Cloudflow vs Codefresh
Overview
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CLI (Node.js)
Manual
Detailed Comparison
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. | It enables you to quickly develop, orchestrate, and operate distributed streaming applications on Kubernetes. With Cloudflow, streaming applications are comprised of small composable components wired together with schema-based contracts. It can dramatically accelerate streaming application development—reducing the time required to create, package, and deploy—from weeks to hours. |
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. | Apache Spark, Apache Flink, and Akka Streams;
Focus only on business logic, leave the boilerplate to us;
We provide all the tooling for going from business logic to a deployable Docker image;
We provide Kubernetes tooling to deploy your distributed system with a single command, and manage durable connections between processing stages;
With a Lightbend subscription, you get all the tools you need to provide insights, observability, and lifecycle management for evolving your distributed streaming application |
Statistics | |
GitHub Stars - | GitHub Stars 323 |
GitHub Forks - | GitHub Forks 89 |
Stacks 64 | Stacks 5 |
Followers 111 | Followers 13 |
Votes 47 | Votes 0 |
Pros & Cons | |
Pros
Cons
| No community feedback yet |
Integrations | |
What are some alternatives to Codefresh, Cloudflow?
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.
Apache Spark
Spark is a fast and general processing engine compatible with Hadoop data. It can run in Hadoop clusters through YARN or Spark's standalone mode, and it can process data in HDFS, HBase, Cassandra, Hive, and any Hadoop InputFormat. It is designed to perform both batch processing (similar to MapReduce) and new workloads like streaming, interactive queries, and machine learning.
Presto
Distributed SQL Query Engine for Big Data
Amazon Athena
Amazon Athena is an interactive query service that makes it easy to analyze data in Amazon S3 using standard SQL. Athena is serverless, so there is no infrastructure to manage, and you pay only for the queries that you run.
Apache Flink
Apache Flink is an open source system for fast and versatile data analytics in clusters. Flink supports batch and streaming analytics, in one system. Analytical programs can be written in concise and elegant APIs in Java and Scala.
