1596110100
Using Kubernetes to serve multi tenants is not a trivial task. Kubernetes provides the tools that are necessary(RBAC, Rolebinding, Network Policy, ResourceQuota and etc) to provide isolation between tenants but building/implementing an architecture is solely upon users. In this webinar, we would like to introduce multiple approaches that can be taken to provide multi-tenancy in the kubernetes cluster. We will also talk about how others in the communities are doing to achieve multi-tenancy. We’ll analyze pros and cons of different approaches and share specific use-cases that fit each approach. Finally, we will look in to lessons we’ve learned and we have implemented these factors into our on-premise cloud environment.
#kubernetes #a multi-tenant kubernetes cluster #kubernetes cluster #on-premise cloud environment
1602964260
Last year, we provided a list of Kubernetes tools that proved so popular we have decided to curate another list of some useful additions for working with the platform—among which are many tools that we personally use here at Caylent. Check out the original tools list here in case you missed it.
According to a recent survey done by Stackrox, the dominance Kubernetes enjoys in the market continues to be reinforced, with 86% of respondents using it for container orchestration.
(State of Kubernetes and Container Security, 2020)
And as you can see below, more and more companies are jumping into containerization for their apps. If you’re among them, here are some tools to aid you going forward as Kubernetes continues its rapid growth.
(State of Kubernetes and Container Security, 2020)
#blog #tools #amazon elastic kubernetes service #application security #aws kms #botkube #caylent #cli #container monitoring #container orchestration tools #container security #containers #continuous delivery #continuous deployment #continuous integration #contour #developers #development #developments #draft #eksctl #firewall #gcp #github #harbor #helm #helm charts #helm-2to3 #helm-aws-secret-plugin #helm-docs #helm-operator-get-started #helm-secrets #iam #json #k-rail #k3s #k3sup #k8s #keel.sh #keycloak #kiali #kiam #klum #knative #krew #ksniff #kube #kube-prod-runtime #kube-ps1 #kube-scan #kube-state-metrics #kube2iam #kubeapps #kubebuilder #kubeconfig #kubectl #kubectl-aws-secrets #kubefwd #kubernetes #kubernetes command line tool #kubernetes configuration #kubernetes deployment #kubernetes in development #kubernetes in production #kubernetes ingress #kubernetes interfaces #kubernetes monitoring #kubernetes networking #kubernetes observability #kubernetes plugins #kubernetes secrets #kubernetes security #kubernetes security best practices #kubernetes security vendors #kubernetes service discovery #kubernetic #kubesec #kubeterminal #kubeval #kudo #kuma #microsoft azure key vault #mozilla sops #octant #octarine #open source #palo alto kubernetes security #permission-manager #pgp #rafay #rakess #rancher #rook #secrets operations #serverless function #service mesh #shell-operator #snyk #snyk container #sonobuoy #strongdm #tcpdump #tenkai #testing #tigera #tilt #vert.x #wireshark #yaml
1596110100
Using Kubernetes to serve multi tenants is not a trivial task. Kubernetes provides the tools that are necessary(RBAC, Rolebinding, Network Policy, ResourceQuota and etc) to provide isolation between tenants but building/implementing an architecture is solely upon users. In this webinar, we would like to introduce multiple approaches that can be taken to provide multi-tenancy in the kubernetes cluster. We will also talk about how others in the communities are doing to achieve multi-tenancy. We’ll analyze pros and cons of different approaches and share specific use-cases that fit each approach. Finally, we will look in to lessons we’ve learned and we have implemented these factors into our on-premise cloud environment.
#kubernetes #a multi-tenant kubernetes cluster #kubernetes cluster #on-premise cloud environment
1601051854
Kubernetes is a highly popular container orchestration platform. Multi cloud is a strategy that leverages cloud resources from multiple vendors. Multi cloud strategies have become popular because they help prevent vendor lock-in and enable you to leverage a wide variety of cloud resources. However, multi cloud ecosystems are notoriously difficult to configure and maintain.
This article explains how you can leverage Kubernetes to reduce multi cloud complexities and improve stability, scalability, and velocity.
Maintaining standardized application deployments becomes more challenging as your number of applications and the technologies they are based on increase. As environments, operating systems, and dependencies differ, management and operations require more effort and extensive documentation.
In the past, teams tried to get around these difficulties by creating isolated projects in the data center. Each project, including its configurations and requirements were managed independently. This required accurately predicting performance and the number of users before deployment and taking down applications to update operating systems or applications. There were many chances for error.
Kubernetes can provide an alternative to the old method, enabling teams to deploy applications independent of the environment in containers. This eliminates the need to create resource partitions and enables teams to operate infrastructure as a unified whole.
In particular, Kubernetes makes it easier to deploy a multi cloud strategy since it enables you to abstract away service differences. With Kubernetes deployments you can work from a consistent platform and optimize services and applications according to your business needs.
The Compelling Attributes of Multi Cloud Kubernetes
Multi cloud Kubernetes can provide multiple benefits beyond a single cloud deployment. Below are some of the most notable advantages.
Stability
In addition to the built-in scalability, fault tolerance, and auto-healing features of Kubernetes, multi cloud deployments can provide service redundancy. For example, you can mirror applications or split microservices across vendors. This reduces the risk of a vendor-related outage and enables you to create failovers.
#kubernetes #multicloud-strategy #kubernetes-cluster #kubernetes-top-story #kubernetes-cluster-install #kubernetes-explained #kubernetes-infrastructure #cloud
1594162500
A multi-cloud approach is nothing but leveraging two or more cloud platforms for meeting the various business requirements of an enterprise. The multi-cloud IT environment incorporates different clouds from multiple vendors and negates the dependence on a single public cloud service provider. Thus enterprises can choose specific services from multiple public clouds and reap the benefits of each.
Given its affordability and agility, most enterprises opt for a multi-cloud approach in cloud computing now. A 2018 survey on the public cloud services market points out that 81% of the respondents use services from two or more providers. Subsequently, the cloud computing services market has reported incredible growth in recent times. The worldwide public cloud services market is all set to reach $500 billion in the next four years, according to IDC.
By choosing multi-cloud solutions strategically, enterprises can optimize the benefits of cloud computing and aim for some key competitive advantages. They can avoid the lengthy and cumbersome processes involved in buying, installing and testing high-priced systems. The IaaS and PaaS solutions have become a windfall for the enterprise’s budget as it does not incur huge up-front capital expenditure.
However, cost optimization is still a challenge while facilitating a multi-cloud environment and a large number of enterprises end up overpaying with or without realizing it. The below-mentioned tips would help you ensure the money is spent wisely on cloud computing services.
Most organizations tend to get wrong with simple things which turn out to be the root cause for needless spending and resource wastage. The first step to cost optimization in your cloud strategy is to identify underutilized resources that you have been paying for.
Enterprises often continue to pay for resources that have been purchased earlier but are no longer useful. Identifying such unused and unattached resources and deactivating it on a regular basis brings you one step closer to cost optimization. If needed, you can deploy automated cloud management tools that are largely helpful in providing the analytics needed to optimize the cloud spending and cut costs on an ongoing basis.
Another key cost optimization strategy is to identify the idle computing instances and consolidate them into fewer instances. An idle computing instance may require a CPU utilization level of 1-5%, but you may be billed by the service provider for 100% for the same instance.
Every enterprise will have such non-production instances that constitute unnecessary storage space and lead to overpaying. Re-evaluating your resource allocations regularly and removing unnecessary storage may help you save money significantly. Resource allocation is not only a matter of CPU and memory but also it is linked to the storage, network, and various other factors.
The key to efficient cost reduction in cloud computing technology lies in proactive monitoring. A comprehensive view of the cloud usage helps enterprises to monitor and minimize unnecessary spending. You can make use of various mechanisms for monitoring computing demand.
For instance, you can use a heatmap to understand the highs and lows in computing visually. This heat map indicates the start and stop times which in turn lead to reduced costs. You can also deploy automated tools that help organizations to schedule instances to start and stop. By following a heatmap, you can understand whether it is safe to shut down servers on holidays or weekends.
#cloud computing services #all #hybrid cloud #cloud #multi-cloud strategy #cloud spend #multi-cloud spending #multi cloud adoption #why multi cloud #multi cloud trends #multi cloud companies #multi cloud research #multi cloud market
1595339417
At Kubermatic, we have been helping our customers deliver Kubernetes clusters and other cloud-native solutions since before they were buzzwords. We helped customers build clusters using Ansible, Terraform, and a variety of other non-cloud-native tools…and we helped them rebuild the clusters when we ran into the limits of these tools. In these early days, two things quickly became clear to us:
Since then, these ideas have largely been validated by a variety of organizations around the world including the CNCF, Twitter, USA Today, Zalando, and Alibaba.
Knowing that every company running Kubernetes at scale would need to effectively administer multi-cluster management, we created the recently open sourced Kubermatic Kubernetes Platform. This article will cover why you need multi-cluster management, how Kubermatic Kubernetes Platform leverages Kubernetes Operators to automate cluster life cycle management across multiple clusters, clouds, and regions and how you can get started with the project today.
Kubernetes lacks hard multi-tenancy capabilities that give users, organizations, or operators the ability to allow untrusted tenants to share infrastructure resources or separate different pieces of software. This presents both a security and operational problem. When operators seek to separate workloads by type (sensitive vs nonsensitive data processing) or even just production vs. non-production there is no way to do this on the cluster level, creating a security nightmare. On the operational side, trying to deploy too many applications into the same cluster can result in version conflicts, configuration conflicts, and problems with software lifecycle management. Finally, without proper isolation, there is an increased risk of cascading failures.
Without hard multi-tenancy within a cluster, separate clusters must be used to provide adequate separation for workloads with different security requirements. Having multiple clusters to deploy applications into also allows operators to deploy similar applications together while segregating those with different life cycles from each other. Applications deployed into the same cluster can be upgraded together to reduce the operational load while applications that require different versions, configurations, and dependencies can run in separate clusters and be upgraded on their own.
If running multiple clusters is the only solution to meeting these workload and infrastructure requirements, the operational burden of this model must also be considered. Running a multitude of clusters is a massive operational challenge if done manually. For this reason, any operator considering running Kubernetes at scale should carefully evaluate their multi-cluster management strategy. At Kubermatic, we have chosen to do multi-cluster management with Kubernetes Operators.
#cloud #automation #kubernetes #operator #multi-cluster