Hello Everyone, Thanks for participating in the vote and discussions about Eagle.
Binding votes = 10 Non-binding votes = 14 Total votes = 24 Thanks, Arun On 10/25/15, 8:37 PM, "Don Bosco Durai" <bo...@apache.org> wrote: >+1 non binding >Bosco > > > > _____________________________ >From: Li Yang <liy...@apache.org> >Sent: Sunday, October 25, 2015 8:13 PM >Subject: Re: [VOTE] Accept Eagle into Apache Incubation >To: <general@incubator.apache.org> > > >+1 (non-binding) > >On Mon, Oct 26, 2015 at 10:50 AM, hongbin ma <mahong...@apache.org> wrote: > >> +1 (non binding) >> >> On Mon, Oct 26, 2015 at 12:20 AM, Ralph Goers >><ralph.go...@dslextreme.com> >> wrote: >> >> > +1 (binding) >> > >> > Ralph >> > >> > > On Oct 23, 2015, at 7:11 AM, Manoharan, Arun <armanoha...@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 >> > user’s 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 user’s >> > 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 today’s businesses, >>which >> > makes data security one of the top priorities of today’s 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 today’s 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 >>10’s >> 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 Apache’s 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 O’Malley < 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. >> > > >> > >> > >> > >> > --------------------------------------------------------------------- >> > To unsubscribe, e-mail: general-unsubscr...@incubator.apache.org >> > For additional commands, e-mail: general-h...@incubator.apache.org >> > >> > >> >> >> -- >> Regards, >> >> *Bin Mahone | 马洪宾* >> Apache Kylin: http://kylin.io >> Github: https://github.com/binmahone
