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Argo vs Kubernetes: What are the differences?
Introduction
In this Markdown code, we will discuss the key differences between Argo and Kubernetes.
Namespace Scope: One significant difference between Argo and Kubernetes is their scope. Kubernetes operates at the cluster level, where all resources are organized within a cluster-wide namespace. On the other hand, Argo has a broader scope as it operates at the multi-cluster level, allowing management and coordination of resources across different clusters.
Workflow Execution: Argo and Kubernetes also differ in their approach to workflow execution. Kubernetes primarily focuses on managing containerized applications, while Argo specializes in workflow orchestration. Argo provides a higher-level abstraction for defining and executing complex workflows, enabling the coordination of multiple interdependent steps, tasks, and services.
Workflow Metrics and Visualization: Another difference lies in the built-in support for workflow metrics and visualization. While Kubernetes offers basic monitoring and logging capabilities, Argo provides additional features specifically designed for workflow metrics and visualization. Argo enables users to track workflow progress, visualize dependencies between tasks, and monitor resource utilization, providing better visibility into the workflow execution.
Built-in Retry and Error Handling: Argo excels in providing built-in functionality for retrying and handling potential errors within workflows. It allows users to define custom retry policies, set time limits, and handle failures gracefully, ensuring robust and reliable workflow execution. Kubernetes, on the other hand, does not offer native support for these features, requiring developers to implement their own error handling mechanisms.
Resource Management and Auto-scaling: While both Argo and Kubernetes support resource management and auto-scaling, they differ in their capabilities. Kubernetes focuses on managing and scaling individual containers and pods, while Argo extends this functionality to the workflow level. Argo enables dynamic resource allocation and auto-scaling based on the workflow requirements, ensuring optimal resource utilization throughout the workflow execution.
Integration with CI/CD: Argo and Kubernetes also vary in their integration with continuous integration and continuous deployment (CI/CD) pipelines. Argo integrates seamlessly with popular CI/CD tools, such as Jenkins, GitLab, and GitHub Actions, providing native support for automating workflow execution within the CI/CD pipeline. Kubernetes, although compatible with CI/CD workflows, primarily focuses on container orchestration and requires additional tools or extensions for full CI/CD integration.
In summary, Argo and Kubernetes differ in their scope, workflow execution approach, metrics and visualization capabilities, built-in retry and error handling, resource management and auto-scaling capabilities, and integration with CI/CD pipelines. Argo provides a more comprehensive solution for workflow orchestration, while Kubernetes focuses on container management and orchestration at the cluster level.
Hello, we have a bunch of local hosts (Linux and Windows) where Docker containers are running with bamboo agents on them. Currently, each container is installed as a system service. Each host is set up manually. I want to improve the system by adding some sort of orchestration software that should install, update and check for consistency in my docker containers. I don't need any clouds, all hosts are local. I'd prefer simple solutions. What orchestration system should I choose?
If you just want the basic orchestration between a set of defined hosts, go with Docker Swarm. If you want more advanced orchestration + flexibility in terms of resource management and load balancing go with Kubernetes. In both cases, you can make it even more complex while making the whole architecture more understandable and replicable by using Terraform.
We develop rapidly with docker-compose orchestrated services, however, for production - we utilise the very best ideas that Kubernetes has to offer: SCALE! We can scale when needed, setting a maximum and minimum level of nodes for each application layer - scaling only when the load balancer needs it. This allowed us to reduce our devops costs by 40% whilst also maintaining an SLA of 99.87%.
Our whole DevOps stack consists of the following tools:
- GitHub (incl. GitHub Pages/Markdown for Documentation, GettingStarted and HowTo's) for collaborative review and code management tool
- Respectively Git as revision control system
- SourceTree as Git GUI
- Visual Studio Code as IDE
- CircleCI for continuous integration (automatize development process)
- Prettier / TSLint / ESLint as code linter
- SonarQube as quality gate
- Docker as container management (incl. Docker Compose for multi-container application management)
- VirtualBox for operating system simulation tests
- Kubernetes as cluster management for docker containers
- Heroku for deploying in test environments
- nginx as web server (preferably used as facade server in production environment)
- SSLMate (using OpenSSL) for certificate management
- Amazon EC2 (incl. Amazon S3) for deploying in stage (production-like) and production environments
- PostgreSQL as preferred database system
- Redis as preferred in-memory database/store (great for caching)
The main reason we have chosen Kubernetes over Docker Swarm is related to the following artifacts:
- Key features: Easy and flexible installation, Clear dashboard, Great scaling operations, Monitoring is an integral part, Great load balancing concepts, Monitors the condition and ensures compensation in the event of failure.
- Applications: An application can be deployed using a combination of pods, deployments, and services (or micro-services).
- Functionality: Kubernetes as a complex installation and setup process, but it not as limited as Docker Swarm.
- Monitoring: It supports multiple versions of logging and monitoring when the services are deployed within the cluster (Elasticsearch/Kibana (ELK), Heapster/Grafana, Sysdig cloud integration).
- Scalability: All-in-one framework for distributed systems.
- Other Benefits: Kubernetes is backed by the Cloud Native Computing Foundation (CNCF), huge community among container orchestration tools, it is an open source and modular tool that works with any OS.
Pros of Argo
- Open Source3
- Autosinchronize the changes to deploy2
- Online service, no need to install anything1
Pros of Kubernetes
- Leading docker container management solution164
- Simple and powerful128
- Open source106
- Backed by google76
- The right abstractions58
- Scale services25
- Replication controller20
- Permission managment11
- Supports autoscaling9
- Cheap8
- Simple8
- Self-healing6
- No cloud platform lock-in5
- Promotes modern/good infrascture practice5
- Open, powerful, stable5
- Reliable5
- Scalable4
- Quick cloud setup4
- Cloud Agnostic3
- Captain of Container Ship3
- A self healing environment with rich metadata3
- Runs on azure3
- Backed by Red Hat3
- Custom and extensibility3
- Sfg2
- Gke2
- Everything of CaaS2
- Golang2
- Easy setup2
- Expandable2
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Cons of Argo
Cons of Kubernetes
- Steep learning curve16
- Poor workflow for development15
- Orchestrates only infrastructure8
- High resource requirements for on-prem clusters4
- Too heavy for simple systems2
- Additional vendor lock-in (Docker)1
- More moving parts to secure1
- Additional Technology Overhead1
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What is Argo?
What is Kubernetes?
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