Sending files over MSMQ - ftp

In a retail scenario where each stores report their daily transaction to the backend system at the end of the day. Today a file consisting of the daily transactions and some other meta information is transferred from the stores to the backend using FTP. I’m currently investigating replacing FTP with something else. MSMQ has been suggested as an alternative transport mechanism. So my question is, do we need to write a custom windows service that sticks the daily transactions file into a message object and sends it on its way or is there any out the box mechanism in MSMQ to handle this?
Also, since the files we want to transfer can reach 5-6 Mb for large stores should we rule out MSMQ? In that case is there any other suggested technologies we should investigate?
Cheers!

NServiceBus provides a nice abstraction over MSMQ for situations like this. You get the reliable messaging aspects of MSMQ, along with a very nice programming model for defining your messages.
MSMQ is limited to a 4MB message size, however, and there are two ways you could deal with this in NServiceBus:
NServiceBus has a concept called the Data Bus, which takes the large attachments in your messages and transmits them reliably using another method. This is handled by the infrastructure and as far as your message handlers are concerned, the data is just there.
You could break up the payload into smaller atomic messages and send them as normal messages. The NServiceBus infrastructure would ensure that they all arrive at their destination and are processed. I would recommend this method unless it's absolutely critical that the entire huge data dump is processed as one atomic transaction.
One other thing to note is that the fact that you do nightly dumps is probably a limitation of a previous system. With NServiceBus it may be possible to change the system so that these bits of information are sent in a more immediate fashion, which will result in much more up-to-date data all the time, which may be a big win for the business.

You can look at IBM Sterling Managed File Transfer and WebSphere MQ Managed File Transfer products.
You can consider WebSphere MQ MFT if you require both messaging and file transfer capabilities. On the other hand if your requirement is just file transfer then you can look at Sterling MFT.

Sending files over a messaging transport is not trivial. If you put the entire file into a single message you can have the atomicity you need but tuning the messaging provider for wide variance in message sizes can be challenging. If all the files are of about the same size, one per message is about the simplest solution.
On the other hand, you can split the files into multiple messages but then you've got to reassemble them, in the right order, include a protocol to detect and resend missing segments, integrity-check the file received against the file sent, etc. You also probably want to check that the files on either end did not change during the transmission.
With any of these systems you also need the system to be smart enough to manage the disposition of sending and receiving files under normal and exception conditions, log the transfers, etc.
So when considering whether to move to messaging the two best options are either to move natively to messaging and give up files altogether, or to use an enterprise managed file transfer solution that runs atop the messaging provider that you choose. None of the off-the-shelf MFT products will cost as much in the long run as developing it yourself if you wish to do it right with robust exception handling and reporting.

If the stores are on separate networks and communicating over the internet, then MSMQ is not really an option. NServiceBus provides a concept of a gateway, which allows to asynchronously transport MSMQ messages over HTTP or HTTPS.

Related

Preventing data loss in client authoritative database writes

A project I'm working on requires users to insert themselves into a list on a server. We expect a few hundred users over a weekend and while very unlikely, a collision could happen in which two users submit the list concurrently and one of them is lost. The server has no validation, it simply allows you to get and put data.
I was pointed in the direction of "optimistic locking" but I'm having trouble grasping when exactly the data should be validated and how it prevents this from happening. If one of the clients reads the data, adds itself and then checks again to ensure that the data is the same with the use of an index or timestamp, how does this prevent the other client from doing the same and then one overwriting the other?
I'm trying to understand the flow in the context of two clients getting data and putting data.
The point of optimistic locking is that the decision to accept or reject a write is taken on the server, and is protected against concurrency by a pessimistic transaction or some sort of hardware protection, such as compare-and-swap. So a client requests a write together with some sort of timestamp or version identifier, and the server only accepts the write if the timestamp is still accurate. If it isn't the client gets some sort of rejection code and will have to try again. If it is, the client gets told that its write succeeded.
This is not the only way to handle receiving data from multiple clients. One popular alternative is to use a reliable messaging system - for example the Java Messaging Service specifies an interface for such systems for which you can find open source implementations. Clients write into the messaging system and can go away as soon as their message is accepted. The server reads requests from the messaging system and acts on them. If the server or the network goes down it's no big deal: the messages will still be there to be read when they come back (typically they are written to disk and have the same level of protection as database data although if you look at a reliable message queue implementation you may find that it is not, in fact, built on top of a standard database table).
One example of a writeup of the details of optimistic locking is the HTTP server Etag specification e.g. https://en.wikipedia.org/wiki/HTTP_ETag

Exchange files (up to many GB)

For my project, I have to create a file manager which aims at storing many files (from many locations) and exposing URL to download them.
In a micro-service ecosystem (I am used to use spring boot), I wonder what is the best way to exchange such files, I mean sending files to file manager?
On a one hand, I always thought it is better to exchange them asynchronously, so HTTP does not seem a good choice. But maybe I am wrong.
Is it a good choice to split files into fragments (in order to reduce number of bytes for each part) and send each of them through something like RabbitMQ or Kafka? Or should I rather transfer entire files on a NAS or through FTP and let file manager handling them? Or something else, like for example storing bytes in a temp database (maybe not a good choice)...
The problem of fragmentation is I have to implement a logic for keeping sort of each fragments which complicates processing of queues of topics.
IMO, never send actual files through a message broker.
First, setup some object storage system, for example S3 (with AWS or locally with Ceph), then send the path to the file as a string with the producer, then have the consumer read that path, and download the file.
If you want to collect files off of NAS or FTP, then Apache NiFi is one tool that has connectors to systems like that.
Based on my professional experience working with distributed systems (JMS based), to transfer huge content between participants:
a fragment approach should be used for request - reply model + control signals (has next, fragment counter)
delta approach for updates.
To avoid corrupt data, a hash function result can also be transmitted and checked in both scenarios.
But as mentioned in this e-mail thread, a better approach is to use FTP for this kind of scenarios:
RabbitMQ should actually not be used for big file transfers or only
with great care and fragmenting the files into smaller separate
messages.
When running a single broker instance, you'd still be safe, but in a
clustered setup, very big messages will break the cluster.
Clustered nodes are connected via 1 tcp connection, which must also
transport a (erlang) heartbeat. If your big message takes more time to
transfer between nodes than the heartbeat timeout (anywhere between
~20-45 seconds if I'm correct), the cluster will break and your
message is lost.
The preferred architecture for file transfer over amqp is to just send
a message with a link to a downloadable resource and let the file
transfer be handle by specialized protocol like ftp :-)
Hope it helps.

Using Akka.net / Actor System for an ETL process

I'm new in the world of actor modeling and I am in love with the idea. But does some pattern exists for processing a batch of messages simply for bulk storage in a safe manner?
I'm afraid if I read 400 messages of expected 500 and put them in a list, if the system closes, I don't want to lose those 400 messages from the (persisted)
mailbox. In a service bus world you could ask for a batch of messages and only when processed, commit all of them. Thank you.
You may want to combine your actor system with some service bus/reliable queues, like RabbitMQ or Azure Service Bus, at use actor system only for message processing.
From within Akka.NET itself, you have persistence extension, which can be used for storing actor state in persistent backend of your choice. It also contains a dedicated kind of an actor, AtLeastOnceDeliveryActor that may be used to resend messages until they will be confirmed.
you can extend split and aggregate in your ESB to do it, I made something similar with mule ESB from long time.

When to use persistence with Java Messaging and Queuing Systems

I'm performing a trade study on (Java) Messaging & Queuing systems for an upcoming re-design of a back-end framework for a major web application (on Amazon's EC2 Cloud, x-large instances). I'm currently evaluating ActiveMQ and RabbitMQ.
The plan is to have 5 different queues, with one being a dead-letter queue. The number of messages sent per day will be anywhere between 40K and 400K. As I plan for the message content to be a pointer to an XML file location on a data store, I expect the messages to be about 64 bytes. However, for evaluation purposes, I would also like to consider sending raw XML in the messages, with an average file size of 3KB.
My main questions: When/how many messages should be persisted on a daily basis? Is it reasonable to persist all messages, considering the amounts I specified above? I know that persisting will decrease performance, perhaps by a lot. But, by not persisting, a lot of RAM is being used. What would some of you recommend?
Also, I know that there is a lot of information online regarding ActiveMQ (JMS) vs RabbitMQ (AMQP). I have done a ton of research and testing. It seems like either implementation would fit my needs. Considering the information that I provided above (file sizes and # of messages), can anyone point out a reason(s) to use a particular vendor that I may have missed?
Thanks!
When/how many messages should be persisted on a daily basis? Is it
reasonable to persist all messages, considering the amounts I
specified above?
JMS persistence doesn't replace a database, it should be considered a short-lived buffer between producers and consumers of data. that said, the volume/size of messages you mention won't tax the persistence adapters on any modern JMS system (configured properly anyways) and can be used to buffer messages for extended durations as necessary (just use a reliable message store architecture)
I know that persisting will decrease performance, perhaps by a lot.
But, by not persisting, a lot of RAM is being used. What would some of
you recommend?
in my experience, enabling message persistence isn't a significant performance hit and is almost always done to guarantee messages. for most applications, the processes upstream (producers) or downstream (consumers) end up being the bottlenecks (especially database I/O)...not JMS persistence stores
Also, I know that there is a lot of information online regarding
ActiveMQ (JMS) vs RabbitMQ (AMQP). I have done a ton of research and
testing. It seems like either implementation would fit my needs.
Considering the information that I provided above (file sizes and # of
messages), can anyone point out a reason(s) to use a particular vendor
that I may have missed?
I have successfully used ActiveMQ on many projects for both low and high volume messaging. I'd recommend using it along with a routing engine like Apache Camel to streamline integration and complex routing patterns
A messaging system must be used as a temporary storage. Applications should be designed to pull the messages as soon as possible. The more number of messages lesser the performance. If you are pulling of messages then there will be a better performance as well as lesser memory usage. Whether persistent or not memory will still be used as the messages are kept in memory for better performance and will backed up on disk if a message type is persistent only.
The decision on message persistence depends on how critical a message is and does it require to survive a messaging provider restart.
You may want to have a look at IBM WebSphere MQ. It can meet your requirements. It has JMS as well as proprietary APIs for developing applications.
ActiveMQ is a good choice for open source JMS, more expensive ones I can recommend are TIBCO EMS or maybe Solace.
But JMS is actually built for once-only delivery and longer persistence is left out of the specification. You could of course go database, but that's heavy weight and possibly expensive.
What I would recommend (Note: I work for CodeStreet) is our 'ReplayService for JMS'. It let's you store any type of JMS messages (or native WebSphere MQ ones) in a high-performance file-based disk storage. Each message is automatically assigned a nanosecond timestamp and a globalMsgID that you can overwrite on publication. So the XML messages could be recorded by the ReplayServer and your actual message could just contain the globalMsgID as reference. And maybe some properties ?
Once a receiver receives the globalMsgID, it could then replay that message from the ReplayServer, if needed.
But on the other hand, 400K*3KB XML message should be easily doable for ActiveMQ or others. Also, you should compress your XML messages before sending.

Factors Affected for Low Performance of middleware Messaging Softwares

I am planning to inegrate messaging middleware in my web application. Right now I am tesing different messaging middleware software like RabbitMQ,JMS, HornetQ, etc..
Examples provided with this softwares are working but its not giving as desired results.
So, I want to know that which are the factors which are responsible to improve peformance that one should keep in eyes?
Which are the areas, a developer should take care of to improve the performance of middleware messaging software?
I'm the project lead for HornetQ but I will try to give you a generic answer that could be applied to any message system you choose.
A common question that I see is people asking why a single producer / single consumer won't give you the expected performance.
When you send a message, and are asking confirmation right away, you need to wait:
The message transfer from client to server
The message being persisted on the disk
The server acknowledging receipt of the message by sending a callback to the client
Similarly when you are receiving a message, you ACK to the server:
The ACK is sent from client to server
The ACK is persisted
The server sends back a callback saying that the callback was achieved
And if you need confirmation for all your message-sends and mesage-acks you need to wait these steps as you have a hardware involved on persisting the disk and sending bits on the network.
Message Systems will try to scale up with many producers and many consumers. That is if many are producing they should all use the resources available at the server shared for all the consumers.
There are ways to speed up a single producer or single consumer:
One is by using transactions. So, you minimize the blocks and syncs you perform on disk while persisting at the server and roundtrips on the network. (This is actually the same on any database)
Another one, is by using Callbacks instead of blocking at the consumer. (JMS 2 is proposing a Callback similar to the ConfirmationHandler on HornetQ).
Also: most providers I know will have a performance section on their docs with requirements and suggestions for that specific product. You should look individually at each product

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