We are using the following method in a Stateful Service on Service-Fabric. The service has partitions. Sometimes we get a FabricNotReadableException from this peace of code.
public async Task HandleEvent(EventHandlerMessage message)
{
var queue = await StateManager.GetOrAddAsync<IReliableQueue<EventHandlerMessage>>(EventHandlerServiceConstants.EventHandlerQueueName);
using(ITransaction tx = StateManager.CreateTransaction())
{
await queue.EnqueueAsync(tx, message);
await tx.CommitAsync();
}
}
Does that mean that the partition is down and is being moved? Of that we hit a secondary partition? Because there is also a FabricNotPrimaryException that is being raised in some cases.
I have seen the MSDN link (https://msdn.microsoft.com/en-us/library/azure/system.fabric.fabricnotreadableexception.aspx). But what does
Represents an exception that is thrown when a partition cannot accept reads.
mean? What happened that a partition cannot accept a read?
Under the covers Service Fabric has several states that can impact whether a given replica can safely serve reads and writes. They are:
Granted (you can think of this as normal operation)
Not Primary
No Write Quorum (again mainly impacting writes)
Reconfiguration Pending
FabricNotPrimaryException which you mention can be thrown whenever a write is attempted on a replica which is not currently the Primary, and maps to the NotPrimary state.
FabricNotReadableException maps to the other states (you don't really need to worry or differentiate between them), and can happen in a variety of cases. One example is if the replica you are trying to perform the read on is a "Standby" replica (a replica which was down and which has been recovered, but there are already enough active replicas in the replica set). Another example is if the replica is a Primary but is being closed (say due to an upgrade or because it reported fault), or if it is currently undergoing a reconfiguration (say for example that another replica is being added). All of these conditions will result in the replica not being able to satisfy writes for a small amount of time due to certain safety checks and atomic changes that Service Fabric needs to handle under the hood.
You can consider FabricNotReadableException retriable. If you see it, just try the call again and eventually it will resolve into either NotPrimary or Granted. If you get FabricNotPrimary exception, generally this should be thrown back to the client (or the client in some way notified) that it needs to re-resolve in order to find the current Primary (the default communication stacks that Service Fabric ships take care of watching for non-retriable exceptions and re-resolving on your behalf).
There are two current known issues with FabricNotReadableException.
FabricNotReadableException should have two variants. The first should be explicitly retriable (FabricTransientNotReadableException) and the second should be FabricNotReadableException. The first version (Transient) is the most common and is probably what you are running into, certainly what you would run into in the majority of cases. The second (non-transient) would be returned in the case where you end up talking to a Standby replica. Talking to a standby won't happen with the out of the box transports and retry logic, but if you have your own it is possible to run into it.
The other issue is that today the FabricNotReadableException should be deriving from FabricTransientException, making it easier to determine what the correct behavior is.
Posted as an answer (to asnider's comment - Mar 16 at 17:42) because it was too long for comments! :)
I am also stuck in this catch 22. My svc starts and immediately receives messages. I want to encapsulate the service startup in OpenAsync and set up some ReliableDictionary values, then start receiving message. However, at this point the Fabric is not Readable and I need to split this "startup" between OpenAsync and RunAsync :(
RunAsync in my service and OpenAsync in my client also seem to have different Cancellation tokens, so I need to work around how to deal with this too. It just all feels a bit messy. I have a number of ideas on how to tidy this up in my code but has anyone come up with an elegant solution?
It would be nice if ICommunicationClient had a RunAsync interface that was called when the Fabric becomes ready/readable and cancelled when the Fabric shuts down the replica - this would seriously simplify my life. :)
I was running into the same problem. My listener was starting up before the main thread of the service. I queued the list of listeners needing to be started, and then activated them all early on in the main thread. As a result, all messages coming in were able to be handled and placed into the appropriate reliable storage. My simple solution (this is a service bus listener):
public Task<string> OpenAsync (CancellationToken cancellationToken)
{
string uri;
Start ();
uri = "<your endpoint here>";
return Task.FromResult (uri);
}
public static object lockOperations = new object ();
public static bool operationsStarted = false;
public static List<ClientAuthorizationBusCommunicationListener> pendingStarts = new List<ClientAuthorizationBusCommunicationListener> ();
public static void StartOperations ()
{
lock (lockOperations)
{
if (!operationsStarted)
{
foreach (ClientAuthorizationBusCommunicationListener listener in pendingStarts)
{
listener.DoStart ();
}
operationsStarted = true;
}
}
}
private static void QueueStart (ClientAuthorizationBusCommunicationListener listener)
{
lock (lockOperations)
{
if (operationsStarted)
{
listener.DoStart ();
}
else
{
pendingStarts.Add (listener);
}
}
}
private void Start ()
{
QueueStart (this);
}
private void DoStart ()
{
ServiceBus.WatchStatusChanges (HandleStatusMessage,
this.clientId,
out this.subscription);
}
========================
In the main thread, you call the function to start listener operations:
protected override async Task RunAsync (CancellationToken cancellationToken)
{
ClientAuthorizationBusCommunicationListener.StartOperations ();
...
This problem likely manifested itself here as the bus in question already had messages and started firing the second the listener was created. Trying to access anything in state manager was throwing the exception you were asking about.
I consume a WCF service asynchronously. If I can't connect to the service or an exception occurs it went to faulted state and it writes the error to the Error property of the AsyncCompletedEventArgs.
What do I have to do with the service client? I cannot close it because it would throw a CommunicationObjectFaultedException. What else do I have to do after logging the error?
Here's my code:
MyServiceClient serviceClient = new MyServiceClient();
//Close the connection with the Service or log an error
serviceClient.JustAMethod += (object sender, AsyncCompletedEventArgs args) =>
{
if (args.Error != null)
{
//Log error
ErrorHandler.Log(args.Error);
}
else
{
serviceClient.Close();
}
};
//Call the service
serviceClient.JustAMethodAsync();
You can abort it, and create a new one. Here's a fragment from a class I wrote that deals with that issue. Everything that it touches here is legal to touch when the client is in the faulted state.
if (_client.InnerChannel.State == CommunicationState.Faulted)
{
_client.Abort();
_client = new TServiceClient();
}
TServiceClient is any subclass of System.ServiceModel.ClientBase<TIClientInterface>.
I wrote that because I've had constant access issues calling webservices from the server end of an MVC4 web app, with the browser client accessing the page via RDS.
However, as of now, the above code isn't in use. For reasons I don't understand, it had a lot more access-denied exceptions than the simplest approach of invariably creating a new client for every call, and disposing it after. I never bother checking faulted state because I never use them for more than one call anyway.
using (var cli = new Blah.Blah.FooWCFClient())
{
_stuff = cli.GetStuff();
}
...in a try/catch, of course. If you see any issues with the client-caching/Abort approach, I'd suggest you try creating a new client for every call. Maybe it costs a few cycles, but it's silly to call a web service and then start worrying about runtime efficiency. That horse has left the barn.
I don't know how this would interact with the asynchronous business, other than a vague intuition about keeping things simple and not sharing anything across threads.
Welcome to my nightmare. I haven't yet identified the cause of our access issues, but I doubt things can possibly be that bad for you. So I hope at least one of those two options will work out.
UPDATE
Here's some .tt-generated service wrapper code from our XAML application. Every web service call method gets wrapped like this, and it's been bulletproof for years. I would recommend doing essentially this:
public static POCO.Thing GetThing(int thingID)
{
var proxy = ServiceFactory.CreateNewFooWCFClientInstance();
try
{
var returnValue = proxy.GetThing(thingID);
proxy.Close();
return returnValue;
}
catch(Exception ex)
{
// ***********************************
// Error logging boilerplate redacted
// ***********************************
proxy.Abort();
throw;
}
}
I have a feeling that it's just as well if you don't reuse WCF client objects at all.
There is not much you can do with it. Create a new one and let the garbage collector collect the other one.
I've got a C# console app running on Windows Server 2003 whose purpose is to read a table called Notifications and a field called "NotifyDateTime" and send an email when that time is reached. I have it scheduled via Task Scheduler to run hourly, check to see if the NotifyDateTime falls within that hour, and then send the notifications.
It seems like because I have the notification date/times in the database that there should be a better way than re-running this thing every hour.
Is there a lightweight process/console app I could leave running on the server that reads in the day's notifications from the table and issues them exactly when they're due?
I thought service, but that seems overkill.
My suggestion is to write simple application, which uses Quartz.NET.
Create 2 jobs:
First, fires once a day, reads all awaiting notification times from database planned for that day, creates some triggers based on them.
Second, registered for such triggers (prepared by the first job), sends your notifications.
What's more,
I strongly advice you to create windows service for such purpose, just not to have lonely console application constantly running. It can be accidentally terminated by someone who have access to the server under the same account. What's more, if the server will be restarted, you have to remember to turn such application on again, manually, while the service can be configured to start automatically.
If you're using web application you can always have this logic hosted e.g. within IIS Application Pool process, although it is bad idea whatsoever. It's because such process is by default periodically restarted, so you should change its default configuration to be sure it is still working in the middle of the night, when application is not used. Unless your scheduled tasks will be terminated.
UPDATE (code samples):
Manager class, internal logic for scheduling and unscheduling jobs. For safety reasons implemented as a singleton:
internal class ScheduleManager
{
private static readonly ScheduleManager _instance = new ScheduleManager();
private readonly IScheduler _scheduler;
private ScheduleManager()
{
var properties = new NameValueCollection();
properties["quartz.scheduler.instanceName"] = "notifier";
properties["quartz.threadPool.type"] = "Quartz.Simpl.SimpleThreadPool, Quartz";
properties["quartz.threadPool.threadCount"] = "5";
properties["quartz.threadPool.threadPriority"] = "Normal";
var sf = new StdSchedulerFactory(properties);
_scheduler = sf.GetScheduler();
_scheduler.Start();
}
public static ScheduleManager Instance
{
get { return _instance; }
}
public void Schedule(IJobDetail job, ITrigger trigger)
{
_scheduler.ScheduleJob(job, trigger);
}
public void Unschedule(TriggerKey key)
{
_scheduler.UnscheduleJob(key);
}
}
First job, for gathering required information from the database and scheduling notifications (second job):
internal class Setup : IJob
{
public void Execute(IJobExecutionContext context)
{
try
{
foreach (var kvp in DbMock.ScheduleMap)
{
var email = kvp.Value;
var notify = new JobDetailImpl(email, "emailgroup", typeof(Notify))
{
JobDataMap = new JobDataMap {{"email", email}}
};
var time = new DateTimeOffset(DateTime.Parse(kvp.Key).ToUniversalTime());
var trigger = new SimpleTriggerImpl(email, "emailtriggergroup", time);
ScheduleManager.Instance.Schedule(notify, trigger);
}
Console.WriteLine("{0}: all jobs scheduled for today", DateTime.Now);
}
catch (Exception e) { /* log error */ }
}
}
Second job, for sending emails:
internal class Notify: IJob
{
public void Execute(IJobExecutionContext context)
{
try
{
var email = context.MergedJobDataMap.GetString("email");
SendEmail(email);
ScheduleManager.Instance.Unschedule(new TriggerKey(email));
}
catch (Exception e) { /* log error */ }
}
private void SendEmail(string email)
{
Console.WriteLine("{0}: sending email to {1}...", DateTime.Now, email);
}
}
Database mock, just for purposes of this particular example:
internal class DbMock
{
public static IDictionary<string, string> ScheduleMap =
new Dictionary<string, string>
{
{"00:01", "foo#gmail.com"},
{"00:02", "bar#yahoo.com"}
};
}
Main entry of the application:
public class Program
{
public static void Main()
{
FireStarter.Execute();
}
}
public class FireStarter
{
public static void Execute()
{
var setup = new JobDetailImpl("setup", "setupgroup", typeof(Setup));
var midnight = new CronTriggerImpl("setuptrigger", "setuptriggergroup",
"setup", "setupgroup",
DateTime.UtcNow, null, "0 0 0 * * ?");
ScheduleManager.Instance.Schedule(setup, midnight);
}
}
Output:
If you're going to use service, just put this main logic to the OnStart method (I advice to start the actual logic in a separate thread not to wait for the service to start, and the same avoid possible timeouts - not in this particular example obviously, but in general):
protected override void OnStart(string[] args)
{
try
{
var thread = new Thread(x => WatchThread(new ThreadStart(FireStarter.Execute)));
thread.Start();
}
catch (Exception e) { /* log error */ }
}
If so, encapsulate the logic in some wrapper e.g. WatchThread which will catch any errors from the thread:
private void WatchThread(object pointer)
{
try
{
((Delegate) pointer).DynamicInvoke();
}
catch (Exception e) { /* log error and stop service */ }
}
You trying to implement polling approach, where a job is monitoring a record in DB for any changes.
In this case we are trying to hit DB for periodic time, so if the one hour delay reduced to 1 min later stage, then this solution turns to performance bottle neck.
Approach 1
For this scenario please use Queue based approach to avoid any issues, you can also scale up number of instances if you are sending so many emails.
I understand there is a program updates NotifyDateTime in a table, the same program can push a message to Queue informing that there is a notification to handle.
There is a windows service looking after this queue for any incoming messages, when there is a message it performs the required operation (ie sending email).
Approach 2
http://msdn.microsoft.com/en-us/library/vstudio/zxsa8hkf(v=vs.100).aspx
you can also invoke C# code from SQL Server Stored procedure if you are using MS SQL Server. but in this case you are making use of your SQL server process to send mail, which is not a good practice.
However you can invoke a web service, OR WCF service which can send emails.
But Approach 1 is error free, Scalable , Track-able, Asynchronous , and doesn't trouble your data base OR APP, you have different process to send email.
Queues
Use MSMQ which is part of windows server
You can also try https://www.rabbitmq.com/dotnet.html
Pre-scheduled tasks (at undefined times) are generally a pain to handle, as opposed to scheduled tasks where Quartz.NET seems well suited.
Furthermore, another distinction is to be made between fire-and-forget for tasks that shouldn't be interrupted/change (ex. retries, notifications) and tasks that need to be actively managed (ex. campaign or communications).
For the fire-and-forget type tasks a message queue is well suited. If the destination is unreliable, you will have to opt for retry levels (ex. try send (max twice), retry after 5 minutes, try send (max twice), retry after 15 minutes) that at least require specifying message specific TTL's with a send and retry queue. Here's an explanation with a link to code to setup a retry level queue
The managed pre-scheduled tasks will require that you use a database queue approach (Click here for a CodeProject article on designing a database queue for scheduled tasks)
. This will allow you to update, remove or reschedule notifications given you keep track of ownership identifiers (ex. specifiy a user id and you can delete all pending notifications when the user should no longer receive notifications such as being deceased/unsubscribed)
Scheduled e-mail tasks (including any communication tasks) require finer grained control (expiration, retry and time-out mechanisms). The best approach to take here is to build a state machine that is able to process the e-mail task through its steps (expiration, pre-validation, pre-mailing steps such as templating, inlining css, making links absolute, adding tracking objects for open tracking, shortening links for click tracking, post-validation and sending and retrying).
Hopefully you are aware that the .NET SmtpClient isn't fully compliant with the MIME specifications and that you should be using a SAAS e-mail provider such as Amazon SES, Mandrill, Mailgun, Customer.io or Sendgrid. I'd suggest you look at Mandrill or Mailgun. Also if you have some time, take a look at MimeKit which you can use to construct MIME messages for the providers allow sending raw e-mail and doesn't necessarily support things like attachments/custom headers/DKIM signing.
I hope this sets you on the right path.
Edit
You will have to use a service to poll at specific intervals (ex. 15 seconds or 1 minute). The database load can be somewhat negated by checkout out a certain amount of due tasks at a time and keeping an internal pool of messages due for sending (with a time-out mechanism in place). When there's no messages returned, just 'sleep' the polling for a while. I'd would advise against building such a system out against a single table in a database - instead design an independant e-mail scheduling system that you can integrate with.
I would turn it into a service instead.
You can use System.Threading.Timer event handler for each of the scheduled times.
Scheduled tasks can be scheduled to run just once at a specific time (as opposed to hourly, daily, etc.), so one option would be to create the scheduled task when the specific field in your database changes.
You don't mention which database you use, but some databases support the notion of a trigger, e.g. in SQL: http://technet.microsoft.com/en-us/library/ms189799.aspx
If you know when the emails need to be sent ahead of time then I suggest that you use a wait on an event handle with the appropriate timeout. At midnight look at the table then wait on an event handle with the timeout set to expire when the next email needs to be sent. After sending the email wait again with the timeout set based on the next mail that should be sent.
Also, based on your description, this should probably be implemented as a service but it is not required.
I have been dealing with the same problem about three years ago. I have changed the process several times before it was good enough, I tell you why:
First implementation was using special deamon from webhosting which called the IIS website. The website checked the caller IP and then check the database and send emails. This was working until one day, when I got a lot of very dirty emails from the users that I have totally spammed their mailboxes. The drawback of keeping email in database and sending from SMTP email is that there is NOTHING which ensure DB to SMTP transaction. You are never sure if the email has been successfully sent or not. Sending email can be successfull, can failed or it can be false positive or it can be false negative (SMTP client tells you, that the email was not sent, but it was). There was some problem with SMTP server and the server returned false(email not send), but the email was sent. The daemon was resending the email every hour the whole day before the dirty emails appears.
Second implementation: To prevent spamming, I have changed the algorithm, that the email is considered to be sent even if it failed (my email notification was not too important). My first advice is: "Don't launch the deamon too often, because this false negative smtp error makes users upset."
After several month there were some changes on the server and the daemon was not working well. I got the idea from the stackoverflow: bind the .NET timer to the web application domain. It wasn't good idea, because it seems, that IIS can restart application from time to time because of memory leaks and the timer never fires if the restarts are more often then timer ticks.
The last implementation. Windows scheduler every hour fires python batch which read local website. This fire ASP.NET code. The advantage is that time windows scheduler call the the local batch and website reliably. IIS doesn't hang, it has restart ability. The timer site is part of my website, it is still one projects. (you can use console app instead). Simple is better. It just works!
Your first choice is the correct option in my opinion. Task Scheduler is the MS recommended way to perform periodic jobs. Moreover it's flexible, can reports failures to ops, is optimized and amortized amongst all tasks in the system, ...
Creating any console-kind app that runs all the time is fragile. It can be shutdown by anyone, needs an open seesion, doesn't restart automatically, ...
The other option is creating some kind of service. It's guaranteed to be running all the time, so that would at least work. But what was your motivation?
"It seems like because I have the notification date/times in the database that there should be a better way than re-running this thing every hour."
Oh yeah optimization... So you want to add a new permanently running service to your computer so that you avoid one potentially unrequired SQL query every hour? The cure looks worse than the disease to me.
And I didn't mention all the drawbacks of the service. On one hand, your task uses no resource when it doesn't run. It's very simple, lightweight and the query efficient (provided you have the right index).
On the other hand, if your service crashes it's probably gone for good. It needs a way to be notified of new e-mails that may need to be sent earlier than what's currently scheduled. It permanently uses computer resources, such as memory. Worse, it may contain memory leaks.
I think that the cost/benefit ratio is very low for any solution other than the trivial periodic task.
I wonder what the best way is to publish and subscribe to channels using BookSleeve. I currently implement several static methods (see below) that let me publish content to a specific channel with the newly created channel being stored in private static Dictionary<string, RedisSubscriberConnection> subscribedChannels;.
Is this the right approach, given I want to publish to channels and subscribe to channels within the same application (note: my wrapper is a static class). Is it enough to create one channel even I want to publish and subscribe? Obviously I would not publish to the same channel than I would subscribe to within the same application. But I tested it and it worked:
RedisClient.SubscribeToChannel("Test").Wait();
RedisClient.Publish("Test", "Test Message");
and it worked.
Here my questions:
1) Will it be more efficient to setup a dedicated publish channel and a dedicated subscribe channel rather than using one channel for both?
2) What is the difference between "channel" and "PatternSubscription" semantically? My understanding is that I can subscribe to several "topics" through PatternSubscription() on the same channel, correct? But if I want to have different callbacks invoked for each "topic" I would have to setup a channel for each topic correct? Is that efficient or would you advise against that?
Here the code snippets.
Thanks!!!
public static Task<long> Publish(string channel, byte[] message)
{
return connection.Publish(channel, message);
}
public static Task SubscribeToChannel(string channelName)
{
string subscriptionString = ChannelSubscriptionString(channelName);
RedisSubscriberConnection channel = connection.GetOpenSubscriberChannel();
subscribedChannels[subscriptionString] = channel;
return channel.PatternSubscribe(subscriptionString, OnSubscribedChannelMessage);
}
public static Task UnsubscribeFromChannel(string channelName)
{
string subscriptionString = ChannelSubscriptionString(channelName);
if (subscribedChannels.Keys.Contains(subscriptionString))
{
RedisSubscriberConnection channel = subscribedChannels[subscriptionString];
Task task = channel.PatternUnsubscribe(subscriptionString);
//remove channel subscription
channel.Close(true);
subscribedChannels.Remove(subscriptionString);
return task;
}
else
{
return null;
}
}
private static string ChannelSubscriptionString(string channelName)
{
return channelName + "*";
}
1: there is only one channel in your example (Test); a channel is just the name used for a particular pub/sub exchange. It is, however, necessary to use 2 connections due to specifics of how the redis API works. A connection that has any subscriptions cannot do anything else except:
listen to messages
manage its own subscriptions (subscribe, psubscribe, unsubscribe, punsubscribe)
However, I don't understand this:
private static Dictionary<string, RedisSubscriberConnection>
You shouldn't need more than one subscriber connection unless you are catering for something specific to you. A single subscriber connection can handle an arbitrary number of subscriptions. A quick check on client list on one of my servers, and I have one connection with (at time of writing) 23,002 subscriptions. Which could probably be reduced, but: it works.
2: pattern subscriptions support wildcards; so rather than subscribing to /topic/1, /topic/2/ etc you could subscribe to /topic/*. The name of the actual channel used by publish is provided to the receiver as part of the callback signature.
Either can work. It should be noted that the performance of publish is impacted by the total number of unique subscriptions - but frankly it is still stupidly fast (as in: 0ms) even if you have tens of multiple thousands of subscribed channels using subscribe rather than psubscribe.
But from publish
Time complexity: O(N+M) where N is the number of clients subscribed to the receiving channel and M is the total number of subscribed patterns (by any client).
I recommend reading the redis documentation of pub/sub.
Edit for follow on questions:
a) I assume I would have to "publish" synchronously (using Result or Wait()) if I want to guarantee the order of sending items from the same publisher is preserved when receiving items, correct?
that won't make any difference at all; since you mention Result / Wait(), I assume you're talking about BookSleeve - in which case the multiplexer already preserves command order. Redis itself is single threaded, and will always process commands on a single connection in order. However: the callbacks on the subscriber may be executed asynchronously and may be handed (separately) to a worker thread. I am currently investigating whether I can force this to be in-order from RedisSubscriberConnection.
Update: from 1.3.22 onwards you can set the CompletionMode to PreserveOrder - then all callbacks will be completed sequentially rather than concurrently.
b) after making adjustments according to your suggestions I get a great performance when publishing few items regardless of the size of the payload. However, when sending 100,000 or more items by the same publisher performance drops rapidly (down to 7-8 seconds just to send from my machine).
Firstly, that time sounds high - testing locally I get (for 100,000 publications, including waiting for the response for all of them) 1766ms (local) or 1219ms (remote) (that might sound counter-intuitive, but my "local" isn't running the same version of redis; my "remote" is 2.6.12 on Centos; my "local" is
2.6.8-pre2 on Windows).
I can't make your actual server faster or speed up the network, but: in case this is packet fragmentation, I have added (just for you) a SuspendFlush() / ResumeFlush() pair. This disables eager-flushing (i.e. when the send-queue is empty; other types of flushing still happen); you might find this helps:
conn.SuspendFlush();
try {
// start lots of operations...
} finally {
conn.ResumeFlush();
}
Note that you shouldn't Wait until you have resumed, because until you call ResumeFlush() there could be some operations still in the send-buffer. With that all in place, I get (for 100,000 operations):
local: 1766ms (eager-flush) vs 1554ms (suspend-flush)
remote: 1219ms (eager-flush) vs 796ms (suspend-flush)
As you can see, it helps more with remote servers, as it will be putting fewer packets through the network.
I cannot use transactions because later on the to-be-published items are not all available at once. Is there a way to optimize with that knowledge in mind?
I think that is addressed by the above - but note that recently CreateBatch was added too. A batch operates a lot like a transaction - just: without the transaction. Again, it is another mechanism to reduce packet fragmentation. In your particular case, I suspect the suspend/resume (on flush) is your best bet.
Do you recommend having one general RedisConnection and one RedisSubscriberConnection or any other configuration to have such wrapper perform desired functions?
As long as you're not performing blocking operations (blpop, brpop, brpoplpush etc), or putting oversized BLOBs down the wire (potentially delaying other operations while it clears), then a single connection of each type usually works pretty well. But YMMV depending on your exact usage requirements.
string uri = "myurl";
string blobstatus = GetBlobStatus(uri);
if (blobstatus != LeaseStatus.Locked.ToString())
{
string response = AquireBlob(uri);
//process data.
string abc = ":em";
ReleaseBlob(response, uri);
}
Above is my code for leasing and releasing locks on blob. I'm looking at this method to use for multi-instance worker role where I want to run a specific code after x interval of time, as multiple instances could execute the code at same time.
The problem is that I manage to get the LeaseId properly but when the second instance checks blob lease status it is always unspecified. Why it is so? any clues?
I followed the following link for getting a head start.
Leasing Windows Azure Blobs Using the Storage Client Library - blog.smarx.com
I think your approach should not rely on checking the blob status first and based on that decide whether to acquire lease or not. You should always try and acquire the lease and capture the exception thrown in that process. That way if this code is running in multi-instance environment, only one instance will be able to acquire the lease (and other instances will just throw an error).
Good suggestions.. i solved the problem. found out that in fact that LeaseStatus property is not good and never returns results.
I had to get status by putting in web request and then i could get a right result.