I have .Net core App deployed on azure and enabled application insights.
Sometimes Azure application insights End-to-end transaction details do not display all telemetry.
Here it only logs the error and not request or maybe request logged but both do not display together over here(difficult to find out due to many people use it)
Should be like:
Sometimes request log but with no error log.
What could be the reason for happening this? do I need to look into application insights specific set-up/feature?
Edit:
As suggested by people here, try to disable the Sampling feature but still not works, Here is open question as well.
This usually happens due to sampling. By default, adaptive sampling is enabled in the ApplicationInsights.config which basically means that only a certain percentage of each telemetry item type (Event, Request, Dependency, Exception, etc.) is sent to Application insights. In your example probably one part of the end to end transaction got sent to the server, another part got sampled out. If you want, you can turn off sampling for specific types, or completely remove the
AdaptiveSamplingTelemetryProcessor
from the config which completely disables sampling. Bear in mind that this leads to higher ingestion traffic and higher costs.
You can also configure sampling in the code itself, if you prefer.
Please find here a good overview of how sampling works and can be configured.
This may be related to :
When using SDK 2.x, you have to track all events and send the telemetries to Application insights
When using auto-instrumentation with 3.x agent, in this case the agent collect automatically the traffic, logs ... and you have to pay attention to the sampling file applicationinsights.json where you can filter the events.
If you are using java, below the accepted Logging libraries :
-java.util.logging
-Log4j, which includes MDC properties
-SLF4J/Logback, which includes MDC properties
We are using Micro services architecture where top services are used for exposing REST API's to end user and backend services does the work of querying database.
When we get 1 user request we make ~30k requests to backend service. We are using RxJava for top service so all 30K requests gets executed in parallel.
We are using haproxy to distribute the load between backend services.
However when we get 3-5 user requests we are getting network connection Exceptions, No Route to Host Exception, Socket connection Exception.
What are the best practices for this kind of use case?
Well you ended up with the classical microservice mayhem. It's completely irrelevant what technologies you employ - the problem lays within the way you applied the concept of microservices!
It is natural in this architecture, that services call each other (preferably that should happen asynchronously!!). Since I know only little about your service APIs I'll have to make some assumptions about what went wrong in your backend:
I assume that a user makes a request to one service. This service will now (obviously synchronously) query another service and receive these 30k records you described. Since you probably have to know more about these records you now have to make another request per record to a third service/endpoint to aggregate all the information your frontend requires!
This shows me that you probably got the whole thing with bounded contexts wrong! So much for the analytical part. Now to the solution:
Your API should return all the information along with the query that enumerates them! Sometimes that could seem like a contradiction to the kind of isolation and authority over data/state that the microservices pattern specifies - but it is not feasible to isolate data/state in one service only because that leads to the problem you currently have - all other services HAVE to query that data every time to be able to return correct data to the frontend! However it is possible to duplicate it as long as the authority over the data/state is clear!
Let me illustrate that with an example: Let's assume you have a classical shop system. Articles are grouped. Now you would probably write two microservices - one that handles articles and one that handles groups! And you would be right to do so! You might have already decided that the group-service will hold the relation to the articles assigned to a group! Now if the frontend wants to show all items in a group - what happens: The group service receives the request and returns 30'000 Article numbers in a beautiful JSON array that the frontend receives. This is where it all goes south: The frontend now has to query the article-service for every article it received from the group-service!!! Aaand your're screwed!
Now there are multiple ways to solve this problem: One is (as previously mentioned) to duplicate article information to the group-service: So every time an article is assigned to a group using the group-service, it has to read all the information for that article form the article-service and store it to be able to return it with the get-me-all-the-articles-in-group-x query. This is fairly simple but keep in mind that you will need to update this information when it changes in the article-service or you'll be serving stale data from the group-service. Event-Sourcing can be a very powerful tool in this use case and I suggest you read up on it! You can also use simple messages sent from one service (in this case the article-service) to a message bus of your preference and make the group-service listen and react to these messages.
Another very simple quick-and-dirty solution to your problem could also be just to provide a new REST endpoint on the articles services that takes an array of article-ids and returns the information to all of them which would be much quicker. This could probably solve your problem very quickly.
A good rule of thumb in a backend with microservices is to aspire for a constant number of these cross-service calls which means your number of calls that go across service boundaries should never be directly related to the amount of data that was requested! We closely monitory what service calls are made because of a given request that comes through our API to keep track of what services calls what other services and where our performance bottlenecks will arise or have been caused. Whenever we detect that a service makes many (there is no fixed threshold but everytime I see >4 I start asking questions!) calls to other services we investigate why and how this could be fixed! There are some great metrics tools out there that can help you with tracing requests across service boundaries!
Let me know if this was helpful or not, and whatever solution you implemented!
Requirement: I need to create a background worker/task that will get data from an external source ( message queue) at certain intervals ( i.e. 10s) and update a database. Need to run non stop 24hrs. An ASP.NET application is placing the data to the message queue.
Possible solutions:
Windows service with timer
Pros: Takes load away from web server
Cons: Separate deployment overhead, Not load balanced
Use one of the methods described here : background task
Pros: No separation deployment required, Can be load balanced - if one server goes down another can pick it up
Cons: Overhead on web server (however, in my case with max 100 concurrent users and seeing the web server resources are under-utilized, I do not think it will be an issue)
Question: What would be a recommended solution and why?
I am looking for a .net based solution.
You shouldn't go with the second option unless there's a really good reason for it. Decoupling your background jobs from your web application brings a number of advantages:
Scalability - It's up to you where to deploy the service. It can share the same server with the web application or you can easily move it to a different server if you see the load going up.
Robustness - If there's a critical bug in either the web application or the service this won't bring the other component down.
Maintanance - Yes, there's a slight overhead as you will have to adjust your deployment process but it's as simple as copying all binaries from the output folder and you will have to do it once only. On the other hand, you won't have to redeploy the application thus brining it down for some time if you just need to fix a small bug in the service.
etc.
Though I recommend you to go with the first option I don't like the idea with timer. There's a much simpler and robust solution. I would implement a WCF service with MSMQ binding as it provides you with a lot of nice features out of the box:
You won't have to implement polling logic. On start up the service will connect to the queue and will sit waiting for new messages.
You can easily use transaction to process queue messages. For example, if there's something wrong with the database and you can't write to it the message which is being processed at the moment won't get lost. This will get back to the queue to be processed later.
You can deploy as many services listening to the same queue as you wish to ensure scalability and availability. WCF will make sure that the same queue message is not processed by more than one service that is if a message is being processed by service A, service B will skip it and get the next available message.
Many other features you can learn about here.
I suggest reading this article for a WCF + MSMQ service sample and see how simple it is to implement one and use the features I mentioned above. As soon as you are done with the WCF service you can easily host it in a windows service.
Hope it helps!
We are applying unittests, integration tests and we are practicing test driven and behaviour driven development.
We are also monitoring our applications and servers from outside (with dedicated software in our network)
What is missing is some standard for a live monitoring inside the apllication.
I give an example:
There should be a cron-like process inside the application, that regularily checks some structural health inside our data structures
We need to monitor that users have done some regular stuff that does not endanger the health of the applications (there are some actions and input that we can not prevent them to do)
My question is, what is the correct name for this so I can further research in the literature. I did a lot of searching but I almosdt always find the xunit and bdd / integration test stuff that I already have.
So how is this called, what is the standard in professional application development, I would like to know if there is some standard structure like xunit, or could xunit libraries even bee used for it? I could not even find appropriate tagging for this question, so please if you read this and know some better tags, why not add them to this answer and remove the ones that don't fit.
I need this for applications written in python, erlang or javascript and those are mostly server side applications, web applications or daemons.
What we are already doing is that we created http gateway from inside the applications that report some stuff and this is monitored by the nagios infrastructure.
I have no problem rolling some cron-like controlled self health scheme inside the applications, but I am interested about knowing some professional standardized way of doing it.
I found this article, it already comes close: Link
It looks like you are asking about approaches how to monitor your application. In general, one can distinguish between active monitoring and passive monitoring.
In active monitoring, you create some artificial user load that would mimic real user behavior, and monitor your application based on these artificial responses from a non-existing user (active = you actively cause traffic to your application). Imagine that you have a web application which allows to get weather forecast for specific city. To have active monitoring, you will need to deploy another application that would call your web application with some predefined request ("get weather for Seattle") every N hours. If your application does not respond within the specified time interval, you will trigger alert based on that.
In passive monitoring, you observe real user behavior over time. You can use log parsing to get number of (un)successful requests/responses, or inject some code into your application that would update some values in database whenever successful or not successful response was returned (passive = you only check other users' traffic). Then, you can create graphs and check whether there is a significant deviation in user traffic. For example, if during the same time of the day one week ago your application served 1000 requests, and today you get only 200 requests, it may mean some problem with your software.
I am building an ASP.NET web application that will be deployed to a 4-node web farm.
My web application's farm is located in California.
Instead of a database for back-end data, I plan to use a set of web services served from a data center in New York.
I have a page /show-web-service-result.aspx that works like this:
1) User requests page /show-web-service-result.aspx?s=foo
2) Page's codebehind queries a web service that is hosted by the third party in New York.
3) When web service returns, the returned data is formatted and displayed to user in page response.
Does this architecture have potential scalability problems? Suppose I am getting hundreds of unique hits per second, e.g.
/show-web-service-result.aspx?s=foo1
/show-web-service-result.aspx?s=foo2
/show-web-service-result.aspx?s=foo3
etc...
Is it typical for web servers in a farm to be using web services for data instead of database? Any personal experience?
What change should I make to the architecture to improve scalability?
You have most definitely a scalability problem: the third-party web service. Unless you have a service-level agreement with that service (agreeing on the number of requests that you can submit per second), chances are real that you overload that service with your anticipated load. That you have four nodes yourself doesn't help you then.
So you should a) come up with an agreement with the third party, and b) test what the actual load is that they can take.
In addition, you need to make sure that your framework can use parallel connections for accessing the remote service. Suppose you have a round-trip time of 20ms from California to New York (which would be fairly good), you can not make more than 50 requests over a single TCP connection. Likewise, starting new TCP connections for every request will also kill performance, so you want pooling on these parallel connections.
I don't see a problem with this approach, we use it quite a bit where I work. However, here are some things to consider:
Is your page rendering going to be blocked while waiting for the web service to respond?
What if the response never comes, i.e. the service is down?
For the first problem I would look into using AJAX to update the page after you get a response back from the web service. You'll also want to consider how to handle the no response or timeout condition.
Finally, you should really think about how you could cache the web service data locally. For example if you are calling a stock quoting service then unless you have a real-time feed, there is no reason to call the web service with every request you get. Store the data locally for a period of time and return that until it becomes stale.
You may have scalability problems but most of these can be carefully engineered around.
I recommend you use ASP.NET's asynchronous tasks so that the web service is queued up, the thread is released while the request waits for the web service to respond, and then another thread picks up when the web service is done to finish off the request.
MSDN Magazine - Wicked Code - Asynchronous Pages in ASP.NET 2.0
Local caching is an absolute must. The fewer times you have to go from California to New York, the better. You might want to look into Microsoft's Velocity (although that's still in CTP) or NCache, or another distributed cache, so that each of your 4 web servers don't all have to make and cache the same data from the web service - once one server gets it, it should be available to all.
Microsoft Project Code Named "Velocity"
NCache
Other things that can go wrong that you should engineer around:
The web service is down (obviously) and data falls out of cache, and you can't get it back. Try to make it so that the data is not actually dropped from cache until you're sure you have an update available. Then the only risk is if the service is down and your application pool is reset, so don't reset it as a first-line troubleshooting maneuver!
There are two different timeouts on web requests, a connect and an overall timeout. Make sure both are set extremely low and you handle both of them timing out. If the service's DNS goes down, this can look like quite a different failure.
Watch perfmon for ASP.NET Queued Requests. This number will rise rapidly if the service goes down and you're not covering it properly.
Research and adjust ASP.NET performance registry settings so you have a highly optimized ASP.NET thread pool. I don't remember the specifics, but I seem to remember that there's a limit on IO Completion Ports and something else of that nature that are absurdly low for the powerful hardware I'm assuming you have on hand.
the trendy answer is REST. Any GET request can be HTTP Response cached (with lots of options on how that is configured) and it will be cached by the internet itself (your ISP, essentially).
Your project has an architecture that reflects they direction that Microsoft and many others in the SOA world want to take us. That said, many people try to avoid this type of real-time risk introduced by the web service.
Your system will have a huge dependency on the web service working in an efficient manner. If it doesn't work, or is slow, people will just see that your page isn't working properly.
At the very least, I would get a web stress tool and performance test your web service to at least the traffic levels you expect to get at peaks, and likely beyond this. When does it break (if ever?), when does it start to slow down? These are good metrics to know.
Other options to look at: perhaps you can get daily batches of data from the web service to a local database and hit the database for your web site. Then, if for some reason the web service is down or slow, you could use the most recently obtained data (if this is feasible for your data).
Overall, it should be doable, but you want to understand and measure the risks, and explore any potential options to minimize those risks.
It's fine. There are some scalability issues. Primarily, with the number of calls you are allowed to make to the external web service per second. Some web services (Yahoo shopping for example) limit how often you can call their service and will lock out your account if you call too often. If you have a large farm and lots of traffic, you might have to throttle your requests.
Also, it's typical in these situations to use an interstitial page that forks off a worker thread to go and do the web service call and redirects to the results page when the call returns. (Think a travel site when you do search, you get an interstitial page while they call out to an external source for the flight data and then you get redirected to a results page when the call completes). This may be unnecessary if your web service call returns quickly.
I recommend you be certain to use WCF, and not the legacy ASMX web services technology as the client. Use "Add Service Reference" instead of "Add Web Reference".
One other issue you need to consider, depending on the type of application and/or data you're pulling down: security.
Specifically, I'm referring to authentication and authorization, both of your end users, and the web application itself. Where are these things handled? All in the web app? by the WS? Or maybe the front-end app is authenticating the users, and flowing the user's identity to the back end WS, allowing that to verify that the user is allowed? How do you verify this? Since many other responders here mention a local data cache on the front end app (an EXCELLENT idea, BTW), this gets even MORE complicated: do you cache data that is allowed to userA, but not for userB? if so, how do you verify that userB cannot access data from the cache? What if the authorization is checked by the WS, how do you cache the permissions then?
On the other hand, how are you verifying that only your web app is allowed to access the WS (and an attacker doesn't directly access your WS data over the Internet, for instance)? For that matter, how do you ensure that your web app contacts the CORRECT WS server, and not a bogus one? And of course I assume that all the connection to the WS is only over TLS/SSL... (but of course also programmatically verify the cert applies to the accessed server...)
In short, its complicated, and many elements to consider here.... but it is NOT insurmountable.
(as far as input validation goes, that's actually NOT an issue, since this should be done by BOTH the front end app AND the back end WS...)
Another aspect here, as mentioned by #Martin, is the need for an SLA on whatever provider/hosting service you have for the NY WS, not just for performance, but also to cover availability. I.e. what happens if the server is inaccessible how quickly they commit to getting it back up, what happens if its down for extended periods of time, etc. That's the only way to legitimately transfer the risk of your availability being controlled by an externality.