The document provides steps for setting up a Hadoop cluster using Cloudera Manager, including downloading and running the Cloudera Manager installer, logging into the Cloudera Manager Admin Console, using Cloudera Manager to automate the installation and configuration of CDH, specifying cluster node and repository information, installing software components on cluster nodes, reviewing installation logs, installing parcels, setting up the cluster and roles, configuring databases and clients, and completing the Cloudera cluster installation process.
This document discusses the APIs and extensibility features of Cloudera Manager. It provides an overview of the Cloudera Manager API introduced in version 4.0, which allows programmatic access to cluster operations and monitoring data. It also discusses how the API has been used by various customers and partners for tasks like installation/deployment, monitoring, and alerting integration. The document outlines Cloudera Manager's monitoring capabilities using the tsquery language and provides examples. Finally, it covers new service extensibility features introduced in Cloudera Manager 5.
Hadoop cluster setup by using cloudera managerCo-graph Inc.
1. The document discusses setting up a Hadoop cluster using Cloudera Manager. It outlines the requirements for Cloudera Manager, including supported operating systems, browsers, databases, and Java versions.
2. The process of setting up the Hadoop cluster with Cloudera Manager is described. It involves installing the Cloudera Manager installer, logging into the admin console, specifying hosts, and configuring services.
3. Flume is introduced as a data collection tool that can run independently or on Hadoop clusters. Its important settings - sources, channels, and sinks - are defined along with example types for each.
This document provides instructions for installing a single node Hadoop cluster on Ubuntu Linux. It describes downloading and configuring Hadoop, Java, and SSH. Configuration files like core-site.xml and hdfs-site.xml are edited. Directions are given for formatting HDFS, starting daemons like NameNode and DataNode, and starting/stopping the Hadoop cluster. The goal is to set up a single node Hadoop 2.2.0 installation for experimentation and testing.
This document discusses using Ansible for automation across various IT use cases. It provides examples of how Ansible can be used for infrastructure orchestration, patch management, network automation, and managing various network devices and platforms including Cisco, Palo Alto, and Fortinet devices. It also provides examples of playbooks for tasks like provisioning servers, configuring firewall rules, and checking for configuration drift. Overall it promotes Ansible as a simple, agentless, and extensible automation tool that can automate technologies across IT operations, DevOps, security and more.
How to scheduled jobs in a cloudera cluster without oozieTiago Simões
This presentation, it’s for everyone that is looking for an oozie alternative to scheduled jobs in a secured Cloudera Cluster.With this, you will be able to add and configure the Airflow Service an manage it with in Cloudera Manager.
How to implement a gdpr solution in a cloudera architectureTiago Simões
Since the implementation of GDPR regulation, all data processors across the world have been struggling to be GDPR compliant and also deal with the new reality in Big Data, that data is constantly drifting and mutating.
In this presentation, the approach will be:
Cloudera architecture
No additional financial cost
Masking & Encrypting
The document provides steps for setting up a Hadoop cluster using Cloudera Manager, including downloading and running the Cloudera Manager installer, logging into the Cloudera Manager Admin Console, using Cloudera Manager to automate the installation and configuration of CDH, specifying cluster node and repository information, installing software components on cluster nodes, reviewing installation logs, installing parcels, setting up the cluster and roles, configuring databases and clients, and completing the Cloudera cluster installation process.
This document discusses the APIs and extensibility features of Cloudera Manager. It provides an overview of the Cloudera Manager API introduced in version 4.0, which allows programmatic access to cluster operations and monitoring data. It also discusses how the API has been used by various customers and partners for tasks like installation/deployment, monitoring, and alerting integration. The document outlines Cloudera Manager's monitoring capabilities using the tsquery language and provides examples. Finally, it covers new service extensibility features introduced in Cloudera Manager 5.
Hadoop cluster setup by using cloudera managerCo-graph Inc.
1. The document discusses setting up a Hadoop cluster using Cloudera Manager. It outlines the requirements for Cloudera Manager, including supported operating systems, browsers, databases, and Java versions.
2. The process of setting up the Hadoop cluster with Cloudera Manager is described. It involves installing the Cloudera Manager installer, logging into the admin console, specifying hosts, and configuring services.
3. Flume is introduced as a data collection tool that can run independently or on Hadoop clusters. Its important settings - sources, channels, and sinks - are defined along with example types for each.
This document provides instructions for installing a single node Hadoop cluster on Ubuntu Linux. It describes downloading and configuring Hadoop, Java, and SSH. Configuration files like core-site.xml and hdfs-site.xml are edited. Directions are given for formatting HDFS, starting daemons like NameNode and DataNode, and starting/stopping the Hadoop cluster. The goal is to set up a single node Hadoop 2.2.0 installation for experimentation and testing.
This document discusses using Ansible for automation across various IT use cases. It provides examples of how Ansible can be used for infrastructure orchestration, patch management, network automation, and managing various network devices and platforms including Cisco, Palo Alto, and Fortinet devices. It also provides examples of playbooks for tasks like provisioning servers, configuring firewall rules, and checking for configuration drift. Overall it promotes Ansible as a simple, agentless, and extensible automation tool that can automate technologies across IT operations, DevOps, security and more.
How to scheduled jobs in a cloudera cluster without oozieTiago Simões
This presentation, it’s for everyone that is looking for an oozie alternative to scheduled jobs in a secured Cloudera Cluster.With this, you will be able to add and configure the Airflow Service an manage it with in Cloudera Manager.
How to implement a gdpr solution in a cloudera architectureTiago Simões
Since the implementation of GDPR regulation, all data processors across the world have been struggling to be GDPR compliant and also deal with the new reality in Big Data, that data is constantly drifting and mutating.
In this presentation, the approach will be:
Cloudera architecture
No additional financial cost
Masking & Encrypting
Accumulo includes a remarkable breadth of testing frameworks, which helps to ensure its correctness, performance, robustness, and protection of your vital data. This presentation takes you on a tour from Accumulo's basic unit testing up through performance and scalability testing exercised on running clusters. Learn the extent to which Accumulo is put through its paces before it is released, and get ideas for how you can similarly enhance testing of your own code.
Find this talk and others at http://www.slideshare.net/AccumuloSummit.
This document discusses PowerShell Desired State Configuration (DSC) and provides steps to set up DSC in different environments. It begins with an overview of DSC and its architecture. It then describes how to set up a native on-premises DSC push server with steps to configure the client and server. Additional sections explain how to set up a native on-premises DSC pull server and how to use the Azure Automation DSC extension to configure virtual machines in Azure.
The document discusses troubleshooting CloudStack. It covers troubleshooting for CloudStack developers and administrators. For developers, it discusses error codes, debugging tips, system virtual machine troubleshooting and port usage. For administrators, it discusses installation, configuration, log analysis, important parameters, best practices, reusing hypervisors and the CloudStack database. The document also provides references and information on getting involved in the CloudStack community.
This document provides an overview of installing Apache Hadoop and Spark from scratch. It discusses prerequisites like servers, operating systems, and Hadoop distributions. Key Hadoop components like YARN, HDFS, MapReduce and Ambari are introduced. Apache Spark is summarized as a fast, general-purpose cluster computing system. The installation process is walked through, including using Ambari to deploy Hadoop services across master and slave nodes. Additional steps like adding nodes, automation with Ansible, and zero-installation options are also covered.
Troubleshooting Strategies for CloudStack Installations by Kirk Kosinski buildacloud
The document provides troubleshooting strategies for CloudStack installations, including network issues, security groups, host connectivity, virtual routers, templates, and log analysis. It discusses common problems such as VLAN misconfigurations, security group rules not being applied, hosts showing in the "avoid set", template preparation errors, and exceptions in the logs. It emphasizes analyzing logs at the management server, hypervisor, and job levels to find the root cause of failures.
Presented at Apache CloudStack Collabration Conference 2014, Denver, CO.
Talked about recently Virtual Router improvement in CloudStack 4.4 to unify and significantly speed up VR command execution, as well as some further improvement ideas.
Enhancing OpenStack FWaaS for real world applicationopenstackindia
This document discusses enhancing the performance and capabilities of OpenStack's firewall-as-a-service (FWaaS). It proposes improvements to FWaaS performance by validating firewall rules and distributing rules only to relevant routers. It also discusses scheduling firewall rules based on time and enabling logging of firewall packets to help with debugging, threat analysis, and rule tuning. The document outlines integrating firewall logging with OpenStack using IPTables rules and collecting logs in a centralized server for analysis. Finally, it proposes extending the Horizon UI to make firewall logs accessible to tenants.
CAPS: What's best for deploying and managing OpenStack? Chef vs. Ansible vs. ...Daniel Krook
Presentation at the OpenStack Summit in Tokyo, Japan on October 29, 2015.
http://sched.co/49vI
This talk will cover the pros and cons of four different OpenStack deployment mechanisms. Puppet, Chef, Ansible, and Salt for OpenStack all claim to make it much easier to configure and maintain hundreds of OpenStack deployment resources. With the advent of large-scale, highly available OpenStack deployments spread across multiple global regions, the choice of which deployment methodology to use has become more and more relevant.
Beyond the initial day-one deployment, when it comes to the day-two and beyond questions of updating and upgrading existing OpenStack deployments, it becomes all the more important choose the right tool.
Come join the Bluebox and IBM team to discuss the pros and cons of these approaches. We look at each of these four tools in depth, explore their design and function, and determine which scores higher than others to address your particular deployment needs.
Daniel Krook - Senior Software Engineer, Cloud and Open Source Technologies, IBM
Paul Czarkowski - Cloud Engineer at Blue Box, an IBM company
Daniel Krook - Senior Software Engineer, Cloud and Open Source Technologies, IBM
The document discusses Spark job failures and Spark/YARN architecture. It describes a Spark job failure due to a task failing 4 times with a NumberFormatException when parsing a string. It then explains that Spark jobs are divided into stages made up of tasks, and the entire job fails if a stage fails. The document also provides an overview of the Spark and YARN architectures, showing how Spark jobs are submitted to and run via the YARN resource manager.
Whats new in Cloudstack 4.11 - behind the headlinesShapeBlue
ShapeBlue is a company that specializes in deploying the Apache CloudStack cloud infrastructure software. The document discusses ShapeBlue and its VP of Technology, Paul Angus. It provides details on Paul's experience and areas of expertise, which include being a global authority on CloudStack and cloud infrastructure design. It also lists some of ShapeBlue's customers, which include large companies like Autodesk, SAP, and British Telecom.
This document provides an overview of troubleshooting CloudStack components including general troubleshooting techniques, secondary storage VMs, console proxy VMs, and virtual routers. It discusses examining log files, enabling debug logging, and using tools like MySQL Workbench. Examples are given for troubleshooting issues like insufficient capacity and calculating primary storage allocation. System VMs each have specific log files and services to check. The presentation aims to help support engineers effectively troubleshoot CloudStack environments.
This document discusses using Chef cookbooks to deploy OpenStack. It provides an overview of Chef principles and how they enable infrastructure as code. It then demonstrates how to use roles and run lists to install and configure OpenStack components like Nova on single-machine and multi-node environments. Finally, it outlines ongoing work to enhance OpenStack support and integration using Chef.
Guide - Migrating from Heroku to AWS using CloudFormationRob Linton
Step by step guide to migrating from Heroku to Amazon AWS using AWS CloudFormation.
Presented at the Australian AWS User Group in Melbourne at the October Meetup.
Red Hat Openstack and Ceph Meetup, Pune | 28th NOV 2015
Sadique Puthen, Principal Technical Support Engineer at Red Hat, Inc., gave an introduction to Red Hat Openstack (RDO) and its components. He discussed how Openstack provides infrastructure services like compute (Nova), storage (Cinder, Swift), networking (Neutron), and database (Trove) as a service. He also covered Openstack deployment options like Packstack, TripleO, and Ironic for bare metal provisioning. The meetup aimed to introduce Openstack components and services and their role in providing infrastructure as a service through a cloud platform.
Chef for OpenStack: OpenStack Spring Summit 2013Matt Ray
This document provides an overview of using Chef to deploy and manage OpenStack. It discusses why Chef is useful for infrastructure as code and its declarative interface. The document outlines the current state of the Chef for OpenStack project, including contributors, available cookbooks, and roadmap. It promotes the project as a way to collaboratively deploy OpenStack in a standardized, automated way and reduce fragmentation.
1. The document discusses how OpenStack can be used to build private and hybrid clouds for enterprises using open source technology free from vendor lock-in.
2. It provides examples of how OpenStack can enable continuous software delivery, cloud-enable applications, and provide IT as a service while reducing reliance on proprietary virtualization.
3. Asdtech offers turnkey OpenStack services including consultancy, cloud setup, custom development, migration, support and training to help enterprises orchestrate their existing infrastructure or build new clouds.
A brief introduction to YARN: how and why it came into existence and how it fits together with this thing called Hadoop.
Focus given to architecture, availability, resource management and scheduling, migration from MR1 to MR2, job history and logging, interfaces, and applications.
Compute node HA - current upstream developmentAdam Spiers
Short presentation made for OpenStack London "Tokyo Aftermath" meetup, on current upstream activity in the OpenStack HA developers community around high availability for compute nodes.
OpenStack Deployment with Chef Workshop at the 2013 Hong Kong OpenStack Summit. Co-presented with Justin Shepherd, a Private Cloud Architect from Rackspace.
Webinar: Productionizing Hadoop: Lessons Learned - 20101208Cloudera, Inc.
Key insights in installing, configuring, and running Hadoop and Cloudera's Distribution for Hadoop in production. These are lessons learned from Cloudera helping organizations move to a productions state with Hadoop.
Hadoop is quickly becoming the standard for data management for enterprises. But Enterprise buyers have more demanding requirements for their systems beyond what the early adopters needed. Join us for our 2-part webinar series and learn about our new advancements within Cloudera Enterprise, the Platform for Big Data, with new capabilities that extend our leadership in delivering what organizations require.
Cloudera set the industry standard with Cloudera Manager, the first end-to-end management application for Apache Hadoop. Now, it is extending that lead with the release of Cloudera Manager 4.5, which delivers expanded capabilities designed to simplify the management and adoption of Hadoop.
This presentation will show you how Cloudera Manager 4.5 allows you to:
- perform rolling platform upgrades
- consistently meet or exceed SLAs and RTOs through simplified management and process automation
- easily correlate and visualize metrics through intuitive and interactive charts
- manage heterogeneous clusters
- better integrate with existing enterprise IT management tools via SNMP
…and much more
Accumulo includes a remarkable breadth of testing frameworks, which helps to ensure its correctness, performance, robustness, and protection of your vital data. This presentation takes you on a tour from Accumulo's basic unit testing up through performance and scalability testing exercised on running clusters. Learn the extent to which Accumulo is put through its paces before it is released, and get ideas for how you can similarly enhance testing of your own code.
Find this talk and others at http://www.slideshare.net/AccumuloSummit.
This document discusses PowerShell Desired State Configuration (DSC) and provides steps to set up DSC in different environments. It begins with an overview of DSC and its architecture. It then describes how to set up a native on-premises DSC push server with steps to configure the client and server. Additional sections explain how to set up a native on-premises DSC pull server and how to use the Azure Automation DSC extension to configure virtual machines in Azure.
The document discusses troubleshooting CloudStack. It covers troubleshooting for CloudStack developers and administrators. For developers, it discusses error codes, debugging tips, system virtual machine troubleshooting and port usage. For administrators, it discusses installation, configuration, log analysis, important parameters, best practices, reusing hypervisors and the CloudStack database. The document also provides references and information on getting involved in the CloudStack community.
This document provides an overview of installing Apache Hadoop and Spark from scratch. It discusses prerequisites like servers, operating systems, and Hadoop distributions. Key Hadoop components like YARN, HDFS, MapReduce and Ambari are introduced. Apache Spark is summarized as a fast, general-purpose cluster computing system. The installation process is walked through, including using Ambari to deploy Hadoop services across master and slave nodes. Additional steps like adding nodes, automation with Ansible, and zero-installation options are also covered.
Troubleshooting Strategies for CloudStack Installations by Kirk Kosinski buildacloud
The document provides troubleshooting strategies for CloudStack installations, including network issues, security groups, host connectivity, virtual routers, templates, and log analysis. It discusses common problems such as VLAN misconfigurations, security group rules not being applied, hosts showing in the "avoid set", template preparation errors, and exceptions in the logs. It emphasizes analyzing logs at the management server, hypervisor, and job levels to find the root cause of failures.
Presented at Apache CloudStack Collabration Conference 2014, Denver, CO.
Talked about recently Virtual Router improvement in CloudStack 4.4 to unify and significantly speed up VR command execution, as well as some further improvement ideas.
Enhancing OpenStack FWaaS for real world applicationopenstackindia
This document discusses enhancing the performance and capabilities of OpenStack's firewall-as-a-service (FWaaS). It proposes improvements to FWaaS performance by validating firewall rules and distributing rules only to relevant routers. It also discusses scheduling firewall rules based on time and enabling logging of firewall packets to help with debugging, threat analysis, and rule tuning. The document outlines integrating firewall logging with OpenStack using IPTables rules and collecting logs in a centralized server for analysis. Finally, it proposes extending the Horizon UI to make firewall logs accessible to tenants.
CAPS: What's best for deploying and managing OpenStack? Chef vs. Ansible vs. ...Daniel Krook
Presentation at the OpenStack Summit in Tokyo, Japan on October 29, 2015.
http://sched.co/49vI
This talk will cover the pros and cons of four different OpenStack deployment mechanisms. Puppet, Chef, Ansible, and Salt for OpenStack all claim to make it much easier to configure and maintain hundreds of OpenStack deployment resources. With the advent of large-scale, highly available OpenStack deployments spread across multiple global regions, the choice of which deployment methodology to use has become more and more relevant.
Beyond the initial day-one deployment, when it comes to the day-two and beyond questions of updating and upgrading existing OpenStack deployments, it becomes all the more important choose the right tool.
Come join the Bluebox and IBM team to discuss the pros and cons of these approaches. We look at each of these four tools in depth, explore their design and function, and determine which scores higher than others to address your particular deployment needs.
Daniel Krook - Senior Software Engineer, Cloud and Open Source Technologies, IBM
Paul Czarkowski - Cloud Engineer at Blue Box, an IBM company
Daniel Krook - Senior Software Engineer, Cloud and Open Source Technologies, IBM
The document discusses Spark job failures and Spark/YARN architecture. It describes a Spark job failure due to a task failing 4 times with a NumberFormatException when parsing a string. It then explains that Spark jobs are divided into stages made up of tasks, and the entire job fails if a stage fails. The document also provides an overview of the Spark and YARN architectures, showing how Spark jobs are submitted to and run via the YARN resource manager.
Whats new in Cloudstack 4.11 - behind the headlinesShapeBlue
ShapeBlue is a company that specializes in deploying the Apache CloudStack cloud infrastructure software. The document discusses ShapeBlue and its VP of Technology, Paul Angus. It provides details on Paul's experience and areas of expertise, which include being a global authority on CloudStack and cloud infrastructure design. It also lists some of ShapeBlue's customers, which include large companies like Autodesk, SAP, and British Telecom.
This document provides an overview of troubleshooting CloudStack components including general troubleshooting techniques, secondary storage VMs, console proxy VMs, and virtual routers. It discusses examining log files, enabling debug logging, and using tools like MySQL Workbench. Examples are given for troubleshooting issues like insufficient capacity and calculating primary storage allocation. System VMs each have specific log files and services to check. The presentation aims to help support engineers effectively troubleshoot CloudStack environments.
This document discusses using Chef cookbooks to deploy OpenStack. It provides an overview of Chef principles and how they enable infrastructure as code. It then demonstrates how to use roles and run lists to install and configure OpenStack components like Nova on single-machine and multi-node environments. Finally, it outlines ongoing work to enhance OpenStack support and integration using Chef.
Guide - Migrating from Heroku to AWS using CloudFormationRob Linton
Step by step guide to migrating from Heroku to Amazon AWS using AWS CloudFormation.
Presented at the Australian AWS User Group in Melbourne at the October Meetup.
Red Hat Openstack and Ceph Meetup, Pune | 28th NOV 2015
Sadique Puthen, Principal Technical Support Engineer at Red Hat, Inc., gave an introduction to Red Hat Openstack (RDO) and its components. He discussed how Openstack provides infrastructure services like compute (Nova), storage (Cinder, Swift), networking (Neutron), and database (Trove) as a service. He also covered Openstack deployment options like Packstack, TripleO, and Ironic for bare metal provisioning. The meetup aimed to introduce Openstack components and services and their role in providing infrastructure as a service through a cloud platform.
Chef for OpenStack: OpenStack Spring Summit 2013Matt Ray
This document provides an overview of using Chef to deploy and manage OpenStack. It discusses why Chef is useful for infrastructure as code and its declarative interface. The document outlines the current state of the Chef for OpenStack project, including contributors, available cookbooks, and roadmap. It promotes the project as a way to collaboratively deploy OpenStack in a standardized, automated way and reduce fragmentation.
1. The document discusses how OpenStack can be used to build private and hybrid clouds for enterprises using open source technology free from vendor lock-in.
2. It provides examples of how OpenStack can enable continuous software delivery, cloud-enable applications, and provide IT as a service while reducing reliance on proprietary virtualization.
3. Asdtech offers turnkey OpenStack services including consultancy, cloud setup, custom development, migration, support and training to help enterprises orchestrate their existing infrastructure or build new clouds.
A brief introduction to YARN: how and why it came into existence and how it fits together with this thing called Hadoop.
Focus given to architecture, availability, resource management and scheduling, migration from MR1 to MR2, job history and logging, interfaces, and applications.
Compute node HA - current upstream developmentAdam Spiers
Short presentation made for OpenStack London "Tokyo Aftermath" meetup, on current upstream activity in the OpenStack HA developers community around high availability for compute nodes.
OpenStack Deployment with Chef Workshop at the 2013 Hong Kong OpenStack Summit. Co-presented with Justin Shepherd, a Private Cloud Architect from Rackspace.
Webinar: Productionizing Hadoop: Lessons Learned - 20101208Cloudera, Inc.
Key insights in installing, configuring, and running Hadoop and Cloudera's Distribution for Hadoop in production. These are lessons learned from Cloudera helping organizations move to a productions state with Hadoop.
Hadoop is quickly becoming the standard for data management for enterprises. But Enterprise buyers have more demanding requirements for their systems beyond what the early adopters needed. Join us for our 2-part webinar series and learn about our new advancements within Cloudera Enterprise, the Platform for Big Data, with new capabilities that extend our leadership in delivering what organizations require.
Cloudera set the industry standard with Cloudera Manager, the first end-to-end management application for Apache Hadoop. Now, it is extending that lead with the release of Cloudera Manager 4.5, which delivers expanded capabilities designed to simplify the management and adoption of Hadoop.
This presentation will show you how Cloudera Manager 4.5 allows you to:
- perform rolling platform upgrades
- consistently meet or exceed SLAs and RTOs through simplified management and process automation
- easily correlate and visualize metrics through intuitive and interactive charts
- manage heterogeneous clusters
- better integrate with existing enterprise IT management tools via SNMP
…and much more
The document discusses installing Cloudera Hadoop (CDH 4) on Ubuntu 12.04 LTS. It provides an overview of Hadoop and its components. It then outlines the installation steps for Cloudera Hadoop which include preparing the system by installing prerequisites like OpenSSH, configuring password-less SSH and sudo, editing the host file, installing MySQL and the JDBC connector, and downloading and running the Cloudera Manager installer.
Henry Robinson works at Cloudera on distributed data collection tools like Flume and ZooKeeper. Cloudera provides support for Hadoop and open source projects like Flume. Flume is a scalable and configurable system for collecting large amounts of log and event data into Hadoop from diverse sources. It allows defining flexible data flows that can reliably move data between collection agents and storage systems.
Livy is an open source REST service for interacting with and managing Spark contexts and jobs. It allows clients to submit Spark jobs via REST, monitor their status, and retrieve results. Livy manages long-running Spark contexts in a cluster and supports running multiple independent contexts simultaneously from different clients. It provides client APIs in Java, Scala, and soon Python to interface with the Livy REST endpoints for submitting, monitoring, and retrieving results of Spark jobs.
The document discusses Cloudera Manager's APIs and extensibility features. It describes how the CM API introduced in version 4 allows programmatic access to cluster operations and monitoring data. It provides examples of how the API has been used to integrate CM with installation/deployment tools and for monitoring and alerting. The document also discusses CM's support for custom metrics charts using tsquery and how service extensibility introduced in version 5 allows for non-CDH services and ISV applications to be managed through CM.
Cloudera User Group Chicago - Cloudera Manager: APIs & ExtensibilityClouderaUserGroups
This document provides an overview of Cloudera Manager APIs and extensibility. It discusses how the Cloudera Manager API, introduced in version 4.0, allows programmatic access to cluster operations and monitoring information. It provides examples of integration with the API for installation/deployment and monitoring/alerting. It also covers the tsquery language for custom metrics and monitoring, and new capabilities in Cloudera Manager 5 for user-defined triggers/alarms and service extensibility.
How Big Data Can Enable Analytics from the Cloud (Technical Workshop)Cloudera, Inc.
In this workshop, we will look outside the box and help expand the problem space to include issues you may not have thought were possible before Big Data. From Near Real Time (NRT) recommendation engines, loan applications to churn detection, Big Data is answering new questions and providing organisations with a competitive edge through revenue increase, cost savings and risk mitigation. We will take a special look at the role the Cloud can play in elevating your analytics environment. We will discuss real world examples of how Big Data answers these questions and does it at a lower cost outlay.
Cloudera GoDataFest Deploying Cloudera in the CloudGoDataDriven
This document discusses deploying Cloudera in the cloud using Cloudera Director and Cloudera Altus. Cloudera Director is a tool for managing the lifecycle of long-running Cloudera clusters in cloud environments, while Cloudera Altus is a platform-as-a-service for transient data engineering workloads like ETL and machine learning. The document provides an example of using Cloudera Altus for data processing and Cloudera Director for interactive querying, and demonstrates Altus and Director in a scenario of a data analyst using them to analyze website sales data.
This presentation provides an overview of the BlueData integration with Cloudera Manager. With this integration, customers of our BlueData EPIC software platform can leverage the power of Cloudera Manager for end-to-end Hadoop systems management and administration.
When the BlueData EPIC platform provisions a virtual CDH cluster, Cloudera Manager can be provisioned as well – so you can easily deploy, manage, monitor and perform diagnostics on your Hadoop cluster. Our customers can take advantage of the Cloudera Manager GUI to monitor their cluster, troubleshoot issues, and administer their Hadoop deployment.
Learn more about BlueData at http://www.bluedata.com
Cloudera training: secure your Cloudera clusterCloudera, Inc.
The first and possibly most important task you perform when you deploy your Cloudera cluster is securing it. Get it wrong and you may inadvertently and unknowingly have introduced a risk to the business. Getting it right eventually leaves you looking back at wasted efforts and false starts. So how do you get it right first time?
Cloudera Director: Unlock the Full Potential of Hadoop in the CloudCloudera, Inc.
Cloud environments are increasingly becoming a popular deployment option for Hadoop. Enterprises can take advantage of the added flexibility and elasticity of the cloud for both long-running clusters, temporary deployments or for spikey workloads. However, as more and more users choose cloud environments for critical Hadoop workloads, they are often forced to compromise on key aspects of their data platform.
Cloudera Director enables the full fidelity of the Enterprise Data Hub in the cloud, without compromises. Announced with the recent 5.2 release, Cloudera Director is the simple, reliable way to deploy and scale Hadoop in the cloud, while maintaining an open and neutral platform with enterprise-grade capabilities.
During this webinar, Tushar Shanbhag, Director of Product Management, will look at why Hadoop cloud environments are becoming so popular and some of the challenges around Hadoop in the cloud. He will then provide an in-depth overview of Cloudera Director, its key features, and how it alleviates these common challenges. Finally, he will discuss some key use cases and provide insight into what’s next for Cloudera and Hadoop in the cloud.
Cloudera Altus: Big Data in der Cloud einfach gemachtCloudera, Inc.
Neueste Studien zeigen, dass Data Scientisten und Analysten bis zu 80% ihrer Zeit dafür nutzen, Daten zu reinigen und vorzubereiten.
Eine ohnehin schon zeitaufwändige Aufgabe kann in der Cloud noch weiter erschwert werden, da das Cluster Management und Operations die Komplexität noch erhöhen.
Nutzer wünschen sich daher, diese komplexen Workflows zu vereinheitlichen und zu vereinfachen.
Um Big Data und Machine Learning Initiativen voranzutreiben, benötigen Unternehmen eine skalierbare und überall verfügbare Plattform. Diese muss Self-Service ermöglichen und Datensilos eliminieren.
Cloudera Navigator provides integrated data governance and security for Hadoop. It includes features for metadata management, auditing, data lineage, encryption, and policy-based data governance. KeyTrustee is Cloudera's key management server that integrates with hardware security modules to securely manage encryption keys. Together, Navigator and KeyTrustee allow users to classify data, audit usage, and encrypt data at rest and in transit to meet security and compliance needs.
Data platform modernization with Databricks.pptxCalvinSim10
The document discusses modernizing a healthcare organization's data platform from version 1.0 to 2.0 using Azure Databricks. Version 1.0 used Azure HDInsight (HDI) which was challenging to scale and maintain. It presented performance issues and lacked integrations. Version 2.0 with Databricks will provide improved scalability, cost optimization, governance, and ease of use through features like Delta Lake, Unity Catalog, and collaborative notebooks. This will help address challenges faced by consumers, data engineers, and the client.
Cloud-Native Machine Learning: Emerging Trends and the Road AheadDataWorks Summit
Big data platforms are being asked to support an ever increasing range of workloads and compute environments, including large-scale machine learning and public and private clouds. In this talk, we will discuss some emerging capabilities around cloud-native machine learning and data engineering, including running machine learning and Spark workloads directly on Kubernetes, and share our vision of the road ahead for ML and AI in the cloud.
Introducing Cloudera Director at Big Data BashAndrei Savu
My slide deck for Big Data Bash. This is a quick introduction on Cloudera Director and it ends with a list of open questions around some interesting future problems we are planning to work on.
The document discusses running Hadoop on the cloud using Cloudera Director. It begins with an introduction of the speaker and Cloudera Director. Several common architectural patterns for running Hadoop in the cloud are presented, including using object storage and running short-term ETL/modeling clusters versus long-term analytics clusters. The presentation envisions a future with a more portable, self-service, self-healing, and granularly secure experience for managing Hadoop in the cloud.
One Hadoop, Multiple Clouds - NYC Big Data MeetupAndrei Savu
The slide deck I presented at NYC Big Data Meetup just before Strata + Hadoop World 2015. It goes into details on what's different about running Hadoop in the cloud, main use case and some lessons learned from working with customers.
The document discusses Cloudera Director, a tool for deploying and managing Hadoop clusters across multiple public clouds. It begins with an introduction of the speaker and outlines some common architectures for running Hadoop in the cloud. Key points covered include cluster lifecycle management, elasticity, high availability, backup/disaster recovery, and a vision for the future of portable, self-service Hadoop experiences across clouds.
Leveraging the cloud for analytics and machine learning 1.29.19Cloudera, Inc.
Learn how organizations are deriving unique customer insights, improving product and services efficiency, and reducing business risk with a modern big data architecture powered by Cloudera on Azure. In this webinar, you see how fast and easy it is to deploy a modern data management platform—in your cloud, on your terms.
This document provides an overview of Apache Hadoop security, both historically and what is currently available and planned for the future. It discusses how Hadoop security is different due to benefits like combining previously siloed data and tools. The four areas of enterprise security - perimeter, access, visibility, and data protection - are reviewed. Specific security capabilities like Kerberos authentication, Apache Sentry role-based access control, Cloudera Navigator auditing and encryption, and HDFS encryption are summarized. Planned future enhancements are also mentioned like attribute-based access controls and improved encryption capabilities.
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.
Optimized Data Management with Cloudera 5.7: Understanding data value with Cl...Cloudera, Inc.
Across all industries, organizations are embracing the promise of Apache Hadoop to store and analyze data of all types, at larger volumes than ever before possible. But to tap into the true value of this data, organizations need to manage this data and its subsequent metadata to understand its context, see how it’s changing, and take actions on it.
Cloudera Navigator is the only integrated data management and governance for Hadoop and is designed to do exactly this. With Cloudera 5.7, we have further expanded the capabilities in Cloudera Navigator to make it even easier to understand your data and maintain metadata consistency as it moves through Hadoop.
Apache Accumulo is a distributed key-value store developed by the National Security Agency. It is based on Google's BigTable and stores data in tables containing sorted key-value pairs. Accumulo uses a master/tablet server architecture and stores data in HDFS files. Data can be queried using scanners or loaded using MapReduce. Accumulo works well with the Hadoop ecosystem and its installation is simplified using complete Hadoop distributions like Cloudera.
Similar to Cloudera User Group SF - Cloudera Manager: APIs & Extensibility (20)
Conversational agents, or chatbots, are increasingly used to access all sorts of services using natural language. While open-domain chatbots - like ChatGPT - can converse on any topic, task-oriented chatbots - the focus of this paper - are designed for specific tasks, like booking a flight, obtaining customer support, or setting an appointment. Like any other software, task-oriented chatbots need to be properly tested, usually by defining and executing test scenarios (i.e., sequences of user-chatbot interactions). However, there is currently a lack of methods to quantify the completeness and strength of such test scenarios, which can lead to low-quality tests, and hence to buggy chatbots.
To fill this gap, we propose adapting mutation testing (MuT) for task-oriented chatbots. To this end, we introduce a set of mutation operators that emulate faults in chatbot designs, an architecture that enables MuT on chatbots built using heterogeneous technologies, and a practical realisation as an Eclipse plugin. Moreover, we evaluate the applicability, effectiveness and efficiency of our approach on open-source chatbots, with promising results.
In the realm of cybersecurity, offensive security practices act as a critical shield. By simulating real-world attacks in a controlled environment, these techniques expose vulnerabilities before malicious actors can exploit them. This proactive approach allows manufacturers to identify and fix weaknesses, significantly enhancing system security.
This presentation delves into the development of a system designed to mimic Galileo's Open Service signal using software-defined radio (SDR) technology. We'll begin with a foundational overview of both Global Navigation Satellite Systems (GNSS) and the intricacies of digital signal processing.
The presentation culminates in a live demonstration. We'll showcase the manipulation of Galileo's Open Service pilot signal, simulating an attack on various software and hardware systems. This practical demonstration serves to highlight the potential consequences of unaddressed vulnerabilities, emphasizing the importance of offensive security practices in safeguarding critical infrastructure.
Taking AI to the Next Level in Manufacturing.pdfssuserfac0301
Read Taking AI to the Next Level in Manufacturing to gain insights on AI adoption in the manufacturing industry, such as:
1. How quickly AI is being implemented in manufacturing.
2. Which barriers stand in the way of AI adoption.
3. How data quality and governance form the backbone of AI.
4. Organizational processes and structures that may inhibit effective AI adoption.
6. Ideas and approaches to help build your organization's AI strategy.
Driving Business Innovation: Latest Generative AI Advancements & Success StorySafe Software
Are you ready to revolutionize how you handle data? Join us for a webinar where we’ll bring you up to speed with the latest advancements in Generative AI technology and discover how leveraging FME with tools from giants like Google Gemini, Amazon, and Microsoft OpenAI can supercharge your workflow efficiency.
During the hour, we’ll take you through:
Guest Speaker Segment with Hannah Barrington: Dive into the world of dynamic real estate marketing with Hannah, the Marketing Manager at Workspace Group. Hear firsthand how their team generates engaging descriptions for thousands of office units by integrating diverse data sources—from PDF floorplans to web pages—using FME transformers, like OpenAIVisionConnector and AnthropicVisionConnector. This use case will show you how GenAI can streamline content creation for marketing across the board.
Ollama Use Case: Learn how Scenario Specialist Dmitri Bagh has utilized Ollama within FME to input data, create custom models, and enhance security protocols. This segment will include demos to illustrate the full capabilities of FME in AI-driven processes.
Custom AI Models: Discover how to leverage FME to build personalized AI models using your data. Whether it’s populating a model with local data for added security or integrating public AI tools, find out how FME facilitates a versatile and secure approach to AI.
We’ll wrap up with a live Q&A session where you can engage with our experts on your specific use cases, and learn more about optimizing your data workflows with AI.
This webinar is ideal for professionals seeking to harness the power of AI within their data management systems while ensuring high levels of customization and security. Whether you're a novice or an expert, gain actionable insights and strategies to elevate your data processes. Join us to see how FME and AI can revolutionize how you work with data!
Essentials of Automations: Exploring Attributes & Automation ParametersSafe Software
Building automations in FME Flow can save time, money, and help businesses scale by eliminating data silos and providing data to stakeholders in real-time. One essential component to orchestrating complex automations is the use of attributes & automation parameters (both formerly known as “keys”). In fact, it’s unlikely you’ll ever build an Automation without using these components, but what exactly are they?
Attributes & automation parameters enable the automation author to pass data values from one automation component to the next. During this webinar, our FME Flow Specialists will cover leveraging the three types of these output attributes & parameters in FME Flow: Event, Custom, and Automation. As a bonus, they’ll also be making use of the Split-Merge Block functionality.
You’ll leave this webinar with a better understanding of how to maximize the potential of automations by making use of attributes & automation parameters, with the ultimate goal of setting your enterprise integration workflows up on autopilot.
Monitoring and Managing Anomaly Detection on OpenShift.pdfTosin Akinosho
Monitoring and Managing Anomaly Detection on OpenShift
Overview
Dive into the world of anomaly detection on edge devices with our comprehensive hands-on tutorial. This SlideShare presentation will guide you through the entire process, from data collection and model training to edge deployment and real-time monitoring. Perfect for those looking to implement robust anomaly detection systems on resource-constrained IoT/edge devices.
Key Topics Covered
1. Introduction to Anomaly Detection
- Understand the fundamentals of anomaly detection and its importance in identifying unusual behavior or failures in systems.
2. Understanding Edge (IoT)
- Learn about edge computing and IoT, and how they enable real-time data processing and decision-making at the source.
3. What is ArgoCD?
- Discover ArgoCD, a declarative, GitOps continuous delivery tool for Kubernetes, and its role in deploying applications on edge devices.
4. Deployment Using ArgoCD for Edge Devices
- Step-by-step guide on deploying anomaly detection models on edge devices using ArgoCD.
5. Introduction to Apache Kafka and S3
- Explore Apache Kafka for real-time data streaming and Amazon S3 for scalable storage solutions.
6. Viewing Kafka Messages in the Data Lake
- Learn how to view and analyze Kafka messages stored in a data lake for better insights.
7. What is Prometheus?
- Get to know Prometheus, an open-source monitoring and alerting toolkit, and its application in monitoring edge devices.
8. Monitoring Application Metrics with Prometheus
- Detailed instructions on setting up Prometheus to monitor the performance and health of your anomaly detection system.
9. What is Camel K?
- Introduction to Camel K, a lightweight integration framework built on Apache Camel, designed for Kubernetes.
10. Configuring Camel K Integrations for Data Pipelines
- Learn how to configure Camel K for seamless data pipeline integrations in your anomaly detection workflow.
11. What is a Jupyter Notebook?
- Overview of Jupyter Notebooks, an open-source web application for creating and sharing documents with live code, equations, visualizations, and narrative text.
12. Jupyter Notebooks with Code Examples
- Hands-on examples and code snippets in Jupyter Notebooks to help you implement and test anomaly detection models.
"Frontline Battles with DDoS: Best practices and Lessons Learned", Igor IvaniukFwdays
At this talk we will discuss DDoS protection tools and best practices, discuss network architectures and what AWS has to offer. Also, we will look into one of the largest DDoS attacks on Ukrainian infrastructure that happened in February 2022. We'll see, what techniques helped to keep the web resources available for Ukrainians and how AWS improved DDoS protection for all customers based on Ukraine experience
For the full video of this presentation, please visit: https://www.edge-ai-vision.com/2024/06/how-axelera-ai-uses-digital-compute-in-memory-to-deliver-fast-and-energy-efficient-computer-vision-a-presentation-from-axelera-ai/
Bram Verhoef, Head of Machine Learning at Axelera AI, presents the “How Axelera AI Uses Digital Compute-in-memory to Deliver Fast and Energy-efficient Computer Vision” tutorial at the May 2024 Embedded Vision Summit.
As artificial intelligence inference transitions from cloud environments to edge locations, computer vision applications achieve heightened responsiveness, reliability and privacy. This migration, however, introduces the challenge of operating within the stringent confines of resource constraints typical at the edge, including small form factors, low energy budgets and diminished memory and computational capacities. Axelera AI addresses these challenges through an innovative approach of performing digital computations within memory itself. This technique facilitates the realization of high-performance, energy-efficient and cost-effective computer vision capabilities at the thin and thick edge, extending the frontier of what is achievable with current technologies.
In this presentation, Verhoef unveils his company’s pioneering chip technology and demonstrates its capacity to deliver exceptional frames-per-second performance across a range of standard computer vision networks typical of applications in security, surveillance and the industrial sector. This shows that advanced computer vision can be accessible and efficient, even at the very edge of our technological ecosystem.
Digital Banking in the Cloud: How Citizens Bank Unlocked Their MainframePrecisely
Inconsistent user experience and siloed data, high costs, and changing customer expectations – Citizens Bank was experiencing these challenges while it was attempting to deliver a superior digital banking experience for its clients. Its core banking applications run on the mainframe and Citizens was using legacy utilities to get the critical mainframe data to feed customer-facing channels, like call centers, web, and mobile. Ultimately, this led to higher operating costs (MIPS), delayed response times, and longer time to market.
Ever-changing customer expectations demand more modern digital experiences, and the bank needed to find a solution that could provide real-time data to its customer channels with low latency and operating costs. Join this session to learn how Citizens is leveraging Precisely to replicate mainframe data to its customer channels and deliver on their “modern digital bank” experiences.
Skybuffer SAM4U tool for SAP license adoptionTatiana Kojar
Manage and optimize your license adoption and consumption with SAM4U, an SAP free customer software asset management tool.
SAM4U, an SAP complimentary software asset management tool for customers, delivers a detailed and well-structured overview of license inventory and usage with a user-friendly interface. We offer a hosted, cost-effective, and performance-optimized SAM4U setup in the Skybuffer Cloud environment. You retain ownership of the system and data, while we manage the ABAP 7.58 infrastructure, ensuring fixed Total Cost of Ownership (TCO) and exceptional services through the SAP Fiori interface.
Generating privacy-protected synthetic data using Secludy and MilvusZilliz
During this demo, the founders of Secludy will demonstrate how their system utilizes Milvus to store and manipulate embeddings for generating privacy-protected synthetic data. Their approach not only maintains the confidentiality of the original data but also enhances the utility and scalability of LLMs under privacy constraints. Attendees, including machine learning engineers, data scientists, and data managers, will witness first-hand how Secludy's integration with Milvus empowers organizations to harness the power of LLMs securely and efficiently.
How information systems are built or acquired puts information, which is what they should be about, in a secondary place. Our language adapted accordingly, and we no longer talk about information systems but applications. Applications evolved in a way to break data into diverse fragments, tightly coupled with applications and expensive to integrate. The result is technical debt, which is re-paid by taking even bigger "loans", resulting in an ever-increasing technical debt. Software engineering and procurement practices work in sync with market forces to maintain this trend. This talk demonstrates how natural this situation is. The question is: can something be done to reverse the trend?
Ivanti’s Patch Tuesday breakdown goes beyond patching your applications and brings you the intelligence and guidance needed to prioritize where to focus your attention first. Catch early analysis on our Ivanti blog, then join industry expert Chris Goettl for the Patch Tuesday Webinar Event. There we’ll do a deep dive into each of the bulletins and give guidance on the risks associated with the newly-identified vulnerabilities.
Dandelion Hashtable: beyond billion requests per second on a commodity serverAntonios Katsarakis
This slide deck presents DLHT, a concurrent in-memory hashtable. Despite efforts to optimize hashtables, that go as far as sacrificing core functionality, state-of-the-art designs still incur multiple memory accesses per request and block request processing in three cases. First, most hashtables block while waiting for data to be retrieved from memory. Second, open-addressing designs, which represent the current state-of-the-art, either cannot free index slots on deletes or must block all requests to do so. Third, index resizes block every request until all objects are copied to the new index. Defying folklore wisdom, DLHT forgoes open-addressing and adopts a fully-featured and memory-aware closed-addressing design based on bounded cache-line-chaining. This design offers lock-free index operations and deletes that free slots instantly, (2) completes most requests with a single memory access, (3) utilizes software prefetching to hide memory latencies, and (4) employs a novel non-blocking and parallel resizing. In a commodity server and a memory-resident workload, DLHT surpasses 1.6B requests per second and provides 3.5x (12x) the throughput of the state-of-the-art closed-addressing (open-addressing) resizable hashtable on Gets (Deletes).
Connector Corner: Seamlessly power UiPath Apps, GenAI with prebuilt connectorsDianaGray10
Join us to learn how UiPath Apps can directly and easily interact with prebuilt connectors via Integration Service--including Salesforce, ServiceNow, Open GenAI, and more.
The best part is you can achieve this without building a custom workflow! Say goodbye to the hassle of using separate automations to call APIs. By seamlessly integrating within App Studio, you can now easily streamline your workflow, while gaining direct access to our Connector Catalog of popular applications.
We’ll discuss and demo the benefits of UiPath Apps and connectors including:
Creating a compelling user experience for any software, without the limitations of APIs.
Accelerating the app creation process, saving time and effort
Enjoying high-performance CRUD (create, read, update, delete) operations, for
seamless data management.
Speakers:
Russell Alfeche, Technology Leader, RPA at qBotic and UiPath MVP
Charlie Greenberg, host