MatbaRofex Argentina exchange and K8S
We use Kubernetes in a big bare metal cluster, and we are here at the Red Hat summit to talk about a migration directly to OpenShift to …
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What is Kubernetes?
Kubernetes is an open-source container cluster manager.
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What is Amazon EKS?
Amazon Elastic Kubernetes Service (Amazon EKS) is a managed container service to run and scale Kubernetes applications in the cloud or on-premises, available on AWS or on-premise through Amazon EKS Anywhere.
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Kubernetes Beginner Tutorial 8 | Step by Step Play with Kubernetes (K8s) Demo
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Demo: Intro to Rancher container management
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[ Kube 68 ] Kubernetes RBAC Demo | Creating Users and Roles
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Kubernetes for the Absolute Beginners - Setup Kubernetes - kubeadm
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Kubernetes Deployment Tutorial - yaml explained + Demo
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What is Kubernetes?
Kubernetes is an open-source container cluster manager.
Kubernetes Technical Details
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(160)Reviews
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May 23, 2023
MatbaRofex Argentina exchange and K8S
Score 9 out of 10
Vetted Review
Verified User
We use Kubernetes in a big bare metal cluster, and we are here at the Red Hat summit to talk about a migration directly to OpenShift to create an hybrid infrastructure that can help us to achieve a more resilient services for our clients, actually we got a lot of problem with the limits of k8s, especially with the calico service middleware, when our transactions are with high demand calico gets crazy and reset connections, for example, also we got and issue with the middleware limits, we are running 160 pods for worker, and we got 6 mega hardware workers, that we cant use it fully hardware for the middleware limits, thats the reason we are leaving k8s and working in a migration to OpenShift en AWS
- multiples deploys in the same infraestructure
- escalability of the solution
- fastes deployments automatized with Ansible
- posibility to handle better the hardware limites, if my hardware is very powerfull i cant use it fully because the limites that i explained before
April 22, 2022
Kubernetes is the answer but, what was the question?
I deploy & manage telco workloads on top of Kubernetes. These are called CNFs (Containerized network functions) which are legacy telco applications converted into K8s objects & connected via a networking & storage solution of your choice, managed by K8s. Just like every other industry, Telcos are no exception converting all their legacy applications sitting on proprietary hardware & boxes to COTS hardware & software architectures adapted toward cloud technologies. Kubernetes helps us to manage the CNFs efficiently & gives a better uptime as compared to VM-based architecture. I see the scope of flexibility & easy scaling in K8s as compared to any other technology.
- Makes sure that the workload remains UP & running by maintaining the desired state.
- Gives a lot of flexibility in choosing the networking, storage, monitoring, etc solutions of your choice.
- The biggest advantage is to upgrade the application with a new version without any downtime.
- Portability of the code is possible up to a great extent.
- Flexibility gives birth to complexity & therefore designing an application on K8s is also complex.
- Writing Yaml manifests manually & then validating them for errors is a pain that should be worked upon with a solution that can write YAMLs & Helm charts in the background with the user designing the application on a GUI-based sketch. Just like they do in OpenStack.
- The overall approach of operations should be shifted from CLI to GUI-based for ease of use.
- Due to a lot of objects & new concepts, the learning curve is really flat i.e. slow.
- Adding GUI-based operations like finding the exact point causing latency OR showing the POD consuming the highest CPU/RAM would be of great help.
April 20, 2022
Kubernetes - Open-Source container management
We have multiple Kubernetes clusters that deploy mainly web-based applications. Containers/Kubernetes. Helm has become a widely used platform for deploying applications and many applications offer this as their preferred standard deployment.
- Deploy applications on multiple nodes.
- Store application definitions in source control.
- Abstract away the implementations of storage and networking.
- Kubernetes is very high-maintenance compared to VM deployments in my opinion.
- Some failure scenarios are hard to recover from.
- High effort is needed for upgrading clusters and deployments to new versions of Kubernetes.
April 07, 2022
Kubernetes Review
Score 10 out of 10
Vetted Review
Verified User
Currently we are using Kubernetes in our project to orchestrate the containers. We are using it for our banking client where some point of time user transection get increased while they try to use banking applications. whenever load get increase Kubernetes spin new pods in the cluster using replicaset to handle the load of user transections.
- container orchestration
- Horizontal pod scaling
- load balancing
- Routes help in exposing internal traffic
- GUI interface
- Monitoring tools like Prometheus and Grafana
On the foundation, Kubernetes manages containers such as docker containers or from other technology and it helps you manage containerization applications that are made of hundreds of containers in different environments such as physical machines, virtual machines or cloud machines, or even hybrid deployment environments. As in my specific scenario, we install a Kubernetes cluster on CentOS 8 with one master node and two worker nodes for orchestration of our existing applications containers.
- With high availability, the application has no downtime means always accessible to users.
- Users have a very high response rate from the application means high performance with scalability.
- Backup and restore - Disaster recovery.
- Specifically, the installation process of the k8s cluster on Linux machines such as CentOS has required an experienced person.
- Kubernetes requires a lot to learn for beginners.
- For small applications k8s overkill.
We have moved almost all the stateless services to Kubernetes so managing the umpty number of services can be so easy. Kubernetes helps us in scaling the services up or down based on business needs. It helps us in upgrading the bunch of clusters with zero to minimal downtime based on the applications. We also moved stateful database services (mostly NoSQL) to Kubernetes to manage a single place and to keep the cost down.
- Scaling the application processes/pods up/down based on business needs.
- Managing the pods from a single source.
- Better security along with different layers of security.
- Orchestrating the pods and the available resources in different machines.
- Easier way to update multiple deployments.
- Better way to manage backups.
Kubernetes was used in my organization by a specific department. The business problem it attempted to address was resource allocation and scheduling. Creating and tearing down containers at will dependant on resource demand. These resources provided API services to the front-end website.
- Resource allocation and scheduling.
- Managing container instances and run-files.
- Allowing for infrastructure as code.
- Usability and user friendliness.
- There is no front end and anything attempting to provide a self-service model must be created currently.
- It uses pretty new technologies so there is a relatively steep learning curve.
April 03, 2019
Great way to deploy/manage your servers.
I am working in a company that is currently working on moving everything to the cloud. We want to leverage as many as cloud managed services as we can. Kubernetes came to our sight when we thinking of containerizing our on-premises servers for fast and easy deployment to cloud. We are still experimenting with Kubernetes but based on what we've got now, it works perfectly for our department.
- Kubernetes is a great tool for managing Docker images. It has great features for managing your containers.
- It is supported almost in every cloud platform. AWS, GCP, Azure. We are mainly using GCP for our products and Kubernetes works great in it.
- It is not hard to learn. Although you can learn and deploy your Kubernetes in a hard way, you do not have to.
- I know Kubernetes was designed to be stateless and it has a lot of reasons to do it. But working to make stateful can be hard sometimes.
- Like any other cloud migration projects, using Kubernetes can be a hard thing to bring to the team. I would not see that as a con of Kubernetes', just a fact.
- Kubernetes is very easy to deploy in the cloud but not easy for platforms other than AWS, GCP, Azure.
February 04, 2019
Kubernetes, a good cluster management system to place bets on
Kubernetes is currently used as an experimental product for building and managing Machine Learning pipelines (ML) at LinkedIn. It is currently used by very few teams to access GPU clusters. Kubernetes makes it easy to deploy training and monitoring workloads on clusters really simple with a robust CLI. It has a very small learning curve as is mainly driven by config files.
- Complex cluster management can be done with simple commands with strong authentication and authorization schemes
- Exhaustive documentation and open community smoothens the learning process
- As a user a few concepts like pod, deployment and service are sufficient to go a long way
- We had several problems with its NFS, which is responsible for syncing the code across the cluster
- On several instances the pods go into UNKNOWN state in which case restarting the entire node is the only solution
- As a user of the existing setup given to me, I wasn't able to allocate only some CPU cores on a single host. It was either all or zero making cluster utilization sub-optimal
December 19, 2018
Kubernetes, managing the future
We use Kubernetes at a department level and across the whole organization. At a department level, we use Kubernetes to manage our developer environments. These environments are made up of 30 containers containing compilers, single sign-on managers, and various other linting tools. We selected Kubernetes to manage these containers because it's quick to deploy and immensely customizable. Across the organization, we use Kubernetes to manage our customer environments. These environments are made up of ~8 containers running various managed web services. Kubernetes was selected for this because it is open source, scalable, and reliable. This allows us to cost-effectively deploy a solution and be confident that it will perform as needed.
- Cost-effectiveness, Kubernetes is free and open source.
- Scalability, Kubernetes works regardless of how many pods it's managing; be it ten or a thousand.
- Low overhead, Kubernetes adds very little performance cost per developer per machine. The benefits of having a managed system vastly outweigh the minor performance cost.
- Large market share, Kubernetes is one of the top container orchestration tools used by developers today. This has been immensely helpful when finding new talent who are familiar with Kubernetes.
- Local development, Kubernetes does tend to be a bit complicated and unnecessary in environments where all development is done locally.
- The need for add-ons, Helm is almost required when running Kubernetes. This brings a whole new tool to manage and learn before a developer can really start to use Kubernetes effectively.
- Finicy configmap schemes. Kubernetes configmaps often have environment breaking hangups. The fail safes surrounding configmaps are sadly lacking.
Kubernetes has become the microservice container orchestration platform of choice. All our software deployed into Kubernetes - including public websites.
- Scales extremely well
- Handles proper rolling updates of microservices
- Makes it super easy to establish a proper CI/CD pipeline
- Makes it easy for developers to adopt and therefore use
- Could improve user access. Currently uses RBAC - but depending on your implementation (i.e. Amazon EKS) - setting up permissions and adding users to the cluster that are to use the cluster only is sometimes challenging.
- Security can always be improved
- Hooks for identity management; there are open source projects (i.e. Dex) - would be nice to see these adopted to the mainline
- UI Dashboard needs some major improvments
July 09, 2018
Kubernetes is "the" tool for Docker orchestration
We as an organization have very diverse hardware infrastructure. We have our own data centers and multiple cloud providers. The technologies we use are also again very diverse, we use VMs, containers as well as server-less technologies. When it comes to container technologies we are using Docker and orchestrate it with Kubernetes. In most of the cases, each Business unit have their own Kubernetes clusters for application hosting, and categorize it separately for preproduction and production environments.
- Kubernetes can run anywhere, i.e in in-house datacenters as well as in Public cloud
- Very efficient management of containers and self healing.
- Out of the box Automated deployment and rollbacks. And support for many deployment strategies like blue-green, rolling update and recreate.
- Efficient secret and configuration management
- Understanding Kubernetes is little hard and has a steep learning curve.
- Kubernetes is complex, it has its own concepts called pods, services and deployments.
- Debugging and troubleshooting in Kubernetes is quite hard and requires experience.
October 05, 2017
Worth the Learning Curve
Kubernetes has massively simplified and sped up the management of microservices deployed within my team. If we need to spin up a new service, even if it doesn't relate to the other services in the cluster, we can simply deploy the docker container to the cluster, complete with service discovery, configuration management, autoscale and fault tolerance. This is invaluable.
- Fault tolerance - the things it does under the hood to handle failure is near magical.
- Configuration management - the ease of managing configs and secrets in kubernetes makes it a snap for integrating services.
- Service discovery - getting services to talk to each other with automated internal DNS and service-discovery makes shipping service dependencies easy.
- Speed of error detection - many times, in attempting to fix a problem, I found that kubernetes just had a delay in handling an automated fix. By changing the system, I was playing a cat and mouse game with kubernetes' attempts to auto-fix the error.
- Sensible logging - many of the logs are difficult to decipher and too verbose to be useful.
- The learning curve is high - it took many months of working with Google, in which both I and Google Support Engineers learned a lot about how Kubernetes works. The learning curve is not for people looking for quick and easy out of the box.
April 14, 2017
Poor man's review
- Whole organization.
- Used as a PaaS.
- Used to deploy mostly stateless and cloud-ready apps.
- Solves the problem of immutable infrastructure. No need for Chef, Puppet or Ansible.
- Low learning curve for users.
- Apps start on failure, can auto scale; burst into cloud;
- Infra is cloud agnostic; works in an in-house datacenter too. Gives leverage to mangement for negotiations with cloud providers
- Container orchestration
- Application scale up and down
- Good PaaS with fluentd, service discovery, secrets etc.
- Huge community support
- Free kubeconfig video, which is awesome
- Quick releases (every quarter)
- Extensive documentation. Design discussion and decisions are all documented.
- Huge ecosystem and a lot of tools built around it. A lot of companies are behind it (Google, Microsoft, Coreos etc.). This project is not going anywhere.
- Better documentation; no document versioning. Stuff is all over. It's difficult to find the right stuff sometimes.
- Easy installation. kubeadm is partly there but not fully HA; minikube is awesome but does not work for multi-node installation; other installation such as kops, kargo are Anisible based, not fully immutable.
March 28, 2017
Easiest containerized deploy, bar none!
It is being used across many departments, with more being added every day. My team was one of the first teams to use Kubernetes 8 for our microservice deployments. It addresses the problem of HDHA applications, agile development, rolling deployments with no downtime. We are also utilizing its service discovery with spring boot admin to provide node level details for all nodes in the cluster.
- Single process microservice containerization that can be scaled up and down at a moments notice.
- Rolling deployments with zero downtime.
- Artifactory/DockerHub integration for deploying from an artifact repo.
- Spring Boot integration with configmaps & secret managment.
- Ingress is HTTP only, so something that is TCP only must be in the cluster.
- Multi-process containers don't behave well.
- Sizing constraints cause slow startups for Spring Boot apps.
- Ingress' are slow to start up.
February 06, 2017
The best way to run your containers
For managing containers across a cluster of servers, I won't use anything but Kubernetes. It makes scheduling containers extremely easy. Bundling applications that we develop into Docker images has made deployment a really simple process for us. It's made it so that we don't have to think too much about the clash that comes of running multiple applications on the same set of hosts. It's also helped our engineers to write idempotent applications better because we scale up and down often.
- Container Scheduling
- Deployments
- Extensibility
- SSL Management
- Cluster Installation
- Ingress Management