36 Apache courses delivered Live Online

Duration 5 Days 30 CPD hours This course is intended for Linux Professional Institute Certification (LPIC-2) 202 training is suitable for individuals with roles of: System administrator Network administrator Technician DevOps Overview Upon successful completion of this course, students will be able to: configure BIND to function as an authoritative and as a recursive, caching-only DNS server install and configure a web server install and configure a proxy server, including access policies, authentication and resource usage set up a Samba server for various clients configure a DHCP server configure PAM to support authentication using various available methods perform queries and updates to an LDAP server configure a basic OpenLDAP server including knowledge of LDIF format and essential access controls manage an e-mail server, including the configuration of e-mail aliases, e-mail quotas and virtual e-mail domains configure an FTP server for anonymous downloads and uploads receive security alerts from various sources, install, configure and run intrusion detection systems and apply security patches and bugfixes configure a VPN (Virtual Private Network) and create secure point-to-point or site-to-site connections. This course prepares students to take the 202 exam of the LPI level 2 certification. To gain LPIC-2 certification, an individual should have an active LPIC-1 certification. Domain Name Server Basic DNS server configuration Create and maintain DNS zones Securing a DNS server HTTP Services Basic Apache configuration Apache configuration for HTTPS Implementing Squid as a caching proxy Implementing Nginx as a web server and a reverse proxy File Sharing Samba Server Configuration NFS Server Configuration Network Client Management DHCP configuration PAM authentication LDAP client usage Configuring an OpenLDAP server E-Mail Services Using e-mail servers Managing E-Mail Delivery Managing Mailbox Access System Security Configuring a router Managing FTP servers Secure shell (SSH) Security tasks OpenVPN Additional course details: Nexus Humans Linux Professional Institute Certification (LPIC-2) 202 training program is a workshop that presents an invigorating mix of sessions, lessons, and masterclasses meticulously crafted to propel your learning expedition forward. This immersive bootcamp-style experience boasts interactive lectures, hands-on labs, and collaborative hackathons, all strategically designed to fortify fundamental concepts. Guided by seasoned coaches, each session offers priceless insights and practical skills crucial for honing your expertise. Whether you're stepping into the realm of professional skills or a seasoned professional, this comprehensive course ensures you're equipped with the knowledge and prowess necessary for success. While we feel this is the best course for the Linux Professional Institute Certification (LPIC-2) 202 course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.

Duration 4 Days 24 CPD hours This course is intended for This course is designed for data analysts, business intelligence specialists, developers, system architects, and database administrators. Overview Skills gained in this training include:The features that Pig, Hive, and Impala offer for data acquisition, storage, and analysisThe fundamentals of Apache Hadoop and data ETL (extract, transform, load), ingestion, and processing with HadoopHow Pig, Hive, and Impala improve productivity for typical analysis tasksJoining diverse datasets to gain valuable business insightPerforming real-time, complex queries on datasets Cloudera University?s four-day data analyst training course focusing on Apache Pig and Hive and Cloudera Impala will teach you to apply traditional data analytics and business intelligence skills to big data. Hadoop Fundamentals The Motivation for Hadoop Hadoop Overview Data Storage: HDFS Distributed Data Processing: YARN, MapReduce, and Spark Data Processing and Analysis: Pig, Hive, and Impala Data Integration: Sqoop Other Hadoop Data Tools Exercise Scenarios Explanation Introduction to Pig What Is Pig? Pig?s Features Pig Use Cases Interacting with Pig Basic Data Analysis with Pig Pig Latin Syntax Loading Data Simple Data Types Field Definitions Data Output Viewing the Schema Filtering and Sorting Data Commonly-Used Functions Processing Complex Data with Pig Storage Formats Complex/Nested Data Types Grouping Built-In Functions for Complex Data Iterating Grouped Data Multi-Dataset Operations with Pig Techniques for Combining Data Sets Joining Data Sets in Pig Set Operations Splitting Data Sets Pig Troubleshoot & Optimization Troubleshooting Pig Logging Using Hadoop?s Web UI Data Sampling and Debugging Performance Overview Understanding the Execution Plan Tips for Improving the Performance of Your Pig Jobs Introduction to Hive & Impala What Is Hive? What Is Impala? Schema and Data Storage Comparing Hive to Traditional Databases Hive Use Cases Querying with Hive & Impala Databases and Tables Basic Hive and Impala Query Language Syntax Data Types Differences Between Hive and Impala Query Syntax Using Hue to Execute Queries Using the Impala Shell Data Management Data Storage Creating Databases and Tables Loading Data Altering Databases and Tables Simplifying Queries with Views Storing Query Results Data Storage & Performance Partitioning Tables Choosing a File Format Managing Metadata Controlling Access to Data Relational Data Analysis with Hive & Impala Joining Datasets Common Built-In Functions Aggregation and Windowing Working with Impala How Impala Executes Queries Extending Impala with User-Defined Functions Improving Impala Performance Analyzing Text and Complex Data with Hive Complex Values in Hive Using Regular Expressions in Hive Sentiment Analysis and N-Grams Conclusion Hive Optimization Understanding Query Performance Controlling Job Execution Plan Bucketing Indexing Data Extending Hive SerDes Data Transformation with Custom Scripts User-Defined Functions Parameterized Queries Choosing the Best Tool for the Job Comparing MapReduce, Pig, Hive, Impala, and Relational Databases Which to Choose?

Duration 5 Days 30 CPD hours This course is intended for Linux system administrators, site reliability engineers, and other IT professionals with some Ansible experience who are interested in learning how to manage and automate the deployment, configuration, and operation of key network services included with Red Hat Enterprise Linux 8. Overview Provide key network services using software included with Red Hat Enterprise Linux 8, including DNS with Unbound and BIND9, DHCP and DHCPv6, client e-mail transmission, printing service, NFS and SMB protocol file sharing, SQL database service with MariaDB, and web services using Apache HTTPD, nginx, Varnish, and HAProxy. Configure advanced networking for server use cases, including device teaming. Use Red Hat Ansible Engine to automate the manual deployment and configuration tasks covered in this course. Learn how to configure, manage, and scale key services used in the data center Red Hat Services Management and Automation (RH358) is designed for IT professionals with some experience managing Linux© systems and want to learn more about how to manage and deploy network services included with Red Hat© Enterprise Linux which are particularly important in the modern IT data center. You will learn how to install, configure, and manage basic configurations of these services manually, and then use Red Hat Ansible© Engine to automate your work in a scalable, repeatable manner. This course is based on Red Hat Ansible Engine 2.9 and Red Hat Enterprise Linux 8.1. 1 - Manage network services Discuss and review key tools and skills needed to manage network services. 2 - Configure link aggregation Improve the redundancy or throughput of network connections of servers by configuring Linux network teaming between multiple network interfaces. 3 - Manage DNS and DNS servers Explain the operation of DNS service, troubleshoot DNS issues, and configure servers to act as a DNS caching nameserver or as an authoritative name server. 4 - Manage DHCP and IP address assignment Explain and configure services used for IPv4 and IPv6 address assignment including DHCP, DHCPv6, and SLAAC. 5 - Manage printers and printing files Configure systems to print to a network printer that supports IPP Everywhere, as well as manage existing printer queues. 6 - Configure email transmission Discuss how mail servers operate, then configure a server to use system tools and Postfix to send email messages through an outbound mail relay. 7 - Configure MariaDB SQL databases Discuss the basic operation of SQL-based relational databases, perform basic SQL queries for troubleshooting, and be able to set up a simple MariaDB database service. 8 - Configure web servers Provide web content from Apache HTTPD or Nginx web servers, then configure them with virtual hosts and TLS-based encryption. 9 - Optimize web server traffic Improve performance of your web servers by using Varnish to cache static content being served and HAProxy to terminate TLS connections and balance load between servers. 10 - Provide file-based network storage Deliver simple file-based network shares to clients using the NFS and SMB protocols. 11 - Access block-based network storage Configure iSCSI initiators on your servers to access block-based storage devices provided by network storage arrays or Ceph storage clusters.

Duration 5 Days 30 CPD hours This course is intended for This is an introductory-level systems administration course geared for Systems Administrators and users who wish to learn how to how to install, configure and maintain an Enterprise Linux system in a networked environment. Overview This course is about 50% lab to lecture ratio, combining expert instructor-led discussions with practical hands-on skills that emphasize current techniques, best practices and standards. Working in this hands-on lab environment, guided by our expert practitioner, attendees will explore Installing the Linux operating system and configuring peripherals Performing and modifying startup and shutdown processes Configuring and maintaining basic networking services Creating and maintaining system users and groups Understanding and administering file permissions on directories and regular files Planning and creating disk partitions and file systems Performing maintenance on file systems Identifying and managing Linux processes Automating tasks with cron Performing backups and restoration of files Working with system log files Troubleshooting system problems Analyzing and taking measures to increase system performance Configuring file sharing with NFS Configuring Samba for file sharing with the Windows clients Setting up a basic Web server Understanding the components for setting up a LAMP server Implementing basic security measures Linux System Administration is a comprehensive hands-on course that teaches students how to install, configure and maintain an Enterprise Linux system in a networked environment. This lab-intensive class explores core administrative tasks such as: creating and managing users, creating and maintaining file systems, determining and implementing security measures and performing software installation and package management. Linux networking topics include installing and supporting SSH, NFS, Samba and the Apache Web server. Students will explore common security issues, as well as several tools, such as the PAM modules that help secure the operating system and network environment. Upon successful completion of this course, students will be prepared to maintain Linux systems in a networked business environment. Although the course includes installing and configuring a CentOS 7 / RHEL 7 Linux system, much of the course content also applies to Oracle, Ubuntu, Scientific and other current versions of mainstream Linux distributions. Labs include user and group maintenance, system backups and restoration, software management, administration tasks automation, file system creation and maintenance, managing remote access, working with cron, and configuring basic file sharing and Web services, as well as working with system logging utilities such as rsyslog and much more. System Administration Overview UNIX, Linux and Open Source Duties of the System Administrator Superusers and the Root Login Sharing Superuser Privileges with Others (su and sudo Commands) TCP/IP Networking Fundamentals Online Help Installation and Configuration Planning: Hardware and Software Considerations Site Planning Installation Methods and Types Installation Classes Partitions Logical Volume Manager - LVM File System Overview Swap Partition Considerations Other Partition Considerations The Linux Boot Loader: grub Software Package Selection Adding and Configuring Peripherals Printers Graphics Controllers Basic Networking Configuration Booting to Recovery Mode Booting and Shutting Down Linux Boot Sequence The systemd Daemon The systemctl Command Targets vs. Run Levels Modifying a Target Service Unit Scripts Changing System States Booting into Rescue Mode Shutdown Commands Managing Software and Devices Identifying Software Packages Using rpm to Manage Software Using yum to Manage Software Installing and Removing Software Identifying Devices Displaying Device and System Information (PCI, USB) Plug and Play Devices Device Configuration Tools Managing Users and Groups Setting Policies User File Management The /etc/passwd file The /etc/shadow file The /etc/group file The /etc/gshadow file Adding Users Modifying User Accounts Deleting User Accounts Working with Groups Setting User Environments Login Configuration Files The Linux File System Filesystem Types Conventional Directory Structure Mounting a File System The /etc/fstab File Special Files (Device Files) Inodes Hard File Links Soft File Links Creating New File Systems with mkfs The lost+found Directory Repairing File Systems with fsck The Journaling Attribute File and Disk Management Tools Linux File Security File Permissions Directory Permissions Octal Representation Changing Permissions Setting Default Permissions Access Control Lists (ACLs) The getfacl and setfacl commands SUID Bit SGID Bit The Sticky Bit Controlling Processes Characteristics of Processes Parent-Child Relationship Examining Running Processes Background Processes Controlling Processes Signaling Processes Killing Processes Automating Processes cron and crontab at and batch System Processes (Daemons) Working with the Linux Kernel Linux Kernel Components Types of Kernels Kernel Configuration Options Recompiling the Kernel Shell Scripting Overview Shell Script Fundamentals Bash Shell Syntax Overview Shell Script Examples System Backups Backup Concepts and Strategies User Backups with the tar Command System Backup Options The xfsdump and xfsrestore Commands Troubleshooting the System Common Problems and Symptoms Troubleshooting Steps Repairing General Boot Problems Repairing the GRUB 2 Boot Loader Hard Drive Problems Restoring Shared Libraries System Logs and rsyslogd Basic Networking Networking Services Overview NetworkManager Introduction Network Configuration Files Locations and Formats Enabling and Restarting Network Services with systemtcl Configuring Basic Networking Manually Configuring Basic Networking with NetworkManager LAMP Server Basics LAMP Overview Configuring the Apache Web Server Common Directives Apache Virtual Hosting Configuring an Open Source Database MySQL MariaDB PHP Basics Perl CGI Scripting Introduction to System Security Security Overview Maintaining System Security Server Access Physical Security Network Security Security Tools Port Probing with nmap Intrusion Detection and Prevention PAM Security Modules Scanning the System Maintaining File Integrity Using Firewalls Introduction to firewalld The Samba File Sharing Facility Configure Samba for Linux to Linux/UNIX File Sharing Configure Samba for Linux to Windows File Sharing Use the smbclient Utility to Transfer Files Mount/Connect Samba Shares to Linux and Windows Clients Networked File Systems (NFS) Using NFS to Access Remote File Systems Configuring the NFS Server Configuring the NFS Client Exporting File Systems from the NFS Server to the NFS Client

Duration 2 Days 12 CPD hours Overview Working in a hands-on learning environment guided by our expert practitioner, students will explore: Introduction to Continuous Integration, Continuous Deployment and Jenkins-CI Installing and Running Jenkins Job Types in Jenkins Securing Jenkins Jenkins Plugin Distributed Builds with Jenkins Continuous Deployment and the Jenkins Pipeline Best Practices for Jenkins Introduction to Jenkins is a two-day, lab intensive hands-on training course geared for experienced programmers who need to learn how to:Install and configure Jenkins in a servlet containerCreate Jenkins buildsConfigure and use Apache Ant and Apache Maven with JenkinsUse Jenkins to generate Java coding standards reports, code coverage reports, and change noticesUse Jenkins to automatically deploy software into a testing environment. Introduction to Continuous Integration, Continuous Deployment and Jenkins-CI Agile Development Agile Development (cont'd) What is Continuous Integration What is Continuous Integration (cont'd) What is Continous Integration (cont'd) Typical Setup for Continuous Integration Continuous Deployment Continuous Deployment (cont'd) DevOps and Continuous Deployment Continuous Deployment Challenges Jenkins Continuous Integration Jenkins Features Running Jenkins Installing and Running Jenkins Downloading and Installing Jenkins Running Jenkins as a Stand-Alone Application Running Jenkins as a Stand-Alone Application (cont'd) Running Jenkins on an Application Server The Jenkins Home Folder Installing Jenkins as a Windows Service Initial Configuration Configuration Wizard Configuration Wizard (cont'd) Configuring Tools Configuring Tools - Best Practices Job Types in Jenkins Different types of Jenkins Items Different types of Jenkins Items (cont'd) Configuring Source Code Management(SCM) Working with Subversion Working with Subversion (cont'd) Working with Git Storing Credentials Storing Credentials (cont'd) Build Triggers Schedule Build Jobs Polling the SCM Maven Build Steps Securing Jenkins Jenkins Security - Overview Jenkins Security Authentication Authorization Confidentiality Activating Security Configure Authentication Using Jenkins's Internal User Database Creating Users Authorization Matrix-Based Security Note ? Create the Administrative User Project-based Matrix Authorization Project-Based Authentication Jenkins Plugin Introduction Jenkins Plugins - SCM Jenkins Plugins ? Build and Test Jenkins Plugins ? Analyzers Jenkins for Teams Installing Jenkins Plugins Distributed Builds with Jenkins Distributed Builds - Overview Distributed Builds ? How? Slave Machines Configure Jenkins Master Configure Projects Continuous Deployment and the Jenkins Pipeline Continuous Deployment Continuous Deployment (cont'd) DevOps and Continuous Deployment Continuous Deployment Challenges Continuous Deployment with Jenkins The Pipeline Plugin The Pipeline Plugin (cont'd) Defining a Pipeline A Pipeline Example Pipeline Example (cont'd) Parallel Execution Creating a Pipeline Invoking the Pipeline Interacting with the Pipeline Best Practices for Jenkins Best Practices - Secure Jenkins Best Practices - Backups Best Practices - Reproducible Builds Best Practices - Testing and Reports Best Practices - Large Systems Best Practices - Distributed Jenkins Additional course details: Nexus Humans Introduction to Jenkins / Jenkins Quick Start (TTDV7520) training program is a workshop that presents an invigorating mix of sessions, lessons, and masterclasses meticulously crafted to propel your learning expedition forward. This immersive bootcamp-style experience boasts interactive lectures, hands-on labs, and collaborative hackathons, all strategically designed to fortify fundamental concepts. Guided by seasoned coaches, each session offers priceless insights and practical skills crucial for honing your expertise. Whether you're stepping into the realm of professional skills or a seasoned professional, this comprehensive course ensures you're equipped with the knowledge and prowess necessary for success. While we feel this is the best course for the Introduction to Jenkins / Jenkins Quick Start (TTDV7520) course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.

Duration 5 Days 30 CPD hours This course is intended for The CHFI course will benefit: Police and other laws enforcement personnel Defense and Military personnel e-Business Security professionals Systems administrators Legal professionals Banking, Insurance and other professionals Government agencies Overview At the end of this course, you will possess the skills needed to: Understand the fundamentals of computer forensics Understand the computer forensic investigation process Describe in detail different types of hard disks and file systems Understand data acquisition and duplication Counteract anti-forensic techniques Leverage forensic skills in Windows, Linux, and Mac Investigate web attacks Understand dark web forensics Deploy forensic techniques for databases, cloud, and networks Investigate email crimes including malware Perform forensics in mobile and IoT environments Every crime leaves a digital footprint, and you need the skills to track those footprints. In this course, students will learn to unravel these pieces of evidence, decode them and report them. From decoding a hack to taking legal action against the perpetrators, they will become an active respondent in times of cyber-breaches. Computer Forensics in Today?s World 1.1. Understand the Fundamentals of Computer Forensics 1.2. Understand Cybercrimes and their Investigation Procedures 1.3. Understand Digital Evidence 1.4. Understand Forensic Readiness, Incident Response and the Role of SOC (Security Operations Center) in Computer Forensics 1.5. Identify the Roles and Responsibilities of a Forensic Investigator 1.6. Understand the Challenges Faced in Investigating Cybercrimes 1.7. Understand Legal Compliance in Computer Forensics Computer Forensics Investigation Process 2.1. Understand the Forensic Investigation Process and its Importance 2.2. Understand the Pre-investigation Phase 2.3. Understand First Response 2.4. Understand the Investigation Phase 2.5. Understand the Post-investigation Phase Understanding Hard Disks and File Systems 3.1. Describe Different Types of Disk Drives and their Characteristics 3.2. Explain the Logical Structure of a Disk 3.3. Understand Booting Process of Windows, Linux and Mac Operating Systems 3.4. Understand Various File Systems of Windows, Linux and Mac Operating Systems 3.5. Examine File System Using Autopsy and The Sleuth Kit Tools 3.6 Understand Storage Systems 3.7. Understand Encoding Standards and Hex Editors 3.8. Analyze Popular File Formats Using Hex Editor Data Acquisition and Duplication 4.1. Understand Data Acquisition Fundamentals 4.2. Understand Data Acquisition Methodology 4.3. Prepare an Image File for Examination Defeating Anti-forensics Techniques 5.1. Understand Anti-forensics Techniques 5.2. Discuss Data Deletion and Recycle Bin Forensics 5.3. Illustrate File Carving Techniques and Ways to Recover Evidence from Deleted Partitions 5.4. Explore Password Cracking/Bypassing Techniques 5.5. Detect Steganography, Hidden Data in File System Structures, Trail Obfuscation, and File Extension Mismatch 5.6. Understand Techniques of Artifact Wiping, Overwritten Data/Metadata Detection, and Encryption 5.7. Detect Program Packers and Footprint Minimizing Techniques 5.8. Understand Anti-forensics Countermeasures Windows Forensics 6.1. Collect Volatile and Non-volatile Information 6.2. Perform Windows Memory and Registry Analysis 6.3. Examine the Cache, Cookie and History Recorded in Web Browsers 6.4. Examine Windows Files and Metadata 6.5. Understand ShellBags, LNK Files, and Jump Lists 6.6. Understand Text-based Logs and Windows Event Logs Linux and Mac Forensics 7.1. Understand Volatile and Non-volatile Data in Linux 7.2. Analyze Filesystem Images Using The Sleuth Kit 7.3. Demonstrate Memory Forensics Using Volatility & PhotoRec 7.4. Understand Mac Forensics Network Forensics 8.1. Understand Network Forensics 8.2. Explain Logging Fundamentals and Network Forensic Readiness 8.3. Summarize Event Correlation Concepts 8.4. Identify Indicators of Compromise (IoCs) from Network Logs 8.5. Investigate Network Traffic 8.6. Perform Incident Detection and Examination with SIEM Tools 8.7. Monitor and Detect Wireless Network Attacks Investigating Web Attacks 9.1. Understand Web Application Forensics 9.2. Understand Internet Information Services (IIS) Logs 9.3. Understand Apache Web Server Logs 9.4. Understand the Functionality of Intrusion Detection System (IDS) 9.5. Understand the Functionality of Web Application Firewall (WAF) 9.6. Investigate Web Attacks on Windows-based Servers 9.7. Detect and Investigate Various Attacks on Web Applications Dark Web Forensics 10.1. Understand the Dark Web 10.2. Determine How to Identify the Traces of Tor Browser during Investigation 10.3. Perform Tor Browser Forensics Database Forensics 11.1. Understand Database Forensics and its Importance 11.2. Determine Data Storage and Database Evidence Repositories in MSSQL Server 11.3. Collect Evidence Files on MSSQL Server 11.4. Perform MSSQL Forensics 11.5. Understand Internal Architecture of MySQL and Structure of Data Directory 11.6. Understand Information Schema and List MySQL Utilities for Performing Forensic Analysis 11.7. Perform MySQL Forensics on WordPress Web Application Database Cloud Forensics 12.1. Understand the Basic Cloud Computing Concepts 12.2. Understand Cloud Forensics 12.3. Understand the Fundamentals of Amazon Web Services (AWS) 12.4. Determine How to Investigate Security Incidents in AWS 12.5. Understand the Fundamentals of Microsoft Azure 12.6. Determine How to Investigate Security Incidents in Azure 12.7. Understand Forensic Methodologies for Containers and Microservices Investigating Email Crimes 13.1. Understand Email Basics 13.2. Understand Email Crime Investigation and its Steps 13.3. U.S. Laws Against Email Crime Malware Forensics 14.1. Define Malware and Identify the Common Techniques Attackers Use to Spread Malware 14.2. Understand Malware Forensics Fundamentals and Recognize Types of Malware Analysis 14.3. Understand and Perform Static Analysis of Malware 14.4. Analyze Suspicious Word and PDF Documents 14.5. Understand Dynamic Malware Analysis Fundamentals and Approaches 14.6. Analyze Malware Behavior on System Properties in Real-time 14.7. Analyze Malware Behavior on Network in Real-time 14.8. Describe Fileless Malware Attacks and How they Happen 14.9. Perform Fileless Malware Analysis - Emotet Mobile Forensics 15.1. Understand the Importance of Mobile Device Forensics 15.2. Illustrate Architectural Layers and Boot Processes of Android and iOS Devices 15.3. Explain the Steps Involved in Mobile Forensics Process 15.4. Investigate Cellular Network Data 15.5. Understand SIM File System and its Data Acquisition Method 15.6. Illustrate Phone Locks and Discuss Rooting of Android and Jailbreaking of iOS Devices 15.7. Perform Logical Acquisition on Android and iOS Devices 15.8. Perform Physical Acquisition on Android and iOS Devices 15.9. Discuss Mobile Forensics Challenges and Prepare Investigation Report IoT Forensics 16.1. Understand IoT and IoT Security Problems 16.2. Recognize Different Types of IoT Threats 16.3. Understand IoT Forensics 16.4. Perform Forensics on IoT Devices

Duration 2 Days 12 CPD hours This course is intended for This course is intended for System and network engineers, technical architects and technical support personnel Overview Upon successful completion of this course, students will be able to install and operate a Cisco DNA Center (DNAC) This course will cover the basics of installing and operation of the Cisco DNA Center (DNAC). The Cisco DNAC is a stand-alone product that provides a single dashboard for every fundamental management task to simplify running an enterprise network. The DNAC is the management piece of the Software Defined Access (SDA) solution. Intent-based Networking overview DNA Center overview. DNA Center as a Platform. DNA Center Architecture & Design. DNA Center Installation DNA Center/Identity Services Engine (ISE) Integration ISE Integration configuration in DNA Center. DNA - Global - Add servers (e.g. ISE server(s)). DNA Center integration configuration in ISE. Approve pxGrid in ISE.Verify DNA/ISE integration DNA Center - Device Inventory Add networks devices to the DNA Center device inventory. Verify DNA Center Inventory configuration. DNA Center - Design - Network Hierarchy. Verify DNA Center - design configuration DNA Center - Design - Software Image Management (SWIM) Review SWIM image repository listing. Create golden software image & role. Verify golden software image creation DNA Center - Design ? Templates and Policies Templates ? Apache Velocity Engine. Command Runner. Policies: Group-Based, Application,Traffic Copy, IP-Based DNA Center - Provision Configuration Add devices to newly created sites/locations. Plug and Play (PnP). Verify DNA Center - provision configuration. DNA Center - Assurance Collection. DNA Center ? Administration

Duration 4 Days 24 CPD hours This course is intended for This class is intended for experienced developers who are responsible for managing big data transformations including: Extracting, loading, transforming, cleaning, and validating data. Designing pipelines and architectures for data processing. Creating and maintaining machine learning and statistical models. Querying datasets, visualizing query results and creating reports Overview Design and build data processing systems on Google Cloud Platform. Leverage unstructured data using Spark and ML APIs on Cloud Dataproc. Process batch and streaming data by implementing autoscaling data pipelines on Cloud Dataflow. Derive business insights from extremely large datasets using Google BigQuery. Train, evaluate and predict using machine learning models using TensorFlow and Cloud ML. Enable instant insights from streaming data Get hands-on experience with designing and building data processing systems on Google Cloud. This course uses lectures, demos, and hand-on labs to show you how to design data processing systems, build end-to-end data pipelines, analyze data, and implement machine learning. This course covers structured, unstructured, and streaming data. Introduction to Data Engineering Explore the role of a data engineer. Analyze data engineering challenges. Intro to BigQuery. Data Lakes and Data Warehouses. Demo: Federated Queries with BigQuery. Transactional Databases vs Data Warehouses. Website Demo: Finding PII in your dataset with DLP API. Partner effectively with other data teams. Manage data access and governance. Build production-ready pipelines. Review GCP customer case study. Lab: Analyzing Data with BigQuery. Building a Data Lake Introduction to Data Lakes. Data Storage and ETL options on GCP. Building a Data Lake using Cloud Storage. Optional Demo: Optimizing cost with Google Cloud Storage classes and Cloud Functions. Securing Cloud Storage. Storing All Sorts of Data Types. Video Demo: Running federated queries on Parquet and ORC files in BigQuery. Cloud SQL as a relational Data Lake. Lab: Loading Taxi Data into Cloud SQL. Building a Data Warehouse The modern data warehouse. Intro to BigQuery. Demo: Query TB+ of data in seconds. Getting Started. Loading Data. Video Demo: Querying Cloud SQL from BigQuery. Lab: Loading Data into BigQuery. Exploring Schemas. Demo: Exploring BigQuery Public Datasets with SQL using INFORMATION_SCHEMA. Schema Design. Nested and Repeated Fields. Demo: Nested and repeated fields in BigQuery. Lab: Working with JSON and Array data in BigQuery. Optimizing with Partitioning and Clustering. Demo: Partitioned and Clustered Tables in BigQuery. Preview: Transforming Batch and Streaming Data. Introduction to Building Batch Data Pipelines EL, ELT, ETL. Quality considerations. How to carry out operations in BigQuery. Demo: ELT to improve data quality in BigQuery. Shortcomings. ETL to solve data quality issues. Executing Spark on Cloud Dataproc The Hadoop ecosystem. Running Hadoop on Cloud Dataproc. GCS instead of HDFS. Optimizing Dataproc. Lab: Running Apache Spark jobs on Cloud Dataproc. Serverless Data Processing with Cloud Dataflow Cloud Dataflow. Why customers value Dataflow. Dataflow Pipelines. Lab: A Simple Dataflow Pipeline (Python/Java). Lab: MapReduce in Dataflow (Python/Java). Lab: Side Inputs (Python/Java). Dataflow Templates. Dataflow SQL. Manage Data Pipelines with Cloud Data Fusion and Cloud Composer Building Batch Data Pipelines visually with Cloud Data Fusion. Components. UI Overview. Building a Pipeline. Exploring Data using Wrangler. Lab: Building and executing a pipeline graph in Cloud Data Fusion. Orchestrating work between GCP services with Cloud Composer. Apache Airflow Environment. DAGs and Operators. Workflow Scheduling. Optional Long Demo: Event-triggered Loading of data with Cloud Composer, Cloud Functions, Cloud Storage, and BigQuery. Monitoring and Logging. Lab: An Introduction to Cloud Composer. Introduction to Processing Streaming Data Processing Streaming Data. Serverless Messaging with Cloud Pub/Sub Cloud Pub/Sub. Lab: Publish Streaming Data into Pub/Sub. Cloud Dataflow Streaming Features Cloud Dataflow Streaming Features. Lab: Streaming Data Pipelines. High-Throughput BigQuery and Bigtable Streaming Features BigQuery Streaming Features. Lab: Streaming Analytics and Dashboards. Cloud Bigtable. Lab: Streaming Data Pipelines into Bigtable. Advanced BigQuery Functionality and Performance Analytic Window Functions. Using With Clauses. GIS Functions. Demo: Mapping Fastest Growing Zip Codes with BigQuery GeoViz. Performance Considerations. Lab: Optimizing your BigQuery Queries for Performance. Optional Lab: Creating Date-Partitioned Tables in BigQuery. Introduction to Analytics and AI What is AI?. From Ad-hoc Data Analysis to Data Driven Decisions. Options for ML models on GCP. Prebuilt ML model APIs for Unstructured Data Unstructured Data is Hard. ML APIs for Enriching Data. Lab: Using the Natural Language API to Classify Unstructured Text. Big Data Analytics with Cloud AI Platform Notebooks What's a Notebook. BigQuery Magic and Ties to Pandas. Lab: BigQuery in Jupyter Labs on AI Platform. Production ML Pipelines with Kubeflow Ways to do ML on GCP. Kubeflow. AI Hub. Lab: Running AI models on Kubeflow. Custom Model building with SQL in BigQuery ML BigQuery ML for Quick Model Building. Demo: Train a model with BigQuery ML to predict NYC taxi fares. Supported Models. Lab Option 1: Predict Bike Trip Duration with a Regression Model in BQML. Lab Option 2: Movie Recommendations in BigQuery ML. Custom Model building with Cloud AutoML Why Auto ML? Auto ML Vision. Auto ML NLP. Auto ML Tables.

This course presents an approach for dealing with security and privacy throughout the entire software development lifecycle. You will learn about vulnerabilities that undermine security, and how to identify and remediate them in your own projects.

Duration 3 Days 18 CPD hours This course is intended for This is an introductory-level course designed to teach experienced systems administrators how to install, maintain, monitor, troubleshoot, optimize, and secure Hadoop. Previous Hadoop experience is not required. Overview Working within in an engaging, hands-on learning environment, guided by our expert team, attendees will learn to: Understand the benefits of distributed computing Understand the Hadoop architecture (including HDFS and MapReduce) Define administrator participation in Big Data projects Plan, implement, and maintain Hadoop clusters Deploy and maintain additional Big Data tools (Pig, Hive, Flume, etc.) Plan, deploy and maintain HBase on a Hadoop cluster Monitor and maintain hundreds of servers Pinpoint performance bottlenecks and fix them Apache Hadoop is an open source framework for creating reliable and distributable compute clusters. Hadoop provides an excellent platform (with other related frameworks) to process large unstructured or semi-structured data sets from multiple sources to dissect, classify, learn from and make suggestions for business analytics, decision support, and other advanced forms of machine intelligence. This is an introductory-level, hands-on lab-intensive course geared for the administrator (new to Hadoop) who is charged with maintaining a Hadoop cluster and its related components. You will learn how to install, maintain, monitor, troubleshoot, optimize, and secure Hadoop. Introduction Hadoop history and concepts Ecosystem Distributions High level architecture Hadoop myths Hadoop challenges (hardware / software) Planning and installation Selecting software and Hadoop distributions Sizing the cluster and planning for growth Selecting hardware and network Rack topology Installation Multi-tenancy Directory structure and logs Benchmarking HDFS operations Concepts (horizontal scaling, replication, data locality, rack awareness) Nodes and daemons (NameNode, Secondary NameNode, HA Standby NameNode, DataNode) Health monitoring Command-line and browser-based administration Adding storage and replacing defective drives MapReduce operations Parallel computing before MapReduce: compare HPC versus Hadoop administration MapReduce cluster loads Nodes and Daemons (JobTracker, TaskTracker) MapReduce UI walk through MapReduce configuration Job config Job schedulers Administrator view of MapReduce best practices Optimizing MapReduce Fool proofing MR: what to tell your programmers YARN: architecture and use Advanced topics Hardware monitoring System software monitoring Hadoop cluster monitoring Adding and removing servers and upgrading Hadoop Backup, recovery, and business continuity planning Cluster configuration tweaks Hardware maintenance schedule Oozie scheduling for administrators Securing your cluster with Kerberos The future of Hadoop