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From "Zhang, Edward (GDI Hadoop)" <yonzh...@ebay.com>
Subject Re: [VOTE] Accept Eagle into Apache Incubation
Date Wed, 04 Nov 2015 00:49:48 GMT
Thanks Henry very much. That is nice we got those mail lists so we can
communicate with community well.

Thanks
Edward Zhang

On 11/3/15, 16:46, "Henry Saputra" <henry.saputra@gmail.com> wrote:

>Follow up announcement, the Apache Eagle incubating mailing lists are
>now available:
>
>€ dev@eagle.incubator.apache.org (subscribe by sending email to
>dev-subscribe@eagle.incubator.apache.org)
>€ commits@eagle.incubator.apache.org (subscribe by sending email to
>commits-subscribe@eagle.incubator.apache.org)
>€ user@eagle.incubator.apache.org (subscribe by sending email to
>user-subscribe@eagle.incubator.apache.org)
>
>
>Thanks,
>
>Henry
>
>
>On Fri, Oct 23, 2015 at 7:11 AM, Manoharan, Arun <armanoharan@ebay.com>
>wrote:
>> Hello Everyone,
>>
>> Thanks for all the feedback on the Eagle Proposal.
>>
>> I would like to call for a [VOTE] on Eagle joining the ASF as an
>>incubation project.
>>
>> The vote is open for 72 hours:
>>
>> [ ] +1 accept Eagle in the Incubator
>> [ ] ±0
>> [ ] -1 (please give reason)
>>
>> Eagle is a Monitoring solution for Hadoop to instantly identify access
>>to sensitive data, recognize attacks, malicious activities and take
>>actions in real time. Eagle supports a wide variety of policies on HDFS
>>data and Hive. Eagle also provides machine learning models for detecting
>>anomalous user behavior in Hadoop.
>>
>> The proposal is available on the wiki here:
>> https://wiki.apache.org/incubator/EagleProposal
>>
>> The text of the proposal is also available at the end of this email.
>>
>> Thanks for your time and help.
>>
>> Thanks,
>> Arun
>>
>> <COPY of the proposal in text format>
>>
>> Eagle
>>
>> Abstract
>> Eagle is an Open Source Monitoring solution for Hadoop to instantly
>>identify access to sensitive data, recognize attacks, malicious
>>activities in hadoop and take actions.
>>
>> Proposal
>> Eagle audits access to HDFS files, Hive and HBase tables in real time,
>>enforces policies defined on sensitive data access and alerts or blocks
>>user¹s access to that sensitive data in real time. Eagle also creates
>>user profiles based on the typical access behaviour for HDFS and Hive
>>and sends alerts when anomalous behaviour is detected. Eagle can also
>>import sensitive data information classified by external classification
>>engines to help define its policies.
>>
>> Overview of Eagle
>> Eagle has 3 main parts.
>> 1.Data collection and storage - Eagle collects data from various hadoop
>>logs in real time using Kafka/Yarn API and uses HDFS and HBase for
>>storage.
>> 2.Data processing and policy engine - Eagle allows users to create
>>policies based on various metadata properties on HDFS, Hive and HBase
>>data.
>> 3.Eagle services - Eagle services include policy manager, query service
>>and the visualization component. Eagle provides intuitive user interface
>>to administer Eagle and an alert dashboard to respond to real time
>>alerts.
>>
>> Data Collection and Storage:
>> Eagle provides programming API for extending Eagle to integrate any
>>data source into Eagle policy evaluation framework. For example, Eagle
>>hdfs audit monitoring collects data from Kafka which is populated from
>>namenode log4j appender or from logstash agent. Eagle hive monitoring
>>collects hive query logs from running job through YARN API, which is
>>designed to be scalable and fault-tolerant. Eagle uses HBase as storage
>>for storing metadata and metrics data, and also supports relational
>>database through configuration change.
>>
>> Data Processing and Policy Engine:
>> Processing Engine: Eagle provides stream processing API which is an
>>abstraction of Apache Storm. It can also be extended to other streaming
>>engines. This abstraction allows developers to assemble data
>>transformation, filtering, external data join etc. without physically
>>bound to a specific streaming platform. Eagle streaming API allows
>>developers to easily integrate business logic with Eagle policy engine
>>and internally Eagle framework compiles business logic execution DAG
>>into program primitives of underlying stream infrastructure e.g. Apache
>>Storm. For example, Eagle HDFS monitoring transforms audit log from
>>Namenode to object and joins sensitivity metadata, security zone
>>metadata which are generated from external programs or configured by
>>user. Eagle hive monitoring filters running jobs to get hive query
>>string and parses query string into object and then joins sensitivity
>>metadata.
>> Alerting Framework: Eagle Alert Framework includes stream metadata API,
>>scalable policy engine framework, extensible policy engine framework.
>>Stream metadata API allows developers to declare event schema including
>>what attributes constitute an event, what is the type for each
>>attribute, and how to dynamically resolve attribute value in runtime
>>when user configures policy. Scalable policy engine framework allows
>>policies to be executed on different physical nodes in parallel. It is
>>also used to define your own policy partitioner class. Policy engine
>>framework together with streaming partitioning capability provided by
>>all streaming platforms will make sure policies and events can be
>>evaluated in a fully distributed way. Extensible policy engine framework
>>allows developer to plugin a new policy engine with a few lines of
>>codes. WSO2 Siddhi CEP engine is the policy engine which Eagle supports
>>as first-class citizen.
>> Machine Learning module: Eagle provides capabilities to define user
>>activity patterns or user profiles for Hadoop users based on the user
>>behaviour in the platform. These user profiles are modeled using Machine
>>Learning algorithms and used for detection of anomalous users
>>activities. Eagle uses Eigen Value Decomposition, and Density Estimation
>>algorithms for generating user profile models. The model reads data from
>>HDFS audit logs, preprocesses and aggregates data, and generates models
>>using Spark programming APIs. Once models are generated, Eagle uses
>>stream processing engine for near real-time anomaly detection to
>>determine if any user¹s activities are suspicious or not.
>>
>> Eagle Services:
>> Query Service: Eagle provides SQL-like service API to support
>>comprehensive computation for huge set of data on the fly, for e.g.
>>comprehensive filtering, aggregation, histogram, sorting, top,
>>arithmetical expression, pagination etc. HBase is the data storage which
>>Eagle supports as first-class citizen, relational database is supported
>>as well. For HBase storage, Eagle query framework compiles user provided
>>SQL-like query into HBase native filter objects and execute it through
>>HBase coprocessor on the fly.
>> Policy Manager: Eagle policy manager provides UI and Restful API for
>>user to define policy with just a few clicks. It includes site
>>management UI, policy editor, sensitivity metadata import, HDFS or Hive
>>sensitive resource browsing, alert dashboards etc.
>> Background
>> Data is one of the most important assets for today¹s businesses, which
>>makes data security one of the top priorities of today¹s enterprises.
>>Hadoop is widely used across different verticals as a big data
>>repository to store this data in most modern enterprises.
>> At eBay we use hadoop platform extensively for our data processing
>>needs. Our data in Hadoop is becoming bigger and bigger as our user base
>>is seeing an exponential growth. Today there are variety of data sets
>>available in Hadoop cluster for our users to consume. eBay has around
>>120 PB of data stored in HDFS across 6 different clusters and around
>>1800+ active hadoop users consuming data thru Hive, HBase and mapreduce
>>jobs everyday to build applications using this data. With this
>>astronomical growth of data there are also challenges in securing
>>sensitive data and monitoring the access to this sensitive data. Today
>>in large organizations HDFS is the defacto standard for storing big
>>data. Data sets which includes and not limited to consumer sentiment,
>>social media data, customer segmentation, web clicks, sensor data,
>>geo-location and transaction data get stored in Hadoop for day to day
>>business needs.
>> We at eBay want to make sure the sensitive data and data platforms are
>>completely protected from security breaches. So we partnered very
>>closely with our Information Security team to understand the
>>requirements for Eagle to monitor sensitive data access on hadoop:
>> 1.Ability to identify and stop security threats in real time
>> 2.Scale for big data (Support PB scale and Billions of events)
>> 3.Ability to create data access policies
>> 4.Support multiple data sources like HDFS, HBase, Hive
>> 5.Visualize alerts in real time
>> 6.Ability to block malicious access in real time
>> We did not find any data access monitoring solution that available
>>today and can provide the features and functionality that we need to
>>monitor the data access in the hadoop ecosystem at our scale. Hence with
>>an excellent team of world class developers and several users, we have
>>been able to bring Eagle into production as well as open source it.
>>
>> Rationale
>> In today¹s world; data is an important asset for any company.
>>Businesses are using data extensively to create amazing experiences for
>>users. Data has to be protected and access to data should be secured
>>from security breaches. Today Hadoop is not only used to store logs but
>>also stores financial data, sensitive data sets, geographical data, user
>>click stream data sets etc. which makes it more important to be
>>protected from security breaches. To secure a data platform there are
>>multiple things that need to happen. One is having a strong access
>>control mechanism which today is provided by Apache Ranger and Apache
>>Sentry. These tools provide the ability to provide fine grain access
>>control mechanism to data sets on hadoop. But there is a big gap in
>>terms of monitoring all the data access events and activities in order
>>to securing the hadoop data platform. Together with strong access
>>control, perimeter security and data access monitoring in place data in
>>the hadoop clusters can be secured against breaches. We looked around
>>and found following:
>> Existing data activity monitoring products are designed for traditional
>>databases and data warehouse. Existing monitoring platforms cannot scale
>>out to support fast growing data and petabyte scale. Few products in the
>>industry are still very early in terms of supporting HDFS, Hive, HBase
>>data access monitoring.
>> As mentioned in the background, the business requirement and urgency to
>>secure the data from users with malicious intent drove eBay to invest in
>>building a real time data access monitoring solution from scratch to
>>offer real time alerts and remediation features for malicious data
>>access.
>> With the power of open source distributed systems like Hadoop, Kafka
>>and much more we were able to develop a data activity monitoring system
>>that can scale, identify and stop malicious access in real time.
>> Eagle allows admins to create standard access policies and rules for
>>monitoring HDFS, Hive and HBase data. Eagle also provides out of box
>>machine learning models for modeling user profiles based on user access
>>behaviour and use the model to alert on anomalies.
>>
>> Current Status
>>
>> Meritocracy
>> Eagle has been deployed in production at eBay for monitoring billions
>>of events per day from HDFS and Hive operations. From the start; the
>>product has been built with focus on high scalability and application
>>extensibility in mind and Eagle has demonstrated great performance in
>>responding to suspicious events instantly and great flexibility in
>>defining policy.
>>
>> Community
>> Eagle seeks to develop the developer and user communities during
>>incubation.
>>
>> Core Developers
>> Eagle is currently being designed and developed by engineers from eBay
>>Inc. ­ Edward Zhang, Hao Chen, Chaitali Gupta, Libin Sun, Jilin Jiang,
>>Qingwen Zhao, Senthil Kumar, Hemanth Dendukuri, Arun Manoharan. All of
>>these core developers have deep expertise in developing monitoring
>>products for the Hadoop ecosystem.
>>
>> Alignment
>> The ASF is a natural host for Eagle given that it is already the home
>>of Hadoop, HBase, Hive, Storm, Kafka, Spark and other emerging big data
>>projects. Eagle leverages lot of Apache open-source products. Eagle was
>>designed to offer real time insights into sensitive data access by
>>actively monitoring the data access on various data sets in hadoop and
>>an extensible alerting framework with a powerful policy engine. Eagle
>>compliments the existing Hadoop platform area by providing a
>>comprehensive monitoring and alerting solution for detecting sensitive
>>data access threats based on preset policies and machine learning models
>>for user behaviour analysis.
>>
>> Known Risks
>>
>> Orphaned Products
>> The core developers of Eagle team work full time on this project. There
>>is no risk of Eagle getting orphaned since eBay is extensively using it
>>in their production Hadoop clusters and have plans to go beyond hadoop.
>>For example, currently there are 7 hadoop clusters and 2 of them are
>>being monitored using Hadoop Eagle in production. We have plans to
>>extend it to all hadoop clusters and eventually other data platforms.
>>There are 10¹s of policies onboarded and actively monitored with plans
>>to onboard more use case. We are very confident that every hadoop
>>cluster in the world will be monitored using Eagle for securing the
>>hadoop ecosystem by actively monitoring for data access on sensitive
>>data. We plan to extend and diversify this community further through
>>Apache. We presented Eagle at the hadoop summit in china and garnered
>>interest from different companies who use hadoop extensively.
>>
>> Inexperience with Open Source
>> The core developers are all active users and followers of open source.
>>They are already committers and contributors to the Eagle Github
>>project. All have been involved with the source code that has been
>>released under an open source license, and several of them also have
>>experience developing code in an open source environment. Though the
>>core set of Developers do not have Apache Open Source experience, there
>>are plans to onboard individuals with Apache open source experience on
>>to the project. Apache Kylin PMC members are also in the same ebay
>>organization. We work very closely with Apache Ranger committers and are
>>looking forward to find meaningful integrations to improve the security
>>of hadoop platform.
>>
>> Homogenous Developers
>> The core developers are from eBay. Today the problem of monitoring data
>>activities to find and stop threats is a universal problem faced by all
>>the businesses. Apache Incubation process encourages an open and diverse
>>meritocratic community. Eagle intends to make every possible effort to
>>build a diverse, vibrant and involved community and has already received
>>substantial interest from various organizations.
>>
>> Reliance on Salaried Developers
>> eBay invested in Eagle as the monitoring solution for Hadoop clusters
>>and some of its key engineers are working full time on the project. In
>>addition, since there is a growing need for securing sensitive data
>>access we need a data activity monitoring solution for Hadoop, we look
>>forward to other Apache developers and researchers to contribute to the
>>project. Additional contributors, including Apache committers have plans
>>to join this effort shortly. Also key to addressing the risk associated
>>with relying on Salaried developers from a single entity is to increase
>>the diversity of the contributors and actively lobby for Domain experts
>>in the security space to contribute. Eagle intends to do this.
>>
>> Relationships with Other Apache Products
>> Eagle has a strong relationship and dependency with Apache Hadoop,
>>HBase, Spark, Kafka and Storm. Being part of Apache¹s Incubation
>>community, could help with a closer collaboration among these projects
>>and as well as others. An Excessive Fascination with the Apache Brand
>>Eagle is proposing to enter incubation at Apache in order to help
>>efforts to diversify the committer-base, not so much to capitalize on
>>the Apache brand. The Eagle project is in production use already inside
>>eBay, but is not expected to be an eBay product for external customers.
>>As such, the Eagle project is not seeking to use the Apache brand as a
>>marketing tool.
>>
>> Documentation
>> Information about Eagle can be found at https://github.com/eBay/Eagle.
>>The following link provide more information about Eagle
>>http://goeagle.io<http://goeagle.io/>.
>>
>> Initial Source
>> Eagle has been under development since 2014 by a team of engineers at
>>eBay Inc. It is currently hosted on Github.com under an Apache license
>>2.0 at https://github.com/eBay/Eagle. Once in incubation we will be
>>moving the code base to apache git library.
>>
>> External Dependencies
>> Eagle has the following external dependencies.
>> Basic
>> €JDK 1.7+
>> €Scala 2.10.4
>> €Apache Maven
>> €JUnit
>> €Log4j
>> €Slf4j
>> €Apache Commons
>> €Apache Commons Math3
>> €Jackson
>> €Siddhi CEP engine
>>
>> Hadoop
>> €Apache Hadoop
>> €Apache HBase
>> €Apache Hive
>> €Apache Zookeeper
>> €Apache Curator
>>
>> Apache Spark
>> €Spark Core Library
>>
>> REST Service
>> €Jersey
>>
>> Query
>> €Antlr
>>
>> Stream processing
>> €Apache Storm
>> €Apache Kafka
>>
>> Web
>> €AngularJS
>> €jQuery
>> €Bootstrap V3
>> €Moment JS
>> €Admin LTE
>> €html5shiv
>> €respond
>> €Fastclick
>> €Date Range Picker
>> €Flot JS
>>
>> Cryptography
>> Eagle will eventually support encryption on the wire. This is not one
>>of the initial goals, and we do not expect Eagle to be a controlled
>>export item due to the use of encryption. Eagle supports but does not
>>require the Kerberos authentication mechanism to access secured Hadoop
>>services.
>>
>> Required Resources
>>
>> Mailing List
>> €eagle-private for private PMC discussions
>> €eagle-dev for developers
>> €eagle-commits for all commits
>> €eagle-users for all eagle users
>>
>> Subversion Directory
>> €Git is the preferred source control system.
>>
>> Issue Tracking
>> €JIRA Eagle (Eagle)
>>
>> Other Resources
>> The existing code already has unit tests so we will make use of
>>existing Apache continuous testing infrastructure. The resulting load
>>should not be very large.
>>
>> Initial Committers
>> €Seshu Adunuthula <sadunuthula at ebay dot com>
>> €Arun Manoharan <armanoharan at ebay dot com>
>> €Edward Zhang <yonzhang at ebay dot com>
>> €Hao Chen <hchen9 at ebay dot com>
>> €Chaitali Gupta <cgupta at ebay dot com>
>> €Libin Sun <libsun at ebay dot com>
>> €Jilin Jiang <jiljiang at ebay dot com>
>> €Qingwen Zhao <qingwzhao at ebay dot com>
>> €Hemanth Dendukuri <hdendukuri at ebay dot com>
>> €Senthil Kumar <senthilkumar at ebay dot com>
>>
>>
>> Affiliations
>> The initial committers are employees of eBay Inc.
>>
>> Sponsors
>>
>> Champion
>> €Henry Saputra <hsaputra at apache dot org> - Apache IPMC member
>>
>> Nominated Mentors
>> €Owen O¹Malley < omalley at apache dot org > - Apache IPMC member,
>>Hortonworks
>> €Henry Saputra <hsaputra at apache dot org> - Apache IPMC member
>> €Julian Hyde <jhyde at hortonworks dot com> - Apache IPMC member,
>>Hortonworks
>> €Amareshwari Sriramdasu <amareshwari at apache dot org> - Apache IPMC
>>member
>> €Taylor Goetz <ptgoetz at apache dot org> - Apache IPMC member,
>>Hortonworks
>>
>> Sponsoring Entity
>> We are requesting the Incubator to sponsor this project.
>>
>
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