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Administering Cisco UCS X-Series Solutions with Intersight (INTUCSX)

By Nexus Human

Duration 5 Days 30 CPD hours This course is intended for The primary audience for this course is as follows: Server Administrators Systems Engineers Storage Administrators Technical Solutions Architects Integrators and Partners Consulting Systems Engineers Network Administrators Network Engineers Network Managers Architects Overview Upon completion of this course, the student will be able to meet these overall objectives: Understand, describe, and configure Cisco Intersight (on prem and SaaS models) Understand, describe, and configure Intersight Advanced features (IST, ICO, IWOM) Understand, describe, and configure IMM and UMM mode for UCS Understand, describe, and configure Cisco X-Series (FI, IFM, X210c Server, Adv Fabric Module) Create Intersight Pools, Policies, and Management for X-Series Design and operate Cisco UCS with Intersight Managed Mode Solutions This deep-dive training covers Cisco UCS X-Series server family and how Intersight can be the enablement platform for all UCS servers. We will cover Intersight features such as IWOM, IST, ICO, and programmability either On-Prem or in the Cloud. Attendees will learn the breadth of the physical X-Series (pools, policies, firmware, so much more) platform as well as maintaining existing infrastructure with Intersight Infrastructures Services. Also covered is how to manage physical, virtual, cloud platforms and deploy to any or all. Section 1: Intersight Foundations Intersight Architecture Flexible Deployment Models Cisco Intersight Infrastructure Service Licensing Intersight Essentials License Tier Intersight Advantage License Tier Intersight Premier License Tier Section 2: Monitoring and Maintaining UCS Infrastructure with Intersight Device Health and Monitoring Standalone Management for UCS C-Series Servers Server Compatibility (HCL), Advisories (CVEs), and Contract Status Firmware Upgrades Section 3: Designing & Operationalizing Cisco UCS Solutions with Intersight Implementing Cisco Hyperflex with Intersight Managing Cisco HyperFlex in vSphere Environment Section 4: Cisco UCS M5, M6, X Overview and Configuration Cisco UCS X-Series with Intersight Deployment Architecture X-Series Fabric Interconnects Compute X-Series Power/Cooling Efficiency Cooling Capacity Airflow Thermal Policies Future-Proof Cooling Power Policies Compute Series Architecture ? C220 M6 Architecture ? C240 M6 Cisco VIC Offerings for M6 GPU Offerings for X-Series Management Options for C220 / C240 M6 Rack Servers UCS 7th Generation Intel Rack Servers Architecture ? C220 M7 Architecture ? C240 M7 Intel 4th Gen IntelÂ© XeonÂ© SP Sapphire Rapids High Level Features M7 Memory DIMMs Architecture ? C225 M6 Architecture ? C245 M6 Section 5: Designing Cisco UCS LAN and SAN Connectivity LAN Connectivity Overview Gen 4 End Host Mode Requirements for Configuring VLANs in Cisco UCS Manager Role of the vNIC in Abstracting MAC Addresses Configuring Compute Node SAN Connectivity Fibre Channel Switching Fibre Channel Operating Modes EHM and N-Port Virtualization Configuring VSANs in Cisco UCS Manager Creating VSANs and FCoE VLANs in Cisco UCS Role of vHBAs when Abstracting WWNNs and WWPNs into a Service Profile Configuring Manual Uplink Pinning and Recovery from Failure Section 6: Configuring Cisco UCS-X in IMM Mode IMM and Domain Profiles Domain Policy Concepts and Usage Cisco Intersight Server Profiles Creating and Deploying a UCS C-Series Server Profile ? Process Overview Importing a Server Profile ? Process Overview Upgrading Firmware Cisco IMM Transition Tool Thermal Policies Power Policies Section 7: Implementing Cisco UCS-X Firmware Updates Intersight Platform Firmware Operations Overview Intersight Firmware Bundles Cisco Stand-Alone Firmware Management Cisco HX Firmware Management UCS Managed Infrastructure Firmware Management UCS Intersight Managed Mode Firmware Management Hardware Compatibility List Section 8: Intersight Workload Optimizer (IWO) Intersight Workload Optimizer Overview IWO Delivery and Tiers Workload Optimizer ? What?s New? IWO Value Proposition Application Resource Management IWO Market Section 9: Intersight Cloud Orchestrator (ICO) Sample Scenario Workflow Designer Validate and Execute a Workflow ICO ? Intersight Cloud Orchestrator Infrastructure Orchestration Infrastructure as Code with ICO Immutability with Intersight Cloud Orchestrator Workflow Versions Rollback Tasks (Task Designer) Section 10: Intersight API Overview Intersight API Resources SDKs / Ansible Modules Use Case Additional course details: Nexus Humans Administering Cisco UCS X-Series Solutions with Intersight (INTUCSX) 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 Administering Cisco UCS X-Series Solutions with Intersight (INTUCSX) 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.

Administering Cisco UCS X-Series Solutions with Intersight (INTUCSX)

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Data Engineering on Google Cloud

By Nexus Human

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.