Bluemix Load Balancer Algorithm - load-balancing

What algorithm is used to balance HTTP load among several instances running on Bluemix? It seems I can use auto-scaling service to scale horizontally, and want to know what algorithm is used when balancing the load.

Cloud Foundry uses round-robin load balancing to distribute requests across the running instances of your app.

Related

Azure application gateway - caching and routing traffic

lets say there are 2 web services. The goal is, that the app gateway routes the requests to both of them. If one of them is down, it should cache all the requests. Once it is up again, which can happen hours later, all the requests cached in the meantime should be send to it in the correct sequence. This is to preserve both services in the same state. Is something like this possible with an application gateway? Or with any other webserver/tool?
Thanks!
u can do that but u need some configuration HTTP Load Balancing
Load Balancer Overview
The capacity of a single server is limited. Once a website gains more and more attraction the instance serving the site comes to a point where it can not handle any more users. The website starts to slow down or even become unavailable as the server goes down from the traffic.
This is the point where a load balancer enters the game. It allows to spread the “load” that all those visitors and their requests create to be “balanced” over a series of different instances.
In case of increasing load on a setup, capacity can easily be increased by adding more instances to the load balancers backend. This allows to scale your infrastructure without any downtime or delays whilst waiting for DNS zones to be updated.

Scaling out the zuul proxy

We have scaled out all sevices in our system by having more than one instance of them registered in eureka service registry.
Also, they are also proxied by a zuul server in the front.
My question is how can we ensure the scalability of zuul proxy when accessed from clients.
One solution i can think of is having multiple instances of the proxy registered in eureka registry. But if that is done how do we decide on which of the instances would be exposed to the clients.
We faced the same issue in our application, having multiple instances of multiple types of micro-service-type applications on our backend. All servers registered with Eureka. The problem is that we also had multiple security gateways configured (based on the architecture described in this excellent tutorial: https://spring.io/guides/tutorials/spring-security-and-angular-js/).
Eventually we decided to use a hardware http load balancer that calls our security gateways in a round-robin approach (our solution is on-prem).
We use Redis with #EnableHttpRedisSession annotation to have the spring session synced across all the servers, so the http load balancer does not have to deal with sticky sessions or stateful considerations. It just does a round-robin to all the security gateways. It doesn't matter if the load balancer hits SG1, SG2 or SG3, they all share the same session information coming from Redis (which is also configured for fail-over with Redis Sentinel).

Is load balancing with sticky sessions limited to a single load balancing server?

If you make a setup with multiple load balancers, can it still support sticky sessions (e.g. cookie based)?
Since sticky sessions rely on state stored at the load balancer, the different load balancers would have to exchange that information. So technically I believe it is feasible.
Are there any free/paying solutions which can be deployed on prem that provide this feature?
I guess load balancers of AWS, Azure, etc implement such a feature?

What is the conceptual difference between Service Discovery tools and Load Balancers that check node health?

Recently several service discovery tools have become popular/"mainstream", and I’m wondering under what primary use cases one should employ them instead of traditional load balancers.
With LBs, you cluster a bunch of nodes behind the balancer, and then clients make requests to the balancer, who then (typically) round robins those requests to all the nodes in the cluster.
With service discovery (Consul, ZK, etc.), you let a centralized “consensus” service determine what nodes for particular service are healthy, and your app connects to the nodes that the service deems as being healthy. So while service discovery and load balancing are two separate concepts, service discovery gives you load balancing as a convenient side effect.
But, if the load balancer (say HAProxy or nginx) has monitoring and health checks built into it, then you pretty much get service discovery as a side effect of load balancing! Meaning, if my LB knows not to forward a request to an unhealthy node in its cluster, then that’s functionally equivalent to a consensus server telling my app not to connect to an unhealty node.
So to me, service discovery tools feel like the “6-in-one,half-dozen-in-the-other” equivalent to load balancers. Am I missing something here? If someone had an application architecture entirely predicated on load balanced microservices, what is the benefit (or not) to switching over to a service discovery-based model?
Load balancers typically need the endpoints of the resources it balances the traffic load. With the growth of microservices and container based applications, runtime created dynamic containers (docker containers) are ephemeral and doesnt have static end points. These container endpoints are ephemeral and they change as they are evicted and created for scaling or other reasons. Service discovery tools like Consul are used to store the endpoints info of dynamically created containers (docker containers). Tools like consul-registrator running on container hosts registers container end points in service discovery tools like consul. Tools like Consul-template will listen for changes to containers end points in consul and update the load balancer (nginx) for sending the traffic to. Thus both Service Discovery Tools like Consul and Load Balancing tools like Nginx co-exist to provide runtime service discovery and load balancing capability respectively.
Follow up: what are the benefits of ephemeral nodes (ones that come and go, live and die) vs. "permanent" nodes like traditional VMs?
[DDG]: Things that come quickly to my mind: Ephemeral nodes like docker containers are suited for stateless services like APIs etc. (There is traction for persistent containers using external volumes - volume drivers etc)
Speed: Spinning up or destroying ephemeral containers (docker containers from image) takes less than 500 milliseconds as opposed to minutes in standing up traditional VMs
Elastic Infrastructure: In the age of cloud we want to scale out and in according to users demand which implies there will be be containers of ephemeral in nature (cant hold on to IPs etc). Think of a markerting campaign for a week for which we expect 200% increase in traffic TPS, quickly scale with containers and then post campaign, destroy it.
Resource Utilization: Data Center or Cloud is now one big computer (compute cluster) and containers pack the compute cluster for max resource utilization and during weak demand destroy the infrastructure for lower bill/resource usage.
Much of this is possible because of lose coupling with ephemeral containers and runtime discovery using service discovery tool like consul. Traditional VMs and tight binding of IPs can stifle this capability.
Note that the two are not necessarily mutually exclusive. It is possible, for example, that you might still direct clients to a load balancer (which might perform other roles such as throttling) but have the load balancer use a service registry to locate instances.
Also worth pointing out that service discovery enables client-side load balancing i.e. the client can invoke the service directly without the extra hop through the load balancer. My understanding is that this was one of the reasons that Netflix developed Eureka, to avoid inter-service calls having to go out and back through the external ELB for which they would have had to pay. Client-side load balancing also provides a means for the client to influence the load-balancing decision based on its own perspective of service availability.
If you look at the tools from a completely different perspective, namely ITSM/ITIL, load balancing becomes "just that", whereas service discovery is a part of keeping your CMDB up to date, and ajour with all your services, and their interconnectivity, for better visibility of impact, in case of downtime, and an overview of areas that may need supplementing, in case of High availability applications.
Furthermore, service-discovery only gives you a picture as of the last scan, and not near-real-time (of course dependent on which scanning interval you have set), whereas load balancing will keep an up-to-date picture of your application's health.

How can i view the UI of Elastic Load Balancer 2.1.0,

HI, just now i download the Elastic Load Balance 2.1.0 from WSO2 ,It
is running on terminal side of Linux ubuntu, but it is not showing the
Management console url. If it is not showing url where can i get UI
of Elastic Load Balance.
i have a multiple esb server with same configuration.if my a1 server
go down that time data load will shift to my a2 server .Is this use of
Elasticloadbalance will you explain me about this what is the exactly
use of this .
No, there is no UI component for ELB. Everything has to be done through configuring physical files.
Elastic LoadBalancer 2.1.0 is based on Hazlecast dependent clustering. This has two parts, one is load balancing and the other is elasticity. Load Balancing is simply distributing workload among a number of endpoints configured in a static or dynamic manner. Elasticity is simply scaling, ie monitoring load on worker nodes and starts or terminates nodes based on need on an IaaS environment.
Not only manages when a node goes down but also depending on load it can spawn new nodes to handle and if the load is low it can kill unwanted instances in an IaaS environment.