We have WCF service X: deployed on server A and Server B, host address:
http://127.0.0.1:8777/ServiceX/
And we load balance the two servers. We accesss the service via http://myappserver/ServiceX
We need to use per-session mode, and we set [reliable sessions] as true:
We don't find any issue till now based on testing. But the below linked MSDN article says that Do not use reliable sessions for Load Balancing with the WSHttp Binding? Please can someone give more details? Thanks a lot.
WCF Load Balancing http://msdn.microsoft.com/en-us/library/ms730128.aspx
Reliable Messaging means all your messages from your established client reach the same endpoint behind any intermediaries like routers and load balancers.
Load balancing means your calls will be distributed across all nodes as the load balancer sees fit.
Those two goals are mutually exclusive. You can have one or the other, not both.
I have not had time to try this myself yet, but I found this old blog entry (https://blogs.msdn.microsoft.com/drnick/2007/07/13/sticky-sessions/):
This division according to groups would allow a feature like reliable messaging to work because the same server would be used to process all of the messages in the reliable session. The feature that this division method represents is typically called “sticky sessions” or some other phrase for affinitization in the load balancer.
Given that you mention that your firewall supports sticky sessions, I suspect/hope you will be fine.
Related
Hi I'm little confused about load balancer concept
I've read some articles about loadbalancer in nginx and from what I've understand is that the load balancer spread the request into multiple servers !
But i thought if one server is down another one is up and running (not simultaneously all server together)
and another thing is when request spread between servers what happen to static data like sessions and InMemory Database like RedisDB
I think i'm confused and missunderstood the loadbalancer mechanism
and from what I've understand is that the load balancer spread the request into multiple servers ! But i thought if one server is down another one is up and running (not simultaneously all server together)
As it comes from the name the goal of load balancer (LB) is to balance the load. As per wiki definition for example:
In computing, load balancing is the process of distributing a set of tasks over a set of resources (computing units), with the aim of making their overall processing more efficient. Load balancing can optimize the response time and avoid unevenly overloading some compute nodes while other compute nodes are left idle.
To perform this task load balancer obviously need to have some monitoring over the resources, including liveness checks (so it can bring out of the rotation the failing servers/nodes). Ideally LB should work with stateless services (i.e. request could be routed to any of the servers supporting handling such request type) but that is not always the case due to multiple reasons, for example in ASP.NET in case of non-distributed session requests should have been routed to servers which handled the previous request from the session, which could have been handled with so called sticky session/cookie.
and another thing is when request spread between servers what happen to static data like sessions and InMemory Database like RedisDB
It is not very clear what is the question here. As I mentioned before ideally you will want to have stateless services which will use some shared datastore (s) to handle the requests, so if request comes for any server/node it can load all the needed data to handle it.
So in short when request comes to LB it selects one of the servers based on some algorithm (round robin, resource based, sharding, response time based, etc.) and send this request to this server so in theory based on the used approach sequential requests from the same source can hit different nodes/servers (so basically this is one of the ways to horizontally scale your application).
I actually found my answer in nginx doc page
Short answer is IP-Hash mechanism
Nginx doc word :
Please note that with round-robin or least-connected load balancing, each subsequent client’s request can be potentially distributed to a different server. There is no guarantee that the same client will be always directed to the same server.
If there is the need to tie a client to a particular application server — in other words, make the client’s session “sticky” or “persistent” in terms of always trying to select a particular server — the ip-hash load balancing mechanism can be used.
With ip-hash, the client’s IP address is used as a hashing key to determine what server in a server group should be selected for the client’s requests. This method ensures that the requests from the same client will always be directed to the same server except when this server is unavailable.
To configure ip-hash load balancing, just add the ip_hash directive to the server (upstream) group configuration:
upstream myapp1 {
ip_hash;
server srv1.example.com;
server srv2.example.com;
server srv3.example.com;
}
http://nginx.org/en/docs/http/load_balancing.html
Hi I am new to Marklogic and Apache. I have been provided task to use apache as loadbalancer for our Marklogic cluster of 3 machines. Marklogic cluster is currently running on Linux servers.
How can we achieve this? Any information regarding this would be helpful.
You could use mod_proxy_balancer. How you configure it depends what MarkLogic client you would like to use. If you would like to use the Java Client API, please follow the second example here to allow apache to generate stickiness cookies. If you would like to use XCC, please configure it to use the ML-Server-generated or backend-generated "SessionID" cookie.
The difference here is that XCC uses sessions whereas the Java Client API builds on the REST API which is stateless, so there are no sessions. However, even in the Java Client API when you use multi-request transactions, that imposes state for the duration of that transaction so the load balancer needs a way to route requests during that transaction to the correct node in the MarkLogic cluster. The stickiness cookie will be resent by the Java Client API with every request that uses a Transaction so the load balancer can maintain that stickiness for requests related to that transaction.
As always, do some testing of your configuration to make sure you got it right. Properly configuring apache plugins is an advanced skill. Since you are new to apache, your best hope of ensuring you got it right is checking with an HTTP monitoring tool like WireShark to look at the HTTP traffic from your application to MarkLogic Server to make sure things are going to the correct node in the cluster as expected.
Note that even with the client APIs (Java, Node.js) its not always obvious or explicit at the language API layer what might cause a session to be created. Explicitly creating multi statement transactions definately will, but other operations may do so as well. If you are using the same connection for UI (browser) and API (REST or XCC) then the browser app is likely to be doing things that create session state.
The safest, but least flexable configuration is "TCP Session Affinity". If they are supported they will eliminate most concerns related to load balancing. Cookie Session Affinity relies on guarenteeing that the load balencer uses the correct cookie. Not all code is equal. I have had cases where it the load balancer didn't always use the cookie provided. Changing the configuration to "Load Balancer provided Cookie Affinity" fixed that.
None of this is needed if all your communications are stateless at the TCP layer, the HTTP layer and the app layer. The later cannot be inferred by the server.
Another conern is if your app or middle tier is co-resident with other apps or the same app connecting to the same load balancer and port. That can be difficult to make sure there are no 'crossed wires' . When ML gets a request it associates its identity with the client IP and port. Even without load balencers, most modern HTTP and TCP client libraries implement socket caching. A great perfomrance win, but a hidden source of subtle random severe errors if the library or app are sharing "cookie jars" (not uncomnon). A TCP and Cookie Jar cache used by different application contexts can end up sending state information from one unrelated app in the same process to another. Mostly this is in middle tier app servers that may simply pass on requests from the first tier without domain knowledge, presuming that relying on the low level TCP libraries to "do the right thing" ... They are doing the right thing -- for the use case the library programmers had in mind -- don't assume that your case is the one the library authors assumed. The symptoms tend to be very rare but catastrophic problems with transaction failures and possibly data corruption
and security problems (at an application layer) because the server cannot tell the difference between 2 connections from the same middle tier.
Sometimes a better strategy is to load balance between the first tier and the middle tier, and directly connect from the middle tier to MarkLogic.
Especially if caching is done at the load balancer. Its more common for caching to be useful between the middle tier and the client then the middle tier and the server. This is also more analogous to the classic 3 tier architecture used with RDBMS's .. where load balancing is between the client and business logic tiers not between business logic and database.
Can someone explain to me how high-availability ("HA") works for a web application ... because I assume HA means that there exist no single-point-of-failure.
However, even if a load balancer is used- isn't that the single point of failure?
I have found this article on the subject:
http://www.tenereillo.com/GSLBPageOfShame.htm
Basically if you do not require long lasting sticky sessions you can configure your DNS servers to return multiple A records (IP addresses) for your website.
Web browsers are smart enough to try all the addresses until they find one that works.
In simple words high availability can be defined as running a system 24*7 without a downtime even if there are hardware and software failures. In other way a fault tolerance application. This helps ensure uninterrupted use of the application for it’s intended users.
Read more on High Availability Deployment Architecture
It works the following way that you setup two HA Proxy servers with heartbeat, so when one fails (stops responding to queries), it's being removed from the cluster.
Requests from HA Proxy can be forwarded to web servers in round robin fashion, and if one web server fails, HA Proxy servers do not try to contact it until it's alive.
Web servers are storing all dynamic information in database, which is replicated across two MySQL instances.
As you can see, HA Proxy and Cluster MySQL (or simply MySQL replication) as well IP Clustering here is the key.
Sure it is when operated alone. Usual highly available setup includes 2 or more load balancers running in cluster in either active/active or active/passive configuration. To further increase the availability you can have 2 different Internet Service Providers (or geo distributed datacenters) each running a pair of clustered load balancers. Then you configure DNS A record resolving to 2 distinct public IP addresses which guarantees round-robin processing splitting DNS requests evenly (CloudFlare is very fast and reliable at this). There's also possibility to return IP address of datacenter closest to your originating geo location by using something like PowerDNS dnsdist
This is what big players do to make their services highly available.
Please read https://docs.oracle.com/cd/E23824_01/html/821-1453/gkkky.html for more clearity. Actually both load balancer uses same vip(Virtual IP Address. https://techterms.com/definition/vip).
HA architecture is a entire field and multiple books were written on it, so it is hard to answer in a short paragraph.
To sum up the ideal situation, you would be using multiple servers, interconnected to a layer of multiple load balancers. The nodes and LB will be located in a few different data centers, and connected to different network backbone. Ideally the data centers will be located all over the world.
In short, all component will have redundancy, including the load balancers.
For a starting point, see Wikipedia for High Availability Cluster
I've written a simple server application which will run distributed on several machines.
My question is how does a network load balancer works, in general?
I've heard of round-robin and other algorithms, but what I haven't got answer to is how does the process really goes? In socket terms.
The client connects to one of the load balancer machines, asks for a "free-to-connect-to" server and simply connects to it?
That's the simpliest way I can think of.
.. or, does it use the load balancer as a proxy (that implies that all the NBs must be always connected to the application servers, and data is transferred through them)?
It's more of a general question. How would you do this?
Thank you all!
There are several different ways to load balance an application. Some are physical devices that sit between your router and the servers; some are software based with a bit of code that runs on each of the load balanced devices.
Microsoft has load balancing built into Windows which is all software based. It's pretty good and easy to set up.
However, I'll cover the physical route.
There are several algorithms here, but the main one is Round Robin with an option for "sticky" sessions. Sticky in this case means that the load balancer will try to keep a history of clients and forward requests from the same client to the same machine. This means the load balancer needs to keep a list of clients and where it directed those clients. Depending on cache size, clients may fall off the list and on future requests they may be forwarded to a different server.
Round Robin is a pretty simple idea. For each request that comes in send it to the next server in the list. More complicated algorithms might take into account how many requests go to a particular server and how long are those requests taking; then try to rebalance new requests to favor faster servers. This part is complicated though.
I have a Glassfish v2u2 cluster with two instances and I want to to fail-over between them. Every document that I read on this subject says that I should use a load balancer in front of Glassfish, like Apache httpd. In this scenario failover works, but I again have a single point of failure.
Is Glassfish able to do that fail-over without a load balancer in front?
The we solved this is that we have two IP addresses which both respond to the URL. The DNS provider (DNS Made Easy) will round robin between the two. Setting the timeout low will ensure that if one server fails the other will answer. When one server stops responding, DNS Made Easy will only send the other host as the server to respond to this URL. You will have to trust the DNS provider, but you can buy service with extremely high availability of the DNS lookup
As for high availability, you can have cluster setup which allows for session replication so that the user won't loose more than potentially one request which fails.
Hmm.. JBoss can do failover without a load balancer according to the docs (http://docs.jboss.org/jbossas/jboss4guide/r4/html/cluster.chapt.html) Chapter 16.1.2.1. Client-side interceptor.
As far as I know glassfish the cluster provides in-memory session replication between nodes. If I use Suns Glassfish Enterprise Application Server I can use HADB which promisses 99.999% of availability.
No, you can't do it at the application level.
Your options are:
Round-robin DNS - expose both your servers to the internet and let the client do the load-balancing - this is quite attractive as it will definitely enable fail-over.
Use a different layer 3 load balancing system - such as "Windows network load balancing" , "Linux Network Load balancing" or the one I wrote called "Fluffy Linux cluster"
Use a separate load-balancer that has a failover hot spare
In any of these cases you still need to ensure that your database and session data etc, are available and in sync between the members of your cluster, which in practice is much harder.