I'm new to microservices architecture and want to create a centralised notification microservice to send emails/sms to users.
My first option was to create a notification Kafka queue where all other microservices can send notifications to. The notification microservice would then listen to this queue and send messages accordingly. If the notification service was restarted or taken down, we would not lose any messages as the messages will be stored on the queue.
My second option was to add a notification message API on the notifications microservice. This would make it easier for all other microservices as they just have to call an API as opposed to integrate with the queue. The API would then internally send the message to the notification Kafka queue and send the message. The only issue here is if the API is not available or there is an error, we will lose messages.
Any recommendations on the best way to handle this?
Either works. Some concepts that might help you decide:
A service that fronts "Kafka" would be helpful to:
Hide the implementation. This gives you the flexibility to change Kafka out later for something else. Your wrapper API would only respond with a 200 once it has put the notification request on the queue. I also see giving services direct access to "your" queue similar to allowing services to directly interact with a database they don't own. If you allow direct-access to Kafka and Kafka proves to be inadequate, a change to Kafka will require all of your clients to change their code.
Enforce the notification request contract (ensure the body of the request is well-formed). If you want to make sure that all of the items put on the queue are well-formed according to contract, an API can help enforce that. That will help prevent issues later when the "notifier" service picks notifications off the queue to send.
Adding a wrapper API would be less desirable if:
You don't want to/can't spend the time. Maybe deadlines are driving you to hurry and the days it would take to stand up a wrapper is just too much.
You are a small team and you don't have the resources/tools/time for service-explosion.
Your first design is simple and will work. If you're looking for the advantages I outlined, then consider your second design. And, to make sure I understand it, I would see it unfold like:
Client 1 needs to put out a notification and calls Service A POST /notifications
Service A that accepts POST /notifications
Service A checks the request, puts it on Kafka, responds to client with 200
Service B picks up notification request from Kafka queue.
Service A should be run as multiple instances for reliability.
Related
I am implementing a REST API that internally places a message on a message queue and receives a message as a response on a different topic.
How could API implementation handle publishing and consuming different messages and responds to the client?
What if it never receives a message?
How does the service handle this time-out scenario?
Example
I am implementing a REST API to process an order. The implementation internally publishes a series of messages to verify the payment, update inventory, and prepare shipping info. Finally, it sends the response back to the client.
Queues are too low-level abstraction to implement your requirements directly. Look at an orchestration solution like temporal.io that makes programming such async systems trivial.
Disclaimer: I'm one of the founders of the Temporal open source project.
How could API implementation handle publishing and consuming different messages and responds to the client?
Even though messaging systems can be used in RPC like fashion:
there is a request topic/queue and a reply topic/queue
with a request identifier in the messages' header/metadata
this type of communication kills the promise of the messaging system: decouple components in time and space.
Back to your example. If ServiceA receives the request then it publishes a message to topicA and returns with an 202 Accepted status code to indicate that the request is received but not yet processed completely. In the response you can indicate an url on which the consumer of ServiceA's API can retrieve the latest status of its previously issued request.
What if it never receives a message?
In that case the request related data remains in the same state as it was at the time of the message publishing.
How does the service handle this time-out scenario?
You can create scheduled jobs to clean-up never finished/got stuck requests. Based on your business requirements you can simple delete them or transfer them to manual processing by the customer service.
Order placement use case
Rather than creating a customer-facing service which waits for all the processing to be done you can define several statuses/stages of the process:
Order requested
Payment verified
Items locked in inventory
...
Order placed
You can inform your customers about these status/stage changes via websocket, push notification, e-mail, etc.. The orchestration of this order placement flow can be achieved for example via the Saga pattern.
Recently I am trying to use MassTransit in our microservice ecosystem.
According to MassTransit vocabulary and from documents my understanding is :
Publish: Sends a message to 1 or many subscribers (Pub/Sub Pattern) to propagate the message.
Send: Used to send messages in fire and forget fashion like publish, but instead It is just used for one receiver. The main difference with Publish is that in Send if your destination didn't receive a message, it would return an exception.
Requests: uses request/reply pattern to just send a message and get a response in a different channel to be able to get response value from the receiver.
Now, my question is according to the Microservice concept, to follow the event-driven design, we use Publish to propagate messages(Events) to the entire ecosystem. but what is exactly the usage (use case) of Send here? Just to get an exception if the receiver doesn't exist?
My next question is that is it a good approach to use Publish, Send and Requests in a Microservices ecosystem at the same time? like publish for propagation events, Send for command (fire and forget), and Requests for getting responses from the destination.
----- Update
I also found here which Chris Patterson clear lots of things. It also helps me a lot.
Your question is not related to MassTransit. MassTransit implements well-known messaging patterns thoughtfully described on popular resources such as Enterprise Integration Patterns
As Eben wrote in his answer, the decision of what pattern to use is driven by intent. There are also technical differences in the message delivery mechanics for each pattern.
Send is for commands, you tell some other service to do something. You do not wait for a reply (fire and forget), although you might get a confirmation of the action success or failure by other means (an event, for example).
It is an implementation of the point-to-point channel, where you also can implement competing consumers to scale the processing, but those will be instances of the same service.
With MassTransit using RabbitMQ it's done by publishing messages to the endpoint exchange rather than to the message type exchange, so no other endpoints will get the message even though they can consume it.
Publish is for events. It's a broadcast type of delivery or fan-out. You might be publishing events to which no one is listening, so you don't really know who will be consuming them. You also don't expect any response.
It is an implementation of the publish-subscribe channel.
MassTransit with RabbitMQ creates exchanges for each message type published and publishes messages to those exchanges. Consumers create bindings between their endpoint exchanges and message exchanges, so each consumer service (different apps) will get those in their independent queues.
Request-response can be used for both commands that need to be confirmed, or for queries.
It is an implementation of the request-reply message pattern.
MassTransit has nice diagrams in the docs explaining the mechanics for RabbitMQ.
Those messaging patterns are frequently used in a complex distributed system in different combinations and variations.
The difference between Send and Publish has to do with intent.
As you stated, Send is for commands and Publish is for events. I worked on a large enterprise system once running on webMethods as the integration engine/service bus and only events were used. I can tell you that it was less than ideal. If the distinction had been there between commands and events it would've made a lot more sense to more people. Anyway, technically one needs a message enqueued and on that level it doesn't matter, which is why a queueing mechanism typically would not care about such semantics.
To illustrate this with a silly example: Facebook places and Event on my timeline that one of my friends is having a birthday on a particular day. I can respond directly (send a message) or I could publish a message on my timeline and hope my friend sees it. Another silly example: You send an e-mail to PersonA and CC 4 others asking "Please produce report ABC". PersonA would be expected to produce the report or arrange for it to be done. If that same e-mail went to all five people as the recipient (no CC) then who gets to do it? I know, even for Publish one could have a 1-1 recipient/topic but what if another endpoint subscribed? What would that mean?
So the sender is responsible, still configurable as subscriptions are, to determine where to Send the message to. For my own service bus I use an implementation of an IMessageRouteProvider interface. A practical example in a system I once developed was where e-mails received had to have their body converted to an image for a content store (IBM FileNet P8 if memory serves). For reasons I will not go into the systems were stopped each night at 20h00 and restarted at 6h00 in the morning. This led to a backlog of usually around 8000 e-mails that had to be converted. The conversion endpoint would process a conversion in about 2 seconds but that still takes a while to work through. In the meantime the web front-end folks could request PDF files for conversion to paged TIFF files. Now, these ended up at the end of the queue and they would have to wait hours for that to come back. The solution was to implement another conversion endpoint, with its own queue, and have the web front-end configured to send the same message type, e.g. ConvertDocumentCommand to that "priority" queue for processing. Pretty easy to do. Now, if that had been a publish how would I do that split? The same event going to 2 different endpoints under different circumstances? Well, you could have another subscription store for your system but now you'd need to maintain both. There could be another answer such as coding this logic into the send bit but that is a design choice and would require coding changes.
In my own Shuttle.Esb service bus I only have Send and Publish. For request/response both the sender and receiver have an inbox and a request would be sent (Send) to the receiver and it in turn could reply (also a Send but uses the sender's URI).
I come across many blog that say using rabbitmq improve the performance of microservices due to asynchronous nature of rabbitmq.
I don't understand in that case how the the http response is send to end user I am elaborating my question below more clearly.
user send a http request to microservice1(which is user facing service)
microservice1 send it to rabbitmq because it need some service from microservice2
microservice2 receive the request process it and send the response to rabbitmq
microservice1 receive the response from rabbitmq
NOW how this response is send to browser?
Does microservice1 waits untill it receive the response from rabbitmq?
If yes then how it become aynchronous??
It's a good question. To answer, you have to imagine the server running one thread at a time. Making a request to a microservice via RestTemplate is a blocking request. The user clicks a button on the web page, which triggers your spring-boot method in microservice1. In that method, you make a request to microservice2, and the microservice1 does a blocking wait for the response.
That thread is busy waiting for microservice2 to complete the request. Threads are not expensive, but on a very busy server, they can be a limiting factor.
RabbitMQ allows microservice1 to queue up a message to microservice2, and then release the thread. Your receive message will be trigger by the system (spring-boot / RabbitMQ) when microservice2 processes the message and provides a response. That thread in the thread pool can be used to process other users' requests in the meantime. When the RabbitMQ response comes, the thread pool uses an unused thread to process the remainder of the request.
Effectively, you're making the server running microservice1 have more threads available more of the time. It only becomes a problem when the server is under heavy load.
Good question , lets discuss one by one
Synchronous behavior:
Client send HTTP or any request and waits for the response HTTP.
Asynchronous behavior:
Client sends the request, There's another thread that is waiting on the socket for the response. Once response arrives, the original sender is notified (usually, using a callback like structure).
Now we can talk about blocking vs nonblocking call
When you are using spring rest then each call will initiate new thread and waiting for response and block your network , while nonblocking call all call going via single thread and pushback will return response without blocking network.
Now come to your question
Using rabbitmq improve the performance of microservices due to
asynchronous nature of rabbitmq.
No , performance is depends on your TPS hit and rabbitmq not going to improve performance .
Messaging give you two different type of messaging model
Synchronous messaging
Asynchronous messaging
Using Messaging you will get loose coupling and fault tolerance .
If your application need blocking call like response is needed else cannot move use Rest
If you can work without getting response go ahaead with non blocking
If you want to design your app loose couple go with messaging.
In short above all are architecture style how you want to architect your application , performance depends on scalability .
You can combine your app with rest and messaging and non-blocking with messaging.
In your scenario microservice 1 could be rest blocking call give call other api using rest template or web client and or messaging queue and once get response will return rest json call to your web app.
I would take another look at your architecture. In general, with microservices - especially user-facing ones that must be essentially synchronous, it's an anti-pattern to have ServiceA have to make a call to ServiceB (which may, in turn, call ServiceC and so on...) to return a response. That condition indicates those services are tightly coupled which makes them fragile. For example: if ServiceB goes down or is overloaded in your example, ServiceA also goes offline due to no fault of its own. So, probably one or more of the following should occur:
Deploy the related services behind a facade that encloses the entire domain - let the client interact synchronously with the facade and let the facade handle talking to multiple services behind the scenes.
Use MQTT or AMQP to publish data as it gets added/changed in ServiceB and have ServiceA subscribe to pick up what it needs so that it can fulfill the user request without explicitly calling another service
Consider merging ServiceA and ServiceB into a single service that can handle requests without having to make external calls
You can also send the HTTP request from the client to the service, set the application-state to waiting or similar, and have the consuming application subscribe to a eventSuccess or eventFail integration message from the bus. The main point of this idea is that you let daisy-chained services (which, again, I don't like) take their turns and whichever service "finishes" the job publishes an integration event to let anyone who's listening know. You can even do things like pass webhook URI's with the initial request to have services call the app back directly on completion (or use SignalR, or gRPC, or...)
The way we use RabbitMQ is to integrate services in real-time so that each service always has the info it needs to be responsive all by itself. To use your example, in our world ServiceB publishes events when data changes. ServiceA only cares about, and subscribes to a small subset of those events (and typically only a field or two of the event data), but it knows within seconds (usually less) when B has changed and it has all the information it needs to respond to requests. Each service literally has no idea what other services exist, it just knows events that it cares about (and that conform to a contract) arrive from time-to-time and it needs to pay attention to them.
You could also use events and make the whole flow async. In this scenario microservice1 creates an event representing the user request and then return a requested created response immediately to the user. You can then notify the user later when the request is finished processing.
I recommend the book Designing Event-Driven Systems written by Ben Stopford.
I asked a similar question to Chris Richardson (www.microservices.io). The result was:
Option 1
You use something like websockets, so the microservice1 can send the response, when it's done.
Option 2
microservice1 responds immediately (OK - request accepted). The client pulls from the server repeatedly until the state changed. Important is that microservice1 stores some state about the request (ie. initial state "accepted", so the client can show the spinner) which is modified, when you finally receive the response (ie. update state to "complete").
I was wondering which of my two methods is more appropriate, or is there event another one?
(1) Direct
Direct communication between GATEWAY and μSERVICE A
UI sends HTTP request to GATEWAY
GATEWAY sends HTTP request to μSERVICE A
μSERVICE A returns either SUCCESS or ERROR
Event is stored in EVENT STORE and published to QUEUE
PROJECTION DATABASE is updated
Other μSERVICES might consume event
(2) Events
Event-based communication via a message queue
UI sends HTTP request to GATEWAY
GATEWAY published event to QUEUE
μSERVICE A consumes event
Event is stored in EVENT STORE and published to QUEUE
PROJECTION DATABASE is updated
Other μSERVICES might consume event
GATEWAY consumes event and sends response (SUCCESS or ERROR) to UI
I am really sorry if I misunderstood some concept, I am relatively new to this style of architecture.
Thanks in advance for every help! :)
Second approach is a preferred way and is async approach.
Direct
In first approach your microsvc B and C wait for the event to get published . The scalability of this system is directly dependent on microsvc A. what if microsvc A is down or falling behind writing events to queue? it's like single point of failure and bottleneck. you can't scale system easily.
Events
In microservices we keep system async so they can scale.
Gateway should be writing to the queue using pub/sub and all these microservices can use events at same time. system over all is more robust and can be scaled.
I am new to Microservices and have a question with RabbitMQ / EasyNetQ.
I am sending messages from one microservice to another microservice.
Each Microservice are Web API's. I am using CQRS where my Command Handler would consume message off the Queue and do some business logic. In order to call the handler, it will need to make a request to the API method.
I would like to know without having to explicit call the API endpoint to hit the code for consuming messages. Is there an automated way of doing it without having to call the API endpoint ?
Suggestion could be creating a separate solution which would be a Console App that will execute the RabbitMQ in order to start listening. Create a while loop to read messages, then call the web api endpoint to handle business logic every time a new message is sent to the queue.
My aim is to create a listener or a startup task where once messages are in the queue it will automatically pick it up from the Queue and continue with command handler but not sure how to do the "Automatic" way as i describe it. I was thinking to utilise Azure Webjob that will continuously be running and it will act as the Consumer.
Looking for a good architectural way of doing it.
Programming language being used is C#
Much Appreciated
The recommended way of hosting RabbitMQ subscriber is by writing a windows service using something like topshelf library and subscribe to bus events inside that service on its start. We did that in multiple projects with no issues.
If you are using Azure, the best place to host RabbitMQ subscriber is in a "Worker Role".
I am using CQRS where my Command Handler would consume message off
the Queue and do some business logic. In order to call the handler, it
will need to make a request to the API method.
Are you sure this is real CQRS? CQRS occures when you handle queries and commands differently in your domain logic. Receiving a message via a calss, that's called CommandHandler and just reacting to it is not yet CQRS.
My aim is to create a listener or a startup task where once messages
are in the queue it will automatically pick it up from the Queue and
continue with command handler but not sure how to do the "Automatic"
way as i describe it. I was thinking to utilise Azure Webjob that will
continuously be running and it will act as the Consumer. Looking for
a good architectural way of doing it.
The easier you do that, the better. Don't go searching for complex solutions until you tried out all the simple ones. When I was implementing something similar, I was just running a pool of message handler scripts using Linux cron. A handler poped a message off the queue, processed it and terminated. Simple.
I think using the CQRS pattern, you will have events as well and corresponding event handlers. As you are using RabbitMQ for asynchronous communication between command and query then any message put on specific channel on RabbitMQ, can be listened by a callback method
Receiving messages from the queue is more complex. It works by subscribing a callback function to a queue. Whenever we receive a message, this callback function is called by the Pika library.