Codecov vs Codefresh

Overview

Codecov

Stacks2.8K

Followers324

Votes102

Codefresh

Stacks64

Followers111

Votes47

Codecov vs Codefresh: What are the differences?

What is Codecov? Hosted coverage reports with awesome features to enhance your CI workflow. Our patrons rave about our elegant coverage reports, integrated pull request comments, interactive commit graphs, our Chrome plugin and security.

What is Codefresh? CI/CD Tailor-Made For Docker. 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.

Codecov can be classified as a tool in the "Code Coverage" category, while Codefresh is grouped under "Container Tools".

Some of the features offered by Codecov are:

Beautiful Reports
Pull Request Comments
Interactive Commit Graphs

On the other hand, Codefresh provides the following key features:

Instant Dev, test and feature preview environments: Enables all team members to run any image as a standalone or composition for feature preview, manual testing, bug reproduction and more. Collaborate on features before pushing them into staging and production.
Testing with every step: Configure your pipeline to run integration and unit tests with every step
Instantly test all code changes in the Codefresh build system before pushing to staging & production. Run integration, unit tests in parallel.

"More stable than coveralls" is the top reason why over 14 developers like Codecov, while over 6 developers mention "Fastest and easiest way to work with Docker" as the leading cause for choosing Codefresh.

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Advice on Codecov, Codefresh

Felipe

May 24, 2020

Needs advice

My website is brand new and one of the few requirements of testings I had to implement was code coverage. Never though it was so hard to implement using a #docker container.
Given my lack of experience, every attempt I tried on making a simple code coverage test using the 4 combinations of #TravisCI, #CircleCi with #Coveralls, #Codecov I failed. The main problem was I was generating the .coverage file within the docker container and couldn't access it with #TravisCi or #CircleCi, every attempt to solve this problem seems to be very hacky and this was not the kind of complexity I want to introduce to my newborn website.
This problem was solved using a specific action for #GitHubActions, it was a 3 line solution I had to put in my github workflow file and I was able to access the .coverage file from my docker container and get the coverage report with #Codecov.

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Comments

Detailed Comparison

Codecov	Codefresh
Our patrons rave about our elegant coverage reports, integrated pull request comments, interactive commit graphs, our Chrome plugin and security.	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.
Beautiful Reports;Pull Request Comments;Interactive Commit Graphs;Chrome Extension;Github Commit Status;Easy to Integrate;Hipchat Integration	Instant Dev, test and feature preview environments: Enables all team members to run any image as a standalone or composition for feature preview, manual testing, bug reproduction and more. Collaborate on features before pushing them into staging and production.; Testing with every step: Configure your pipeline to run integration and unit tests with every step; Instantly test all code changes in the Codefresh build system before pushing to staging & production. Run integration, unit tests in parallel.; 360° view of Docker images: View commit info, test results and build logs for all images; Manage Docker image labels and status, comment and see new feature branches; search and filter based on any attribute.; Out-of-the-box Docker buildpack for all technologies: Seamlessly package your code in a Docker image. Quickly associate a Dockerfile with your repo by selecting the repository technology stack (Java, Node, PHP, etc.). Codefresh then adds a template for Dockerizing apps.; View and Access Running Container Logs: Access each container log directly from within the Codefresh platform. This lets you easily perform root-cause analysis on failed services and allows you to see logs in high debug model level.; Support for Docker Compose 1 & 2: Manage your Docker Compose file natively in one place, with support for both Docker Compose versions 1 and 2. Use a built-in wizard to write Docker Compose files quickly.; YAML file support: Customize and easily define your pipeline steps using a codefresh.yml file.
Statistics
Stacks 2.8K	Stacks 64
Followers 324	Followers 111
Votes 102	Votes 47
Pros & Cons
Pros 17 Easy setup 17 More stable than coveralls 14 GitHub integration 11 They reply their users 10 Easy setup,great ui Cons 1 GitHub org / team integration is a little too tight 0 Delayed results by hours since recent outage 0 Support does not respond to email	Pros 11 Fastest and easiest way to work with Docker 7 Great support/fast builds/awesome ui 6 Great onboarding 5 Freestyle build steps to support custom CI/CD scripting 4 Robust feature-preview/qa environments on-demand Cons 1 Expensive compared to alternatives 1 Questionable product quality and stability
Integrations
HipChat Jenkins Bitbucket GitLab GitHub CircleCI Heroku	Quay.io Docker Compose Docker Swarm BinTray Docker Cloud Amazon EC2 GitHub Bitbucket HipChat BlazeMeter

What are some alternatives to Codecov, Codefresh?

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 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

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

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 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

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.

Coveralls

Coveralls works with your CI server and sifts through your coverage data to find issues you didn't even know you had before they become a problem. Free for open source, pro accounts for private repos, instant sign up with GitHub OAuth.

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

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 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.

Related Comparisons

Some of the features offered by Codecov are:

Beautiful Reports
Pull Request Comments
Interactive Commit Graphs

On the other hand, Codefresh provides the following key features:

Instant Dev, test and feature preview environments: Enables all team members to run any image as a standalone or composition for feature preview, manual testing, bug reproduction and more. Collaborate on features before pushing them into staging and production.
Testing with every step: Configure your pipeline to run integration and unit tests with every step
Instantly test all code changes in the Codefresh build system before pushing to staging & production. Run integration, unit tests in parallel.

Codecov vs Codefresh