This is software design question more than a coding one.
I am about to implement a feature where I can verify user's emails and phone numbers using Twilio's sms and voice apis.
My current implementation instantiates a Voice client at start up of the app and then I reuse this client whenever any user decides to verify email or voice.
Question: Is it a good idea to instantiate Twilio client once and then re-use it each time or should I create a new one each time it is needed?
I have browsed the Net for articles but haven't found something conclusive. Hoping to clarify here.
You are looking at whether the twillo client is thread-safe. A quick google search found this: Twilio Threaded Messages. I have not looked at the source myself, but I would consider this a likely answer that yes, it is thread-safe.
I'm not familiar with Twilio. But usually, since 3rd party API is out of our control, its stability, performance, etc, are all questions, and potentially, you might want to change to another service provider. So, firstly, try your best to decouple your own logic from 3rd ones. For instance, design an interface for this logic, and one implementation for Twilio.
Secondly, you need to test the Twilio client instance, ensure it could keep working for long time after instantiated, and if your programming language or runtime work in multi-thread way, you need to also test to make sure the instance could work properly when it is shared by multi-threads (if not, the instance is not threadsafe, you might consider using some mutex style locking on it).
Furthermore, if the 3rd party services execution is not stable, or, takes time for execution, etc, and specifically, for your email/sms verification case, it is not necessary to call the services synchronously and wait for responses. You could consider to use a worker queue, putting all tasks to the queue, and create some workers, running in asynchronous threads, to get tasks from queue and execute.
Related
I am writing payroll management web application in nodejs for my organisation. In many cases application shall involve cpu intensive mathematical calculation for calculating the figures and that too with many users trying to do this simulatenously.
If i plainly write the logic (setting aside the fact that i already did my best from algorithm and data structure point of view to contain the complexity) it will run synchronously blocking the event loop and make request, response slow.
How to resolve this scenario? What are the possible options to do this asynchronously? I also want to mention that this calculation stuff can be let to run in the background and later i can choose to tell user via notification about the status. I have searched for the solution all over this places and i found some solutions but only in theory & i haven't tested them all by implementing. Mentioning below:
Clustering the node server
Use worker threads
Use an alternate server and do some load balancing.
Use a message queue and couple it with worker thread to do backgound tasks.
Can someone suggest me some tried and battle tested advice on this scenario? and also some tutorial links associated with that.
You might wanna try web workers,easy to use and documented.
https://developer.mozilla.org/en-US/docs/Web/API/Web_Workers_API/Using_web_workers
We're planning on implementing a server-side notification mechanism that pushes out to iOS and Android via ANH. We will have no code footprint on our mobile clients, short of a call to our server API for "registration". In this way our approach is looking similar to this MSDN discussion.
I also see the alternate, more bare-bones, approach noted on MSDN.
Is it fair to conclude that the two approaches will have similar performance on the 'send' side?
It appears the main difference is this:
The former approach has already done the work of integrating with the Task and Async mechanism, presenting a callable C# mechanism that has taken on more of the RESTful API layer,
The DirectBatch/Send API is just that -- the raw RESTful API for you to use as you see fit.
For operations that are available as both REST API and SDK, you shouldn't see any significant difference in performance on the client side because the SDK is just a wrapper around the REST APIs. There are SDKs for both iOS and Android and it's recommended to use those so that you don't have to re-write the wrapper.
Direct Send is only available in .NET SDK at the moment and for other platforms as REST API, so you'd have to implement your own wrapper in case you're using something other than .NET for the operation. You can use the sample to help you in the process.
In terms of performance it depends on what you mean by that.
Direct send will most likely be delivered to customers a bit faster because ANH service doesn't have to do any registrations in the process, it just delivers notifications with your parameters. But it has it's limitations in terms of number of handles you can provide and also you need to manage handles yourself.
If you only mean performance on the client side, then there should be no difference as all calls are asynchronous. And if you take advantage of tags, then you can do really tricky sends in one server call and let ANH figure out the details behind it.
But without knowing your scenario and requirements there's no way to give a proper recommendation.
I have a Node.js app with a small set of users that is currently architected with a single web process. I'm thinking about adding an after save trigger that will get called when a record is added to one of my tables. When that after save trigger is executed, I want to perform a large number of IO operations to external APIs. The number of IO operations depends on the number of elements in an array column on the record. Thus, I could be performing a large number of asynchronous operations after each record is saved in this particular table.
I thought about moving this work to a background job as suggested in Worker Dynos, Background Jobs and Queueing. The article gives as a rule of thumb that tasks that take longer than 500 ms be moved to background job. However, after working through the example using RabbitMQ (Asynchronous Web-Worker Model Using RabbitMQ in Node), I'm not convinced that it's worth the time to set everything up.
So, my questions are:
For an app with a limited amount of concurrent users, is it ok to leave a long-running function in a web process?
If I eventually decide to send this work to a background job it doesn't seem like it would be that hard to change my after save trigger. Am I missing something?
Is there a way to do this that is easier than implementing a message queue?
For an app with a limited amount of concurrent users, is it ok to leave a long-running function in a web process?
this is more a question of preference, than anything.
in general i say no - it's not ok... but that's based on experience in building rabbitmq services that run in heroku workers, and not seeing this as a difficult thing to do.
with a little practice, you may find that this is the simpler solution, as I have (it allows simpler code, and more robust code, as it splits the web away from the background processor - allowing each to run without knowing about each other directly)
If I eventually decide to send this work to a background job it doesn't seem like it would be that hard to change my after save trigger. Am I missing something?
are you missing something? not really
as long as you write your current in-the-web-process code in a well structured and modular fashion, moving it to a background process is not usually a big deal
most of the panic that people get from having to move code into the background, comes from having their code tightly coupled to the HTTP request / response process (i know from personal experience how painful it can be)
Is there a way to do this that is easier than implementing a message queue?
there are many options for distributed computing and background processing. i personally like RabbitMQ and the messaging patterns that it uses.
i would suggest giving it a try and seeing if it's something that can work well for you.
other options include redis with pub/sub libraries on top of it, using direct HTTP API calls to another web server, or just using a timer in your background process to check database tables on a given frequency and having the code run based on the data it finds.
p.s. you may find my RabbitMQ For Developers course of interest, if you are wanting to dig deeper into RMQ w/ node: http://rabbitmq4devs.com
The Problem
Our liferay system is the basis to synchronize data with other web-applications.
And we use Model Listeners for that purpose.
There are a lot of web-service calls and database updates through the listeners and consequently the particular action in liferay is too slow.
For example:
On adding of a User in liferay we need to fire a lot of web-service calls to add user details and update other systems with the userdata, and also some liferay custom tables. So the adding of User is taking a lot of time and in a few rare cases the request may time-out!
Since the code in the UserListener only depends on the User Details and even if there is any exception in UserListener still the User would be added in Liferay, we have thought of the following solution.
We also have a scheduler in liferay which fixes things if there was some exception while executing code in Listeners.
Proposed Solution
We thought of making the code in UserListener asynchronous by using Concurrency API.
So here are my questions:
Is it recommended to have concurrent code in Model Listeners?
If yes, then will it have any adverse effect if we also update Liferay custom tables through this code, like transactions or other stuff?
What can be other general Pros and Cons of this approach?
Is there any other better-way we can have real-time update to other systems without hampering User-experience?
Thank you for any help on this matter
It makes sense that you want to use Concurrency to solve this issue.
Doing intensive work like invoking web services etc in the thread that modifies the model is not really a good idea, apart from the impact it will have on user experience.
Firing off threads within the models' listeners may be somewhat complex and hard to maintain.
You could explore using Liferay's Message Bus paradigm where you can send a message to a disconnected message receiver which will then do all the intensive work outside of the model listener's calling thread.
Read more about the message bus here:
Message Bus Developer Guide
Message Bus Wiki
I'm writing a piece to a project that's responsible for processing tasks outside of the main application facing data server, which is written in javascript using Node.js. It needs to handle tasks which are scheduled in the future and potentially handle tasks that are "right now". The "right now" just means the next time a worker becomes available it will operate on that task, so that bit might not matter. The workers are going to all talk to external resources, an example job would be to send an email. We are a small shop and we don't have a ton of resources so one thing I don't want to do is start mixing languages at this point in the process, and I already see that Node can do this for us pretty easily, so that's what we're going to go with unless I see a compelling reason not to before I start coding, which is soon.
All that said, I can't tell if there is a compelling reason to use an AMQP based server, like OpenAMQ or RabbitMQ over something like Kue or Beanstalkd with a node client. So, here we go:
Is there a compelling reason to use an AMQP based server over something like beanstalkd or redis with Kue? If yes, which AMPQ based server would fit best with the architecture that I laid out? If no, which nosql solution (beanstalkd, redis/Kue) would be easiest to set up and fastest to deploy?
FWIW, I'm not accepting my answer yet, I'm going to explain what I've decided and why. If I don't get any answers that appear to be better than what I've decided, I'll accept my own later.
I decided on Kue. It supports multiple workers running asynchronously, and with cluster it can take advantage of multicore systems. It is easily extended to provide security. It's backed with Redis, which is used all over for this exact thing, so I know I'm not backing my job process server with unproven software (that's not to say that any of the others are unproven.)
The most compelling reasons that I picked Kue is that it provides a JSON api so that the client applications (The first client is going to be a web based application, but we're planning on making smartphone apps also) can add jobs easily without going through the main application facing node instance, so I can be totally out of the way of the rest of my team as I write this. I don't need a route, I don't need anything, and it's all provided for me so I don't need to write anything to support this. This has another advantage, with an extention to provide l/p security only authorized clients can add jobs, so I don;t have to expose my redis server to client applications directly. It also has a built in web console and the API allows the client to pull back lists of jobs associated with a given user very easily, so we can show the user all of their scheduled tasks in a nifty calendar view with 0 effort on my part.
The other compelling reason is the lack of steep learning curve associated with getting redis and Kue going for me. I've set up redis before, and Kue is simple and effective.
Yes, I'm a lazy developer, but I'm the good kind of lazy developer.
UPDATE:
I have it working and doing jobs, the throughput is amazing. I split out the task marshaling logic into it's own node instance, basically all I have to do is deploy my repo to a new machine and run node task-server.js to scale out my workers. I may need to add in some more job searching calls to Kue, because of how I implimented a few things, but that will be easy.