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  1. Stackups
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  4. Container Tools
  5. Argo vs Lens

Argo vs Lens

OverviewComparisonAlternatives

Overview

Argo
Argo
Stacks761
Followers470
Votes6
Lens
Lens
Stacks151
Followers183
Votes9
GitHub Stars23.0K
Forks1.5K

Argo vs Lens: What are the differences?

Introduction:

Argo and Lens are two popular tools used in the field of Container Orchestration. While both aim to simplify the management and operation of containers, they have key differences that set them apart. Below are the six key differences between Argo and Lens.

  1. User Interface and Workflow Management: Argo provides a graphical user interface (GUI) that allows users to easily visualize and manage complex workflows. It offers a drag-and-drop interface for creating and editing workflows, making it user-friendly. On the other hand, Lens focuses more on container management and provides a consolidated view of multiple clusters, allowing users to efficiently monitor and manage their containers.

  2. Feature Set: Argo offers a comprehensive set of features for workflow automation, including Cron workflows, event-driven workflows, and artifact management. It also supports advanced workflow customization and extensibility through the use of templates. In contrast, Lens focuses primarily on cluster management and monitoring, providing features such as resource utilization tracking, logs viewing, and Kubernetes API integration.

  3. Supported Platforms: Argo is primarily designed to work with Kubernetes, but it can also integrate with other container orchestration platforms like Apache Mesos and HashiCorp Nomad. Lens, on the other hand, is created specifically for Kubernetes and provides deep integration and enhanced features for managing Kubernetes clusters.

  4. Multi-Cluster Management: Argo allows users to manage and orchestrate workflows across multiple clusters, providing a centralized control plane. It enables users to distribute workloads across different clusters based on their specific requirements. On the contrary, Lens primarily focuses on managing individual Kubernetes clusters and does not offer native support for multi-cluster management.

  5. Community and Support: Argo has a well-established open-source community and is actively maintained and supported. It has a large user base, which means that users can easily find support and resources. Lens, although it has gained popularity, comparatively has a smaller community and may not have as extensive support resources available.

  6. Integration and Extensibility: Argo provides integration with several external tools and platforms, allowing users to extend its capabilities. It offers integrations with Git, Slack, and Kubernetes clusters, among others. Lens, on the other hand, provides plugins and extensions for integrating with external tools and services, enhancing its functionality and allowing users to customize their experience.

In Summary, Argo and Lens differ in their user interface, workflow management capabilities, supported platforms, multi-cluster management, community support, and integration options. While Argo focuses on workflow automation and supports multiple container orchestration platforms, Lens is designed specifically for Kubernetes and provides enhanced features for managing individual clusters.

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Detailed Comparison

Argo
Argo
Lens
Lens

Argo is an open source container-native workflow engine for getting work done on Kubernetes. Argo is implemented as a Kubernetes CRD (Custom Resource Definition).

It is the only IDE you’ll ever need to take control of your Kubernetes clusters. It is a standalone application for MacOS, Windows and Linux operating systems. It is open source and free.

DAG or Steps based declaration of workflows;Artifact support (S3, Artifactory, HTTP, Git, raw);Step level input & outputs (artifacts/parameters);Loops;Parameterization;Conditionals;Timeouts (step & workflow level);Retry (step & workflow level);Resubmit (memoized);Suspend & Resume;Cancellation;K8s resource orchestration;Exit Hooks (notifications, cleanup);Garbage collection of completed workflow;Scheduling (affinity/tolerations/node selectors);Volumes (ephemeral/existing);Parallelism limits;Daemoned steps;DinD (docker-in-docker);Script steps
Multi Cluster Management; Multiple Workspaces; Built-In Prometheus Stats; Built-in Helm Applications Management; Context Aware Terminal;
Statistics
GitHub Stars
-
GitHub Stars
23.0K
GitHub Forks
-
GitHub Forks
1.5K
Stacks
761
Stacks
151
Followers
470
Followers
183
Votes
6
Votes
9
Pros & Cons
Pros
  • 3
    Open Source
  • 2
    Autosinchronize the changes to deploy
  • 1
    Online service, no need to install anything
Pros
  • 4
    Keep track of cluster changes
  • 2
    Open Source
  • 2
    Easy management of multiple clusters
  • 1
    Local installation, not SaaS
Integrations
Kubernetes
Kubernetes
Docker
Docker
Kubernetes
Kubernetes
Linux
Linux
macOS
macOS
Windows
Windows

What are some alternatives to Argo, Lens?

Kubernetes

Kubernetes

Kubernetes is an open source orchestration system for Docker containers. It handles scheduling onto nodes in a compute cluster and actively manages workloads to ensure that their state matches the users declared intentions.

Rancher

Rancher

Rancher is an open source container management platform that includes full distributions of Kubernetes, Apache Mesos and Docker Swarm, and makes it simple to operate container clusters on any cloud or infrastructure platform.

Docker Compose

Docker Compose

With Compose, you define a multi-container application in a single file, then spin your application up in a single command which does everything that needs to be done to get it running.

Docker Swarm

Docker Swarm

Swarm serves the standard Docker API, so any tool which already communicates with a Docker daemon can use Swarm to transparently scale to multiple hosts: Dokku, Compose, Krane, Deis, DockerUI, Shipyard, Drone, Jenkins... and, of course, the Docker client itself.

Tutum

Tutum

Tutum lets developers easily manage and run lightweight, portable, self-sufficient containers from any application. AWS-like control, Heroku-like ease. The same container that a developer builds and tests on a laptop can run at scale in Tutum.

Portainer

Portainer

It is a universal container management tool. It works with Kubernetes, Docker, Docker Swarm and Azure ACI. It allows you to manage containers without needing to know platform-specific code.

Codefresh

Codefresh

Automate and parallelize testing. Codefresh allows teams to spin up on-demand compositions to run unit and integration tests as part of the continuous integration process. Jenkins integration allows more complex pipelines.

CAST.AI

CAST.AI

It is an AI-driven cloud optimization platform for Kubernetes. Instantly cut your cloud bill, prevent downtime, and 10X the power of DevOps.

k3s

k3s

Certified Kubernetes distribution designed for production workloads in unattended, resource-constrained, remote locations or inside IoT appliances. Supports something as small as a Raspberry Pi or as large as an AWS a1.4xlarge 32GiB server.

Flocker

Flocker

Flocker is a data volume manager and multi-host Docker cluster management tool. With it you can control your data using the same tools you use for your stateless applications. This means that you can run your databases, queues and key-value stores in Docker and move them around as easily as the rest of your app.

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