Are there any destructive calls that can be invoked with a HTTP GET calling Elasticsearch?
Examples of "destructive" might include actions such as delete items/delete indexes/change settings... pretty much anything that can modify settings/state of the Elasticsearch or the data.
I want to make an operational command line tool which would allow any arbitrary GET request to elastic search if GET requests are safe. So there isn't worry about DDOS attacks or anyone on purpose being malicious since operational tool will only be accessible to engineers.
Related
Supposed I have a CQRS-based system and my domain needs some data from an external web service to make its decisions. How do I model this correctly?
I can think of two options:
The command handler runs the domain logic and the domain itself calls out to the web service. Once it gets a response, it attaches the appropriate events to the current aggregate and stores them. The domain basically "waits" for the web service to return.
The command handler runs the domain logic and the domain immediately emits a domain-internal more data needed event. A process manager reacts on this, talks to the web service, reacts on the result, and creates another command on the former aggregate, basically something such as continue.
Which approach is "better", or are both wrong, and I should follow a completely separate way? Basically, I'm fine with option 1, because I think this is basically nothing but a long-running computation inside the domain, but somehow the idea of "waiting" irritates me.
What should I do?
I tend to think of my domain as I do about a physical calculator. It takes input and produces output. That output can be either stored or emitted as events. So in goes data, some behaviour takes place, and out comes data. So very much focused on behaviour.
Your option (1) scenario has resulted in a couple of DDD discussions around injecting services or repositories (or, I guess, an anti-corruption layer) into entities. The general concensus is that it should be avoided and one should opt for, say, double-dispatch. The point is that the domain then needs more information and it either needs to be passed in initially or it needs to be fetched. In my calculator analogy fetching more data is like the calculator prompting you for more input.
If you go with option (1) then whatever is calling the domain needs to handle any web-call failure in order to retry.
If you go with option (2) where you use something like a service bus and, possibly, a process engine of sorts (say saga or workflow) it is quite likely that the service bus handler or the process engine is going to be handling the failures and retries.
I don't think one solution is necessarily 'better' than the other but rather 'different'. I'd go with whatever you feel comfortable with and if you have infrastructure dealing with the failure/retry in some way already then I'd go with the option that is most easily supported by that infrastructure.
Hope that helps :)
I always read that one reason to chose a RESTful architecture is (among others) better scalability for Webapplications with a high load.
Why is that? One reason I can think of is that because of the defined resources which are the same for every client, caching is made easier. After the first request, subsequent requests are served from a memcached instance which also scales well horizontally.
But couldn't you also accomplish this with a traditional approach where actions are encoded in the url, e.g. (booking.php/userid=123&travelid=456&foobar=789).
A part of REST is indeed the URL part (it's the R in REST) but the S is more important for scaling: state.
The server end of REST is stateless, which means that the server doesn't have to store anything across requests. This means that there doesn't have to be (much) communication between servers, making it horizontally scalable.
Of course, there's a small bonus in the R (representational) in that a load balancer can easily route the request to the right server if you have nice URLs, and GET could go to a slave while POSTs go to masters.
I think what Tom said is very accurate, however another problem with scalability is the barrier to change upon scaling. So, one of the biggest tenants of REST as it was intended is HyperMedia. Basically, the server will own the paths and pass them to the client at runtime. This allows you to change your code without breaking existing clients. However, you will find most implementations of REST to simply be RPC hiding behind the guise of REST...which is not scalable.
"Scalable" or "web scale" is one of the most abused terms when it comes to the web, the cloud and REST, and mainly used to convince management to get their support for moving their development team on board the REST train.
It is a buzzword that holds no value. If you search the web for "REST scalability" you'll find a lot of people parroting each other without any concrete evidence.
A REST service is exactly equally scalable as a service exposed over a SOAP interface. Both are just HTTP interfaces to an application service. How well this service actually scales depends entirely on how this service was actually implemented. It's possible to write a service that cannot scale as all in both REST and SOAP.
Yes, you can do things with SOAP that makes it scale worse, like rely on state and sessions. SOAP out of the box does not do this. This requires you to use a smarter load balancer, which you want anyway if you're really concerned with whatever form of scaling.
One thing that REST allows that SOAP doesn't, and that some other answers here address, is caching cacheable responses through an HTTP caching proxy or at the client side. This may make a REST service somewhat more lightly loaded than a SOAP service when a lot of operations' responses are cacheable. All this means is that fewer requests end up in your service.
The main reason behind saying a rest application is scalable is, Its built upon a HTTP protocol. Because HTTP is stateless. Stateless means it wont share anything between other request. So any request can go to any Server in a load balanced cluster. There is nothing forcing this user request go to this server. We can overcome this by using token.
Because of this statelessness,All REST application are very easy to scale. But if you want get high throughput(number of request capable in one second) in each server, then you should optimize blocking things from the application. Follow the following tips
Make each REST resource is a small entity. Don't read data from join of many tables.
Read data from near by databases
Use caches (Redis) instead of databases(You can save DISK I/O)
Always keep data sources as much as near by because these blocks will make server resources (CPU) ideal and it no other request can use that resource while it is ideal.
A reason (perhaps not the reason) is that RESTful services are sessionless. This means you can easily use a load balancer to direct requests to various web servers without having to replicate session state among all of your web servers or making sure all requests from a single session go to the same web server.
I am looking to implement a service (web/windows, .net) that maintains a list of available services and can provide an endpoint based on the nature or type of request. The requester can then pass the actual work request to the provided endpoint. The actual work requests can contain very large chunks (from 10MB up to and possibly exceeding a GB) of data.
WCF routing services sounds like a perfect fit, but turns out not to be because the it requires the actual work request to pass through it, creating a bottleneck at the routing service (the whole point is to get a system to be able to scale out). If I had smaller messages, WCF routing would be a no brainer.
Is there anything out there that fits the bill? Preferably .NET/windows based?
Do you mean because the requests block for work?
Do could use OneWay OperationContract to create async services so as to not block the request pool.
[ServiceContract]
interface IMyContract
{
[OperationContract(IsOneWay = true)]
void DoWork()
}
Update
I think understand your question better now, you are looking to distribute load to different servers to avoid request bottle necks due to heavy traffic load (preferably distributed based on content).
I'd say that MVC Routing is indeed ideal for this. One of the features that you can leverage is the fall over functionality. You can actually define multiple backup endpoints, and in the case where one fails, it will automatically move over to the next. There's a good introduction to how this works here.
There's also a good article here that talks about load balancing with WCF using the same principles. It provides 2 solutions for a round robin filter implementation that allows you to load balance the service requests (even though at the begin he says his general answer to whether it supports load balancing is no for implementation reasons).
If you are worried about all requests routing via the one server and still becoming a bottle neck, then think of web load balancers. It's the same scenario. Sitting in the middle forwarding packets doesn't require much work, and they have no problem handling huge volumes of traffic. I don't think this is an issue IMO.
Which is the best approach for creating a fast response in case a client application asks webserver for "check for updates".
Skype for example takes about 1 second to answer. How to achieve the same?
I assume you are running one or more web servers and one or more back-end servers (with business logic).
One possible approach that I have seen: keep a change counter in webserver and when the back-end state changes, let the business logic notify all webservers with new change counter value.
Each web browser polls regularly the webserver for counter value and compares the value to the previous value. In case old_value != new_value, the web browser goes and asks the webserver for new content.
This allows the regular polling to be super-fast (1ms) and cheap. And only if something has really changed the browser will ask for more resource-expensive content generation.
The other option would be to use some asynchronous HTTP magic (cometd) but the approach outlined above is simpler, more understandable and easier to troubleshoot.
The simple approach is to just have a flat text or XML file on the server, containing the details of the most recent version. The client app fetches it via http GET, compares the version, and reacts accordingly. The http server is simply returning a small file, which is what http servers are designed to do. You should be able to handle hundreds of requests per second this way.
Use a large, distributed systems, depending on the number of your users. Put your web server(s) closer to clients, avoiding longer latencies. Use cluster and load balancing software to enhance performance. Use reverse proxies to cache data.
But is is really important that a "check for updates" is that fast? You can also check in a background thread. I would improve performance for other tasks.
What kind of server do you people see in real projects?
1) Web Services MUST be stateless: Basically you must send username/password with every request, every request must use HTTPS and I will authenticate and load the User object everytime if needed.
2) A Session for Web Services: like in a web container so I can at least save the authenticated User object and have something similar to a session ID so I don't need to authenticate, load and check the User on every request.
3) Sticky Service (persistent service across requests): https://jax-ws.dev.java.net/nonav/2.1/docs/statefulWebservice.html
I understand the scalability problems of stateful services (and of web application sessions), but sometimes you must have some kind of state, for example for a shopping cart. But you can also put this state in the database (use the back-end as a kind of session argh) or passing the entire state to the client (the client becomes responsible for resending the entire shopping cart).
The truth is, at least for web applications, the session helps a lot in many situations. Scalability issues can be ignored if your system accepts that "the user must start over doing whatever he is doing if his web server happens to go down" or you can try a session cluster if that's unacceptable.
How it is for web services? I am inclined to conclude that web services are very different than web applications and accept option 1) (always stateless), but it would be nice to hear other opinions based on real project experience.
While it's only a small difference but it should still be mentioned:
It's not state in web services that kill scalability, rather it's state on the App Server that's hosting the web services that will kill scalability. The moment you say that this user needs to access this server (as done in sticky sessions) you are effectively limiting your scalability options. The point you want to get to is that 'Any of your free load-balanced App servers' can handle this web service request and if I add 1 more App Server I should be able to handle % more users.
It's totally fine (and personally recommended) if you want to maintain state to pass in an authentication token and on each request get the service to retrieve your 'state' from a data store (preferably a redundant and partitioned one, e.g. distributed+replicated key/value data store). That's how Amazon does it with SimpleDb and Google with BigTable.
Ebay takes a slightly different approach and stores most of the clients state in a cookie so it gets passed in with every request. Although it generates a lot more traffic, it still scalable as any of their servers can still handle the request.
If you want a scalable data store I would recommend looking at redis it has speed and features that can't be beat in a key/value data store.
You should also check out highscalability.com if you want access to good material on how to build fast and scalable services.
Ideally webservices (and web sites) should be stateless.
Unfortunately this takes very well thought out problem domain, and clear separation of concerns.
I've found that in practice most real-world web sites depend on state even though this limits their scalability.
I've also found that many real-world web-services also rely on state.
Ultimately the 'right' decision is the one that works for the specific problem, so it's probably okay to write a webservice that relies on state, and refactor it later if scalability becomes an issue.
Highly dependent on whether the service is single transaction oriented (say getting stock quotes) or if the output from the service is dependent on a data provided from a particular client across multiple transactions(in that case state must be maintained.)
As far as scalability issues, storing state in a database isn't actually a bad way to go (in fact it's probably the only way to go if you're load balancing your service across a server farm.)
I think with Flex clients the state is moved out of the service and into the client tier. Keep the services stateless and let the clients maintain the state needed. The services stay simple, and the clients are free to mash them together as they wish.
You seem to be equating state and authentication. Perhaps you're accustomed to storing username and password in session state?
This is not necessary, even with old ASMX web services. Simply pass whatever information you need to your "Login" operation. This operation will be defined to return an "Authentication Ticket" header.
All other operations that require authentication will require this "Authentication Ticket" header. They will each check the header to see if it represents a valid, authenticated user. If so, then they will perform their task. If not, then they will return a SOAP Fault indicating that authentication is required.
No state is required. Simply make sure that the authentication ticket can be validated on any server your service runs on (for instance, in a web farm), and you'll be fine.