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Eskimo components

Big Data Web Console to build, manage and operate Big Data 2.0 clusters using Docker, SystemD and Mesos

Eskimo Zeppelin Demo

Eskimo Community Edition is 100% open source platform distribution, including Apache Spark, Apache Flink andf ElasticSearch and built specifically to meet Data Science demands on Big Data.
Eskimo delivers everything you need for enterprise data science use right out of the box. By integrating more than a dozen of critical open source projects in docker and systemd, Eskimo has created a functionally advanced system that helps you perform end-to-end Big Data workflows.

Eskimo Core Components

Elastic Logstash

Logstash is an open source, server-side data processing pipeline that ingests data from a multitude of sources simultaneously, transforms it, and then sends it to your favorite "stash."

Logstash dynamically ingests, transforms, and ships your data regardless of format or complexity. Derive structure from unstructured data with grok, decipher geo coordinates from IP addresses, anonymize or exclude sensitive fields, and ease overall processing.

Elastic Logstash
Apache Mesos

Apache Mesos

Apache Mesos abstracts CPU, memory, storage, and other compute resources away from machines (physical or virtual), enabling fault-tolerant and elastic distributed systems to easily be built and run effectively.

Mesos is a distributed system kernel. Mesos is built using the same principles as the Linux kernel, only at a different level of abstraction. The Mesos kernel runs on every machine and provides applications (e.g., Hadoop, Spark, Kafka, Elasticsearch) with API’s for resource management and scheduling across entire datacenter and cloud environments.

Gluster FS

Gluster is a free and open source software scalable network filesystem.

GlusterFS is a scalable network filesystem suitable for data-intensive tasks such as cloud storage and media streaming. GlusterFS is free and open source software and can utilize common off-the-shelf hardware.

Gluster FS

Apache Zookeeper

Apache ZooKeeper is an effort to develop and maintain an open-source server which enables highly reliable distributed coordination.

ZooKeeper is a centralized service for maintaining configuration information, naming, providing distributed synchronization, and providing group services. All of these kinds of services are used in some form or another by distributed applications


Prometheus is an open-source systems monitoring and alerting toolkit.

Prometheus's main features are: a multi-dimensional data model with time series data identified by metric name and key/value pairs, PromQL - a flexible query language to leverage this dimensionality, automatic discovery of nodes and targets, etc.



Grafana is the open source analytics & monitoring solution for every database.

Within Eskimo, Grafana is meant as the data visualization tool for monitoring purposes on top of pometheus.

One can use Grafana though for a whole range of other data visualization use cases.


Elasticsearch is a distributed, RESTful search and analytics engine capable of addressing a growing number of use cases. As the heart of the Elastic Stack, it centrally stores your data so you can discover the expected and uncover the unexpected.

Elasticsearch lets you perform and combine many types of searches — structured, unstructured, geo, metric — any way you want. Start simple with one question and see where it takes you.



Cerebro is an open source elasticsearch web admin tool.

Monitoring the nodes here includes all indexes, all the data nodes, index size, total index size, etc

Apache Kafka

Apache Kafka is a stributed Streaming platform.

Kafka is used for building real-time data pipelines and streaming apps. It is horizontally scalable, fault-tolerant, wicked fast, and runs in production in thousands of companies.

Kafka Manager

Kafka Manager

Kafka Manager is a tool for managing Apache Kafka.

KafkaManager enables to manage multiples clusters, nodes, create and delete topics, run preferred replica election, generate partition assignments, monitor statistics, etc.

Apache Flink

Apache Flink is an open-source stream-processing framework

Apache Flink is a framework and distributed processing engine for stateful computations over unbounded and bounded data streams. Flink has been designed to run in all common cluster environments, perform computations at in-memory speed and at any scale.

Apache Flink's dataflow programming model provides event-at-a-time processing on both finite and infinite datasets. At a basic level, Flink programs consist of streams and transformations. Conceptually, a stream is a (potentially never-ending) flow of data records, and a transformation is an operation that takes one or more streams as input, and produces one or more output streams as a result.


Apache Spark

Apache Spark is an open-source distributed general-purpose cluster-computing framework. Spark provides an interface for programming entire clusters with implicit data parallelism and fault tolerance.

Spark provides high-level APIs and an optimized engine that supports general execution graphs. It also supports a rich set of higher-level tools including Spark SQL for SQL and structured data processing, MLlib for machine learning, GraphX for graph processing, and Spark Streaming.

Elastic Kibana

Kibana lets you visualize your Elasticsearch data and navigate the Elastic Stack so you can do anything from tracking query load to understanding the way requests flow through your apps.

Kibana gives you the freedom to select the way you give shape to your data. And you don’t always have to know what you’re looking for. With its interactive visualizations, start with one question and see where it leads you


Apache zeppelin

Apache Zeppelin is a web-based notebook that enables data-driven, interactive data analytics and collaborative documents with SQL, Scala and more.

Zeppelin is a multiple purpose notebook, the place for all your needs, from Data Discovery to High-end Data Analytics supporting a Multiple Language Backend.

Within Eskimo, zeppelin can be used to run flink and spark jobs, discover data in ElasticSearch, manipulate files in Gluster, etc.