I setup an Active/Passive cluster with Pacemaker/Corosync/DRBD. I wanted to make an Asterisk server HA. The solution works perfectly but when the service fails on one server and starts on another all registered SIP clients with the active server will be lost. And the passive server show nothing in the output of:
sip show peers
Until clients make a call or register again. One solution is to set the Registration rate on clients to 1 Min or so. Are there other options? For example integrating Asterisk with a DBMS helps to save this kind of state in a DB??
First of all doing clusters by non-expert is bad idea.
You can use realtime sip architecture, it save state in database. Complexity - average. Note, "sip show peers" for realtime also show nothing.
You can use memory duplicating cluster(some solution for xen exists) which will copy memory state from one server to other. Complexity - very complex.
Related
I'm trying to build instant messaging app. Clients will not only send messages but also often send audios. And I've decided to use websocket connection to communicate with clients. It is fast and allows to send binary data.
The main idea is to receive from client1 message and notify about it client2. But here's the thing. My app will be running on GAE. And what if client1's socket is opened on server1 and client2's is opened on server2. This servers don't know about each others clients.
I have one idea how to solve it, but I am sure it is shitty way. I am going to use some sort of communication between servers(for example JMS or open another websocket connection between servers, doesn't matter right now).
But it surely will lead to a disaster. I can't even imagine how often those servers will speak to each other. For each message server1 should notify server2, server2 should notify client2. But things become even worse when serverN comes into play.
Another way I see this to work is Firebase. But it restricts message size to 4KB. So I can't send audios via it. As a solution I can notify client about new audio and he goes to my server for it.
Hope I clearly explained the problem. Does anyone know how to solve it? Or maybe there are another ways to build such apps?
If you are building a messaging cluster and expect communicating clients to connect to different instances of the server then server-server communication is inevitable. Usually it's not a problem though.
First, if you don't use any load balancing your clients will connect to the same server 50% of time on average (in case of 2 servers).
Second, intra-datacenter links are fast and free in all known public clouds.
Third, you can often do something smart on the frontend to make sure two likely to communicate clients connect to the same server. For instance direct all clients from the same country to the same server using DNS load balancing.
The second part of the question is about passing large media files. It's a common best practice to send it out of band - store on the server and only pass the reference to it. Like someone suggested in the comment, save the audio on the server and just send a message like "audio is available, fetch it from here ...". You don't need to poll the server for that. Just fetch it once when the receiving client requests it.
In general, it seems like you are trying to reinvent the wheel. Just use something off the shelf.
Let all client get connected to multiple servers and each server keeps this metadata
A centralized system like zookeeper stores active servers details
When a client c1 sends a message to client c2:
the message is received by a server (say s1, we can add a load balancer to distribute incoming requests)
s1 will broadcast this information to all other servers to get which server the client c2 is connected to OR a better approach to use consistent hashing which decides which server the client can connect to & in this approach message broadcast is not required
the corresponding server responses to server s1 (say s2)
now s1 sends the message m to s2 and server s2 to client c2
Cons of the above approach:
Each server will have a connection with the n-1 servers, creating a mesh topology
Centralized system (zookeeper) becomes a single point of failures (which is solvable)
Apps like Whatsapp, G-Talk uses XMPP and TCP/IP.
I m studying Microservices architecture and I m actually wondering something.
I m quite okay with the fact of using (back) service discovery to make request able on REST based microservices. I need to know where's the service (or at least the front of the server cluster) to make requests. So it make sense to be able to discover an ip:port in that case.
But I was wondering what could be the aim of using service registry / discovery when dealing with AMQP (based only, without HTTP possible calls) ?
I mean, using AMQP is just like "I need that, and I expect somebody to answer me", I dont have to know who's the server that sent me back the response.
So what is the aim of using service registry / discovery with AMQP based microservice ?
Thanks for your help
AMQP (any MOM, actually) provides a way for processes to communicate without having to mind about actual IP addresses, communication security, routing, among other concerns. That does not necessarily means that any process can trust or even has any information about the processes it communicates with.
Message queues do solve half of the process: how to reach the remote service. But they do not solve the other half: which service is the right one for me. In other words, which service:
has the resources I need
can be trusted (is hosted on a reliable server, has a satisfactory service implementation, is located in a country where the local laws are compatible with your requirements, etc)
charges what you want to pay (although people rarely discuss cost when it comes to microservices)
will be there during the whole time window needed to process your service -- keep in mind that servers are becoming more and more volatile. Some servers are actually containers that can last for a couple minutes.
Those two problems are almost linearly independent. To solve the second kind of problems, you have resource brokers in Grid computing. There is also resource allocation in order to make sure that the last item above is correctly managed.
There are some alternative strategies such as multicasting the intention to use a service and waiting for replies with offers. You may have reverse auction in such a case, for instance.
In short, the rule of thumb is that if you do not have an a priori knowledge about which service you are going to use (hardcoded or in some configuration file), your agent will have to negotiate, which includes dynamic service discovery.
The server consists of several services with which a user interacts: profiles, game logics, physics.
I heard that it's a bad practice to have multiple client connections to the same server.
I'm not sure whether I will use UDP or TCP.
The services are realtime, they should reply as fast as possible so I don't want to include any additional rerouting if there are no really important reasons. So are there any reasons to rerote traffic through one external endpoint service to specific internal services in my case?
This seems to be multiple questions in one package. I will try to answer the ones I can identify as separate...
UDP vs TCP: You're saying "real-time", this usually means UDP is the right choice. However, that means having to deal with lost packets and possible re-ordering of packets. But, using UDP leaves a couple of possible delay-decreasing tricks open.
Multiple connections from a single client to a single server: This consumes resources (end-points, as it were) on both the client (probably ignorable) and on the server (possibly a problem, possibly ignorable). The advantage of using separate connections for separate concerns (profiles, physics, ...) is that when you need to separate these onto separate servers (or server farms), you don't need to update the clients, they just need to connect to other end-points, using code that's already tested.
"Re-router" (or "load balancer") needed: Probably not going to be an issue initially. However, it will probably become an issue later. Depending on your overall design and server OS, using UDP may actually become an asset here. UDP packet arrives at the load balancer, dispatched to the right backend and that could then in theory send back a reply with the source IP of the load balancer.
An alternative would be to have a "session broker". The client makes an initial connection to a well-known endpoint, says "I am a client, tell me where my profile, physics, what-have0-you servers are", the broker considers the current load, possibly the location of the client and other things that may make sense and the client then connects to the relevant backends on its own. The downside of this is that it's harder (not impossible, but harder) to silently migrate an ongoing session to a new backend, when there's a load-balancer in the way, this can be done essentially-transparently.
I am building a distributed system that consists of potentially millions of clients which all need to keep an open (preferrably HTTP) connection to wait for a command from the server (which is running somewhere else). The load of messages / commmands will not be very high, maybe one message / sec / 1000 clients which means it would be 1000 msg/sec # 1 million clients. => it's basically about the concurrent connections.
The requirements are simple too. One way messaging (server->client), only 1 client per "channel".
I am pretty open in terms of technology (xmpp / websockets / comet / ...). I am using Google App Engine as server, but their "channels" won't work for me unfortunately (too low quotas and no Java client). XMPP was an option but is quite expensive. So far I was using URL Fetch & pubnub, but they just started charging for connections (big time).
So:
Does anyone know of a service out there that can do that for me in an affordable way? Most I have found restrict or heavily charge for connections.
Any experience with implementing such a server yourself? I have actually done that already and it works pretty well (based on Tomcat & NIO) but I haven't had the time yet to actually set up a large load test environment (partially because this is still a fallback solution, I'd prefer a battle hardened msg server). Any experience to how many users you get per GB? Any hard limits?
My architecture also allows to fragment the msg servers, but I'd like to maximize the concurrent connections because the msg processing CPU overhead is minimal.
I have meanwhile implemented my own message server using netty.io. Netty makes use of Java NIO and scales extremely well. For idle connections I get a memory footprint of 500 bytes per connection. I am doing only very simple message forwarding (no caching, storage or other fancy stuff) but with that am easily getting 1000 - 1500 msg / sec (each half a KB) on the small amazon instance (1ECU / 1.6GB).
Otherwise if you are looking for a (paid) service then I can recommend spire.io (they do not charge for connections but have a higher price per message) or pubnub (they do charge for connections but are cheaper per message).
You have to look more in architecture of making such environment.
First of all, if you will write sockets management by yourself, then don't use Thread per Client Socket. Use Asynchronous methods for receiving and sending data.
WebSockets might be too heavy if your messages are small. Because it implements framing, which has to be applied to each message for each socket individually (caching can be used for different versions of WebSockets protocols), that makes them slower to process both directions: for receive and for send, especially because of data masking.
It is possible to create millions of sockets, but only most advanced technologies are capable to do so. Erlang is able to handle millions connections, and is pretty scalable.
If you would like to have millions of connections using other higher level technologies, then you need to think about clustering of what you are trying to accomplish.
For example using gateway server that will keep track of all processing servers. And have data of them (IP, ports, load (if it will be one internal network, firewalling and port forwarding might be handy here).
Client software connects to that gateway server, gateway server checks the least loaded server and sends ip and port to client. Client creates connection directly to working server using provided address.
That way you will have gateway which as well can handle authorization, and wont hold connections for long, so one of them might be enough. And many workers that are doing publishing of data and keeping connections.
This is very related to your needs, and might not be suitable for your solutions.
Recently I've added some load-balancing capabilities to a piece of software that I wrote. It is a networked application that does some data crunching based on input coming from a SQL database. Since the crunching can be pretty intensive I've added the capability to have multiple instances of this application running on different servers to split the load but as it is now the load balancing is a manual act. A user must specify which instances take which portion of the input domain.
I would like to take that to the next level and program the instances to automatically negotiate the diving up of the input data and to recognize if one of them "disappears" (has crashed or has been powered down) so that the remaining instances can take on the failed instance's workload.
In order to implement this I'm considering using a simple heartbeat protocol between the instances to determine who's online and who isn't and while this is not terribly complicated I'd like to know if there are any established heartbeat network protocols (based on UDP, TCP or both).
Obviously this happens a lot in the networking world with clustering, fail-over and high-availability technologies so I guess in the end I'd like to know if maybe there are any established protocols or algorithms that I should be aware of or implement.
EDIT
It seems, based on the answers, that either there are no well established heart-beat protocols or that nobody knows about them (which would imply that they aren't so well established after all) in which case I'm just going to roll my own.
While none of the answers offered what I was looking for specifically I'm going to vote for Matt Davis's answer since it was the closest and he pointed out a good idea to use multicast.
Thank you all for your time~
Distribued Interactive Simulation (DIS), which is defined under IEEE Standard 1278, uses a default heartbeat of 5 seconds via UDP broadcast. A DIS heartbeat is essentially an Entity State PDU, which fully defines the state, including the position, of the given entity. Due to its application within the simulation community, DIS also uses a concept referred to as dead-reckoning to provide higher frequency heartbeats when the actual position, for example, is outside a given threshold of its predicted position.
In your case, a DIS Entity State PDU would be overkill. I only mention it to make note of the fact that heartbeats can vary in frequency depending on the circumstances. I don't know that you'd need something like this for the application you described, but you never know.
For heartbeats, use UDP, not TCP. A heartbeat is, by nature, a connectionless contrivance, so it goes that UDP (connectionless) is more relevant here than TCP (connection-oriented).
The thing to keep in mind about UDP broadcasts is that a broadcast message is confined to the broadcast domain. In short, if you have computers that are separated by a layer 3 device, e.g., a router, then broadcasts are not going to work because the router will not transmit broadcast messages from one broadcast domain to another. In this case, I would recommend using multicast since it will span the broadcast domains, providing the time-to-live (TTL) value is set high enough. It's also a more automated approach than directed unicast, which would require the sender to know the IP address of the receiver in order to send the message.
Broadcast a heartbeat every t using UDP; if you haven't heard from a machine in more than k*t, then it's assumed down. Be careful that the aggregate bandwidth used isn't a drain on resources. You can use IP broadcast addresses, or keep a list of specific IPs you're doing work for.
Make sure the heartbeat includes a "reboot count" as well as "machine ID" so that you know previous server state isn't around.
I'd recommend using MapReduce if it fits. It would save a lot of work.
I'm not sure this will answer the question but you might be interested by the way Weblogic Server clustering work under the hood. From the book Mastering BEA WebLogic Server:
[...] WebLogic Server clustering provides a loose coupling of the servers in the cluster. Each server in the cluster is independent and does not rely on any other server for any fundamental operations. Even if contact with every other server is lost, each server will continue to run and be able to process the requests it receives. Each server in the cluster maintains its own list of other servers in the cluster through periodic heartbeat messages. Every 10 seconds, each server sends a heartbeat message to the other servers in the cluster to let them know it is still alive. Heartbeat messages are sent using IP multicast technology built into the JVM, making this mechanism efficient and scalable as the number of servers in the cluster gets large. Each server receives these heartbeat messages from other servers and uses them to maintain its current cluster membership list. If a server misses receiving three heartbeat messages in a row from any other server, it takes that server out of its membership list until it receives another heartbeat message from that server. This heartbeat technology allows servers to be dynamically added and dropped from the cluster with no impact on the existing servers’ configurations.
Cisco content switches are a hardware solution for this problem. They implement a virtual IP address as a front end to multiple real servers, whose real IP addresses are known to the switch. The switch periodically sends HTTP HEAD requests to the web servers, to verify they are still running (which the switch software calls a "keepalive", although this doesn't keep the server itself alive). The Cisco switch accepts traffic on the virtual IP and forwards it to the actual web servers, using configurable load balancing such as round-robin, or user-defined load balancing.
These switches retail in the $3-10K range, although my business partner picked one up on eBay for about $300 a year ago. If you can afford one, they do represent a proven hardware solution to the question of how to have a service spread transparently across multiple servers. Redhat includes a built-in port configuration so that you could implement your own Cisco switch using a cheap RedHat box. Google for "virtual ip address" and "cisco content router" for more information.
In addition to trying hardware load-balancers, you can also try a free-open-source load-balancing software application such as HAProxy, available for Linux and the BSDs.