I have implemented client server program using boost::asio library.
In my implementation there are times when io_service.run() blocks indefinitely. In case I pass another request to io_service, the blocked call begins to execute normally.
Is there any way to see what are the pending requests inside the io_service queue ?
I have not used work object to block the run call!
There are no official ways to query into the io_service to find all pending request. However, there are a few techniques to debug the problem:
Boost 1.47 introduced handler tracking. Simply define BOOST_ASIO_ENABLE_HANDLER_TRACKING and Boost.Asio will write debug output, including timestamps, an identifier, and the operation type, to the standard error stream.
Attach a debugger dig through the layers to find and examine operation queues. This answer covers both understanding handler tracking and using a debugger to examine an operation queue for the epoll_reactor.
Finally, if you believe it is a bug, then it may be worth updating to the latest version or checking the revision history for relevant changes. Regardless, describing the problem in more detail may allow others to help identify the source of the problem and potential solutions.
Now i spent a few hours reading and experimenting (i need more boost::asio functionality for work as well) and it turns out: Kind of.
But it is not as straightforward or readable as one might hope.
Under the hood (well, under the outermost hood) io_service has a bunch of other services registered, which do the work async_ operations of their respective fields require.
These are the "Services" described in the reference.
Now sadly, the services stay registered, wether there is work to do or not. For example if your io_service has a udp socket, it will still have all the corresponding services, even if the socket itself is inactive.
But you can ask your io_service which services it has. Lets say you want to know wether your io_service called m_io_service has an udp datagram_socket_service. Then you can call something like:
if (boost::asio::has_service<boost::asio::datagram_socket_service<boost::asio::ip::udp> >(m_io_service))
{
//Whatever
}
That does not help a lot, because it will be true no matter wether the socket is active or not. But after you know, that you have that service, you can get a ref to it using use_service instead of has_service but with the same elegant amount of <>.
And now you can inspect the service to see what it is up to. Sadly, it will not tell you what the outstanding handlers names are (probably partly because it does not know them) but if it is a socket, you can get its implemention_type and with that check whether it currently is_open or find either the local_endpoint as well as the remote_endpoint.
In case of a deadline_timer_service you can, among other stuff, find out when it expires_at.
See the reference for more information what the service is and is not willing to tell you.
http://www.boost.org/doc/libs/1_54_0/doc/html/boost_asio/reference.html
This information should then hopefully allow you to determine which async_ operation did not return.
And if not, at the very least you can cancel any unexpectedly active services.
Related
Background:
I am trying to write a program in Elixir to test distributed algorithms by running them on a set of processes and recording certain statistics. To begin with I will be running these processes on the same machine, but the intention is eventually to have them running on separate machines/VMs.
Problem:
One of the requirements for algorithms I wish to implement is that messages include authentication. That is, whenever a process sends a message to another process, the receiver should be able to verify that this message did indeed come from the sender, and wasn't forged by another process. The following snippets should help to illustrate the idea:
# Sender
a = authenticate(self, receiver, msg)
send(receiver, {msg, self, a})
# Receiver
if verify(msg, sender, a) do
deliver(msg)
end
Thoughts so far:
I have searched far and wide for any documentation of authenticated communication between Elixir processes, and haven't been able to find anything. Perhaps in some way this is already done for me behind the scenes, but so far I haven't been able to verify this. If it were the case, I wonder if it would still be correct when the processes aren't running on the same machine.
I have looked into the possibility of using SSL/TLS functions provided by Erlang, but with my limited knowledge in this area, I'm not sure how this would apply to my situation of running a set of processes as opposed to the more standard use in client-server systems and HTTPS. If I went down this route, I believe I would have to set up all the keys and signatures myself beforehand, which I believe could possible using the X509 Elixir package, though I'm not sure if this is appropriate and may be more work than is necessary.
In summary:
Is there a standard/pre-existing way to achieve authenticated communication between processes in Elixir?
If yes, will it be suitable for processes communicating between separate machines/VMs?
If no to either of the above, what is the simplest way I could achieve this myself?
As Aleksei and Paweł point out, if something is in your cluster, it is already trusted. It's not quite like authenticating random web requests that could have originated virtually anywhere, you are talking about messages originating from inside your local network of trusted machines. If some nefarious actor is running on one of your servers, you have far bigger problems to worry about than just authenticating messages.
There are very few limitations put on Elixir/Erlang processes running inside a cluster with respect to security: their states can be inspected by any other process, for example. Some of this transparency is by-design and necessary in order to have a fault-tolerant system capable of doing hot-code reloads, but the conversation about the specific how's and why's is too nuanced for me to do it justice.
If you really need to do some logging to have an auditable "paper trail" to verify which process sent which message, I think you'll have to roll your own solution which could rely on a number of common techniques (such as keys + signatures, block-chains, etc.). But keep in mind: these are concerns that would come up if you were dealing with web requests between different servers anyhow! And there are already protocols for establishing secure connections between computers, so I would not recommend re-inventing those network protocols in your application.
Your time may be better spent working on the algorithms themselves and not trying to re-invent the wheel on security. Your app should focus on the unique stuff that nobody else is doing (algorithms in your case). If you have multiple interconnected VMs passing messages to each other, all the "security" requirements there come with defining the proper access to each machine/subnet, and that requirement holds no matter what application/language you're running on them.
The more I read what are you trying to achieve, the more I am sure all you need is the footprint of the calling process.
For synchronous calls GenServer.handle_call/3 you already have the second parameter as a footprint.
For asynchronous messages, you might add the caller information to the messages themselves. Like, instead of sending a plain :foo message, send {:foo, pid()} or somewhat even more sophisticated like {:foo, {pid(), timestamp(), ip(), ...} and make callee to verify those.
That would be safe by all means: erlang cluster would ensure these messages are coming from trusted sources, and your internal validation might ensure that the source is valid within your internal rules.
In some exceptional situations I need somehow to tell consumer on receiving point that some messages shouldn’t be processed. Otherwise two systems will become out-of-sync (we deal with some outdates external systems, and if, for example, connection is dropped we have to discard all queued operations in scope of that connection).
Take a risk and resolve problem messages manually? Compensation actions (that could be tough to support in my case)? Anything else?
There are a few ways:
You can set a time-to-live when sending a message: await endpoint.Send(myMessage, c => c.TimeToLive = TimeSpan.FromHours(1));, but this will apply to all messages that are sent (or published) like this. I would consider this, after looking at your requirements. This is technical, but it is a proper messaging pattern.
Make TTL and generation timestamp properties of your message itself and let the consumer decide if the message is still worth processing. This is more business and, probably, the most correct way.
Combine tech and business - keep the timestamp and TTL in message headers so they don't pollute your message contracts, and filter them out using a custom middleware. In this case, you need to be careful to log such drops so you won't be left wonder why messages disappear now and then.
Almost any unreliable integration can be monitored using sagas, with timeouts. For example, we use a saga to integrate with Twilio. Since we have no ability to open a webhook for them, we poll after some interval to check the message status. You can start a saga when you get a message and schedule a message to check if the processing is still waiting. As discussed in comments, you can either use the "human intervention required" way to fix the issue or let the saga decide to drop the message.
A similar way could be to use a lookup table, where you put the list of messages that aren't relevant for processing. Such a table would be similar to the list of sagas. It seems that this way would also require scheduling. Both here, and for the saga, I'd recommend using a separate receive endpoint (a queue) for the DropIt message, with only one consumer. It would prevent DropIt messages from getting stuck behind the integration messages that are waiting to be processed (and some should be already dropped)
Use RMQ management API to remove messages from the queue. This is the worst method, I won't recommend it.
From what I understand, you're building a system that sends messages to 3rd party systems. In other words, systems you don't control. It has an API but compensating actions aren't always possible, because the API doesn't provide it or because actions are performed inside the 3rd party system that can't be compensated or rolled back?
If possible try to solve this via sagas. Make sure the saga executes the different steps (the sending of messages) in the right order. So that messages that cannot be compensated are sent last. This way message that can be compensated if they fail, will be compensated by the saga. The ones that cannot be compensated should be sent last, when you're as sure as possible that they don't have to be compensated. Because that last message is the last step in synchronizing all systems.
All in all this is one of the problems with distributed systems, keeping everything in sync. Compensating actions is the way to deal with this. If compensating actions aren't possible, you're in a very difficult situation. Try to see if the business can help by becoming more flexible and accepting that you need to compensate things, where they'll tell you it's not possible.
In some exceptional situations I need somehow to tell consumer on receiving point that some messages shouldn’t be processed.
Can't you revert this into:
Tell the consumer that an earlier message can be processed.
This way you can easily turn this in a state machine (like a saga) that acts on two messages. If the 2nd message never arrives then you can discard the 1st after a while or do something else.
The strategy here is to halt/wait until certain that no actions need to be reverted.
I'm struggling to understand how to implement Eventual Consistency with the exposed example of BacklogItems and Tasks from Vaughn Vernon. The statement I've understood so far is (considering the case where he splits BacklogItem and Task into separate aggregate roots):
A BacklogItem can contain one or more tasks. When all remaining hours from a the tasks of a BacklogItem are 0, the status of the BacklogItem should change to "DONE"
I'm aware about the rule that says that you should not update two aggregate roots in the same transaction, and that you should accomplish that with eventual consistency.
Once a Domain Service updates the amount of hours of a Task, a TaskRemainingHoursUpdated event should be published to a DomainEventPublisher which lives in the same thread as the executing code. And here it is where I'm at a loss with the following questions:
I suppose that there should be a subscriber (also living in the same thread I guess) that should react to TaskRemainingHoursUpdated events. At which point in your Desktop/Web application you perform this subscription to the Bus? At the very initialization of your app? In the application code? Is there any reasoning to place domain subscriptors in a specific place?
Should that subscriptor (in the same thread) call a BacklogItem repository and perform the update? (But that would be a violation of the rule of not updating two aggregates in the same transaction since this would happen synchronously, right?).
If you want to achieve eventual consistency to fulfil the previously mentioned rule, do I really need a Message Broker like RabbitMQ even though both BacklogItem and Task live inside the same Bounded Context?
If I use this message broker, should I have a background thread or something that just consumes events from a RabbitMQ queue and then dispatches the event to update the product?
I'd appreciate if someone can shed some clear light over this since it is quite complex to picture in its completeness.
So to start with, you need to recognize that, if the BacklogItem is the authority for whether or not it is "Done", then it needs to have all of the information to compute that for itself.
So somewhere within the BacklogItem is data that is tracking which Tasks it knows about, and the known state of those tasks. In other words, the BacklogItem has a stale copy of information about the task.
That's the "eventually consistent" bit; we're trying to arrange the system so that the cached copy of the data in the BacklogItem boundary includes the new changes to the task state.
That in turn means we need to send a command to the BacklogItem advising it of the changes to the task.
From the point of view of the backlog item, we don't really care where the command comes from. We could, for example, make it a manual process "After you complete the task, click this button here to inform the backlog item".
But for the sanity of our users, we're more likely to arrange an event handler to be running: when you see the output from the task, forward it to the corresponding backlog item.
At which point in your Desktop/Web application you perform this subscription to the Bus? At the very initialization of your app?
That seems pretty reasonable.
Should that subscriptor (in the same thread) call a BacklogItem repository and perform the update? (But that would be a violation of the rule of not updating two aggregates in the same transaction since this would happen synchronously, right?).
Same thread and same transaction are not necessarily coincident. It can all be coordinated in the same thread; but it probably makes more sense to let the consequences happen in the background. At their core, events and commands are just messages - write the message, put it into an inbox, and let the next thread worry about processing.
If you want to achieve eventual consistency to fulfil the previously mentioned rule, do I really need a Message Broker like RabbitMQ even though both BacklogItem and Task live inside the same Bounded Context?
No; the mechanics of the plumbing matter not at all.
I'm trying to understand how to persist data in a Twisted application. Let's say I've decided to write a Twisted server that:
Accepts inbound SMTP requests
Sends the message to a 3rd party system for modification
Relays the modified message to its destination
A typical Twisted tutorial would have you build this app using Deferreds and callbacks, roughly:
A Factory handles inbound requests
Each time a full email is received a call is sent to the remote message processor, returning a deferred
Add an errback that substitutes the original message if anything goes wrong in the modify call.
Add a callback to send the message on to the recipient, which again returns a deferred.
A real server would add/include additional call/errbacks to retry or notify the sender or whatnot. Again for simplicity, assume we consider this an acceptable amount of effort and just log errors.
Of course, this persists NO data in the event of a crash/restart/something else. I get that a solution involves a 3rd party persistent datastore (RabbitMQ is often mentioned) and could probably come up with a dozen random ways to achieve the outcome.
However, I imagine there are a few approaches that work best in a Twisted app. What do they look like? How do they store (and restore in the event of a crash) the in-process messages?
If you found this question, you probably already know that Twisted is event-based. It sounds simple, but the "hardest" part of the answer is to get the persistence platform generating the events we need when we need them. Naturally, you can persist the data in a DB or a message queue, but some platforms don't naturally generate events. For example:
ZeroMQ has (or at least had) no callback for new data. It's also relatively poor at persistence.
In other cases, events are easy but reliability is a problem:
pgSQL can be configured to generate events using triggers, but they're one-time things so you can't resume incomplete events
The light at the end of the tunnel seems to be something like RabbitMQ.
RabbitMQ can persist the message in a database to survive a crash
We can use acknowledgements on both legs (incoming SMTP to RabbitMQ and RabbitMQ to outgoing SMTP) to ensure the application is reliable. Importantly, RabbitMQ supports acknowledgements.
Finally, several of the RabbitMQ clients provide full asynchronous support (see for example pika, txampq, and puka)
It's enough for our purposes that the RabbitMQ client provides us an event-based interface.
At a more theoretical level, however, this need not be the case. In fact, despite the "notification" issue above, ZeroMQ has an event-based client. Even if our software is elegantly event-based, we will run into systems that aren't. In these cases, we have no choice but to fall back on polling. In principle, if not in practice, we just query the message provider for messages. When we exhaust the current queue (and immediately if there are no messages), we use a callLater command to check again in the future. It may feel anti-pattern, but it's (to the best of my knowledge anyway) the right way to handle this particular case.
I'm still trying to master Twisted while in the midst of finishing an application that uses it.
My question is:
My application uses LineReceiver.sendLine to send messages from a Twisted TCP server.
I would like to know if the sendLine succeeded.
I gather that I need to somehow add a success (and error?) callback to sendLine but I don't know how to do this.
Thanks for any pointers / examples
You need to define "succeeded" in order to come up with an answer to this.
All sendLine does immediately (probably) is add some bytes to a send buffer. In some sense, as long as it doesn't raise an exception (eg, MemoryError because your line is too long or TypeError because your line was the number 3 instead of an actual line) it has succeeded.
That's not a very useful kind of success, though. Unfortunately, the useful kind of success is more like "the bytes were added to the send buffer, the send buffer was flushed to the socket, the peer received the bytes, and the receiving application acted on the data in a persistent way".
Nothing in LineReceiver can tell you that all those things happened. The standard solution is to add some kind of acknowledgement to your protocol: when the receiving application has acted on the data, it sends back some bytes that tell the original sender the message has been handled.
You won't get LineReceiver.sendLine to help you much here because all it really knows how to do is send some bytes in a particular format. You need a more complex protocol to handle acknowledgements.
Fortunately, Twisted comes with a few. twisted.protocols.amp is one: it offers remote method calls (complete with responses) as a basic feature. I find that AMP is suitable for a wide range of applications so it's often safe to recommend for new development. It largely supersedes the older twisted.spread (aka "PB") which also provides both remote method calls and remote object references (and is therefore more complex - in my experience, more complex than most applications need). There are also some options that are a bit more standard: for example, Twisted Web includes an HTTP implementation (HTTP, as you may know, is good at request/response style interaction).