TrustRadius Insights
Telcos have found Kubernetes to be a valuable tool for deploying and managing their legacy telco applications. By converting these …
Overview
What is Kubernetes?
Kubernetes is an open-source container cluster manager.
Recent Reviews
Reviewer Pros & Cons
Pricing
Entry-level set up fee?
- No setup fee
Offerings
- Free Trial
- Free/Freemium Version
- Premium Consulting/Integration Services
Would you like us to let the vendor know that you want pricing?
3 people also want pricing
Alternatives Pricing
What is Vultr?
Vultr is an independent cloud computing platform on a mission to provide businesses and developers around the world with unrivaled ease of use, price-to-performance, and global reach.
Product Demos
Kubernetes Beginner Tutorial 8 | Step by Step Play with Kubernetes (K8s) Demo
YouTube
Demo: Intro to Rancher container management
YouTube
[ Kube 68 ] Kubernetes RBAC Demo | Creating Users and Roles
YouTube
Kubernetes for the Absolute Beginners - Setup Kubernetes - kubeadm
YouTube
Kubernetes Deployment Tutorial - yaml explained + Demo
YouTube
Product Details
- About
- Tech Details
What is Kubernetes?
Kubernetes is an open-source container cluster manager.
Kubernetes Technical Details
| Operating Systems | Unspecified |
|---|---|
| Mobile Application | No |
Comparisons
Compare with
Reviews and Ratings
(164)
Community Insights
TrustRadius Insights are summaries of user sentiment data from TrustRadius reviews and, when necessary, 3rd-party data sources. Have feedback on this content? Let us know!
- Business Problems Solved
- Pros
- Cons
- Recommendations
Telcos have found Kubernetes to be a valuable tool for deploying and managing their legacy telco applications. By converting these applications into Kubernetes objects, telcos have been able to improve uptime and scalability. The simplicity and speed of Kubernetes make it ideal for managing microservices, enabling easy deployment, service discovery, configuration management, autoscaling, and fault tolerance. This has been particularly useful for organizations like LinkedIn, which has used Kubernetes as an experimental product for building and managing Machine Learning pipelines and accessing GPU clusters. Additionally, Kubernetes is widely adopted as a PaaS solution throughout organizations, solving the problem of immutable infrastructure and providing a low learning curve for users. It offers scalability and reliability, making it suitable for managing developer and customer environments at both departmental and organizational levels. Moreover, Kubernetes excels in orchestration across diverse hardware infrastructures, including data centers and multiple cloud providers. It effectively manages containerization applications consisting of hundreds of containers deployed on physical machines, virtual machines, or cloud machines. This addresses resource allocation and scheduling challenges by creating and tearing down containers based on resource demand. Furthermore, Kubernetes serves as a powerful tool for containerizing on-premises servers for seamless deployment to the cloud. Its versatility and standard deployment through Helm have made it the preferred microservice container orchestration platform for deploying web-based applications. Overall, Kubernetes offers a wide range of use cases that enhance the deployment, management, and scalability of various applications in different environments.
Flexibility in Customization: Many reviewers have praised Kubernetes for its flexibility in choosing networking, storage, monitoring, and other solutions, allowing them to customize their workload according to their needs. This feature has been appreciated by a significant number of users.
Seamless Upgrades: Users have mentioned that Kubernetes provides the ability to upgrade applications to a new version without any downtime, making it seamless and efficient. Several reviewers have highlighted this as a valuable feature of the platform.
High Portability: The high level of portability offered by Kubernetes has been positively acknowledged by many users. They appreciate being able to move their applications to different environments easily.
Complex Application Design: Several users have found designing applications on Kubernetes to be complex and time-consuming, especially when manually writing YAML manifests and validating them for errors.
Steep Learning Curve: Many reviewers have mentioned that the learning curve for Kubernetes is slow due to a large number of objects and new concepts. They suggest adding GUI-based operations to help with tasks like finding latency points or identifying resource-consuming pods.
Difficulty in Troubleshooting and Documentation: Users have encountered challenges in understanding and troubleshooting Kubernetes, particularly for beginners. Some users have also found it difficult to find relevant information as the documentation is scattered. They suggest better documentation and versioning for easier access to relevant information.
Based on user reviews, users commonly recommend the following for Kubernetes:
Consider using Kubernetes for companies with a large microservice environment. Users believe that Kubernetes is helpful for managing complex applications and recommend it specifically for organizations with a significant number of microservices.
Acquire a basic understanding and knowledge of Kubernetes before using it. Users suggest that having some familiarity with Kubernetes before implementation is beneficial in order to fully utilize its features and capabilities.
Utilize specialized support and platforms like Rancher when deploying Kubernetes. Users recommend seeking assistance from specialized companies that provide support for Kubernetes, as well as using platforms like Rancher in conjunction with Kubernetes.
Overall, users emphasize the importance of evaluating specific requirements and capabilities before choosing Kubernetes as the container management solution, acquiring knowledge beforehand, and leveraging external support to enhance the deployment experience.
Reviews
(1-7 of 7)Companies can't remove reviews or game the system. Here's why
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.
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.
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
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.