1395 Software courses in Coventry delivered Live Online

Duration 4 Days 24 CPD hours This course is intended for This in an intermediate-level Java development course geared for students experienced with Java and Spring programming essentials. This course does not cover Java or Spring development basics. Overview Working within in an engaging, hands-on learning environment, guided by our expert team, attendees will: Understand the ReactiveX specification Understand the basics of Reactive Programming Discuss the advantages and limitations of Observables Write a client application capable of handling Reactive events Apply operators to event streams to filter, modify and combine the objects emitted by event publishers Select the appropriate type of Event Source Use both Cold and Hot Observables Deal with backpressure problems in reactive programming Develop a reactive web application using Spring WebFlux Define application flows of a WebFlux application Use the WebClient API to work with both synchronous and streaming APIs Develop Unit and Integration tests to test WebFlux endpoints Creating a reactive REST endpoint Become familiar with the basics of WebSockets Create a WebSocket endpoint using Spring Create a WebSocket client Understand the basics of NoSQL Become familiar with the basics of MongoDB Understand how the data in MongoDB can be retrieved using a Reactive API Define Spring Data MongoDB repositories Query the MongoDB using Spring Data Define a reactive repository using MongoDB Explore the Spring Data R2DBC API to perform reactive CRUD operations against a relational database Spring Data reative allow us to implement database operations relying on Reative Programming APIs. While the Spring R2DBC initiative aims to bring reactive programming to relational databaes, several NoSQL databases already provide this possibility. After an introduction to NoSQL and the MongoDB, this courses covers the APIs available to communicate with this NoSQL database using both blocking and reactive APIs.Introdcution to Reactive Spring is a comprehensive Java training workshop geared for experienced developers who wish to explore concurrent, asynchronous and reactive programming APIs and techniques using Spring. After an introduction to reactive programming, Reactive Streams and the Project Reactor APIs, this course will show how this APIs are integrated into Spring. Spring 5 includes Spring WebFlux, providing a reactive programming model for web applications, including support for Reactive REST APIs. Spring WebSocket assists in the creation of web applications which provide a full-duplex, two-way communication between client and server. Introduction to Reactive Programming Reactive Manifesto Introduce ReactiveX ReactiveX implementations The Observer, Iterator pattern and functional programming Discuss hot and cold publishers Reactive Streams API Introduce the Reactive Streams specification Publisher and Subscribers java.util.concurrent.Flow Transformation of Messages (Processor) Controlling messages Tutorial: Setup Eclipse for Using Maven Introduction Introduce the Reactor Building blocks Flux and Mono Creating observables Subscribing to a stream Testing Event Sources (introduction) Testing reactive implementations StepVerifier : test sequence of emitted items Defining expectations TestPublisher: produce test data to test downstream operators Reactive Operators Introduce Operators Show the use of marble diagrams Explain some commonly used operators Callback operators Schedulers (Multithreading) Thread usage of subscriber and consumer Using the subscribeOn method Introduce the Scheduler interface Using the observeOn method Backpressure Strategies for dealing with Backpressure ?reactive pull? backpressure Exception Handling Handling errors in onError Exception handling strategies Using onErrorReturn or onErrorNext operators Using the retry operators The Global Error Handler Spring Data Review Quick review of Spring Data repositories Query return types Defining Query methods Pagination and sorting R2DBC Reactive Relational Database Connectivity DatabaseClient Performing CRUD operations Reactive Query annotated methods Spring WebFlux: Introduction Annotated Controllers Functional Endpoints WebFlux configuration Creating a reactive REST endpoint Defining flows Defining the application flow Actions Defining decision Navigating flows RouterFunction View Technologies View technologies Using Thymeleaf to create the view View Configuration Spring WebClient: Introduction to WebClient Working with asynchronous and streaming APIs Making requests Handling the response Lab: WebClient WebTestClient Testing WebFlux server endpoints Testing controllers or functions Define integration tests Introduction to Spring Reactive WebSockets Be familiar with the basics of WebSockets Understand the HTTP handshake and upgrade Name some of the advantages of WebSockets Defining the WebSocket WebSocket Message Handling WebSocketSession Implementing the WebSockethandler Creating a Browser WebSocket Client WebSocket STOMP Streaming (or Simple) text-orientated messaging protocol Introduce SockJS Connecting to the STOMP endpoint Configuring the message broker STOMP destinations Reactive WebSocket Reactive WebSocket support Implement the reactive WebSocketHandler BigData Introduce Big Data Explain the need for enhanced data storage Introduction to MongoDB JavaScript Object Notation Overview Introduce Binary JSON (BSON) Starting the database Creating Collections and Documents Executing ?simple? database commands Introduce the ObjectID Searching for documents using query operators Updating and deleting documents MongoDB Compass Spring and MongoDB MongoDB Support in Spring Data MongoClient and MongoTemplate Spring Data MongoDB configuration @EnableMongoRepositories Adding documents to the database The @Document and @Field annotations Polymorphism and the _class property The Criteria object Spring Data MongoDB MongoRepository Field naming strategy Using JSON queries to find documents The @PersistenceConstructor annotation Reactive Repositories with MongoDB Using reactive repositories ReactiveMongoTemplate RxJava or Reactor Additional course details: Nexus Humans Introduction to Reactive Spring (TT3355 ) 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 Reactive Spring (TT3355 ) 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 Security Professionals working with Kubernetes Clusters Container Orchestration Engineers DevOps Professionals Overview In this course, students will learn and practice essential Kubernetes concepts and tasks in the following sections: Cloud Security Fundamentals Cluster Hardening System Hardening Minimize Microservice Vulnerabilities Supply Chain Security Disaster Recovery Secure Back-up and Restore This class prepares students for the Certified Kubernetes Security Specialist (CKS) exam. Kubernetes is a Cloud Orchestration Platform providing reliability, replication, and stabilitywhile maximizing resource utilization for applications and services. By the conclusion of this hands-on, vendor agnostic training you will be equipped with a thorough understanding ofcloud security fundamentals, along with the knowledge, skills and abilities to secure a Kubernetes cluster, detect threats, and properly resolve a security catastrophe. This courseincludes hands-on instruction which develops skills and knowledge for securing container-based applications and Kubernetes platforms, during build, deployment, and runtime. We prioritizecovering all objectives and concepts necessary for passing the Certified Kubernetes Security Specialist (CKS) exam. You will be provided the components necessary to assemble your ownhigh availability Kubernetes environment and harden it for your security needs. Learning Your Environment Underlying Infrastructure Using Vim Tmux Cloud Security Primer Basic Principles Threat Analysis Approach CIS Benchmarks Securing your Kubernetes Cluster Kubernetes Architecture Pods and the Control Plane Kubernetes Security Concepts Install Kubernetes using kubeadm Configure Network Plugin Requirements Kubeadm Basic Cluster Installing Kubeadm Join Node to Cluster Kubeadm Token Manage Kubeadm Tokens Kubeadm Cluster Upgrade Securing the kube-apiserver Configuring the kube-apiserver Enable Audit Logging Falco Deploy Falco to Monitor System Calls Enable Pod Security Policies Encrypt Data at Rest Encryption Configuration Benchmark Cluster with Kube-Bench Kube-Bench Securing ETCD ETCD Isolation ETCD Disaster Recovery ETCD Snapshot and Restore Purge Kubernetes Purge Kubeadm 3Purge Kubeadm Image Scanning Container Essentials Secure Containers Creating a Docker Image Scanning with Trivy Trivy Snyk Security Manually Installing Kubernetes Kubernetes the Alta3 Way Deploy Kubernetes the Alta3 Way Validate your Kubernetes Installation Sonobuoy K8s Validation Test Kubectl (Optional) Kubectl get and sorting kubectl get kubectl describe Labels (Optional) Labels Labels and Selectors Annotations Insert an Annotation Securing your Application Scan a Running Container Tracee Security Contexts for Pods Understanding Security Contexts AppArmor Profiles AppArmor Isolate Container Kernels gVisor Pod Security Pod Security Policies Deploy a PSP Pod Security Standards Enable PSS Open Policy Agent (OPA) Admission Controller Create a LimitRange Open Policy Agent Policy as Code Deploy Gatekeeper User Administration Contexts Contexts Authentication and Authorization Role Based Access Control Role Based Access Control RBAC Distributing Access Service Accounts Limit Pod Service Accounts Securing Secrets Secrets Create and Consume Secrets Hashicorp Vault Deploy Vault Securing the Network Networking Plugins NetworkPolicy Deploy a NetworkPolicy mTLS Linkerd mTLS with istio istio Threat Detection Active Threat Analysis Host Intrusion Detection Deploy OSSEC Network Intrusion Detection Deploy Suricata Physical Intrusion Detection Disaster Recovery Harsh Reality of Security Deploy a Response Plan Kasten K10 Backups Deploy K10

Duration 3 Days 18 CPD hours Discover and explore how to use the fundamental building blocks of the Swift programming language. class will teach you the basic concepts of Swift programming, including syntax, logic, structures, functions, and patterns. It also includes detailed explanations of language syntax and coding exercises. Introduction to Swift Constants, Variables, and Data TypesOperatorsControl FlowStrings & FunctionsStructures & ClassesOptionalsCollectionsLoopsType CastingGuard StatementsScope & EnumerationsProtocolsClosuresExtensions

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.

Duration 5 Days 30 CPD hours This course is intended for This course is designed for Java developers who want to learn more about the specifications that comprise the world of Java Enterprise Edition (Java EE). Overview As a result of attending this course, you should be able to describe most of the specifications in Java EE 7 and create a component with each specification. You will be able to convert a Java SE program into a multi-tiered Java EE application. You should be able to demonstrate these skills: Describe the architecture of multi-tiered Java EE applications. Package Java EE applications and deploy to Red Hat JBoss Enterprise Application Platform with various tools. Create an Enterprise Java Bean instance. Manage the persistence of data using Java Persistence API. Create a web service using JAX-RS. Properly apply context scopes to beans and inject resources into Java Beans. Store and retrieve messages using the Java Messaging Service. Secure a Java EE application. Red Hat Application Development I: Programming in Java EE with exam (AD184) exposes experienced Java Standard Edition (Java SE) developers to the world of Java Enterprise Edition (Java EE). This course is based on Red Hat© Enterprise Application Platform 7.0. This course is a combination of Red Hat Application Development I: Programming in Java EE (AD183) and Red Hat Certified Enterprise Application Developer Exam (EX183). In this course, you will learn about the various specifications that make up Java EE. Through hands-on labs, you will transform a simple Java SE command line application into a multi-tiered enterprise application using various Java EE specifications, including Enterprise Java Beans, Java Persistence API, Java Messaging Service, JAX-RS for REST services, Contexts and Dependency Injection (CDI), and JAAS for securing the application. Transition to multi-tiered applications Describe Java EE features and distinguish between Java EE and Java SE applications. Package and deploying applications to an application server Describe the architecture of a Java EE application server, package an application, and deploy the application to an EAP server. Create Enterprise Java Beans Develop Enterprise Java Beans, including message-driven beans. Manage persistence Create persistence entities with validations. Manage entity relationships Define and manage JPA entity relationships. Create REST services Create REST APIs using the JAX-RS specification. Implement Contexts and Dependency Injection Describe typical use cases for using CDI and successfully implement it in an application. Create messaging applications with JMS Create messaging clients that send and receive messages using the JMS API. Secure Java EE applications Use JAAS to secure a Java EE application. Comprehensive review of Red Hat JBoss Development I: Java EE Demonstrate proficiency of the knowledge and skills obtained during the course. Additional course details: Nexus Humans Red Hat Application Development I: Programming in Java EE with exam (AD184) 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 Red Hat Application Development I: Programming in Java EE with exam (AD184) 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 3 Days 18 CPD hours Overview In this course you?ll learn how to: Containerize and deploy a new Python script Configure the deployment with ConfigMaps, Secrets and SecurityContexts Understand multi-container pod design Configure probes for pod health Update and roll back an application Implement services and NetworkPolicies Use PersistentVolumeClaims for state persistence And more In this vendor agnostic course, you will use Python to build, monitor and troubleshoot scalable applications in Kubernetes. Introduction Objectives Who You Are The Linux Foundation Linux Foundation Training Preparing Your System Course Registration Labs Kubernetes Architecture What Is Kubernetes? Components of Kubernetes Challenges The Borg Heritage Kubernetes Architecture Terminology Master Node Minion (Worker) Nodes Pods Services Controllers Single IP per Pod Networking Setup CNI Network Configuration File Pod-to-Pod Communication Cloud Native Computing Foundation Resource Recommendations Labs Build Container Options Containerizing an Application Hosting a Local Repository Creating a Deployment Running Commands in a Container Multi-Container Pod readinessProbe livenessProbe Testing Labs Design Traditional Applications: Considerations Decoupled Resources Transience Flexible Framework Managing Resource Usage Multi-Container Pods Sidecar Container Adapter Container Ambassador Points to Ponder Labs Deployment Configuration Volumes Overview Introducing Volumes Volume Spec Volume Types Shared Volume Example Persistent Volumes and Claims Persistent Volume Persistent Volume Claim Dynamic Provisioning Secrets Using Secrets via Environment Variables Mounting Secrets as Volumes Portable Data with ConfigMaps Using ConfigMaps Deployment Configuration Status Scaling and Rolling Updates Deployment Rollbacks Jobs Labs Security Security Overview Accessing the API Authentication Authorization ABAC RBAC RBAC Process Overview Admission Controller Security Contexts Pod Security Policies Network Security Policies Network Security Policy Example Default Policy Example Labs Exposing Applications Service Types Services Diagram Service Update Pattern Accessing an Application with a Service Service without a Selector ClusterIP NodePort LoadBalancer ExternalName Ingress Resource Ingress Controller Labs Troubleshooting Troubleshotting Overview Basic Troubleshooting Steps Ongoing (Constant) Change Basic Troubleshooting Flow: Pods Basic Troubleshooting Flow: Node and Security Basic Troubleshooting Flow: Agents Monitoring Logging Tools Monitoring Applications System and Agent Logs Conformance Testing More Resource Labs Additional course details: Nexus Humans Kubernetes for App Developers 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 Kubernetes for App Developers 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 3 Days 18 CPD hours This course is intended for Application developers who want to build cloud-native applications or redesign existing applications that will run on Google Cloud Platform Overview This course teaches participants the following skills: Use best practices for application development. Choose the appropriate data storage option for application data. Implement federated identity management. Develop loosely coupled application components or microservices. Integrate application components and data sources. Debug, trace, and monitor applications. Perform repeatable deployments with containers and deployment services. Choose the appropriate application runtime environment; use Google Container Engine as a runtime environment and later switch to a no-ops solution with Google App Engine flexible environment. Learn how to design, develop, and deploy applications that seamlessly integrate components from the Google Cloud ecosystem. This course uses lectures, demos, and hands-on labs to show you how to use Google Cloud services and pre-trained machine learning APIs to build secure, scalable, and intelligent cloud-native applications. Best Practices for Application Development Code and environment management. Design and development of secure, scalable, reliable, loosely coupled application components and microservices. Continuous integration and delivery. Re-architecting applications for the cloud. Google Cloud Client Libraries, Google Cloud SDK, and Google Firebase SDK How to set up and use Google Cloud Client Libraries, Google Cloud SDK, and Google Firebase SDK. Lab: Set up Google Client Libraries, Cloud SDK, and Firebase SDK on a Linux instance and set up application credentials. Overview of Data Storage Options Overview of options to store application data. Use cases for Google Cloud Storage, Cloud Firestore, Cloud Bigtable, Google Cloud SQL, and Cloud Spanner. Best Practices for Using Cloud Firestore Best practices related to using Cloud Firestore in Datastore mode for:Queries, Built-in and composite indexes, Inserting and deleting data (batch operations),Transactions,Error handling. Bulk-loading data into Cloud Firestore by using Google Cloud Dataflow. Lab: Store application data in Cloud Datastore. Performing Operations on Cloud Storage Operations that can be performed on buckets and objects. Consistency model. Error handling. Best Practices for Using Cloud Storage Naming buckets for static websites and other uses. Naming objects (from an access distribution perspective). Performance considerations. Setting up and debugging a CORS configuration on a bucket. Lab: Store files in Cloud Storage. Handling Authentication and Authorization Cloud Identity and Access Management (IAM) roles and service accounts. User authentication by using Firebase Authentication. User authentication and authorization by using Cloud Identity-Aware Proxy. Lab: Authenticate users by using Firebase Authentication. Using Pub/Sub to Integrate Components of Your Application Topics, publishers, and subscribers. Pull and push subscriptions. Use cases for Cloud Pub/Sub. Lab: Develop a backend service to process messages in a message queue. Adding Intelligence to Your Application Overview of pre-trained machine learning APIs such as Cloud Vision API and Cloud Natural Language Processing API. Using Cloud Functions for Event-Driven Processing Key concepts such as triggers, background functions, HTTP functions. Use cases. Developing and deploying functions. Logging, error reporting, and monitoring. Managing APIs with Cloud Endpoints Open API deployment configuration. Lab: Deploy an API for your application. Deploying Applications Creating and storing container images. Repeatable deployments with deployment configuration and templates. Lab: Use Deployment Manager to deploy a web application into Google App Engine flexible environment test and production environments. Execution Environments for Your Application Considerations for choosing an execution environment for your application or service:Google Compute Engine (GCE),Google Kubernetes Engine (GKE), App Engine flexible environment, Cloud Functions, Cloud Dataflow, Cloud Run. Lab: Deploying your application on App Engine flexible environment. Debugging, Monitoring, and Tuning Performance Application Performance Management Tools. Stackdriver Debugger. Stackdriver Error Reporting. Lab: Debugging an application error by using Stackdriver Debugger and Error Reporting. Stackdriver Logging. Key concepts related to Stackdriver Trace and Stackdriver Monitoring. Lab: Use Stackdriver Monitoring and Stackdriver Trace to trace a request across services, observe, and optimize performance.

Duration 5 Days 30 CPD hours This course is intended for Motivations: Use and manage containers from first principles & architect basic applications for Kubernetes Roles: general technical audiences & IT professionals CN251 is an intensive cloud native training bootcamp for IT professionals looking to develop skills in deploying and administering containerized applications in Kubernetes. Over the course of five days, students will start with learning about first principles for application containerization followed by learning how to stand up a containerized application in Kubernetes, and, finally, ramping up the skills for day-1 operating tasks for managing a Kubernetes production environment. CN251 is an ideal course for those who need to accelerate the development of their IT skills for a rapidly-changing technology landscape. Additional course details: Nexus Humans Cloud Native Operations Bootcamp 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 Cloud Native Operations Bootcamp 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 Professionals who need to maintain or set up a Kubernetes cluster Container Orchestration Engineers DevOps Professionals Overview Cluster architecture, installation, and configuration Rolling out and rolling back applications in production Scaling clusters and applications to best use How to create robust, self-healing deployments Networking configuration on cluster nodes, services, and CoreDNS Persistent and intelligent storage for applications Troubleshooting cluster, application, and user errors Vendor-agnostic cloud provider-based Kubernetes Kubernetes is a Cloud Orchestration Platform providing reliability, replication, and stability while maximizing resource utilization for applications and services. By the conclusion of this hands-on, vendor agnostic training you will go back to work with the knowledge, skills, and abilities to design, implement, and maintain a production-grade Kubernetes cluster. We prioritize covering all objectives and concepts necessary for passing the Certified Kubernetes Administrator (CKA) exam. You will be provided the components necessary to assemble your own high availability Kubernetes environment and configure, expand, and control it to meet the demands made of cluster administrators. Your week of intensive, hands-on training will conclude with a mock CKA exam that simulates the real exam. Cluster Architecture, Installation & Configuration Each student will be given an environment that allows them to build a Kubernetes cluster from scratch. After a detailed discussion on key architectural components and primitives, students will install and compare two production grade Kubernetes clusters. Review: Kubernetes Fundamentals After successfully instantiating their own Kubernetes Cluster, students will be guided through foundational concepts of deploying and managing applications in a production environment. Workloads & Scheduling After establishing a solid Kubernetes command line foundation, students will be led through discussion and hands-on labs which focus on effectively creating applications that are easy to configure, simple to manage, quick to scale, and able to heal themselves. Services & Networking Thoroughly understanding the underlying physical and network infrastructure of a Kubernetes cluster is an essential skill for a Certified Kubernetes Administrator. After an in-depth discussion of the Kubernetes Networking Model, students explore the networking of their cluster?s Control Plane, Workers, Pods, and Services. Storage Certified Kubernetes Administrators are often in charge of designing and implementing the storage architecture for their clusters. After discussing many common cluster storage solutions and how to best use each, students practice incorporating stateful storage into their applications. Troubleshooting A Certified Kubernetes Administrator is expected to be an effective troubleshooter for their cluster. The lecture covers a variety of ways to evaluate and optimize available log information for efficient troubleshooting, and the labs have students practice diagnosing and resolving several typical issues within their Kubernetes Cluster. Certified Kubernetes Administrator Practice Exam Just like the Cloud Native Computing Foundation CKA Exam, the students will be given two hours to complete hands-on tasks in their own Kubernetes environment. Unlike the certification exam, students taking the Alta3 CKA Practice Exam will have scoring and documented answers available immediately after the exam is complete, and will have built-in class time to re-examine topics that they wish to discuss in greater depth.

Duration 5 Days 30 CPD hours This course is intended for Anyone who plans to work with Kubernetes at any level or tier of involvement Any company or individual who wants to advance their knowledge of the cloud environment Application Developers Operations Developers IT Directors/Managers Overview All topics required by the CKAD exam, including: Deploy applications to a Kubernetes cluster Pods, ReplicaSets, Deployments, DaemonSets Self-healing and observable applications Multi-container Pod Design Application configuration via Configmaps, Secrets Administrate cluster use for your team A systematic understanding of Kubernetes architecture Troubleshooting and debugging tools Kubernetes networking and services Kubernetes is a Cloud Orchestration Platform providing reliability, replication, and stability while maximizing resource utilization for applications and services. By the conclusion of this hands-on training, you will go back to work with all necessary commands and practical skills to empower your team to succeed, as well as gain knowledge of important concepts like Kubernetes architecture and container orchestration. We prioritize covering all objectives and concepts necessary for passing the Certified Kubernetes Application Developer (CKAD) exam. You will command and configure a high availability Kubernetes environment (and later, build your own!) capable of demonstrating all ?K8s'' features discussed and demonstrated in this course. Your week of intensive, hands-on training will conclude with a mock CKAD exam that matches the real thing. Kubernetes Architecture Components Understand API deprecations Containers Define, build and modify container images Pods Master Services Node Services K8s Services YAML Essentials Creating a K8s Cluster kubectl Commands Kubernetes Resources Kubernetes Namespace Kubernetes Contexts Pods What is a Pod? Create, List, Delete Pods How to Access Running Pods Kubernetes Resources Managing Cloud Resource Consumption Multi-Container Pod Design Security Contexts Init Containers Understand multi-container Pod design patterns (e.g. sidecar, init and others) Pod Wellness Tracking Networking Packet Forwarding ClusterIP and NodePort Services Provide and troubleshoot access to applications via services Ingress Controllers Use Ingress rules to expose applications NetworkPolicy resource Demonstrate basic understanding of NetworkPolicies Network Plugins Defining the Service Mesh Service mesh configuration examples ReplicaSets Services ReplicaSet Function Deploying ReplicaSets Deployments Deployment Object Updating/Rolling Back Deployments Understand Deployments and how to perform rolling updates Deployment Strategies Use Kubernetes primitives to implement common deployment strategies (e.g. blue/green or canary) Scaling ReplicaSets Autoscaling Labels and Annotations Labels Annotations Node Taints and Tolerations Jobs The K8s Job and CronJob Understand Jobs and CronJobs Immediate vs. scheduled internal use Application Configuration Understanding and defining resource requirements, limits and quotas Config Maps Create & consume Secrets Patching Custom Resource Definition Discover and use resources that extend Kubernetes (CRD) Managing ConfigMaps and Secrets as Volumes Storage Static and dynamic persistent volumes via StorageClass K8s volume configuration Utilize persistent and ephemeral volumes Adding persistent storage to containers via persistent volume claims Introduction to Helm Helm Introduction Charts Use the Helm package manager to deploy existing packages Application Security Understand authentication, authorization and admission control Understand ServiceAccounts Understand SecurityContexts Application Observability and Maintenance Use provided tools to monitor Kubernetes applications How to Troubleshoot Kubernetes Basic and Advanced Logging Techniques Utilize container logs Accessing containers with Port-Forward Debugging in Kubernetes Hands on Labs: Define, build and modify container images Deploy Kubernetes using Ansible Isolating Resources with Kubernetes Namespaces Cluster Access with Kubernetes Context Listing Resources with kubectl get Examining Resources with kubectl describe Create and Configure Basic Pods Debugging via kubectl port-forward Imperative vs. Declarative Resource Creation Performing Commands inside a Pod Understanding Labels and Selectors Insert an Annotation Create and Configure a ReplicaSet Writing a Deployment Manifest Perform rolling updates and rollbacks with Deployments Horizontal Scaling with kubectl scale Implement probes and health checks Understanding and defining resource requirements, limits and quotas Understand Jobs and CronJobs Best Practices for Container Customization Persistent Configuration with ConfigMaps Create and Consume Secrets Understand the Init container multi-container Pod design pattern Using PersistentVolumeClaims for Storage Dynamically Provision PersistentVolumes with NFS Deploy a NetworkPolicy Provide and troubleshoot access to applications via services Use Ingress rules to expose applications Understand the Sidecar multi-container Pod design pattern Setting up a single tier service mesh Tainted Nodes and Tolerations Use the Helm package manager to deploy existing packages A Completed Project Install Jenkins Using Helm and Run a Demo Job Custom Resource Definitions (CRDs) Patching Understanding Security Contexts for Cluster Access Control Utilize container logs Advanced Logging Techniques Troubleshooting Calicoctl Deploy a Kubernetes Cluster using Kubeadm Monitoring Applications in Kubernetes Resource-Based Autoscaling Create ServiceAccounts for use with the Kubernetes Dashboard Saving Your Progress With GitHub CKAD Practice Drill Alta Kubernetes Course Specific Updates Sourcing Secrets from HashiCorp Vault Example CKAD Test Questions