+1 (binding)
On Fri, 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. > >
