I'm a little new to Redis, but I'd like to see if it can be used to keep track of how many concurrent HTTP connections I'm making.
Here's the high level plan:
INCR requests
// request begins
HTTP.get(...)
// request ends
DECR.requests
Then at any point, just call GET requests to see how many are currently open.
The ultimate goal here is to throttle my http requests to stay below some arbitrary amount, say 50 requests/s.
Is this the right way to do it? Are there any pitfalls?
As for pitfalls, the only one I can see is that a server that goes down or loses connection to Redis mid-request may never call DECR.
Since you don't know which server does which request, you can never reset the count to the correct value without bringing the system to a halt and reset to 0.
I'm not clear what you'd gain by using redis in this situation. It seems to me it would be more suitable to use just a global variable in your server. If your server goes down, so does your counter, so you don't have to put complicated things in place to deal with disconnection, inconsistencies, etc...
Related
I read there are web servers their behaviors are called blocking whereas Node.js's is said non-blocking.
Would a blocking web server get hung up to the sense it needs restarting, if many http clients send requests at most in parallel?
As a complement, I don't say that it needs restarting while it potentially works fine again after the flood of parallel requests have stopped.
And I currently don't understand how request buffers and overflows work for web servers.
Although technically it could be possible to make a single-thread, single-process blocking server that can only handle 1 request at a time, it doesn't really practically make sense. Concurrency is kind of important.
The three main paradigms for parallelism (that I know of) are:
Multi-process/forking
Threading
Using an event loop/reactor pattern
Node falls in the third category, and also a bit in the second category depending on how you look at it.
Most languages can look at a socket and read from it, and immediately move on if there was nothing to read. Therefore most languages can have this non-blocking behavior.
I am currently developing a Microservice that is interacting with other microservices.
The problem now is that those interactions are really time-consuming. I already implemented concurrent calls via Uni and uses caching where useful. Now I still have some calls that still need some seconds in order to respond and now I thought of another thing, which I could do, in order to improve the performance:
Is it possible to send a response before the sucessfull persistence of data? I send requests to the other microservices where they have to persist the results of my methods. Can I already send the user the result in a first response and make a second response if the persistence process was sucessfull?
With that, the front-end could already begin working even though my API is not 100% finished.
I saw that there is a possible status-code 207 but it's rather used with streams where someone wants to split large files. Is there another possibility? Thanks in advance.
"Is it possible to send a response before the sucessfull persistence of data? Can I already send the user the result in a first response and make a second response if the persistence process was sucessfull? With that, the front-end could already begin working even though my API is not 100% finished."
You can and should, but it is a philosophy change in your API and possibly you have to consider some edge cases and techniques to deal with them.
In case of a long running API call, you can issue an "ack" response, a traditional 200 one, only the answer would just mean the operation is asynchronous and will complete in the future, something like { id:49584958, apicall:"create", status:"queued", result:true }
Then you can
poll your API with the returned ID to see if the operation that is still ongoing, has succeeded or failed.
have a SSE channel (realtime server side events) where your server can issue status messages as pending operations finish
maybe using persistent connections and keepalives, or flushing the response in the middle, you can achieve what you point out, ie. like a segmented response. I am not familiar with that approach as I normally go for the suggesions above.
But in any case, edge cases apply exactly the same: For example, what happens if then through your API a user issues calls dependent on the success of an ongoing or not even started previous command? like for example, get information about something still being persisted?
You will have to deal with these situations with mechanisms like:
Reject related operations until pending call is resolved "server side": Api could return ie. a BUSY error informing that operations are still ongoing when you want to, for example, delete something that still is being created.
Queue all operations so the server executes all them sequentially.
Allow some simulatenous operations if you find they will not collide (ie. create 2 unrelated items)
I have a server to which my client sends a HTTP GET request with some values. The server on its end simply stores these values to a database.
Now, I am observing that sometimes I do not observe these values in the database. One of the following could have happened:
The client never sent it
The server never received it
The server failed in writing to the database
My strongest doubt is that the reason is 2 - but I am unable to explain it completely. Since this is an HTTP request (which means there is TCP underneath) reliable delivery of the GET request should be guaranteed, right? Is it possible that even though I send a GET request to the server - it was never received by the server? If yes, what is TCP doing there?
Or, can I confidently assert that if the server is up and running and everything sent to the server is written to the database, then the absence of the details of the GET request in the database means the client never sent it?
Not sure if the details will help - but I am running a tomcat server and I am just sending a name-value pair through the get request.
There are a few things you seem to be missing. First of all, yes, if TCP finishes successfully, you pretty much have a guarantee that your message (i.e. the TCP payload) has reached the other side: TCP assures that it will take care of lost packages and the order in which packages arrive. However, this is not universially failproof, as there are still things beyond the powers of TCP (think of a physical disconnect by cutting through an ethernet cable). There is also no assertion regarding the syntactical correctness of the protocol "above." Any checks beyond delivering a bit-perfect copy is simply not TCP's concern.
So, there is a chance that the requests issued by your client are faulty or that they are indeed correct but not parsed correctly by your server. Former is striking me as more likely as latter one as Tomcat is a very mature piece of software. I think it would help tremendously if you would record and analyse some of your generated traffic through e.g. Wireshark.
You do not really mention what database you have in use. But there are some sacrificing acid-compliance in favour of increased write speeds. The nature of these databases brings it that you can never be really sure wether something actually got written to disk or is still residing in some buffer in memory. Should you happen to use such a db, this were another line of investigation.
Programmatically, I advise you take the following steps when dealing with HTTP traffic:
Has writing to the socket finishes without error?
Could a response be read from the socket?
Does the response carry a code in the 2xx range (indicating a successful operation)?
If any of these fail, you should really log something.
On a realated note, what you are doing there does not call for the GET method but for POST as you are changing application state. Consider it as a nice-to-have ;)
Without knowing the specifics, you can break it down into two parts. The HTTP request and the DB write. The client will receive a 200 OK response from the server when its GET request has been acknowledged. I've written code under Tomcat to connect to a MySQL DB using DAO. In the case of a failure an exception would be thrown and logged. Which ever method you're using, you'll want to figure out how failures are logged.
From a lot of articles and commercial API I saw, most people make their APIs idempotent by asking the client to provide a requestId or idempotent-key (e.g. https://www.masteringmodernpayments.com/blog/idempotent-stripe-requests) and basically store the requestId <-> response map in the storage. So if there's a request coming in which already is in this map, the application would just return the stored response.
This is all good to me but my problem is how do I handle the case where the second call coming in while the first call is still in progress?
So here is my questions
I guess the ideal behaviour would be the second call keep waiting until the first call finishes and returns the first call's response? Is this how people doing it?
if yes, how long should the second call wait for the first call to be finished?
if the second call has a wait time limit and the first call still hasn't finished, what should it tell the client? Should it just not return any responses so the client will timeout and retry again?
For wunderlist we use database constraints to make sure that no request id (which is a column in every one of our tables) is ever used twice. Since our database technology (postgres) guarantees that it would be impossible for two records to be inserted that violate this constraint, we only need to react to the potential insertion error properly. Basically, we outsource this detail to our datastore.
I would recommend, no matter how you go about this, to try not to need to coordinate in your application. If you try to know if two things are happening at once then there is a high likelihood that there would be bugs. Instead, there might be a system you already use which can make the guarantees you need.
Now, to specifically address your three questions:
For us, since we use database constraints, the database handles making things queue up and wait. This is why I personally prefer the old SQL databases - not for the SQL or relations, but because they are really good at locking and queuing. We use SQL databases as dumb disconnected tables.
This depends a lot on your system. We try to tune all of our timeouts to around 1s in each system and subsystem. We'd rather fail fast than queue up. You can measure and then look at your 99th percentile for timings and just set that as your timeout if you don't know ahead of time.
We would return a 504 http status (and appropriate response body) to the client. The reason for having a idempotent-key is so the client can retry a request - so we are never worried about timing out and letting them do just that. Again, we'd rather timeout fast and fix the problems than to let things queue up. If things queue up then even after something is fixed one has to wait a while for things to get better.
It's a bit hard to understand if the second call is from the same client with the same request token, or a different client.
Normally in the case of concurrent requests from different clients operating on the same resource, you would also want to implementing a versioning strategy alongside a request token for idempotency.
A typical version strategy in a relational database might be a version column with a trigger that auto increments the number each time a record is updated.
With this in place, all clients must specify their request token as well as the version they are updating (typical the IfMatch header is used for this and the version number is used as the value of the ETag).
On the server side, when it comes time to update the state of the resource, you first check that the version number in the database matches the supplied version in the ETag. If they do, you write the changes and the version increments. Assuming the second request was operating on the same version number as the first, it would then fail with a 412 (or 409 depending on how you interpret HTTP specifications) and the client should not retry.
If you really want to stop the second request immediately while the first request is in progress, you are going down the route of pessimistic locking, which doesn't suit REST API's that well.
In the case where you are actually talking about the client retrying with the same request token because it received a transient network error, it's almost the same case.
Both requests will be running at the same time, the second request will start because the first request still has not finished and has not recorded the request token to the database yet, but whichever one ends up finishing first will succeed and record the request token.
For the other request, it will receive a version conflict (since the first request has incremented the version) at which point it should recheck the request token database table, find it's own token in there and assume that it was a concurrent request that finished before it did and return 200.
It's seems like a lot, but if you want to cover all the weird and wonderful failure modes when your dealing with REST, idempotency and concurrency this is way to deal with it.
We have a memory intensive processing for certain functionality and we would like to limit the number of parallel requests to this processing. We are able to configure by using "Work Managers" in WebLogic and putting a limit on the number of threads for that servlet.
For example, if we put maximim thread limit as 3, then if there are 10 parallel requests; 7 requests are in queue. There could be situations where these the requests waiting in queue could take up to 30-40 minutes to be processed. We did simple testing and the received page cannot be displayed due to timeout after 15 mins and received the message after 1 hour.
Does any one know if there is a setting in WebLogic to increase/decrease timeout and avoid page cannot be displayed?
Appreciate if any one has any thoughts around this.
Does any one know if there is a setting in WebLogic to increase/decrease timeout and avoid page cannot be displayed?
There might be something but I actually didn't check as it would be a bad advice anyway. By looking for this, you are trying to solve the wrong problem here. A browser is just not made for long-running process like the one you are describing (>30mn) even if you don't mind the user waiting (not mentioning that he could refresh the page and queue more and more jobs).
So, the right answer here is in my opinion: use asynchronism, this is the perfect use case. When the user clicks on the button, send a JMS message to a queue (or create a Quartz job) and send the user a page with a request ID telling him to come back later. When the processing is done, update the status somewhere and make the status/result available to the user. Really, the user experience will be better doing this and you'll face less problems than with a browser.
1) Use some other tool (not browser) like WGET where you can control timeout parameter (--timeout).
2) Why do you use HTTP? Use message driven beans and send message JMS to that and don't care about time outs.
Perhaps quartz can do what you need? Start a job and check in on it as you need to?