compile, giving you error: The 'http://www.w3.org/2001/XMLSchema:schema' element is not declared. You should be able to work around that, but I've had no luck in BizTalk Server 2006 R2 – instead you can safely change that xs:schema element to be another xs:any type: <xs:elementminOccurs="0"name="GetDataSetResult"nillable="true">  <xs:complexType>     <xs:sequence>       <xs:any />       <xs:any />     </xs:sequence>  </xs:complexType> </xs:element>  (This snippet omits the annotation, but you can leave it in the schema). For an XML instance to pass validation through the schema, you'll also need to flag the any attributes so they can contain any namespace and skip validation:  <xs:elementminOccurs="0"name="GetDataSetResult"nillable="true">  <xs:complexType>     <xs:sequence>       <xs:anynamespace="##any"processContents="skip" />       <xs:anynamespace="##any"processContents="skip" />     </xs:sequence>  </xs:complexType> </xs:element>  You should now have a compiling schema which can be successfully tested against a serialised DataSet. Transforms If you're mapping a DataSet element between schemas, you'll need to use the Mass Copy Functoid to populate the target node from the contents of both the xs:any type elements on the source node: This should give you a compiled map which you can test against a serialized instance. And if you have a .NET consumer on the other side of the mapped BizTalk output, it will correctly deserialize the response into a DataSet.

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  • Welcome to www.badapi.net, a REST API with badly-behaved endpoints

    - by Elton Stoneman
    Originally posted on: http://geekswithblogs.net/EltonStoneman/archive/2014/08/14/welcome-to-www.badapi.net-a-rest-api-with-badly-behaved-endpoints.aspxI've had a need in a few projects for a REST API that doesn't behave well - takes a long time to respond, or never responds, returns unexpected status codes etc.That can be very useful for testing that clients cope gracefully with unexpected responses.Till now I've always coded a stub API in the project and run it locally, but I've put a few 'misbehaved' endpoints together and published them at www.badapi.net, and the source is on GitHub here: sixeyed/badapi.net.You can browse to the home page and see the available endpoints. I'll be adding more as I think of them, and I may give the styling of the help pages a bit more thought...As of today's release, the misbehaving endpoints available to you are:GET longrunning?between={between}&and={and} - Waits for a (short) random period before returningGET verylongrunning?between={between}&and={and} -Waits for a (long) random period before returningGET internalservererror    - Returns 500: Internal Server ErrorGET badrequest - Returns 400: BadRequestGET notfound - Returns 404: Not FoundGET unauthorized - Returns 401: UnauthorizedGET forbidden - Returns 403: ForbiddenGET conflict -Returns 409: ConflictGET status/{code}?reason={reason} - Returns the provided status code Go bad.

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  • Caching in the .NET Stack: Inside-Out

    - by Elton Stoneman
    Originally posted on: http://geekswithblogs.net/EltonStoneman/archive/2013/06/28/caching-in-the-.net-stack-inside-out.aspxI'm delighted to have my first course published on Pluralsight - Caching in the .NET Stack: Inside-out.   It's a pretty comprehensive look at caching in .NET solutions. The first half covers using local, remote and persistent cache stores inside the solution, including the .NET MemoryCache, NCache Express, AppFabric Caching, memcached, Azure Table Storage and local disk stores. The second half covers caching outside the solution in HTTP clients and proxies, and how to set up ASP.NET WebForms, MVC, Web API and WCF projects to use HTTP validation and expiration caching.   The course takes a hands-on approach, starting with a distributed solution that has no caching, analysing key points which can benefit from caching, and adding different types of cache. At the end of the course I run through a set of before and after performance tests, stressing the solution under load. Without caching and with 60 concurrent users the page response time maxes out at 18 seconds - with caching that falls to 2 seconds, so it's a huge improvement from very little effort. I’d be glad to hear feedback if you watch the course, especially if it’s as positive as my editor’s.

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  • Nginx and PHP Fundamentals

    - by Elton Stoneman
    Originally posted on: http://geekswithblogs.net/EltonStoneman/archive/2013/08/01/nginx-and-php-fundamentals.aspxHot on the heels of my .NET caching course, I’ve had my first “fundamentals” course released on Pluralsight: Nginx and PHP Fundamentals. It’s a practical look at two of the biggest technologies on the web – Nginx, which is the fastest growing HTTP server around (currently hosting 100+ million sites), and PHP, which powers more websites than any other server-side framework (currently 240+ million sites). The two technologies work well together, both are open-source and cross-platform and both are lightweight and easy to get started with - you just need to download and unzip the runtimes, and with a text editor you can create and host dynamic websites. I’ve used PHP as a second (sometimes third) language since 2005 when I was brought cold into an established codebase to help improve performance, and Nginx to host tier 2 apps for the last couple of years. As with any training course, you learn new things as you produce it, and it was good to focus on a different stack from my commercial .NET world. In the course I start with a website in two parts – one which is just static content, and one which processes a user registration form using ASP.NET MVC, both running in IIS. Over four modules I migrate the app to Nginx and PHP: Hosting Static Content in Nginx – how to deploy and configure Nginx for a basic website; PHP Part 1: Basic Web Forms – installing PHP and an IDE, and building a simple form with server-side validation; PHP Part 2: Packages and Integration – using PECL and Composer for packages to connect to Azure, AWS, Mongo and reCAPTCHA; Hosting PHP in Nginx – configuring Nginx to host our PHP site. Along the way I run some performance stats with JMeter, and the headlines are that Nginx running on Linux outperforms IIS on Windows for static content,by 800 requests per second over 1000 concurrent requests; and Linux+Ngnix+PHP outperforms Windows+IIS+ASP.NET MVC by 700 request per second with the same load. Of course, the headline stats don’t tell the whole story, and when you add OpCode caching for PHP and the ASP.NET Output Cache, the results are very different. As Web architecture moves away from heavy server-side processing, to Single Page Apps with client-side frameworks like AngularJS and Knockout, I think there’s an increasing need for high-performance, low-cost server technologies, and the combination of Nginx and PHP makes a compelling case.

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  • Sixeyed.Caching available now on NuGet and GitHub!

    - by Elton Stoneman
    Originally posted on: http://geekswithblogs.net/EltonStoneman/archive/2013/10/22/sixeyed.caching-available-now-on-nuget-and-github.aspxThe good guys at Pluralsight have okayed me to publish my caching framework (as seen in Caching in the .NET Stack: Inside-Out) as an open-source library, and it’s out now. You can get it here: Sixeyed.Caching source code on GitHub, and here: Sixeyed.Caching package v1.0.0 on NuGet. If you haven’t seen the course, there’s a preview here on YouTube: In-Process and Out-of-Process Caches, which gives a good flavour. The library is a wrapper around various cache providers, including the .NET MemoryCache, AppFabric cache, and  memcached*. All the wrappers inherit from a base class which gives you a set of common functionality against all the cache implementations: •    inherits OutputCacheProvider, so you can use your chosen cache provider as an ASP.NET output cache; •    serialization and encryption, so you can configure whether you want your cache items serialized (XML, JSON or binary) and encrypted; •    instrumentation, you can optionally use performance counters to monitor cache attempts and hits, at a low level. The framework wraps up different caches into an ICache interface, and it lets you use a provider directly like this: Cache.Memory.Get<RefData>(refDataKey); - or with configuration to use the default cache provider: Cache.Default.Get<RefData>(refDataKey); The library uses Unity’s interception framework to implement AOP caching, which you can use by flagging methods with the [Cache] attribute: [Cache] public RefData GetItem(string refDataKey) - and you can be more specific on the required cache behaviour: [Cache(CacheType=CacheType.Memory, Days=1] public RefData GetItem(string refDataKey) - or really specific: [Cache(CacheType=CacheType.Disk, SerializationFormat=SerializationFormat.Json, Hours=2, Minutes=59)] public RefData GetItem(string refDataKey) Provided you get instances of classes with cacheable methods from the container, the attributed method results will be cached, and repeated calls will be fetched from the cache. You can also set a bunch of cache defaults in application config, like whether to use encryption and instrumentation, and whether the cache system is enabled at all: <sixeyed.caching enabled="true"> <performanceCounters instrumentCacheTotalCounts="true" instrumentCacheTargetCounts="true" categoryNamePrefix ="Sixeyed.Caching.Tests"/> <encryption enabled="true" key="1234567890abcdef1234567890abcdef" iv="1234567890abcdef"/> <!-- key must be 32 characters, IV must be 16 characters--> </sixeyed.caching> For AOP and methods flagged with the cache attribute, you can override the compile-time cache settings at runtime with more config (keyed by the class and method name): <sixeyed.caching enabled="true"> <targets> <target keyPrefix="MethodLevelCachingStub.GetRandomIntCacheConfiguredInternal" enabled="false"/> <target keyPrefix="MethodLevelCachingStub.GetRandomIntCacheExpiresConfiguredInternal" seconds="1"/> </targets> It’s released under the MIT license, so you can use it freely in your own apps and modify as required. I’ll be adding more content to the GitHub wiki, which will be the main source of documentation, but for now there’s an FAQ to get you started. * - in the course the framework library also wraps NCache Express, but there's no public redistributable library that I can find, so it's not in Sixeyed.Caching.

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  • AWS .NET SDK v2: the message-pump pattern

    - by Elton Stoneman
    Originally posted on: http://geekswithblogs.net/EltonStoneman/archive/2013/10/11/aws-.net-sdk-v2--the-message-pump-pattern.aspxVersion 2 of the AWS SDK for .NET has had a few pre-release iterations on NuGet and is stable, if a bit lacking in step-by-step guides. There’s at least one big reason to try it out: the SQS queue client now supports asynchronous reads, so you don’t need a clumsy polling mechanism to retrieve messages. The new approach  is easy to use, and lets you work with AWS queues in a similar way to the message-pump pattern used in the latest Azure SDK for Service Bus queues and topics. I’ve posted a simple wrapper class for subscribing to an SQS hub on gist here: A wrapper for the SQS client in the AWS SDK for.NET v2, which uses the message-pump pattern. Here’s the core functionality in the subscribe method: private async void Subscribe() { if (_isListening) { var request = new ReceiveMessageRequest { MaxNumberOfMessages = 10 }; request.QueueUrl = QueueUrl; var result = await _sqsClient.ReceiveMessageAsync(request, _cancellationTokenSource.Token); if (result.Messages.Count > 0) { foreach (var message in result.Messages) { if (_receiveAction != null && message != null) { _receiveAction(message.Body); DeleteMessage(message.ReceiptHandle); } } } } if (_isListening) { Subscribe(); } } which you call with something like this: client.Subscribe(x=>Log.Debug(x.Body)); The async SDK call returns when there is something in the queue, and will run your receive action for every message it gets in the batch (defaults to the maximum size of 10 messages per call). The listener will sit there awaiting messages until you stop it with: client.Unsubscribe(); Internally it has a cancellation token which it sets when you call unsubscribe, which cancels any in-flight call to SQS and stops the pump. The wrapper will also create the queue if it doesn’t exist at runtime. The Ensure() method gets called in the constructor so when you first use the client for a queue (sending or subscribing), it will set itself up: if (!Exists()) { var request = new CreateQueueRequest(); request.QueueName = QueueName; var response = _sqsClient.CreateQueue(request); QueueUrl = response.QueueUrl; } The Exists() check has to do make a call to ListQueues on the SNS client, as it doesn’t provide its own method to check if a queue exists. That call also populates the Amazon Resource Name, the unique identifier for this queue, which will be useful later. To use the wrapper, just instantiate and go: var queueClient = new QueueClient(“ProcessWorkflow”); queueClient.Subscribe(x=>Log.Debug(x.Body)); var message = {}; //etc. queueClient.Send(message);

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  • Implementing the Reactive Manifesto with Azure and AWS

    - by Elton Stoneman
    Originally posted on: http://geekswithblogs.net/EltonStoneman/archive/2013/10/31/implementing-the-reactive-manifesto-with-azure-and-aws.aspxMy latest Pluralsight course, Implementing the Reactive Manifesto with Azure and AWS has just been published! I’d planned to do a course on dual-running a messaging-based solution in Azure and AWS for super-high availability and scale, and the Reactive Manifesto encapsulates exactly what I wanted to do. A “reactive” application describes an architecture which is inherently resilient and scalable, being event-driven at the core, and using asynchronous communication between components. In the course, I compare that architecture to a classic n-tier approach, and go on to build out an app which exhibits all the reactive traits: responsive, event-driven, scalable and resilient. I use a suite of technologies which are enablers for all those traits: ASP.NET SignalR for presentation, with server push notifications to the user Messaging in the middle layer for asynchronous communication between presentation and compute Azure Service Bus Queues and Topics AWS Simple Queue Service AWS Simple Notification Service MongoDB at the storage layer for easy HA and scale, with minimal locking under load. Starting with a couple of console apps to demonstrate message sending, I build the solution up over 7 modules, deploying to Azure and AWS and running the app across both clouds concurrently for the whole stack - web servers, messaging infrastructure, message handlers and database servers. I demonstrating failover by killing off bits of infrastructure, and show how a reactive app deployed across two clouds can survive machine failure, data centre failure and even whole cloud failure. The course finishes by configuring auto-scaling in AWS and Azure for the compute and presentation layers, and running a load test with blitz.io. The test pushes masses of load into the app, which is deployed across four data centres in Azure and AWS, and the infrastructure scales up seamlessly to meet the load – the blitz report is pretty impressive: That’s 99.9% success rate for hits to the website, with the potential to serve over 36,000,000 hits per day – all from a few hours’ build time, and a fairly limited set of auto-scale configurations. When the load stops, the infrastructure scales back down again to a minimal set of servers for high availability, so the app doesn’t cost much to host unless it’s getting a lot of traffic. This is my third course for Pluralsight, with Nginx and PHP Fundamentals and Caching in the .NET Stack: Inside-Out released earlier this year. Now that it’s out, I’m starting on the fourth one, which is focused on C#, and should be out by the end of the year.

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  • Why would you dual-run an app on Azure and AWS?

    - by Elton Stoneman
    Originally posted on: http://geekswithblogs.net/EltonStoneman/archive/2013/11/10/why-would-you-dual-run-an-app-on-azure-and-aws.aspxI had this question from a viewer of my Pluralsight course, Implementing the Reactive Manifesto with Azure and AWS, and thought I’d publish the response. So why would you dual-run your cloud app by hosting it on Azure and AWS? Sounds like a lot of extra development and management overhead. Well the most compelling reasons are reliability and portability. In 2012 I was working for a client who was making a big investment in the cloud, and at the end of the year we published their first external API for business partners. It was hosted in Azure and used some really nice features to route back into existing on-premise services. We were able to publish a clean, simple API to partners, and hide away the underlying complexity of the internal services while still leveraging them to do all the work. Two days after we went live, we were hit by the Azure SSL certificate expiry outage, and our API was unavailable for the best part of 3 days. Fortunately we had planned a gradual roll-out to partners, so the impact was minimal, but we’d been intending to ramp up quickly, and if the outage had happened a week or two later we would have been in a very bad place. Not least because our app could only run on Azure, we couldn’t package it up for another service without going back and reworking the code. More recently AWS had an issue with a networking device in one of their data centres which caused an outage that took the best part of a day to resolve. In both scenarios the SLAs are worthless, as you’ll get back a small percentage of your cloud expenditure, which is going to be negligible compared to your costs in dealing with the outage. And if your app is built specifically for AWS or Azure then if there’s an extended outage you can’t just deploy it onto a new set of kit from a different supplier. And the chances are pretty good there will be another extended outage, both for Microsoft and for Amazon. But the chances are small that it will happen to both at the same time. So my basic guidance has been: ignore the SLAs, go for better uptime by using two clouds. As soon as you need to scale beyond a single instance, start by scaling out to another cloud. Then scale out to different data centres in both clouds. Then you’ve got dual-cloud, quadruple-datacentre redundancy, so any more scaling you need can be left to the clouds to auto-scale themselves. By running in both clouds, you’ve made your app portable, so in the highly unlikely event that both AWS and Azure go down in multiple regions, you’ll have a deployment package which will let you spin up a new stack on yet another cloud, without having to rework your solution.

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  • AWS .NET SDK v2: setting up queues and topics

    - by Elton Stoneman
    Originally posted on: http://geekswithblogs.net/EltonStoneman/archive/2013/10/13/aws-.net-sdk-v2-setting-up-queues-and-topics.aspxFollowing on from my last post, reading from SQS queues with the new SDK is easy stuff, but linking a Simple Notification Service topic to an SQS queue is a bit more involved. The AWS model for topics and subscriptions is a bit more advanced than in Azure Service Bus. SNS lets you have subscribers on multiple different channels, so you can send a message which gets relayed to email address, mobile apps and SQS queues all in one go. As the topic owner, when you request a subscription on any channel, the owner needs to confirm they’re happy for you to send them messages. With email subscriptions, the user gets a confirmation request from Amazon which they need to reply to before they start getting messages. With SQS, you need to grant the topic permission to write to the queue. If you own both the topic and the queue, you can do it all in code with the .NET SDK. Let’s say you want to create a new topic, a new queue as a topic subscriber, and link the two together. Creating the topic is easy with the SNS client (which has an expanded name, AmazonSimpleNotificationServiceClient, compare to the SQS class which is just called QueueClient): var request = new CreateTopicRequest(); request.Name = TopicName; var response = _snsClient.CreateTopic(request); TopicArn = response.TopicArn; In the response from AWS (which I’m assuming is successful), you get an ARN – Amazon Resource Name – which is the unique identifier for the topic. We create the queue using the same code from my last post, AWS .NET SDK v2: the message-pump pattern, and then we need to subscribe the queue to the topic. The topic creates the subscription request: var response = _snsClient.Subscribe(new SubscribeRequest { TopicArn = TopicArn, Protocol = "sqs", Endpoint = _queueClient.QueueArn }); That response will give you an ARN for the subscription, which you’ll need if you want to set attributes like RawMessageDelivery. Then the SQS client needs to confirm the subscription by allowing the topic to send messages to it. The SDK doesn’t give you a nice mechanism for doing that, so I’ve extended my AWS wrapper with a method that encapsulates it: internal void AllowSnsToSendMessages(TopicClient topicClient) { var policy = Policies.AllowSendFormat.Replace("%QueueArn%", QueueArn).Replace("%TopicArn%", topicClient.TopicArn); var request = new SetQueueAttributesRequest(); request.Attributes.Add("Policy", policy); request.QueueUrl = QueueUrl; var response = _sqsClient.SetQueueAttributes(request); } That builds up a policy statement, which gets added to the queue as an attribute, and specifies that the topic is allowed to send messages to the queue. The statement itself is a JSON block which contains the ARN of the queue, the ARN of the topic, and an Allow effect for the sqs:SendMessage action: public const string AllowSendFormat= @"{ ""Statement"": [ { ""Sid"": ""MySQSPolicy001"", ""Effect"": ""Allow"", ""Principal"": { ""AWS"": ""*"" }, ""Action"": ""sqs:SendMessage"", ""Resource"": ""%QueueArn%"", ""Condition"": { ""ArnEquals"": { ""aws:SourceArn"": ""%TopicArn%"" } } } ] }"; There’s a new gist with an updated QueueClient and a new TopicClient here: Wrappers for the SQS and SNS clients in the AWS SDK for .NET v2. Both clients have an Ensure() method which creates the resource, so if you want to create a topic and a subscription you can use:  var topicClient = new TopicClient(“BigNews”, “ImListening”); And the topic client has a Subscribe() method, which calls into the message pump on the queue client: topicClient.Subscribe(x=>Log.Debug(x.Body)); var message = {}; //etc. topicClient.Publish(message); So you can isolate all the fiddly bits and use SQS and SNS with a similar interface to the Azure SDK.

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  • Monitoring Windows Azure Service Bus Endpoint with BizTalk 360?

    - by Michael Stephenson
    I'm currently working with a customer who is undergoing an initiative to expose some of their line of business applications to external partners and SAAS applications and as part of this we have been looking at using the Windows Azure Service Bus. For the first part of the project we were focused on some synchronous request response scenarios where an external application would use the Service Bus relay functionality to get data from some internal applications. When we were looking at the operational monitoring side of the solution it was obvious that although most of the normal server monitoring capabilities would be required for the on premise components we would have to look at new approaches to validate that the operation of the service from outside of the organization was working as expected. A number of months ago one of my colleagues Elton Stoneman wrote about an approach I have introduced with a number of clients in the past where we implement a diagnostics service in each service component we build. This service would allow us to make a call which would flex some of the working parts of the system to prove it was working within any SLA. This approach is discussed on the following article: http://geekswithblogs.net/EltonStoneman/archive/2011/12/12/the-value-of-a-diagnostics-service.aspx In our solution we wanted to take the same approach but we had to consider that the service clients were external to the service. We also had to consider that by going through Windows Azure Service Bus it's not that easy to make most of your standard monitoring solutions just give you an easy way to do this. In a previous article I have described how you can use BizTalk 360 to monitor things using a custom extension to the Web Endpoint Manager and I felt that we could use this approach to provide an excellent way to monitor our service bus endpoint. The previous article is available on the following link: http://geekswithblogs.net/michaelstephenson/archive/2012/09/12/150696.aspx   The Monitoring Solution BizTalk 360 currently has an easy way to hook up the endpoint manager to a url which it will then call and if a successful response is returned it then considers the endpoint to be in a healthy state. We would take advantage of this by creating an ASP.net web page which would be called by BizTalk 360 and behind this page we would implement the functionality to call the diagnostics service on our Service Bus endpoint. The ASP.net page could include logic to work out how to handle the response from the diagnostics service. For example if the overall result of the diagnostics service was successful but the call to the diagnostics service was longer than a certain amount of time then we could return an error and indicate the service is taking too long. The following diagram illustrates the monitoring pattern.   The diagnostics service which is hosted in the line of business application allows us to ping a simple message through the Azure Service Bus relay to the WCF services in the LOB application and we they get a response back indicating that the service is working fine. To implement this I used the exact same approach I described in my previous post to create a custom web page which calls the diagnostics service and then it would return an HTTP response code which would depend on the error condition returned or a 200 if it was successful. One of the limitations of this approach is that the competing consumer pattern for listening to messages from service bus means that you cannot guarantee which server would process your diagnostics check message but with BizTalk 360 you could simply add multiple endpoint checks so that it could access the individual on-premise web servers directly to ensure that each server is working fine and then check that messages can also be processed through the cloud. Conclusion It took me about 15 minutes to get a proof of concept of this up and running which was able to monitor our web services which had been exposed via Windows Azure Service Bus. I was then able to inherit all of the monitoring benefits of BizTalk 360 to provide an enterprise class monitoring solution for our cloud enabled API.

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  • Using CMS for App Configuration - Part 1, Deploying Umbraco

    - by Elton Stoneman
    Originally posted on: http://geekswithblogs.net/EltonStoneman/archive/2014/06/04/using-cms-for-app-configurationndashpart-1-deploy-umbraco.aspxSince my last post on using CMS for semi-static API content, How about a new platform for your next API… a CMS?, I’ve been using the idea for centralized app configuration, and this post is the first in a series that will walk through how to do that, step-by-step. The approach gives you a platform-independent, easily configurable way to specify your application configuration for different environments, with a built-in approval workflow, change auditing and the ability to easily rollback to previous settings. It’s like Azure Web and Worker Roles where you can specify settings that change at runtime, but it's not specific to Azure - you can use it for any app that needs changeable config, provided it can access the Internet. The series breaks down into four posts: Deploying Umbraco – the CMS that will store your configurable settings and the current values; Publishing your config – create a document type that encapsulates your settings and a template to expose them as JSON; Consuming your config – in .NET, a simple client that uses dynamic objects to access settings; Config lifecycle management – how to publish, audit, and rollback settings. Let’s get started. Deploying Umbraco There’s an Umbraco package on Azure Websites, so deploying your own instance is easy – but there are a couple of things to watch out for, so this step-by-step will put you in a good place. Create From Gallery The easiest way to get started is with an Azure subscription, navigate to add a new Website and then Create From Gallery. Under CMS, you’ll see an Umbraco package (currently at version 7.1.3): Configure Your App For high availability and scale, you’ll want your CMS on separate kit from anything else you have in Azure, so in the configuration of Umbraco I’d create a new SQL Azure database – which Umbraco will use to store all its content: You can use the free 20mb database option if you don’t have demanding NFRs, or if you’re just experimenting. You’ll need to specify a password for a SQL Server account which the Umbraco service will use, and changing from the default username umbracouser is probably wise. Specify Database Settings You can create a new database on an existing server if you have one, or create new. If you create a new server *do not* use the same username for the database server login as you used for the Umbraco account. If you do, the deployment will fail later. Think of this as the SQL Admin account that you can use for managing the db, the previous account was the service account Umbraco uses to connect. Make Tea If you have a fast kettle. It takes about two minutes for Azure to create and provision the website and the database. Install Umbraco So far we’ve deployed an empty instance of Umbraco using the Azure package, and now we need to browse to the site and complete installation. My Website was called my-app-config, so to complete installation I browse to http://my-app-config.azurewebsites.net:   Enter the credentials you want to use to login – this account will have full admin rights to the Umbraco instance. Note that between deploying your new Umbraco instance and completing installation in this step, anyone can browse to your website and complete the installation themselves with their own credentials, if they know the URL. Remote possibility, but it’s there. From this page *do not* click the big green Install button. If you do, Umbraco will configure itself with a local SQL Server CE database (.sdf file on the Web server), and ignore the SQL Azure database you’ve carefully provisioned and may be paying for. Instead, click on the Customize link and: Configure Your Database You need to enter your SQL Azure database details here, so you’ll have to get the server name from the Azure Management Console. You don’t need to explicitly grant access to your Umbraco website for the database though. Click Continue and you’ll be offered a “starter” website to install: If you don’t know Umbraco at all (but you are familiar with ASP.NET MVC) then a starter website is worthwhile to see how it all hangs together. But after a while you’ll have a bunch of artifacts in your CMS that you don’t want and you’ll have to work out which you can safely delete. So I’d click “No thanks, I do not want to install a starter website” and give yourself a clean Umbraco install. When it completes, the installation will log you in to the welcome screen for managing Umbraco – which you can access from http://my-app-config.azurewebsites.net/umbraco: That’s It Easy. Umbraco is installed, using a dedicated SQL Azure instance that you can separately scale, sync and backup, and ready for your content. In the next post, we’ll define what our app config looks like, and publish some settings for the dev environment.

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  • AWS: setting up auto-scale for EC2 instances

    - by Elton Stoneman
    Originally posted on: http://geekswithblogs.net/EltonStoneman/archive/2013/10/16/aws-setting-up-auto-scale-for-ec2-instances.aspxWith Amazon Web Services, there’s no direct equivalent to Azure Worker Roles – no Elastic Beanstalk-style application for .NET background workers. But you can get the auto-scale part by configuring an auto-scaling group for your EC2 instance. This is a step-by-step guide, that shows you how to create the auto-scaling configuration, which for EC2 you need to do with the command line, and then link your scaling policies to CloudWatch alarms in the Web console. I’m using queue size as my metric for CloudWatch,  which is a good fit if your background workers are pulling messages from a queue and processing them.  If the queue is getting too big, the “high” alarm will fire and spin up a new instance to share the workload. If the queue is draining down, the “low” alarm will fire and shut down one of the instances. To start with, you need to manually set up your app in an EC2 VM, for a background worker that would mean hosting your code in a Windows Service (I always use Topshelf). If you’re dual-running Azure and AWS, then you can isolate your logic in one library, with a generic entry point that has Start() and Stop()  functions, so your Worker Role and Windows Service are essentially using the same code. When you have your instance set up with the Windows Service running automatically, and you’ve tested it starts up and works properly from a reboot, shut the machine down and take an image of the VM, using Create Image (EBS AMI) from the Web Console: When that completes, you’ll have your own AMI which you can use to spin up new instances, and you’re ready to create your auto-scaling group. You need to dip into the command-line tools for this, so follow this guide to set up the AWS autoscale command line tool. Now we’re ready to go. 1. Create a launch configuration This launch configuration tells AWS what to do when a new instance needs to be spun up. You create it with the as-create-launch-config command, which looks like this: as-create-launch-config sc-xyz-launcher # name of the launch config --image-id ami-7b9e9f12 # id of the AMI you extracted from your VM --region eu-west-1 # which region the new instance gets created in --instance-type t1.micro # size of the instance to create --group quicklaunch-1 #security group for the new instance 2. Create an auto-scaling group The auto-scaling group links to the launch config, and defines the overall configuration of the collection of instances: as-create-auto-scaling-group sc-xyz-asg # auto-scaling group name --region eu-west-1 # region to create in --launch-configuration sc-xyz-launcher # name of the launch config to invoke for new instances --min-size 1 # minimum number of nodes in the group --max-size 5 # maximum number of nodes in the group --default-cooldown 300 # period to wait (in seconds) after each scaling event, before checking if another scaling event is required --availability-zones eu-west-1a eu-west-1b eu-west-1c # which availability zones you want your instances to be allocated in – multiple entries means EC@ will use any of them 3. Create a scale-up policy The policy dictates what will happen in response to a scaling event being triggered from a “high” alarm being breached. It links to the auto-scaling group; this sample results in one additional node being spun up: as-put-scaling-policy scale-up-policy # policy name -g sc-psod-woker-asg # auto-scaling group the policy works with --adjustment 1 # size of the adjustment --region eu-west-1 # region --type ChangeInCapacity # type of adjustment, this specifies a fixed number of nodes, but you can use PercentChangeInCapacity to make an adjustment relative to the current number of nodes, e.g. increasing by 50% 4. Create a scale-down policy The policy dictates what will happen in response to a scaling event being triggered from a “low” alarm being breached. It links to the auto-scaling group; this sample results in one node from the group being taken offline: as-put-scaling-policy scale-down-policy -g sc-psod-woker-asg "--adjustment=-1" # in Windows, use double-quotes to surround a negative adjustment value –-type ChangeInCapacity --region eu-west-1 5. Create a “high” CloudWatch alarm We’re done with the command line now. In the Web Console, open up the CloudWatch view and create a new alarm. This alarm will monitor your metrics and invoke the scale-up policy from your auto-scaling group, when the group is working too hard. Configure your metric – this example will fire the alarm if there are more than 10 messages in my queue for over a minute: Then link the alarm to the scale-up policy in your group: 6. Create a “low” CloudWatch alarm The opposite of step 4, this alarm will trigger when the instances in your group don’t have enough work to do (e.g fewer than 2 messages in the queue for 1 minute), and will invoke the scale-down policy. And that’s it. You don’t need your original VM as the auto-scale group has a minimum number of nodes connected. You can test out the scaling by flexing your CloudWatch metric – in this example, filling up a queue from a  stub publisher – and watching AWS create new nodes as required, then stopping the publisher and watch AWS kill off the spare nodes.

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  • Running a Mongo Replica Set on Azure VM Roles

    - by Elton Stoneman
    Originally posted on: http://geekswithblogs.net/EltonStoneman/archive/2013/10/15/running-a-mongo-replica-set-on-azure-vm-roles.aspxSetting up a MongoDB Replica Set with a bunch of Azure VMs is straightforward stuff. Here’s a step-by-step which gets you from 0 to fully-redundant 3-node document database in about 30 minutes (most of which will be spent waiting for VMs to fire up). First, create yourself 3 VM roles, which is the minimum number of nodes you need for high availability. You can use any OS that Mongo supports. This guide uses Windows but the only difference will be the mechanism for starting the Mongo service when the VM starts (Windows Service, daemon etc.) While the VMs are provisioning, download and install Mongo locally, so you can set up the replica set with the Mongo shell. We’ll create our replica set from scratch, doing one machine at a time (if you have a single node you want to upgrade to a replica set, it’s the same from step 3 onwards): 1. Setup Mongo Log into the first node, download mongo and unzip it to C:. Rename the folder to remove the version – so you have c:\MongoDB\bin etc. – and create a new folder for the logs, c:\MongoDB\logs. 2. Setup your data disk When you initialize a node in a replica set, Mongo pre-allocates a whole chunk of storage to use for data replication. It will use up to 5% of your data disk, so if you use a Windows VM image with a defsault 120Gb disk and host your data on C:, then Mongo will allocate 6Gb for replication. And that takes a while. Instead you can create yourself a new partition by shrinking down the C: drive in Computer Management, by say 10Gb, and then creating a new logical disk for your data from that spare 10Gb, which will be allocated as E:. Create a new folder, e:\data. 3. Start Mongo When that’s done, start a command line, point to the mongo binaries folder, install Mongo as a Windows Service, running in replica set mode, and start the service: cd c:\mongodb\bin mongod -logpath c:\mongodb\logs\mongod.log -dbpath e:\data -replSet TheReplicaSet –install net start mongodb 4. Open the ports Mongo uses port 27017 by default, so you need to allow access in the machine and in Azure. In the VM, open Windows Firewall and create a new inbound rule to allow access via port 27017. Then in the Azure Management Console for the VM role, under the Configure tab add a new rule, again to allow port 27017. 5. Initialise the replica set Start up your local mongo shell, connecting to your Azure VM, and initiate the replica set: c:\mongodb\bin\mongo sc-xyz-db1.cloudapp.net rs.initiate() This is the bit where the new node (at this point the only node) allocates its replication files, so if your data disk is large, this can take a long time (if you’re using the default C: drive with 120Gb, it may take so long that rs.initiate() never responds. If you’re sat waiting more than 20 minutes, start another instance of the mongo shell pointing to the same machine to check on it). Run rs.conf() and you should see one node configured. 6. Fix the host name for the primary – *don’t miss this one* For the first node in the replica set, Mongo on Windows doesn’t populate the full machine name. Run rs.conf() and the name of the primary is sc-xyz-db1, which isn’t accessible to the outside world. The replica set configuration needs the full DNS name of every node, so you need to manually rename it in your shell, which you can do like this: cfg = rs.conf() cfg.members[0].host = ‘sc-xyz-db1.cloudapp.net:27017’ rs.reconfig(cfg) When that returns, rs.conf() will have your full DNS name for the primary, and the other nodes will be able to connect. At this point you have a working database, so you can start adding documents, but there’s no replication yet. 7. Add more nodes For the next two VMs, follow steps 1 through to 4, which will give you a working Mongo database on each node, which you can add to the replica set from the shell with rs.add(), using the full DNS name of the new node and the port you’re using: rs.add(‘sc-xyz-db2.cloudapp.net:27017’) Run rs.status() and you’ll see your new node in STARTUP2 state, which means its initializing and replicating from the PRIMARY. Repeat for your third node: rs.add(‘sc-xyz-db3.cloudapp.net:27017’) When all nodes are finished initializing, you will have a PRIMARY and two SECONDARY nodes showing in rs.status(). Now you have high availability, so you can happily stop db1, and one of the other nodes will become the PRIMARY with no loss of data or service. Note – the process for AWS EC2 is exactly the same, but with one important difference. On the Azure Windows Server 2012 base image, the MongoDB release for 64-bit 2008R2+ works fine, but on the base 2012 AMI that release keeps failing with a UAC permission error. The standard 64-bit release is fine, but it lacks some optimizations that are in the 2008R2+ version.

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  • How about a new platform for your next API&hellip; a CMS?

    - by Elton Stoneman
    Originally posted on: http://geekswithblogs.net/EltonStoneman/archive/2014/05/22/how-about-a-new-platform-for-your-next-apihellip-a.aspxSay what? I’m seeing a type of API emerge which serves static or long-lived resources, which are mostly read-only and have a controlled process to update the data that gets served. Think of something like an app configuration API, where you want a central location for changeable settings. You could use this server side to store database connection strings and keep all your instances in sync, or it could be used client side to push changes out to all users (and potentially driving A/B or MVT testing). That’s a good candidate for a RESTful API which makes proper use of HTTP expiration and validation caching to minimise traffic, but really you want a front end UI where you can edit the current config that the API returns and publish your changes. Sound like a Content Mangement System would be a good fit? I’ve been looking at that and it’s a great fit for this scenario. You get a lot of what you need out of the box, the amount of custom code you need to write is minimal, and you get a whole lot of extra stuff from using CMS which is very useful, but probably not something you’d build if you had to put together a quick UI over your API content (like a publish workflow, fine-grained security and an audit trail). You typically use a CMS for HTML resources, but it’s simple to expose JSON instead – or to do content negotiation to support both, so you can open a resource in a browser and see a nice visual representation, or request it with: Accept=application/json and get the same content rendered as JSON for the app to use. Enter Umbraco Umbraco is an open source .NET CMS that’s been around for a while. It has very good adoption, a lively community and a good release cycle. It’s easy to use, has all the functionality you need for a CMS-driven API, and it’s scalable (although you won’t necessarily put much scale on the CMS layer). In the rest of this post, I’ll build out a simple app config API using Umbraco. We’ll define the structure of the configuration resource by creating a new Document Type and setting custom properties; then we’ll build a very simple Razor template to return configuration documents as JSON; then create a resource and see how it looks. And we’ll look at how you could build this into a wider solution. If you want to try this for yourself, it’s ultra easy – there’s an Umbraco image in the Azure Website gallery, so all you need to to is create a new Website, select Umbraco from the image and complete the installation. It will create a SQL Azure website to store all the content, as well as a Website instance for editing and accessing content. They’re standard Azure resources, so you can scale them as you need. The default install creates a starter site for some HTML content, which you can use to learn your way around (or just delete). 1. Create Configuration Document Type In Umbraco you manage content by creating and modifying documents, and every document has a known type, defining what properties it holds. We’ll create a new Document Type to describe some basic config settings. In the Settings section from the left navigation (spanner icon), expand Document Types and Master, hit the ellipsis and select to create a new Document Type: This will base your new type off the Master type, which gives you some existing properties that we’ll use – like the Page Title which will be the resource URL. In the Generic Properties tab for the new Document Type, you set the properties you’ll be able to edit and return for the resource: Here I’ve added a text string where I’ll set a default cache lifespan, an image which I can use for a banner display, and a date which could show the user when the next release is due. This is the sort of thing that sits nicely in an app config API. It’s likely to change during the life of the product, but not very often, so it’s good to have a centralised place where you can make and publish changes easily and safely. It also enables A/B and MVT testing, as you can change the response each client gets based on your set logic, and their apps will behave differently without needing a release. 2. Define the response template Now we’ve defined the structure of the resource (as a document), in Umbraco we can define a C# Razor template to say how that resource gets rendered to the client. If you only want to provide JSON, it’s easy to render the content of the document by building each property in the response (Umbraco uses dynamic objects so you can specify document properties as object properties), or you can support content negotiation with very little effort. Here’s a template to render the document as HTML or JSON depending on the Accept header, using JSON.NET for the API rendering: @inherits Umbraco.Web.Mvc.UmbracoTemplatePage @using Newtonsoft.Json @{ Layout = null; } @if(UmbracoContext.HttpContext.Request.Headers["accept"] != null &amp;&amp; UmbracoContext.HttpContext.Request.Headers["accept"] == "application/json") { Response.ContentType = "application/json"; @Html.Raw(JsonConvert.SerializeObject(new { cacheLifespan = CurrentPage.cacheLifespan, bannerImageUrl = CurrentPage.bannerImage, nextReleaseDate = CurrentPage.nextReleaseDate })) } else { <h1>App configuration</h1> <p>Cache lifespan: <b>@CurrentPage.cacheLifespan</b></p> <p>Banner Image: </p> <img src="@CurrentPage.bannerImage"> <p>Next Release Date: <b>@CurrentPage.nextReleaseDate</b></p> } That’s a rough-and ready example of what you can do. You could make it completely generic and just render all the document’s properties as JSON, but having a specific template for each resource gives you control over what gets sent out. And the templates are evaluated at run-time, so if you need to change the output – or extend it, say to add caching response headers – you just edit the template and save, and the next client request gets rendered from the new template. No code to build and ship. 3. Create the content With your document type created, in  the Content pane you can create a new instance of that document, where Umbraco gives you a nice UI to input values for the properties we set up on the Document Type: Here I’ve set the cache lifespan to an xs:duration value, uploaded an image for the banner and specified a release date. Each property gets the appropriate input control – text box, file upload and date picker. At the top of the page is the name of the resource – myapp in this example. That specifies the URL for the resource, so if I had a DNS entry pointing to my Umbraco instance, I could access the config with a URL like http://static.x.y.z.com/config/myapp. The setup is all done now, so when we publish this resource it’ll be available to access.  4. Access the resource Now if you open  that URL in the browser, you’ll see the HTML version rendered: - complete with the  image and formatted date. Umbraco lets you save changes and preview them before publishing, so the HTML view could be a good way of showing editors their changes in a usable view, before they confirm them. If you browse the same URL from a REST client, specifying the Accept=application/json request header, you get this response:   That’s the exact same resource, with a managed UI to publish it, being accessed as HTML or JSON with a tiny amount of effort. 5. The wider landscape If you have fairy stable content to expose as an API, I think  this approach is really worth considering. Umbraco scales very nicely, but in a typical solution you probably wouldn’t need it to. When you have additional requirements, like logging API access requests - but doing it out-of-band so clients aren’t impacted, you can put a very thin API layer on top of Umbraco, and cache the CMS responses in your API layer:   Here the API does a passthrough to CMS, so the CMS still controls the content, but it caches the response. If the response is cached for 1 minute, then Umbraco only needs to handle 1 request per minute (multiplied by the number of API instances), so if you need to support 1000s of request per second, you’re scaling a thin, simple API layer rather than having to scale the more complex CMS infrastructure (including the database). This diagram also shows an approach to logging, by asynchronously publishing a message to a queue (Redis in this case), which can be picked up later and persisted by a different process. Does it work? Beautifully. Using Azure, I spiked the solution above (including the Redis logging framework which I’ll blog about later) in half a day. That included setting up different roles in Umbraco to demonstrate a managed workflow for publishing changes, and a couple of document types representing different resources. Is it maintainable? We have three moving parts, which are all managed resources in Azure –  an Azure Website for Umbraco which may need a couple of instances for HA (or may not, depending on how long the content can be cached), a message queue (Redis is in preview in Azure, but you can easily use Service Bus Queues if performance is less of a concern), and the Web Role for the API. Two of the components are off-the-shelf, from open source projects, and the only custom code is the API which is very simple. Does it scale? Pretty nicely. With a single Umbraco instance running as an Azure Website, and with 4x instances for my API layer (Standard sized Web Roles), I got just under 4,000 requests per second served reliably, with a Worker Role in the background saving the access logs. So we had a nice UI to publish app config changes, with a friendly Web preview and a publishing workflow, capable of supporting 14 million requests in an hour, with less than a day’s effort. Worth considering if you’re publishing long-lived resources through your API.

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