How many namespace can a cluster k8s hold? - kubernetes

If I want to develop a SaaS system and want to use k8's namespace to do isolation, i.e., I will create a namespace for every user, it's a multi-tenancy system, then, how many namespaces can I have? Will k8s be slowdown when namespace increases?

To answer your question, namespace is a logical entity that is used to isolate the application environment from another application environment. It doesn't consume cluster resources like cpu and memory. Ideally you can create any number of namespaces. Am not sure if there is a limit on number of namespaces that is allowed in a custer
On the other hand it is not a good approach to have one namespace each for user. Applications multi tenancy should be better handled in the application code itself. Namespace is recommended to isolate the environment like one for Development, one for TEST, one for QA and Another one for production

This is a pretty good write-up on some best-practices around namespaces and how to organize things with them:
https://cloud.google.com/blog/products/containers-kubernetes/kubernetes-best-practices-organizing-with-namespaces
There are likely use-cases where you can have too many namespaces, but it is very unlikely that you will see this unless you have a custom application or controller that is doing something unwise and needs some of its logic reworked.

Related

Horizontal Scalability with Drools

Knowing that drools work with in memory data. Is there a way to distribute horizontally on different drools instances to enhance performance when performing CRUD operations on rules, fact types, etc? I guess the instances would need to be on sync with each other in some way, so they all have the same data in memory or share in some way a knowledge base. I'm kinda new on drools and trying to research on a way to move a monolith on a cloud environment (gcp) so it can take advantage on load balancing, scaling, etc. Want to know if there is any feature on drools itself that supports this or if there is any way to implement this myself, thanks in advance for any information/documentation/use case on this matter.
Currently I haven't tried a way to do this, but my goal is to improve performance and availability by using automatic scaling or support multiple instances of my app.
I'm not sure what kind of "CRUD" you're doing on Drools (or how). But if you just want to deploy new rules (for example), then this is identical to pushing any data or application changes to your deployment in a distributed system -- either your nodes are gradually updated, so during the upgrade process you have some mix of old and new logic/code; or you deploy new instances with the new logic/code and then transition traffic to your new instances and away from the old ones -- either all at once or in a controlled blue/green (or similar) fashion.
If you want to split a monolith, I think the best approach for you would be to consider Kogito [1] and microservice architecture. With microservices, you could even consider using the Function as a service approach - having small immutable service instances, that are just executed and disposed. Kogito mainly targets Quarkus platform, but there are also some Spring Boot examples. There is also OpenShift operator available.
As far as sharing the working memory, there was a project in the KIE community called HACEP [2]. Unfortunately that is now deprecated and we are researching other solutions to make the working memory persisted.
[1] https://kogito.kie.org/
[2] https://github.com/kiegroup/openshift-drools-hacep
The term "entry point" is related to the fact that we have multiple partitions in a Working Memory and you can choose which one you are inserting into. If you can organize your business logic to work with different entry points you can process 'logical partitions' on different machines in parallel safely. At a glance drools entry points gives you something like table partitioning in Oracle which implies the same options.
Use load balancer with sticky sessions if you can (from business point of view) partition 'by client'
you question looks more like an architecture question.
As a start, I would have a look into the Kie Execution Server component provided with Drools that helps you to create microservice decisions based on Drools rulesets.
Kie Execution Server (used in stateless mode by clients) could be embedded in different pods/instances/servers to ensure horizontal scalability.
As mentioned by #RoddyoftheFrozenPeas , one of the problem you'll face will be the simultaneous hot deploy of new rulesets on the "swarm" of kieserver that hosts your services.
That would have to be handled using a proper devops strategy.
Best
Emmanuel

Usage of Namespaces in Kubernetes

I got a question regarding namespaces and seeking your expertise to clear out my doubts.
What I understood about namespaces is that they are there to introduce logical boundaries among teams and projects.
Of course, I read somewhere namespaces can be used to introduce/define different environments within the same cluster.
E.g Test, UAT and PRODUCTION.
However, if an organization is developing a solution and that solution consists of X number of microservices and have dedicated teams to look after those services,
should we still need to use namespaces to separate them or are they gonna deploy in one single namespace reflecting the solution?
E.g if we are developing an e-commerce application:
Inventory, ShoppingCart, Payment, Orders etc. would be the microservices that I can think of. Should we deploy them under the namespace of sky-commerce for an instance? or should they need dedicated namespaces.?
My other question is. if we deploy services in different namespaces, is it possible for us to access them through APIGateway/ Ingress controller?
For an instance, I have the front-end SPA application and it has its BFF (Backend For Frontend). can the BFF access the other services through the APIGateway/Ingress controller?
Please help me to clear these doubts.
Thanks in advance for your prompt reply in this regard.
RSF
Namespaces are cheap, use lots of them. Only ever put two things in the same namespace if they are 100% a single unit (two daemons that are always updated at the same time and are functionally a single deployment) or if you must because a related object is used (such as a Service being in the same ns as Pods it references).
When creating a new Kubernetes namespace, a request is sent using the namespace API using the defined syscalls, and since Kubernetes has admin privileges, a new namespace will be created. The new namespace will contain specifications for the capabilities of a new process assigned under its domain.
In regards to your question above, yes you can keep services in different namespaces as long as they are able to talk together and render the services to the outside world as one piece.
Since all organizations are different, it is up to you to figure out how best to implement and manage Kubernetes Namespaces. In general, aim to:
Create an effective Kubernetes Namespace structure
Keep namespaces simple and application-specific
Label everything
Use cluster separation when necessary

Kubernetes - Create a separate namespace for each customer

I want to deploy a traditional monolithic application in Kubernetes.
Thousands of customers use this application and each customer has its own instance of application. if we have 5 customers we should run 5 separate instances of this application.
The application also calls Kubernetes API for running some jobs.
I want to make sure that everything is isolated, Is it a good idea to create a separate namespace for each customer? Does it cause some performance issues? Is there any better solution for it?
I think you should create multi-tenant cluster.
Such clusters shared by multiple users and/or workloads which are referred to as "tenants". The operators of multi-tenant clusters must isolate tenants from each other to avoid the damage that a compromised. You should know that cluster resources must be fairly allocated among tenants.
When you plan a multi-tenant architecture you should consider the layers of resource isolation in Kubernetes: cluster, namespace, node, pod, and container. You should also consider the security aspects of sharing different types of resources among specific tenants.
Although Kubernetes cannot guarantee perfectly secure isolation between tenants, it does offer features that may be sufficient for specific solutions. For example you can separate each tenant and their Kubernetes resources into their own separate namespaces. Then use policies to enforce tenant isolation. Policies are usually scoped by namespace and can be used to restrict API access, to constrain resource usage, and to restrict what containers are allowed to do.
Read more: multi-tenant-cluster.
However while implementing multi-tenancy with Kubernetes, you need to decide if you need soft multi-tenancy (is focused on minimising accidents and managing the fallout) or hard multi-tenancy(assumes tenants to be malicious and therefore advocates zero trust between them). In any case, you have to answer questions: how to limit their resource usage, how to manage the users/tenants and how to isolate them from each other. There are many tools, for example: loft which can help you to get multi-tenancy with Kubernetes.
See: multi-tenant-loft.
Take a look: best-practices-multitenant.

How to create a replicaset through a custom resource?

I want to create a custom resource that is able to create a replicaset under a certain event. What is the best way to accomplish this?
Note that I am aware of deployment, but deployment does not meet my intended use cases.
Seems like you might be looking into building something that would suit more or less the operator pattern.
https://coreos.com/operators/
https://coreos.com/blog/introducing-operators.html
https://github.com/coreos/prometheus-operator
Generaly you need to watch on some resources including your custom ones with kube client and act based on events propagated from kube API.

How are CoreOS Kubernetes Operators different from native Kubernetes initializers?

Kubernetes 1.7 has an alpha feature called initializers. CoreOS has the concept of an operator. Both seem to involve deploying code that watches the Kubernetes API server for changes to resources—possibly custom—in the cluster, based on annotations those resources contain and which the code understands.
What's the difference? If initializers are part of the core platform, why would I need to create something new that does what looks to my eyes like the same thing?
Operators are standalone "microservices" continuously and asynchronously reconciling the configured desired state towards the system's current state. Initializers are synchronous hooks validating or mutating runtime objects before they are created or updated. Also see admission controllers. They are usually baked into some "microservice". When you consider the lifecycle of a runtime object then initializers are first to act, like once. Then operators watching runtime objects reconcile the system upon their desired definitions.
Kubernetes had the concept of initializers way before 1.7, but then they were a fixed part of the API server. The new initializers feature that you linked to is mainly a decoupling of those parts from the API server:
Today each of these plugins must be compiled into Kubernetes. As Kubernetes grows, the requirement that all policy enforcement beyond coarse grained access control be done through in-tree compilation and distribution becomes unwieldy and limits administrators and the growth of the ecosystem.
(from the design document)