John F. Zuniga has over 20 years of experience in information technology and security. He has held roles such as Network Defense Manager, Operations Manager, and Training Manager. Zuniga has a Bachelor's degree in Computer Network Security and various IT certifications. He has expertise implementing server operating system migrations, virtualization technologies, and Active Directory environments. Zuniga also has experience with cybersecurity monitoring, vulnerability assessments, and ensuring compliance with security policies.
Multi-Tenant Operations with Cloudera 5.7 & BTCloudera, Inc.
One benefit of Apache Hadoop is the ability to power multiple workloads, across many different users and departments, all within a single, shared cluster. Hear how BT is doing this today and learn about new features in Cloudera Manager to provide better visibility for multi-tenant operations.
What the Enterprise Requires - Business Continuity and VisibilityCloudera, Inc.
Cloudera Enterprise BDR delivers centralized disaster recovery for data and metadata, enabling you to prepare for disaster by moving data to your secondary site automatically. Cloudera Navigator 1.0 provides data governance capabilities such as verifying access privileges and auditing access to all data stored in Hadoop, which are critical for customers that are in highly regulated industries and have stringent compliance requirements.
This presentation will teach you how to:
- Centrally configure and manage replication workflows for files (HDFS) and metadata (Hive)
- Consistently meet or exceed SLAs and RTOs through simplified management and process automation
- Track access permissions and actual accesses to all data objects in Hive, HBase, and HDFS
- Answer the questions:
- Who has access to which data object(s)
- Which data objects were accessed by a user
- When was a data object accessed and by whom
- What data assets were accessed using a service
- Which device was used to access
Data is being generated at a feverish pace and many businesses want all of it at their disposal to solve complex strategic problems. As decision making moves to real-time, enterprises need data ready for analysis immediately. Sean Anderson and Amandeep Khurana will discuss common pipeline trends in modern streaming architectures, Hadoop components that enable streaming capabilities, and popular use cases that are enabling the world of IOT and real-time data science.
Risk Management for Data: Secured and GovernedCloudera, Inc.
Cloudera Tech Day Presentation by Eddie Garcia, Chief Security Architect, Cloudera. Protecting enterprise data is an increasingly complex challenge given the diversity and sophistication of threat actors and their cyber-tactics. In this session, participants will hear a comprehensive introduction to Hadoop Security, including the “three A’s” for secure operating environments: Authentication, Authorization, and Audit. In addition, the presenter will cover strategies to orchestrate data security, encryption, and compliance, and will explain the Cloudera Security Maturity Model for Hadoop. Attendees will leave with a greater understanding of how effective INFOSEC relies on an enterprise big data governance and risk management approach.
Faster Batch Processing with Cloudera 5.7: Hive-on-Spark is ready for productionCloudera, Inc.
It’s no secret that Apache Spark is becoming the successor to MapReduce for data processing in Hadoop. With it’s easy development, flexible API, and performance benefits, Spark is a powerful data processing engine that has quickly gained popularity within the community. On the other hand Hive continues to be the most widely used data warehouse/ETL engine with large scale adoption across enterprises. Therefore, it’s imperative to enable Spark as the underlying execution engine for Hive to seamlessly allow existing and future Hive workloads to leverage the advantages of Spark.
With the recent release of Cloudera 5.7, we have delivered on this goal by adding support for Hive-on-Spark. Data engineers and ETL developers can now transition from MR to Spark for their Hive workloads seamlessly thereby benefitting from the advantages of Spark without any disruption on their end.
Join Santosh Kumar, Senior Product Manager at Cloudera, and Rui Li, Apache Hive committer and engineer at Intel, as we discuss:
An Introduction to Spark and its advantages over MR
An introduction of Hive-on-Spark: Goals and Design Principles
Migrating to HoS and a live demo
Configuring and tuning for batch workloads
What’s next for both tools
Unprotected data stores are prone to data breaches. In this talk, I'll explain how to implement security on Hadoop. This talks covers basic elements, such as firewall, HA, backup, Kerberos, data encryption (both at rest and in transit).
I also shed light on how Cloudera handles security vulnerability reports, and a little bit on partner product certification process.
Multi-Tenant Operations with Cloudera 5.7 & BTCloudera, Inc.
One benefit of Apache Hadoop is the ability to power multiple workloads, across many different users and departments, all within a single, shared cluster. Hear how BT is doing this today and learn about new features in Cloudera Manager to provide better visibility for multi-tenant operations.
What the Enterprise Requires - Business Continuity and VisibilityCloudera, Inc.
Cloudera Enterprise BDR delivers centralized disaster recovery for data and metadata, enabling you to prepare for disaster by moving data to your secondary site automatically. Cloudera Navigator 1.0 provides data governance capabilities such as verifying access privileges and auditing access to all data stored in Hadoop, which are critical for customers that are in highly regulated industries and have stringent compliance requirements.
This presentation will teach you how to:
- Centrally configure and manage replication workflows for files (HDFS) and metadata (Hive)
- Consistently meet or exceed SLAs and RTOs through simplified management and process automation
- Track access permissions and actual accesses to all data objects in Hive, HBase, and HDFS
- Answer the questions:
- Who has access to which data object(s)
- Which data objects were accessed by a user
- When was a data object accessed and by whom
- What data assets were accessed using a service
- Which device was used to access
Data is being generated at a feverish pace and many businesses want all of it at their disposal to solve complex strategic problems. As decision making moves to real-time, enterprises need data ready for analysis immediately. Sean Anderson and Amandeep Khurana will discuss common pipeline trends in modern streaming architectures, Hadoop components that enable streaming capabilities, and popular use cases that are enabling the world of IOT and real-time data science.
Risk Management for Data: Secured and GovernedCloudera, Inc.
Cloudera Tech Day Presentation by Eddie Garcia, Chief Security Architect, Cloudera. Protecting enterprise data is an increasingly complex challenge given the diversity and sophistication of threat actors and their cyber-tactics. In this session, participants will hear a comprehensive introduction to Hadoop Security, including the “three A’s” for secure operating environments: Authentication, Authorization, and Audit. In addition, the presenter will cover strategies to orchestrate data security, encryption, and compliance, and will explain the Cloudera Security Maturity Model for Hadoop. Attendees will leave with a greater understanding of how effective INFOSEC relies on an enterprise big data governance and risk management approach.
Faster Batch Processing with Cloudera 5.7: Hive-on-Spark is ready for productionCloudera, Inc.
It’s no secret that Apache Spark is becoming the successor to MapReduce for data processing in Hadoop. With it’s easy development, flexible API, and performance benefits, Spark is a powerful data processing engine that has quickly gained popularity within the community. On the other hand Hive continues to be the most widely used data warehouse/ETL engine with large scale adoption across enterprises. Therefore, it’s imperative to enable Spark as the underlying execution engine for Hive to seamlessly allow existing and future Hive workloads to leverage the advantages of Spark.
With the recent release of Cloudera 5.7, we have delivered on this goal by adding support for Hive-on-Spark. Data engineers and ETL developers can now transition from MR to Spark for their Hive workloads seamlessly thereby benefitting from the advantages of Spark without any disruption on their end.
Join Santosh Kumar, Senior Product Manager at Cloudera, and Rui Li, Apache Hive committer and engineer at Intel, as we discuss:
An Introduction to Spark and its advantages over MR
An introduction of Hive-on-Spark: Goals and Design Principles
Migrating to HoS and a live demo
Configuring and tuning for batch workloads
What’s next for both tools
Unprotected data stores are prone to data breaches. In this talk, I'll explain how to implement security on Hadoop. This talks covers basic elements, such as firewall, HA, backup, Kerberos, data encryption (both at rest and in transit).
I also shed light on how Cloudera handles security vulnerability reports, and a little bit on partner product certification process.
Treat your enterprise data lake indigestion: Enterprise ready security and go...DataWorks Summit
Most enterprises with large data lakes today are flying blind when it comes to the extent to which they can understand how the data in their data lakes is organized, accessed, and utilized to create real business value. Couple this with the need to democratize data, enterprises often realize they have created a data swamp loaded with all kinds of data assets without any curation and without appropriate security controls hoping that developers and analysts can responsibly collaborate to generate insights. In this talk we will provide a broad overview of how organizations can use open source frameworks such as Apache Ranger and Apache Knox to secure their data lakes and Apache Atlas to effectively provide open metadata and governance services for Hadoop ecosystem. We will provide an overview of the new features that have been added in each of these Apache projects recently and how enterprises can leverage these new features to build a robust security and governance model for their data lakes.
Speaker
Owen O'Malley, Co-Founder & Technical Fellow, Hortonworks
A deep dive into running data analytic workloads in the cloudCloudera, Inc.
Aishwarya Venkataraman, Jason Wang, Mala Ramakrishnan, Stefan Salandy, and Vinithra Varadharajan lead a deep dive into running data analytic workloads in a managed service capacity in the public cloud and highlight cloud infrastructure best practices.
Discover the origins of big data, discuss existing and new projects, share common use cases for those projects, and explain how you can modernize your architecture using data analytics, data operations, data engineering and data science.
Big Data Fundamentals is your prerequisite to building a modern platform for machine learning and analytics optimized for the cloud.
We’ll close out with a live Q&A with some of our technical experts as well.
Stretch your brain with a packed agenda:
Open source software
Data storage
Data ingestion
Data analytics
Data engineering
IoT and life after Lambda architectures
Data science
Cybersecurity
Cluster management
Big data in the cloud
Success stories
Simplifying Hadoop with RecordService, A Secure and Unified Data Access Path ...Cloudera, Inc.
SFHUG presentation from February 2, 2016. One of the key values of the Hadoop ecosystem is its flexibility. There is a myriad of components that make up this ecosystem, allowing Hadoop to tackle otherwise intractable problems. However, having so many components provides a significant integration, implementation, and usability burden. Features that ought to work in all the components often require sizable per-component effort to ensure correctness across the stack.
Lenni Kuff explores RecordService, a new solution to this problem that provides an API to read data from Hadoop storage managers and return them as canonical records. This eliminates the need for components to support individual file formats, handle security, perform auditing, and implement sophisticated IO scheduling and other common processing that is at the bottom of any computation.
Lenni discusses the architecture of the service and the integration work done for MapReduce and Spark. Many existing applications on those frameworks can take advantage of the service with little to no modification. Lenni demonstrates how this provides fine grain (column level and row level) security, through Sentry integration, and improves performance for existing MapReduce and Spark applications by up to 5×. Lenni concludes by discussing how this architecture can enable significant future improvements to the Hadoop ecosystem.
About the speaker: Lenni Kuff is an engineering manager at Cloudera. Before joining Cloudera, he worked at Microsoft on a number of projects including SQL Server storage engine, SQL Azure, and Hadoop on Azure. Lenni graduated from the University of Wisconsin-Madison with degrees in computer science and computer engineering.
Intel and Cloudera: Accelerating Enterprise Big Data SuccessCloudera, Inc.
The data center has gone through several inflection points in the past decades: adoption of Linux, migration from physical infrastructure to virtualization and Cloud, and now large-scale data analytics with Big Data and Hadoop.
Please join us to learn about how Cloudera and Intel are jointly innovating through open source software to enable Hadoop to run best on IA (Intel Architecture) and to foster the evolution of a vibrant Big Data ecosystem.
Today enterprises desire to move more and more of their data lakes to the cloud to help them execute faster, increase productivity, drive innovation while leveraging the scale and flexibility of the cloud. However, such gains come with risks and challenges in the areas of data security, privacy, and governance. In this talk we cover how enterprises can overcome governance and security obstacles to leverage these new advances that the cloud can provide to ease the management of their data lakes in the cloud. We will also show how the enterprise can have consistent governance and security controls in the cloud for their ephemeral analytic workloads in a multi-cluster cloud environment without sacrificing any of the data security and privacy/compliance needs that their business context demands. Additionally, we will outline some use cases and patterns as well as best practices to rationally manage such a multi-cluster data lake infrastructure in the cloud.
Speaker:
Jeff Sposetti, Product Management, Hortonworks
Unlock Hadoop Success with Cloudera Navigator OptimizerCloudera, Inc.
Cloudera Navigator Optimizer analyzes existing SQL workloads to provide instant insights into your workloads and turns that into an intelligent optimization strategy so you can unlock peak performance and efficiency with Hadoop.
Enterprises have been using both Big Data and Cloud Computing technologies for years. Until recently, the two have not been combined. Now the agility and efficiency benefits of self-service elastic infrastructure are being extended to Big Data initiatives – whether on-premises or in the public cloud.
This session at Hadoop Summit in San Jose, California (June 2016) discusses the emerging category of Big-Data-as-a-Service (BDaaS) - representing the intersection of Big Data and Cloud Computing.
In this session, Kris Applegate (Cloud and Big Data Solution Architect at Dell) and Thomas Phelan (Co-Founder and Chief Architect at BlueData) outlined the following:
- Innovations that paved the way for Big-Data-as-a-Service
- Definition and categories of Big-Data-as-a-Service
- Key considerations for Big-Data-as-a-Service in the enterprise, including public cloud or on-premises deployment options
A video replay can also be found here: https://youtu.be/_ucPoTKuj8Q
Big data journey to the cloud rohit pujari 5.30.18Cloudera, Inc.
We hope this session was valuable in teaching you more about Cloudera Enterprise on AWS, and how fast and easy it is to deploy a modern data management platform—in your cloud and on your terms.
Protect your Private Data in your Hadoop Clusters with ORC Column EncryptionDataWorks Summit
Fine-grained data protection at a column level in data lake environments has become a mandatory requirement to demonstrate compliance with multiple local and international regulations across many industries today. ORC is a self-describing type-aware columnar file format designed for Hadoop workloads that provides optimized streaming reads, but with integrated support for finding required rows quickly. In this talk, we will outline the progress made in Apache community for adding fine-grained column level encryption natively into ORC format that will also provide capabilities to mask or redact data on write while protecting sensitive column metadata such as statistics to avoid information leakage. The column encryption capabilities will be fully compatible with Hadoop Key Management Server (KMS) and use the KMS to manage master keys providing the additional flexibility to use and manage keys per column centrally. An end to end scenario that demonstrates how this capability can be leveraged will be also demonstrated.
Securing Data in Hybrid on-premise and Cloud Environments using Apache RangerDataWorks Summit
Companies are increasingly moving to the cloud to store and process data. One of the challenges companies have is in securing data across hybrid environments with easy way to centrally manage policies. In this session, we will talk through how companies can use Apache Ranger to protect access to data both in on-premise as well as in cloud environments. We will go into details into the challenges of hybrid environment and how Ranger can solve it. We will also talk through how companies can further enhance the security by leveraging Ranger to anonymize or tokenize data while moving into the cloud and de-anonymize dynamically using Apache Hive, Apache Spark or when accessing data from cloud storage systems. We will also deep dive into the Ranger’s integration with AWS S3, AWS Redshift and other cloud native systems. We will wrap it up with an end to end demo showing how policies can be created in Ranger and used to manage access to data in different systems, anonymize or de-anonymize data and track where data is flowing.
Startup Case Study: Leveraging the Broad Hadoop Ecosystem to Develop World-Fi...DataWorks Summit
Back in 2014, our team set out to change the way the world exchanges and collaborates with data. Our vision was to build a single tenant environment for multiple organisations to securely share and consume data. And we did just that, leveraging multiple Hadoop technologies to help our infrastructure scale quickly and securely.
Today Data Republic’s technology delivers a trusted platform for hundreds of enterprise level companies to securely exchange, commercialise and collaborate with large datasets.
Join Head of Engineering, Juan Delard de Rigoulières and Senior Solutions Architect, Amin Abbaspour as they share key lessons from their team’s journey with Hadoop:
* How a startup leveraged a clever combination of Hadoop technologies to build a secure data exchange platform
* How Hadoop technologies helped us deliver key solutions around governance, security and controls of data and metadata
* An evaluation on the maturity and usefulness of some Hadoop technologies in our environment: Hive, HDFS, Spark, Ranger, Atlas, Knox, Kylin: we've use them all extensively.
* Our bold approach to expose APIs directly to end users; as well as the challenges, learning and code we created in the process
* Learnings from the front-line: How our team coped with code changes, performance tuning, issues and solutions while building our data exchange
Whether you’re an enterprise level business or a start-up looking to scale - this case study discussion offers behind-the-scenes lessons and key tips when using Hadoop technologies to manage data governance and collaboration in the cloud.
Speakers:
Juan Delard De Rigoulieres, Head of Engineering, Data Republic Pty Ltd
Amin Abbaspour, Senior Solutions Architect, Data Republic
Part 2: Cloudera’s Operational Database: Unlocking New Benefits in the CloudCloudera, Inc.
3 Things to Learn About:
*On-premises versus the cloud
*Design & benefits of real-time operational data in the cloud
*Best practices and architectural considerations
Treat your enterprise data lake indigestion: Enterprise ready security and go...DataWorks Summit
Most enterprises with large data lakes today are flying blind when it comes to the extent to which they can understand how the data in their data lakes is organized, accessed, and utilized to create real business value. Couple this with the need to democratize data, enterprises often realize they have created a data swamp loaded with all kinds of data assets without any curation and without appropriate security controls hoping that developers and analysts can responsibly collaborate to generate insights. In this talk we will provide a broad overview of how organizations can use open source frameworks such as Apache Ranger and Apache Knox to secure their data lakes and Apache Atlas to effectively provide open metadata and governance services for Hadoop ecosystem. We will provide an overview of the new features that have been added in each of these Apache projects recently and how enterprises can leverage these new features to build a robust security and governance model for their data lakes.
Speaker
Owen O'Malley, Co-Founder & Technical Fellow, Hortonworks
A deep dive into running data analytic workloads in the cloudCloudera, Inc.
Aishwarya Venkataraman, Jason Wang, Mala Ramakrishnan, Stefan Salandy, and Vinithra Varadharajan lead a deep dive into running data analytic workloads in a managed service capacity in the public cloud and highlight cloud infrastructure best practices.
Discover the origins of big data, discuss existing and new projects, share common use cases for those projects, and explain how you can modernize your architecture using data analytics, data operations, data engineering and data science.
Big Data Fundamentals is your prerequisite to building a modern platform for machine learning and analytics optimized for the cloud.
We’ll close out with a live Q&A with some of our technical experts as well.
Stretch your brain with a packed agenda:
Open source software
Data storage
Data ingestion
Data analytics
Data engineering
IoT and life after Lambda architectures
Data science
Cybersecurity
Cluster management
Big data in the cloud
Success stories
Simplifying Hadoop with RecordService, A Secure and Unified Data Access Path ...Cloudera, Inc.
SFHUG presentation from February 2, 2016. One of the key values of the Hadoop ecosystem is its flexibility. There is a myriad of components that make up this ecosystem, allowing Hadoop to tackle otherwise intractable problems. However, having so many components provides a significant integration, implementation, and usability burden. Features that ought to work in all the components often require sizable per-component effort to ensure correctness across the stack.
Lenni Kuff explores RecordService, a new solution to this problem that provides an API to read data from Hadoop storage managers and return them as canonical records. This eliminates the need for components to support individual file formats, handle security, perform auditing, and implement sophisticated IO scheduling and other common processing that is at the bottom of any computation.
Lenni discusses the architecture of the service and the integration work done for MapReduce and Spark. Many existing applications on those frameworks can take advantage of the service with little to no modification. Lenni demonstrates how this provides fine grain (column level and row level) security, through Sentry integration, and improves performance for existing MapReduce and Spark applications by up to 5×. Lenni concludes by discussing how this architecture can enable significant future improvements to the Hadoop ecosystem.
About the speaker: Lenni Kuff is an engineering manager at Cloudera. Before joining Cloudera, he worked at Microsoft on a number of projects including SQL Server storage engine, SQL Azure, and Hadoop on Azure. Lenni graduated from the University of Wisconsin-Madison with degrees in computer science and computer engineering.
Intel and Cloudera: Accelerating Enterprise Big Data SuccessCloudera, Inc.
The data center has gone through several inflection points in the past decades: adoption of Linux, migration from physical infrastructure to virtualization and Cloud, and now large-scale data analytics with Big Data and Hadoop.
Please join us to learn about how Cloudera and Intel are jointly innovating through open source software to enable Hadoop to run best on IA (Intel Architecture) and to foster the evolution of a vibrant Big Data ecosystem.
Today enterprises desire to move more and more of their data lakes to the cloud to help them execute faster, increase productivity, drive innovation while leveraging the scale and flexibility of the cloud. However, such gains come with risks and challenges in the areas of data security, privacy, and governance. In this talk we cover how enterprises can overcome governance and security obstacles to leverage these new advances that the cloud can provide to ease the management of their data lakes in the cloud. We will also show how the enterprise can have consistent governance and security controls in the cloud for their ephemeral analytic workloads in a multi-cluster cloud environment without sacrificing any of the data security and privacy/compliance needs that their business context demands. Additionally, we will outline some use cases and patterns as well as best practices to rationally manage such a multi-cluster data lake infrastructure in the cloud.
Speaker:
Jeff Sposetti, Product Management, Hortonworks
Unlock Hadoop Success with Cloudera Navigator OptimizerCloudera, Inc.
Cloudera Navigator Optimizer analyzes existing SQL workloads to provide instant insights into your workloads and turns that into an intelligent optimization strategy so you can unlock peak performance and efficiency with Hadoop.
Enterprises have been using both Big Data and Cloud Computing technologies for years. Until recently, the two have not been combined. Now the agility and efficiency benefits of self-service elastic infrastructure are being extended to Big Data initiatives – whether on-premises or in the public cloud.
This session at Hadoop Summit in San Jose, California (June 2016) discusses the emerging category of Big-Data-as-a-Service (BDaaS) - representing the intersection of Big Data and Cloud Computing.
In this session, Kris Applegate (Cloud and Big Data Solution Architect at Dell) and Thomas Phelan (Co-Founder and Chief Architect at BlueData) outlined the following:
- Innovations that paved the way for Big-Data-as-a-Service
- Definition and categories of Big-Data-as-a-Service
- Key considerations for Big-Data-as-a-Service in the enterprise, including public cloud or on-premises deployment options
A video replay can also be found here: https://youtu.be/_ucPoTKuj8Q
Big data journey to the cloud rohit pujari 5.30.18Cloudera, Inc.
We hope this session was valuable in teaching you more about Cloudera Enterprise on AWS, and how fast and easy it is to deploy a modern data management platform—in your cloud and on your terms.
Protect your Private Data in your Hadoop Clusters with ORC Column EncryptionDataWorks Summit
Fine-grained data protection at a column level in data lake environments has become a mandatory requirement to demonstrate compliance with multiple local and international regulations across many industries today. ORC is a self-describing type-aware columnar file format designed for Hadoop workloads that provides optimized streaming reads, but with integrated support for finding required rows quickly. In this talk, we will outline the progress made in Apache community for adding fine-grained column level encryption natively into ORC format that will also provide capabilities to mask or redact data on write while protecting sensitive column metadata such as statistics to avoid information leakage. The column encryption capabilities will be fully compatible with Hadoop Key Management Server (KMS) and use the KMS to manage master keys providing the additional flexibility to use and manage keys per column centrally. An end to end scenario that demonstrates how this capability can be leveraged will be also demonstrated.
Securing Data in Hybrid on-premise and Cloud Environments using Apache RangerDataWorks Summit
Companies are increasingly moving to the cloud to store and process data. One of the challenges companies have is in securing data across hybrid environments with easy way to centrally manage policies. In this session, we will talk through how companies can use Apache Ranger to protect access to data both in on-premise as well as in cloud environments. We will go into details into the challenges of hybrid environment and how Ranger can solve it. We will also talk through how companies can further enhance the security by leveraging Ranger to anonymize or tokenize data while moving into the cloud and de-anonymize dynamically using Apache Hive, Apache Spark or when accessing data from cloud storage systems. We will also deep dive into the Ranger’s integration with AWS S3, AWS Redshift and other cloud native systems. We will wrap it up with an end to end demo showing how policies can be created in Ranger and used to manage access to data in different systems, anonymize or de-anonymize data and track where data is flowing.
Startup Case Study: Leveraging the Broad Hadoop Ecosystem to Develop World-Fi...DataWorks Summit
Back in 2014, our team set out to change the way the world exchanges and collaborates with data. Our vision was to build a single tenant environment for multiple organisations to securely share and consume data. And we did just that, leveraging multiple Hadoop technologies to help our infrastructure scale quickly and securely.
Today Data Republic’s technology delivers a trusted platform for hundreds of enterprise level companies to securely exchange, commercialise and collaborate with large datasets.
Join Head of Engineering, Juan Delard de Rigoulières and Senior Solutions Architect, Amin Abbaspour as they share key lessons from their team’s journey with Hadoop:
* How a startup leveraged a clever combination of Hadoop technologies to build a secure data exchange platform
* How Hadoop technologies helped us deliver key solutions around governance, security and controls of data and metadata
* An evaluation on the maturity and usefulness of some Hadoop technologies in our environment: Hive, HDFS, Spark, Ranger, Atlas, Knox, Kylin: we've use them all extensively.
* Our bold approach to expose APIs directly to end users; as well as the challenges, learning and code we created in the process
* Learnings from the front-line: How our team coped with code changes, performance tuning, issues and solutions while building our data exchange
Whether you’re an enterprise level business or a start-up looking to scale - this case study discussion offers behind-the-scenes lessons and key tips when using Hadoop technologies to manage data governance and collaboration in the cloud.
Speakers:
Juan Delard De Rigoulieres, Head of Engineering, Data Republic Pty Ltd
Amin Abbaspour, Senior Solutions Architect, Data Republic
Part 2: Cloudera’s Operational Database: Unlocking New Benefits in the CloudCloudera, Inc.
3 Things to Learn About:
*On-premises versus the cloud
*Design & benefits of real-time operational data in the cloud
*Best practices and architectural considerations
1. John F. Zuniga
114 Villa Park Drive ♦ Hubert, North Carolina 28539 ♦ (703) 725-7206 ♦ zunigajf@gmail.com
PROFESSIONAL SUMMARY
Expert Information Technology Systems Manager/Engineer. Works well autonomously and collectively. Implemented
two server operating systemmigrations and 1 Technical Refresh projects for assigned area. Interacted with up to 20
entities, as well as customers, users,individual users,VIP’s and groups. Meticulous, organized, quick learner, flexible,
multitasker, and goal oriented. Well-versed in Microsoft Systems and Virtualization Technologies. Bilingual English/
Spanish.
KEY QUALIFICATIONS
Top Secret/SCI Clearance
20 years IT Experience
Bilingual: English/Spanish
CCENT Certified
Certified Ethical Hacker
A+, Network +, Security +, CTT+ Certified
MCSE 2003 with Security, MCSA 2003 with
Exchange.
70-640 MCTS: Configuring Windows Server
2008 Active Directory
PROFESSIONAL EXPERIENCE
INFORMATION TECHNOLOGY
Experience configuring, maintaining, troubleshooting common services such as DHCP, DNS, Active Directory,
IIS, File, and Print.
Planned, designed,and rapidly implemented a comprehensive plan to migrate HQMC's application hosting
environment from the Navy Annex (a physical environment) into the Pentagon (a virtual environment).
Navy Annex (FOB 2) SIPRNet Migration
o Worked with a small team to plan, design, document, and brief migration efforts for more than 21
separate IT systems/applications from FOB 2 to the Pentagon.
o Operations included:
Converting the majority of systems to a virtual environment utilizing VSphere hypervisors on
IBM and HP Blade servers.
Migrating existing customer applications from Windows Server 2000 and 2003 to 2008R2.
Detailed architectural diagrams of individual systems and networks.
Various client meetings and coordination efforts to meet requirements.
HQI Domain Migration
o VMware Upgrade (3.5 to 4.1)
Upgraded 30 Physical Hypervisors (HP and Dell Blade Servers).
Installed 31 Additional hosts to support the network expansion.
NAS installation and configuration.
o Domain Services
Active Directory (Created the domain hierarchy and infrastructure)
DNS (Installed DNS as part of the DC installation and created DNS records as required)
DHCP (Created the scopes,reservations,exclusions and various option)
File (Created a file server as a data repository. Soft quotas were implemented)
Print (Created a print server to support print services)
Failover sites (Made certain that COOP sites were operational and that failover services were
running).
o Customer Systems supported
SQL (Installed SQL on four servers to support all of the HQI application requiring it)
IIS (Installed IIS on six servers to support web services for the HQI environment).
SMTP relay (Installed an SMTP relay since an Exchange Server was not authorized).
SharePoint environment design and implementation:
o 3 SharePoint sites/environments (Production, Staging, and Testing)
o 45 Servers, 15 per site (Provided the servers and support as needed to the SharePoint administrators ).
Managed Hosting environment for HQMC customers
o 61 physicalservers (VSphere Hypervisors)
o 116 Virtual Machines
o Server Templates management and maintenance
o New systems request fulfillment as required per the Operations Officer.
2. John F. Zuniga Page 2
INFORMATION SECURITY
Advised the Regional Information Technology (RIT) Center Network Defense Manageron emerging computer
network attack and exploitation (CNA/CNE) issues and remediation techniques.
Monitored systems throughout the Pacific Area (Korea, Iwakuni, Okinawa and Hawaii), reported findings to
higher headquarters and provided guidance and assistance to ensure compliance with Cyber Security policies and
procedures to each department.
Validated elevated privilege account requests and made approval recommendations.
Enforced Information Assurance (IA) policies and procedures as established by the U.S. Marine Corps and
Department of Defense (DoD).
Accounted for 3,500 computers and servers,conducted network vulnerability and risk assessments on RIT
Western Pacific systems and initiated appropriate steps to mitigate security vulnerabilities.
Supervised the compliance of over 200 security Operational Directives for all networks in Okinawa, Korea, and
Iwakuni, Japan.
Oversaw the monitoring of Host Based Systems Security (HBSS) ensuring 95% compliance.
Prepared the organization for Command Cyber Readiness Inspection (CCRI) in the following areas: Traditional
Security, Program of Records (POR), printers, video teleconference equipment, and digital senders.Conducted
follow-up inspections.
Trained and mentored 45 junior Marines to promote professionaldevelopment and improve job proficiency
ADMINISTRATION AND MANAGEMENT
Oversaw the execution of 12 Corrective Maintenance Service Requests totaling $1Million of serialized Principal
End Items (PEI), as well as over 70 SL-3 Service Requests (SR’s) valuing over $362K, allowing the Cyber
Department to be operationally ready.
Supervised the inspection, induction, and execution of all required Preventive Maintenance Checks and Service
Requests ensuring all vehicles were properly maintained and available.
Inducted 30 pieces of Calibration equipment into the maintenance cycle, by staggering the induction times of the
gear to avoid operational interruption.
Instructed the Cyber Maintenance Office in the proper method of inspection, induction, and verification of
equipment requiring related maintenance actions.
Assisted with the review of maintenance records to ensure the accuracy of record keeping.
Successfully planned and managed student network training classrooms.
Revised the Network Operations Center Training objectives for applicability.
As the Training Supervisor, I maintained the training network in the NMCI classrooms up and running without
interruption of service and with fault tolerance.
WORK HISTORY
United States Marine Corps August 1996 - Present
Maintenance Manager, Camp Lejeune, NC July 2015-Present
Network Defense Manager, Okinawa, Japan August 2012-July 2015
Operations Manager and Plans Engineer, The Pentagon, Washington,D.C. June 2009-August 2012
Training Manager/Supervisor/Student, Norfolk, VA June 2007-June 2009
EDUCATION
Bachelor of Science, Computer Network Security
University of Maryland University College
Adelphi, Maryland, 2016
Associate of Arts, General Studies
American Military University
Manassas,Virginia, 2008
TRAINING
VMWare Courses,2011 and 2015
Communication Planners Course, 2010
Navy's Advance Network Analyst School, Honor Graduate 97.3% GPA, 2009
Data Systems Manager’s Course, 2005
3. John F. Zuniga Page 3
CERTIFICATIONS
Security+ Certified Professional Microsoft Certified Professional (MCP 2008)
Network+ Certified Professional Securing Windows 7 for System Administrators
A+ Certified Professional Microsoft Technology Associate (3)
CTT+ Certified Professional Army RETINA scannervirtual training course
Certified Ethical Hacker DISA HBSS 4.5 Administrator
Microsoft Systems Administrator 2003 (MCSA
2003 with Exchange)
ACAS Introduction (Vulnerability and
Compliance
Microsoft Systems Engineer 2003 (MCSE 2003
with Security)
Communication Planners Course (Marine Corps)
ITILv3 Foundation certified
Microsoft Certified Technology Specialist
(MCTS 2008)
Soccer Coaching Licenses (F, G, E)
AWARDS
Marine Corps Good Conduct Medal (6) – Awarded for exemplary conduct, awarded every 3 years
Navy and Marine Corps Commendation Medal (1) – Network Migration of the Navy Annex to the Pentagon
Navy and Marine Corps Achievement Medal (2) – Awarded for Hurricane Katrina evacuation network transition, and for
excellence in Aviation Supply.
Military Outstanding Volunteer Service Medal – Coaching and Community Service; Habitat for Humanity
Certificate of Commendation (1) –Superior Performance as a Flight Line Helicopter Mechanic (Marine of the Quarter)