My angular application is consuming dotnet core API. My API is comsuming other APIs to send response. Sometimes, the other APIs I'm consuming takes too long to respond.
Thus, I dont want my angular application to keeps waiting for too long. I want to create a timeout middleware which returns, i dont know, a response saying "Request Timeout" or something for all the requests that takes more than 3-4 seconds.
I'm using dotnet core 2.2.
Related
SetUp:
We have gRPC pods running in a k8s cluster. The service mesh we use is linkerd. Our gRPC microservices are written in python (asyncio grpcs as the concurrency mechanism), with the exception of the entry-point. That microservice is written in golang (using gin framework). We have an AWS API GW that talks to an NLB in front of the golang service. The golang service communicates to the backend via nodeport services.
Requests on our gRPC Python microservices can take a while to complete. Average is 8s, up to 25s in the 99th %ile. In order to handle the load from clients, we've horizontally scaled, and spawned more pods to handle concurrent requests.
Problem:
When we send multiple requests to the system, even sequentially, we sometimes notice that requests go to the same pod as an ongoing request. What can happen is that this new request ends up getting "queued" in the server-side (not fully "queued", some progress gets made when context switches happen). The issue with queueing like this is that:
The earlier requests can start getting starved, and eventually timeout (we have a hard 30s cap from API GW).
The newer requests may also not get handled on time, and as a result get starved.
The symptom we're noticing is 504s which are expected from our hard 30s cap.
What's strange is that we have other pods available, but for some reason the loadbalancer isn't routing it to those pods smartly. It's possible that linkerd's smarter load balancing doesn't work well for our high latency situation (we need to look into this further, however that will require a big overhaul to our system).
One thing I wanted to try doing is to stop this queuing up of requests. I want the service to immediately reject the request if one is already in progress, and have the client (meaning the golang service) retry. The client retry will hopefully hit a different pod (do let me know if that won’t happen). In order to do this, I set the "maximum_concurrent_rpcs" to 1 on the server-side (Python server). When i sent multiple requests in parallel to the system, I didn't see any RESOURCE_EXHAUSTED exceptions (even under the condition when there is only 1 server pod). What I do notice is that the requests are no longer happening in parallel on the server, they happen sequentially (I think that’s a step in the right direction, the first request doesn’t get starved). That being said, I’m not seeing the RESOURCE_EXHAUSTED error in golang. I do see a delay between the entry time in the golang client and the entry time in the Python service. My guess is that the queuing is now happening client-side (or potentially still server side, but it’s not visible to me)?
I then saw online that it may be possible for requests to get queued up on the client-side as a default behavior in http/2. I tried to test this out in custom Python client that mimics the golang one with:
channel = grpc.insecure_channel(
"<some address>",
options=[("grpc.max_concurrent_streams", 1)]
)
# create stub to server with channel…
However, I'm not seeing any change here either. (Note, this is a test dummy client - eventually i'll need to make this run in golang. Any help there would be appreciated as well).
Questions:
How can I get the desired effect here? Meaning server sends resource exhausted if already handling a request, golang client retries, and it hits a different pod?
Any other advice on how to fix this issue? I'm grasping at straws here.
Thank you!
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 have a project that is related to job postings. Consultants or employers register on my website and then start posting jobs. I want to make push notifications for all users. When a consultant or employer posts a job, all online users must get notified that an employer has posted this job without any page refreshes on jquery setInterval or timeout.
I am using Spring framework. I have searched for the solution but found nothing. I want to know whether Spring provided WebSockets in their latest version. Is this possible to do with WebSockets?
I want a proper resource so that I can implement it on my website.
There are two ways to satisfy your need;
First is polling in which you repeatedly send requests from client to the server. On server side you somehow need have a kind of message queue for each client to deliver the incidents on a request. There also is a different type of polling in which you send a request from client and never end the request on the server-side thus you have a kind of pipe between two ends. This is called long polling.
Disadvantage of polling is that you have to send requests to the server forever from the client and in many cases server sends empty messages as there is no events happened.
The real application of pushing messages is recently avaliable with websockets (thanks to html5). However this requires the application server to be capable of websocket functionality. afaik jetty and tomcat has this ability. Spring 4 has websocket here you can find the tutorial; http://syntx.io/using-websockets-in-java-using-spring-4/
You can find a related stackoverflow post here
I am developing a client-side single-page-application (SPA) with AngularJS and ASP.Net WebAPI.
One of the features of the SPA includes uploading large CSV file, processing it on the server, and returning the output to the user.
Obviously, this kind of computation can not be done online, and therefore I implemented an UploadController in charge of receiving the file, and a PollingController in charge of notifying the user when the computation is complete.
The client side application monitors the PollingController every few seconds.
I have no experience in Message Queues, but my gut tells me that they are required in this situation.
How would you recommend to implement this functionality in a non-blocking, efficient way ?
Examples will be highly appreciated
I've used message based service bus frameworks for this in the past.
You write an application (running as a windows service), that listens for messages broadcast across a event bus.
Your frontend can publish these messages into the bus.
The most popular framework for this in .NET is NServiceBus, however it recently became commercial. You can also look into MassTransit, though this one has very poor documentation.
The workflow you would do:
MVC App accepts upload and places it into some directory accessible by the windows service
MVC App publishes "UploadReady" message.
Service receives message, processes file, and updates some state for the polling controller.
Polling controller watches for this state to change. Usually a DB record etc.
The nice bit about using a framework like this is that if your service goes down, or you redeploy it, any processing can queue and resume, so you won't have any downtime.
For long running operations you need separate Windows Service application (or Worker Role, if it is Windows Azure). IIS may kill ASP.NET processes on pool recycling and your operation will not finish.
Message queue is mostly for communication. You can use it between your web and worker parts. But it is not required there unless your data is not super critical. You can establish communication using database, cache, file system or 100 other different ways :)
You can use SignalR to notify your client about finished processing.
Currently I am using Jersey 1.0 and about to switch to 2.0. For REST requests the may last over a second or two I use the following pattern:
Client calls GET or PUT
Server returns a polling URL to the client
The client polls the URL until it gets a redirect to the completed resource
Pretty standard and straightforward. However, I noticed that Jersey 2.0 has an AsyncResponse capability. But it looks like this is done with no changes on the wire. In other words, the client still blocks for the result while the server is asynchronously processing the request.
So what good is this? Should I be using it instead of my current asynchronous approach for calls >1 second? Or is it really just to keep the connections freed on the server for calls that would be only a few hundred milliseconds?
I want my server to be as scalable as possible but the approach I use now can be tedious for the client. AsyncResponse seems super simple but I'm not sure how it would work for something like a heroku service where you want very short connection times.
AsyncResponse presumably gives you more scalability within the web app server for standard standard requests in terms of thread pooling resources, but I don't think it changes anything about the client experience which will continue to block on read on their connection. Therefore, if you already implemented a polling solution from your client side, this won't add much of any value to you imho.