Oversikt over relevante kurs innen Kurs i programvare og applikasjoner i Trysil

Elasticsearch [-]

AZ-400: Designing and Implementing Microsoft DevOps solutions [-]

  Studieår: 2013-2014   Gjennomføring: Høst og vår Antall studiepoeng: 5.0 Forutsetninger: Generelt gode IT-kunnskaper. Bør ha kjennskap til bruk av Windows server og fordel med MS SQL server. Kjennskap til AD, RDP og DNS. Innleveringer: 8 obligatoriske øvinger Personlig veileder: ja Vurderingsform: 2 dagers praktisk hjemmeeskamen med både teoretiske og praktiske oppgaver. Ansvarlig: Stein Meisingseth Eksamensdato: 17.12.13 / 20.05.14         Læremål: KUNNSKAPER:Kandidaten skal:- kjenne til fordelen med å ta i bruk Citrix XenApp for en bedrift/organisasjon- kunne gjøre rede for hvordan Citrix XenApp brukes som publiseringsplattform- kunne beskrive Citrix XenApp brukes for å rulle ut applikasjoner- kunne gjøre rede for hvordan XenApp kan tas i bruk som applikasjonsvirtualisering på klientside (streaming) og på serverside (publishing)- kunne oppnå optimal applikasjonsytelse og fleksible leveransemuligheter FERDIGHETER:Kandidaten skal:- kunne installere Citrix XenApp- kunne sette opp administrativ konfigurasjon- kunne sette opp og publisere applikasjoner, innhold og desktops for brukere- kunne konfigurere applikasjoner for streaming til servere og til desktops- kunne vurdere hvilken sikkerhet som kreves- kunne sette opp og konfigurere overvåkning- kunne konfigurere og bruke et administrativt grensesnitt GENERELL KOMPETANSEKandidaten:- har kompetanse til selvstendig både å formidle og å ta i bruk sine kunnskaper og ferdigheter i en bedrift som vil bruke Citrix XenApp- kan i et forklare og gjøre bruk av sin kunnskap for bruk av Citrix XenApp Innhold:- introduksjon til Citrix XenApp - installasjon av Citrix XenApp (6.5) - praktisk bruk - konfigurasjon - bruk av Web Interface - publisere applikasjoner og innhold - streame applikasjoner - sette opp restriksjoner - konfigurere lastbalansering - maksimere brukeropplevelse - bruke av skrivere - sikkerhet - overvåkningLes mer om faget her Påmeldingsfrist: 25.08.13 / 25.01.14         Velg semester:  Høst 2013    Vår 2014     Fag Citrix XenApp 4980,-         Semesteravgift og eksamenskostnader kommer i tillegg.   [-]

AZ-700: Designing and Implementing Microsoft Azure Networking Solutions [-]

Etter den fantastiske suksessen med Premiere Pro-klassen vår for nybegynnere, bestemte vi oss for å lage en oppfølging. Grundig produsert med tanke på en morsom og engasjerende læringsopplevelse. Kursmål Du vil lære alle funksjonene i Adobe Premiere Pro som lar deg gjøre følgende: Ulike redigeringsarbeidsflytteknikker Avanserte innstillinger og alternativer Jobber med snarveier Bildetekster og undertekster Lag egendefinerte forhåndsinnstillinger og maler Overgangsteknikker Stabiliser og reverser bevegelsesklipp Tidsomlegging Maskering og sporing Fargekorrigering og gradering Fikser og forbedrer lyd Arbeid med kodeker og gjengivelsesalternativer [-]

Fleksible kurs for fremtidenNy kunnskap skal gi umiddelbar effekt, og samtidig være holdbar og bærekraftig på lang sikt. NTI AS har 30 års erfaring innen kurs og kompetanseheving, og utdanner årlig rundt 10.000 personer i Nord Europa innen CAD, BIM, industri, design og konstruksjon. Her er et utvalg av temaene du vil lære på kurset: Strømlinjeformet prosjektoppstart med riktig malfil Nullpunkt i Revit Delte koordinater Terrengmodellering Detaljering av vegger, tak og trapper Koordinering og linking av fagmodeller Rehabilitering og faser Alternative løsningsforslag I dette kurset ser vi nærmere på funksjoner som gir mulighet for å utføre mer avanserte oppgaver. For eksempel kan det skapes et stort overblikk i forbindelse med rehabilitering og etappeoppdelte oppgaver. Det arbeides med ferdigstilling av prosjekter, bl.a. designforslag i et prosjekt.      Tilpassete kurs for bedrifterVi vil at kundene våre skal være best på det de gjør - hele tiden.  Derfor tenker vi langsiktig om kompetanseutvikling og ser regelmessig kunnskapsløft som en naturlig del av en virksomhet. Vårt kurskonsept bygger på et moderne sett av ulike læringsmiljøer, som gjør det enkelt å finne riktig løsning uansett behov.   Ta kontakt med oss på telefon 483 12 300, epost: salg@nticad.no eller les mer på www.nticad.no   [-]

COURSE OVERVIEW ou will learn how to configure and manage Cisco Nexus 9000 Series Switches in ACI mode, how to connect the Cisco ACI fabric to external networks and services, and fundamentals of Virtual Machine Manager (VMM) integration. You will gain hands-on practice implementing key capabilities such as fabric discovery, policies, connectivity, VMM integration, and more. This course is based on ACI Software v5.2 release.   This course helps you prepare to take the exam, Implementing Cisco Application Centric Infrastructure(300-620 DCACI), which leads to CCNP® Data Center and Cisco Certified Specialist – Data Center ACI Implementation certifications. TARGET AUDIENCE Individuals who need to understand how to configure and manage a data center network environment with the Cisco Nexus 9000 Switch operating in ACI Mode.   COURSE OBJECTIVES After completing this course, you should be able to: Describe Cisco ACI Fabric Infrastructure and basic Cisco ACI concepts Describe Cisco ACI policy model logical constructs Describe Cisco ACI basic packet forwarding Describe external network connectivity Describe VMM Integration Describe Layer 4 to Layer 7 integrations Explain Cisco ACI management features COURSE CONTENT Introducing Cisco ACI Fabric Infrastructure and Basic Concepts What Is Cisco ACI? Cisco ACI Topology and Hardware Cisco ACI Object Model Faults, Event Record, and Audit Log Cisco ACI Fabric Discovery Cisco ACI Access Policies Describing Cisco ACI Policy Model Logical Constructs Cisco ACI Logical Constructs Tenant Virtual Routing and Forwarding Bridge Domain Endpoint Group Application Profile Tenant Components Review Adding Bare-Metal Servers to Endpoint Groups Contracts Describing Cisco ACI Basic Packet Forwarding Endpoint Learning Basic Bridge Domain Configuration **** Introducing External Network Connectivity Cisco ACI External Connectivity Options External Layer 2 Network Connectivity External Layer 3 Network Connectivity Introducing VMM Integration VMware vCenter VDS Integration Resolution Immediacy in VMM Alternative VMM Integrations Describing Layer 4 to Layer 7 Integrations Service Appliance Insertion Without ACI L4-L7 Service Graph Service Appliance Insertion via ACI L4-L7 Service Graph Service Graph Configuration Workflow Service Graph PBR Introduction Explaining Cisco ACI Management Out-of-Band Management In-Band Management Syslog Simple Network Management Protocol Configuration Backup Authentication, Authorization, and Accounting Role-Based Access Control Cisco ACI Upgrade Collect Tech Support Labs Validate Fabric Discovery Configure Network Time Protocol (NTP) Create Access Policies and Virtual Port Channel (vPC) Enable Layer 2 Connectivity in the Same Endpoint Group (EPG) Enable Inter-EPG Layer 2 Connectivity Enable Inter-EPG Layer 3 Connectivity Compare Traffic Forwarding Methods in a Bridge Domain Configure External Layer 2 (L2Out) Connection Configure External Layer 3 (L3Out) Connection Integrate Application Policy Infrastructure Controller (APIC) With VMware vCenter Using VMware Distributed Virtual Switch (DVS) TEST CERTIFICATION Recommended as preparation for the following exams: 300-620 DCACI - Implementing Cisco Application Centric Infrastructure [-]

The course is designed for Azure system administrators, solutions architects, and SysOps administrators who are familiar with Azure features and setup and want to gain experience configuring Google Cloud products immediately.  This course uses lectures, demos, and hands-on labs to show you the similarities and differences between the two platforms and teach you about some basic tasks on Google Cloud. Objectives This course teaches participants the following skills: Identify Google Cloud counterparts for Azure IaaS, Azure PaaS, Azure SQL, Azure Blob Storage, Azure Application Insights, and Azure Data Lake Configure accounts, billing, projects, networks, subnets, firewalls, VMs, disks, auto-scaling, load balancing, storage, databases, IAM, and more Manage and monitor applications Explain feature and pricing model differences All courses will be delivered in partnership with ROI Training, Google Cloud Premier Partner, using a Google Authorized Trainer. Course Outline Module 1: Introducing Google Cloud -Explain the advantages of Google Cloud-Define the components of Google’s network infrastructure, including points of presence, data centers, regions, and zones-Understand the difference between Infrastructure-as-a-Service (IaaS) and Platform-as-a-Service (PaaS) Module 2: Getting Started with Google Cloud -Identify the purpose of projects on Google Cloud-Understand how Azure’s resource hierarchy differs from Google Cloud’s-Understand the purpose of and use cases for Identity and Access Management-Understand how Azure AD differs from Google Cloud IAM-List the methods of interacting with Google Cloud-Launch a solution using Cloud Marketplace Module 3: Virtual Machines in the Cloud -Identify the purpose and use cases for Google Compute Engine-Understand the basics of networking in Google Cloud-Understand how Azure VPC differs from Google VPC-Understand the similarities and differences between Azure VM and Google Compute Engine-Understand how typical approaches to load-balancing in Google Cloud differ from those in AzureDeploy applications using Google Compute Engine Module 4: Storage in the Cloud -Understand the purpose of and use cases for: Cloud Storage, Cloud SQL, Cloud Bigtable and Cloud Datastore-Understand how Azure Blob compares to Cloud Storage-Compare Google Cloud’s managed database services with Azure SQL-Learn how to choose among the various storage options on Google Cloud-Load data from Cloud Storage into BigQuery Module 5: Containers in the Cloud -Define the concept of a container and identify uses for containers-Identify the purpose of and use cases for Google Container Engine and Kubernetes-Understand how Azure Kubernetes Service differs from Google Kubernetes Engine-Provision a Kubernetes cluster using Kubernetes Engine-Deploy and manage Docker containers using kubectl Module 6: Applications in the Cloud -Understand the purpose of and use cases for Google App Engine-Contrast the App Engine Standard environment with the App Engine Flexible environment-Understand how App Engine differs from Azure App Service-Understand the purpose of and use cases for Google Cloud Endpoints Module 7: Developing, Deploying and Monitoring in the Cloud -Understand options for software developers to host their source code-Understand the purpose of template-based creation and management of resources-Understand how Cloud Deployment Manager differs from Azure Resource Manager-Understand the purpose of integrated monitoring, alerting, and debugging-Understand how Google Monitoring differs from Azure Application Insights and Azure Log Analytics-Create a Deployment Manager deployment-Update a Deployment Manager deployment-View the load on a VM instance using Google Monitoring Module 8: Big Data and Machine Learning in the Cloud -Understand the purpose of and use cases for the products and services in the Google Cloud big data and machine learning platforms-Understand how Google Cloud BigQuery differs from Azure Data Lake-Understand how Google Cloud Pub/Sub differs from Azure Event Hubs and Service Bus-Understand how Google Cloud’s machine-learning APIs differ from Azure’s-Load data into BigQuery from Cloud Storage-Perform queries using BigQuery to gain insight into data Module 9: Summary and Review -Review the products that make up Google Cloud and remember how to choose among them-Understand next steps for training and certification-Understand, at a high level, the process of migrating from Azure to Google Cloud [-]

Vil du lære å lage visittkort, annonser, brosjyrer og plakater i InDesign? Enten du jobber i en markedsavdeling, grafisk bedrift, avis eller magasin, er dette det profesjonelle programmet du bruker til jobben.  Arbeider du med markedsføring og layout, vil du ha stor nytte av å kunne sette sammen tekst og bilder selv. Du slipper å sette ut arbeidet,  får større kontroll på layouten og mer ut av markedsbudsjettet. Du velger dette kurset for å lære alt du trenger for å komme igang med programmet InDesign. Hvem passer kurset for? Kurset passer for deg som har liten eller ingen erfaring med å jobbe i InDesign. InDesign er bransjestandarden for å lage annonser, brosjyrer, magasiner, plakater, DM, rapporter og bøker. Uansett hva du skal bruke programme til, så passer dette kurset for deg! Dette lærer du: Bli kjent med menyer og verktøy Effektiv jobbing med tekst- og sidemaler Grunnleggende typografi Importere og tilpasse bilder og tekst Plassere bilder med tekst rundt Lage egne farger Bruk av effekter Kontroll av dokumenter og eksport til pdf https://igm.no/indesign-grunnkurs/ [-]

Filer i SharePoint lagres i bibliotek. Her tar vi en grundig gjennomgang av bibliotek og tilpasningsmuligheter for disse, som versjonering, maler og Office-integrasjon. Webinaret varer i 2 timer og består av to økter à 45 min. Etter hver økt er det 10 min spørsmålsrunde. Mellom øktene er det 10 min pause. Webinaret kan også spesialtilpasses og holdes bedriftsinternt kun for din bedrift.   Kursinnhold:   Om bibliotek Møt biblioteksmalene i SharePoint Opplasting, nedlasting Office-programmene og bibliotek Områdepapirkurv   Tilpasse bibliotek Endre Office-mal for et bibliotek Tilpass kolonner og metadata   Tips til bibliotek Bruke kolonner i Word Bibliotek i Windows Utforsker   Utvidet om bibliotek Gjennomgang av versjonering Bli kjent med godkjenning Arkivering og Send til   Veien videre Introduksjon til innholdstyper Introduksjon til dokumentsenter og innholds-sortering 3 gode grunner til å delta 1. Møt SharePoint sine bibliotek-apper og lær måter å åpne og lagre i bibliotek og håndtere innholdet 2. Forstå mer om versjonering, godkjenning og arkivering 3. Bli kjent med dokumentsenter og innholds-sortering   [-]

Informasjon i SharePoint er lagret i lister. Bli kjent med SharePoint liste-apper og hvordan du tilpasser eller lager egne med krav til utfylling, oppslag i andre lister, beregninger og validering av innfylte verdier. Webinaret varer i 2 timer og består av to økter à 45 min. Etter hver økt er det 10 min spørsmålsrunde. Mellom øktene er det 10 min pause. Webinaret kan også spesialtilpasses og holdes bedriftsinternt kun for din bedrift.   Kursinnhold:   Om Lister Bruk av listemalene i SharePoint Lag liste av Excel-bok Lag liste fra bunn av i SharePoint   Bruke lister Kolonnetyper og eksempler på bruk Opprette en liste og listeinnstillinger Krav om utfylling   Utvide lister Valider verdier bruker fyller inn Logg-kolonne Beregningskolonner og formler Presenter informasjon med visninger   Avanserte temaer Visnings-stiler Innføring i områdekolonner Veien videre til innholdstyper   3 gode grunner til å delta 1. Møt SharePoint sine liste-apper og lær å lage liste fra bunn eller fra eksisterende Excel-bok 2. Lær om kolonner som beregner eller sjekker inntastede verdier 3. Presenter informasjonen med visninger    [-]

CCNA: Implementing and Administering Cisco Solutions [-]

Fleksible kurs for fremtidenNy kunnskap skal gi umiddelbar effekt, og samtidig være holdbar og bærekraftig på lang sikt. NTI AS har 30 års erfaring innen kurs og kompetanseheving, og utdanner årlig rundt 10.000 personer i Nord Europa innen CAD, BIM, industri, design og konstruksjon. Fusion 360 Her er et utvalg av temaene du vil lære på kurset: Fusion 360 Dashboard - Data og prosjekthåndtering Formgivning - konseptuelt design og parametrisk Samlinger og 2D-tegninger, inkludert stykklister  Dataimport - håndtering av data fra andre CAD-plattformer Kurset for deg som er industriell designer, arbeider med produktdesign eller annen kompleks forgivning. Kurset har fokus på oppbygning av modeller med kompliserte overflater. Du vil få kunnskap til å skape og korrigere avanserte og komplekse 3D-modeller, og samtidig lage avanserte 3D-modeller på bakgrunn av konseptuelle skisser, vedlikeholde og dokumentere dem i forskjellige varianter.    Dette er et populært kurs, meld deg på nå! Tilpassete kurs for bedrifterVi vil at kundene våre skal være best på det de gjør - hele tiden.  Derfor tenker vi langsiktig om kompetanseutvikling og ser regelmessig kunnskapsløft som en naturlig del av en virksomhet. Vårt kurskonsept bygger på et moderne sett av ulike læringsmiljøer, som gjør det enkelt å finne riktig løsning uansett behov. Ta kontakt med oss på telefon 483 12 300, epost: salg@nticad.no eller les mer på www.nticad.no [-]

The students will learn how to interactively explore data stored in files in a data lake. They will learn the various ingestion techniques that can be used to load data using the Apache Spark capability found in Azure Synapse Analytics or Azure Databricks, or how to ingest using Azure Data Factory or Azure Synapse pipelines. The students will also learn the various ways they can transform the data using the same technologies that is used to ingest data. The student will spend time on the course learning how to monitor and analyze the performance of analytical system so that they can optimize the performance of data loads, or queries that are issued against the systems. They will understand the importance of implementing security to ensure that the data is protected at rest or in transit. The student will then show how the data in an analytical system can be used to create dashboards, or build predictive models in Azure Synapse Analytics. After completing this course, students will be able to: Explore compute and storage options for data engineering workloads in Azure Design and Implement the serving layer Understand data engineering considerations Run interactive queries using serverless SQL pools Explore, transform, and load data into the Data Warehouse using Apache Spark Perform data Exploration and Transformation in Azure Databricks Ingest and load Data into the Data Warehouse Transform Data with Azure Data Factory or Azure Synapse Pipelines Integrate Data from Notebooks with Azure Data Factory or Azure Synapse Pipelines Optimize Query Performance with Dedicated SQL Pools in Azure Synapse Analyze and Optimize Data Warehouse Storage Support Hybrid Transactional Analytical Processing (HTAP) with Azure Synapse Link Perform end-to-end security with Azure Synapse Analytics Perform real-time Stream Processing with Stream Analytics Create a Stream Processing Solution with Event Hubs and Azure Databricks Build reports using Power BI integration with Azure Synpase Analytics Perform Integrated Machine Learning Processes in Azure Synapse Analytics Course prerequisites Successful students start this course with knowledge of cloud computing and core data concepts and professional experience with data solutions.Recommended prerequisites:M-DP900 - Microsoft Azure Data FundamentalsM-AZ900 - Microsoft Azure Fundamentals Agenda Module 1: Explore compute and storage options for data engineering workloads This module provides an overview of the Azure compute and storage technology options that are available to data engineers building analytical workloads. This module teaches ways to structure the data lake, and to optimize the files for exploration, streaming, and batch workloads. The student will learn how to organize the data lake into levels of data refinement as they transform files through batch and stream processing. Then they will learn how to create indexes on their datasets, such as CSV, JSON, and Parquet files, and use them for potential query and workload acceleration. Module 2: Design and implement the serving layer This module teaches how to design and implement data stores in a modern data warehouse to optimize analytical workloads. The student will learn how to design a multidimensional schema to store fact and dimension data. Then the student will learn how to populate slowly changing dimensions through incremental data loading from Azure Data Factory. Module 3: Data engineering considerations for source files This module explores data engineering considerations that are common when loading data into a modern data warehouse analytical from files stored in an Azure Data Lake, and understanding the security consideration associated with storing files stored in the data lake. Module 4: Run interactive queries using Azure Synapse Analytics serverless SQL pools In this module, students will learn how to work with files stored in the data lake and external file sources, through T-SQL statements executed by a serverless SQL pool in Azure Synapse Analytics. Students will query Parquet files stored in a data lake, as well as CSV files stored in an external data store. Next, they will create Azure Active Directory security groups and enforce access to files in the data lake through Role-Based Access Control (RBAC) and Access Control Lists (ACLs). Module 5: Explore, transform, and load data into the Data Warehouse using Apache Spark This module teaches how to explore data stored in a data lake, transform the data, and load data into a relational data store. The student will explore Parquet and JSON files and use techniques to query and transform JSON files with hierarchical structures. Then the student will use Apache Spark to load data into the data warehouse and join Parquet data in the data lake with data in the dedicated SQL pool. Module 6: Data exploration and transformation in Azure Databricks This module teaches how to use various Apache Spark DataFrame methods to explore and transform data in Azure Databricks. The student will learn how to perform standard DataFrame methods to explore and transform data. They will also learn how to perform more advanced tasks, such as removing duplicate data, manipulate date/time values, rename columns, and aggregate data. Module 7: Ingest and load data into the data warehouse This module teaches students how to ingest data into the data warehouse through T-SQL scripts and Synapse Analytics integration pipelines. The student will learn how to load data into Synapse dedicated SQL pools with PolyBase and COPY using T-SQL. The student will also learn how to use workload management along with a Copy activity in a Azure Synapse pipeline for petabyte-scale data ingestion. Module 8: Transform data with Azure Data Factory or Azure Synapse Pipelines This module teaches students how to build data integration pipelines to ingest from multiple data sources, transform data using mapping data flowss, and perform data movement into one or more data sinks. Module 9: Orchestrate data movement and transformation in Azure Synapse Pipelines In this module, you will learn how to create linked services, and orchestrate data movement and transformation using notebooks in Azure Synapse Pipelines. Module 10: Optimize query performance with dedicated SQL pools in Azure Synapse In this module, students will learn strategies to optimize data storage and processing when using dedicated SQL pools in Azure Synapse Analytics. The student will know how to use developer features, such as windowing and HyperLogLog functions, use data loading best practices, and optimize and improve query performance. Module 11: Analyze and Optimize Data Warehouse Storage In this module, students will learn how to analyze then optimize the data storage of the Azure Synapse dedicated SQL pools. The student will know techniques to understand table space usage and column store storage details. Next the student will know how to compare storage requirements between identical tables that use different data types. Finally, the student will observe the impact materialized views have when executed in place of complex queries and learn how to avoid extensive logging by optimizing delete operations. Module 12: Support Hybrid Transactional Analytical Processing (HTAP) with Azure Synapse Link In this module, students will learn how Azure Synapse Link enables seamless connectivity of an Azure Cosmos DB account to a Synapse workspace. The student will understand how to enable and configure Synapse link, then how to query the Azure Cosmos DB analytical store using Apache Spark and SQL serverless. Module 13: End-to-end security with Azure Synapse Analytics In this module, students will learn how to secure a Synapse Analytics workspace and its supporting infrastructure. The student will observe the SQL Active Directory Admin, manage IP firewall rules, manage secrets with Azure Key Vault and access those secrets through a Key Vault linked service and pipeline activities. The student will understand how to implement column-level security, row-level security, and dynamic data masking when using dedicated SQL pools. Module 14: Real-time Stream Processing with Stream Analytics In this module, students will learn how to process streaming data with Azure Stream Analytics. The student will ingest vehicle telemetry data into Event Hubs, then process that data in real time, using various windowing functions in Azure Stream Analytics. They will output the data to Azure Synapse Analytics. Finally, the student will learn how to scale the Stream Analytics job to increase throughput. Module 15: Create a Stream Processing Solution with Event Hubs and Azure Databricks In this module, students will learn how to ingest and process streaming data at scale with Event Hubs and Spark Structured Streaming in Azure Databricks. The student will learn the key features and uses of Structured Streaming. The student will implement sliding windows to aggregate over chunks of data and apply watermarking to remove stale data. Finally, the student will connect to Event Hubs to read and write streams. Module 16: Build reports using Power BI integration with Azure Synapase Analytics In this module, the student will learn how to integrate Power BI with their Synapse workspace to build reports in Power BI. The student will create a new data source and Power BI report in Synapse Studio. Then the student will learn how to improve query performance with materialized views and result-set caching. Finally, the student will explore the data lake with serverless SQL pools and create visualizations against that data in Power BI. Module 17: Perform Integrated Machine Learning Processes in Azure Synapse Analytics This module explores the integrated, end-to-end Azure Machine Learning and Azure Cognitive Services experience in Azure Synapse Analytics. You will learn how to connect an Azure Synapse Analytics workspace to an Azure Machine Learning workspace using a Linked Service and then trigger an Automated ML experiment that uses data from a Spark table. You will also learn how to use trained models from Azure Machine Learning or Azure Cognitive Services to enrich data in a SQL pool table and then serve prediction results using Power BI. [-]

Through a combination of presentations, demos, and hands-on labs, participants explore and deploy solution elements, including infrastructure components such as pods, containers, deployments, and services; as well as networks and application services. This course also covers deploying practical solutions including security and access management, resource management, and resource monitoring. Objectives This course teaches participants the following skills: Understand how software containers work Understand the architecture of Kubernetes Understand the architecture of Google Cloud Platform Understand how pod networking works in Kubernetes Engine Create and manage Kubernetes Engine clusters using the GCP Console and gcloud/kubectl commands Launch, roll back and expose jobs in Kubernetes Manage access control using Kubernetes RBAC and Google Cloud IAM Managing pod security policies and network policies Using Secrets and ConfigMaps to isolate security credentials and configuration artifacts Understand GCP choices for managed storage services Monitor applications running in Kubernetes Engine   Course Outline Module 1: Introduction to Google Cloud Platform Use the Google Cloud Platform Console Use Cloud Shell Define cloud computing Identify GCP’s compute services Understand regions and zones Understand the cloud resource hierarchy Administer your GCP resources Module 2: Containers and Kubernetes in GCP Create a container using Cloud Build Store a container in Container Registry Understand the relationship between Kubernetes and Google Kubernetes Engine (GKE) Understand how to choose among GCP compute platforms Module 3: Kubernetes Architecture Understand the architecture of Kubernetes: pods, namespaces Understand the control-plane components of Kubernetes Create container images using Google Cloud Build Store container images in Google Container Registry Create a Kubernetes Engine cluster Module 4: Kubernetes Operations Work with the kubectl command Inspect the cluster and Pods View a Pod’s console output Sign in to a Pod interactivelty Module 5: Deployment, Jobs, and Scaling Create and use Deployments Create and run Jobs and CronJobs Scale clusters manually and automatically Configure Node and Pod affinity Get software into your cluster with Helm charts and Kubernetes Marketplace Module 6: GKE Networking Create Services to expose applications that are running within Pods Use load balancers to expose Services to external clients Create Ingress resources for HTTP(S) load balancing Leverage container-native load balancing to improve Pod load balancing Define Kubernetes network policies to allow and block traffic to pods Module 7: Persistent Data and Storage Use Secrets to isolate security credentials Use ConfigMaps to isolate configuration artifacts Push out and roll back updates to Secrets and ConfigMaps Configure Persistent Storage Volumes for Kubernetes Pods Use StatefulSets to ensure that claims on persistent storage volumes persist across restarts Module 8: Access Control and Security in Kubernetes and Kubernetes Engine Understand Kubernetes authentication and authorization Define Kubernetes RBAC roles and role bindings for accessing resources in namespaces Define Kubernetes RBAC cluster roles and cluster role bindings for accessing cluster-scoped resources Define Kubernetes pod security policies Understand the structure of GCP IAM Define IAM roles and policies for Kubernetes Engine cluster administration Module 9: Logging and Monitoring Use Stackdriver to monitor and manage availability and performance Locate and inspect Kubernetes logs Create probes for wellness checks on live applications Module 10: Using GCP Managed Storage Services from Kubernetes Applications Understand pros and cons for using a managed storage service versus self-managed containerized storage Enable applications running in GKE to access GCP storage services Understand use cases for Cloud Storage, Cloud SQL, Cloud Spanner, Cloud Bigtable, Cloud Firestore, and BigQuery from within a Kubernetes application [-]