![ranger kms client loadbalance ranger kms client loadbalance](https://raw.githubusercontent.com/HortonworksUniversity/Security_Labs/master/screenshots/Ranger-KMS-audit.png)
Is there a native solution in Kubernetes? Why does the logic have to be moved into the client? So if these protocols are so popular, why isn't there a standard answer to load balancing? You might recognise most of the protocols above. createPoolCluster ( ) var endpoints = /* retrieve endpoints from the Service */ for ( var of endpoints ) // Make queries to the clustered MySQL databaseĪs you can imagine, several other protocols work over long-lived TCP connections. Index.js var mysql = require ( 'mysql' ) var poolCluster = mysql.
#Ranger kms client loadbalance code
The client-side code that executes the load balancing should follow the logic below: Or you could implement more sophisticated load balancing algorithms.
#Ranger kms client loadbalance how to
Your app could retrieve the list of endpoints from the Service and decide how to distribute the requests.Īs a first try, you could open a persistent connection to every Pod and round-robin requests to them. Services are a collection of IP addresses and ports - usually called endpoints. Since Kubernetes doesn't know how to load balance persistent connections, you could step in and fix it yourself. So you have now achieved better latency and throughput, but you lost the ability to scale your backend.Įven if you have two backend Pods that can receive requests from the frontend Pod, only one is actively used. Since all subsequent requests are channelled through the same TCP connection, iptables isn't invoked anymore. One of the three Pods was selected as the destination. There is a single TCP connection open, and iptables rule were invocated the first time. Isn't iptables supposed to distribute the traffic? What happens when the front-end issues more requests? The backend Pod replies and the front-end receives the response.īut instead of closing the TCP connection, it is kept open for subsequent HTTP requests. The request reaches the Service, and one of the Pod is selected as the destination. The front-end makes the first request to the backend and opens the TCP connection. You have a single instance of the front-end and three replicas for the backend. Let's imagine that front-end and backend support keep-alive.
![ranger kms client loadbalance ranger kms client loadbalance](https://docs.cloudera.com/cdp-private-cloud-base/7.1.6/installation/images/cdpdc-ranger-kms-ha-ranger-kms-kts-service-properties.png)
What happens when you use keep-alive with a Kubernetes Service? Here a few examples on how to implement keep-alive in different languages: The change itself is straightforward, and it's available in most languages and frameworks. It doesn't work out of the box your server and client should be configured to use it. The HTTP protocol has a feature called HTTP keep-alive, or HTTP connection reuse that uses a single TCP connection to send and receive multiple HTTP requests and responses. You can improve the latency and save resources if you open a TCP connection and reuse it for any subsequent HTTP requests. If the front-end makes 100 HTTP requests per second to the backend, 100 different TCP connections are opened and closed in that second. With every HTTP request started from the front-end to the backend, a new TCP connection is opened and closed.
![ranger kms client loadbalance ranger kms client loadbalance](https://docs.cloudera.com/cdp-private-cloud-base/7.1.6/security-ranger-kms-configuring-and-using/images/cdpdc-ranger-kms-ha-ranger-kms-service-properties.png)
Long-lived connections don't scale out of the box in Kubernetes Now that you're familiar with how Services work let's have a look at more exciting scenarios. So the load balancing algorithm is random. Iptables use the statistic module with random mode. The compound probability is that Pod 1, Pod 2 and Pod 3 have all have a one-third chance (33%) to be selected.Īlso, there's no guarantee that Pod 2 is selected after Pod 1 as the destination.
![ranger kms client loadbalance ranger kms client loadbalance](https://docs.cloudera.com/HDPDocuments/HDP2/HDP-2.3.2/bk_Ranger_KMS_Admin_Guide/common/img/pdf.png)
If you have three Pods, kube-proxy writes the following rules: However, you could craft a smart set of rules that could make iptables behave like a load balancer.Īnd this is precisely what happens in Kubernetes. No, iptables is primarily used for firewalls, and it is not designed to do load balancing.