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  1. Stackups
  2. DevOps
  3. Log Management
  4. Log Management
  5. Cloudflow vs Splunk

Cloudflow vs Splunk

OverviewComparisonAlternatives

Overview

Splunk
Splunk
Stacks772
Followers1.0K
Votes20
Cloudflow
Cloudflow
Stacks5
Followers13
Votes0
GitHub Stars323
Forks89

Splunk vs Cloudflow: What are the differences?

Splunk: Search, monitor, analyze and visualize machine data. It provides the leading platform for Operational Intelligence. Customers use it to search, monitor, analyze and visualize machine data; Cloudflow: *Streaming Data Pipeline on Kubernetes *. 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.

Splunk and Cloudflow can be categorized as "Big Data" tools.

Some of the features offered by Splunk are:

  • Predict and prevent problems with one unified monitoring experience
  • Streamline your entire security stack with Splunk as the nerve center
  • Detect, investigate and diagnose problems easily with end-to-end observability

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

  • 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

Cloudflow is an open source tool with 172 GitHub stars and 50 GitHub forks. Here's a link to Cloudflow's open source repository on GitHub.

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Detailed Comparison

Splunk
Splunk
Cloudflow
Cloudflow

It provides the leading platform for Operational Intelligence. Customers use it to search, monitor, analyze and visualize machine data.

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.

Predict and prevent problems with one unified monitoring experience; Streamline your entire security stack with Splunk as the nerve center; Detect, investigate and diagnose problems easily with end-to-end observability
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
772
Stacks
5
Followers
1.0K
Followers
13
Votes
20
Votes
0
Pros & Cons
Pros
  • 3
    Alert system based on custom query results
  • 3
    API for searching logs, running reports
  • 2
    Ability to style search results into reports
  • 2
    Query engine supports joining, aggregation, stats, etc
  • 2
    Dashboarding on any log contents
Cons
  • 1
    Splunk query language rich so lots to learn
No community feedback yet
Integrations
No integrations available
Kubernetes
Kubernetes
Apache Spark
Apache Spark
Akka
Akka
Apache Flink
Apache Flink

What are some alternatives to Splunk, Cloudflow?

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.

Papertrail

Papertrail

Papertrail helps detect, resolve, and avoid infrastructure problems using log messages. Papertrail's practicality comes from our own experience as sysadmins, developers, and entrepreneurs.

Logmatic

Logmatic

Get a clear overview of what is happening across your distributed environments, and spot the needle in the haystack in no time. Build dynamic analyses and identify improvements for your software, your user experience and your business.

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.

Loggly

Loggly

It is a SaaS solution to manage your log data. There is nothing to install and updates are automatically applied to your Loggly subdomain.

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.

Apache Spark

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.

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