726 Computing & Software Development Tools courses delivered Online

Duration 3 Days 18 CPD hours This course is intended for This course is geared for experienced Scala developers who are new to the world of machine learning and are eager to expand their skillset. Professionals such as data engineers, data scientists, and software engineers who want to harness the power of machine learning in their Scala-based projects will greatly benefit from attending. Additionally, team leads and technical managers who oversee Scala development projects and want to integrate machine learning capabilities into their workflows can gain valuable insights from this course Overview Working in a hands-on learning environment led by our expert instructor you'll: Grasp the fundamentals of machine learning and its various categories, empowering you to make informed decisions about which techniques to apply in different situations. Master the use of Scala-specific tools and libraries, such as Breeze, Saddle, and DeepLearning.scala, allowing you to efficiently process, analyze, and visualize data for machine learning projects. Develop a strong understanding of supervised and unsupervised learning algorithms, enabling you to confidently choose the right approach for your data and effectively build predictive models Gain hands-on experience with neural networks and deep learning, equipping you with the know-how to create advanced applications in areas like natural language processing and image recognition. Explore the world of generative AI and learn how to utilize GPT-Scala for creative text generation tasks, broadening your skill set and making you a more versatile developer. Conquer the realm of scalable machine learning with Scala, learning the secrets to tackling large-scale data processing and analysis challenges with ease. Sharpen your skills in model evaluation, validation, and optimization, ensuring that your machine learning models perform reliably and effectively in any situation. Machine Learning Essentials for Scala Developers is a three-day course designed to provide a solid introduction to the world of machine learning using the Scala language. Throughout the hands-on course, you?ll explore a range of machine learning algorithms and techniques, from supervised and unsupervised learning to neural networks and deep learning, all specifically crafted for Scala developers. Our expert trainer will guide you through real-world, focused hands-on labs designed to help you apply the knowledge you gain in real-world scenarios, giving you the confidence to tackle machine learning challenges in your own projects. You'll dive into innovative tools and libraries such as Breeze, Saddle, DeepLearning.scala, GPT-Scala (and Generative AI with Scala), and TensorFlow-Scala. These cutting-edge resources will enable you to build and deploy machine learning models for a wide range of projects, including data analysis, natural language processing, image recognition and more. Upon completing this course, you'll have the skills required to tackle complex projects and confidently develop intelligent applications. You?ll be able to drive business outcomes, optimize processes, and contribute to innovative projects that leverage the power of data-driven insights and predictions. Introduction to Machine Learning and Scala Learning Outcome: Understand the fundamentals of machine learning and Scala's role in this domain. What is Machine Learning? Machine Learning with Scala: Advantages and Use Cases Supervised Learning in Scala Learn the basics of supervised learning and how to apply it using Scala. Supervised Learning: Regression and Classification Linear Regression in Scala Logistic Regression in Scala Unsupervised Learning in Scala Understand unsupervised learning and how to apply it using Scala. Unsupervised Learning:Clustering and Dimensionality Reduction K-means Clustering in Scala Principal Component Analysis in Scala Neural Networks and Deep Learning in Scala Learning Outcome: Learn the basics of neural networks and deep learning with a focus on implementing them in Scala. Introduction to Neural Networks Feedforward Neural Networks in Scala Deep Learning and Convolutional Neural Networks Introduction to Generative AI and GPT in Scala Gain a basic understanding of generative AI and GPT, and how to utilize GPT-Scala for natural language tasks. Generative AI: Overview and Use Cases Introduction to GPT (Generative Pre-trained Transformer) GPT-Scala: A Library for GPT in Scala Reinforcement Learning in Scala Understand the basics of reinforcement learning and its implementation in Scala. Introduction to Reinforcement Learning Q-learning and Value Iteration Reinforcement Learning with Scala Time Series Analysis using Scala Learn time series analysis techniques and how to apply them in Scala. Introduction to Time Series Analysis Autoregressive Integrated Moving Average (ARIMA) Models Time Series Analysis in Scala Natural Language Processing (NLP) with Scala Gain an understanding of natural language processing techniques and their application in Scala. Introduction to NLP: Techniques and Applications Text Processing and Feature Extraction NLP Libraries and Tools for Scala Image Processing and Computer Vision with Scala Learn image processing techniques and computer vision concepts with a focus on implementing them in Scala. Introduction to Image Processing and Computer Vision Feature Extraction and Image Classification Image Processing Libraries for Scala Model Evaluation and Validation Understand the importance of model evaluation and validation, and how to apply these concepts using Scala. Model Evaluation Metrics Cross-Validation Techniques Model Selection and Tuning in Scala Scalable Machine Learning with Scala Learn how to handle large-scale machine learning problems using Scala. Challenges of Large-Scale Machine Learning Data Partitioning and Parallelization Distributed Machine Learning with Scala Machine Learning Deployment and Production Understand the process of deploying machine learning models into production using Scala. Deployment Challenges and Best Practices Model Serialization and Deserialization Monitoring and Updating Models in Production Ensemble Learning Techniques in Scala Discover ensemble learning techniques and their implementation in Scala. Introduction to Ensemble Learning Bagging and Boosting Techniques Implementing Ensemble Models in Scala Feature Engineering for Machine Learning in Scala Learn advanced feature engineering techniques to improve machine learning model performance in Scala. Importance of Feature Engineering in Machine Learning Feature Scaling and Normalization Techniques Handling Missing Data and Categorical Features Advanced Optimization Techniques for Machine Learning Understand advanced optimization techniques for machine learning models and their application in Scala. Gradient Descent and Variants Regularization Techniques (L1 and L2) Hyperparameter Tuning Strategies

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 2 Days 12 CPD hours This course is intended for The audience for this course is data professionals and data architects who want to learn about migrating data platform technologies that exist on Microsoft Azure and how existing SQL based workloads can be migrated and modernized. The secondary audience for this course is individuals who manage data platforms or develop applications that deliver content from the existing data platform technologies. Overview Understand Data Platform Modernization Choose the right tools for Data Migration Migrate SQL Workloads to Azure Virtual Machines Migrate SQL Workloads to Azure SQL Databases Migrate SQL Workloads to Azure SQL Database Managed Instance In this course, the students will explore the objectives of data platform modernization and how it is suitable for given business requirements. They will also explore each stage of the data platform modernization process and define what tasks are involved at each stage, such as the assessment and planning phase. Students will also learn the available migration tools and how they are suitable for each stage of the data migration process. The student will learn how to migrate to the three target platforms for SQL based workloads; Azure Virtual Machines, Azure SQL Databases and Azure SQL Database Managed Instances. The student will learn the benefits and limitations of each target platform and how they can be used to fulfil both business and technical requirements for modern SQL workloads. The student will explore the changes that may need to be made to existing SQL based applications, so that they can make best use of modern data platforms in Azure. Introducing Data Platform Modernization Understand Data Platform Modernization Understanding the stages of migration Data Migration Paths Choose the right tools for Data Migration Discover the Database Migration Guide Build your data estate inventory using Map Toolkit Identify Migration candidates using Data Migration Assistant Evaluate a Data workload using Database Experimentation Assistant Data Migration using Azure Database Migration Service Migrate non-SQL Server workloads to Azure using SQL Migration Assistant Migrating SQL Workloads to Azure Virtual Machines Considerations of SQL Server to Azure VM Migrations SQL Workloads to Azure VM Migration Options Implementing High Availability and Disaster Recovery Scenarios Migrate SQL Workloads to Azure SQL Databases Choose the right SQL Server Instance option in Azure Migrate SQL Server to Azure SQL DB offline Migrate SQL Server to Azure SQL DB online Load and Move data to Azure SQL Database Migrate SQL Workloads to Azure SQL Database Managed Instance Evaluate migration scenarios to SQL Database Managed Instance Migrate to SQL Database Managed instance Load and Move data to SQL Database Managed instance Application Configuration and Optimization

Duration 5 Days 30 CPD hours This course is intended for Sr. Systems Administrator Cloud Engineer Systems Engineer Sr. Network Administrator Sr. Network Engineer Cloud Specialist Cloud Project Manager Overview After completion of this course you will be able to describe: Cloud architecture and design Security within the cloud Automation and virtualization Troubleshooting and Disaster recovery High availability  This course covers in depth the skills and abilities needed to operate in the cloud, validating that candidates have the technical experience needed to deploy, secure, and automate environments regardless of the vendor solution. Understanding Cloud Concepts Topic 1A: Recognize Cloud Concepts Topic 1B: Recognize Cloud Terms Topic 1C: Understand the Troubleshooting Methodology Planning and Designing a Cloud Environment Topic 2A: Meet Cloud Business Requirements Topic 2B: Design Capacity Planning and Requirements Administering Cloud Resources Topic 3A: Manage Cloud Administration Topic 3B: Manage Compute Resources in the Cloud Topic 3C: Manage Memory Resources Managing Cloud Storage Topic 4A: Understand Cloud Storage Types Topic 4B: Configure Cloud Storage Solutions Topic 4C: Configure Cloud Storage Protocols and RAID Managing Networks in the Cloud Topic 5A: Deploying Cloud Network Services Topic 5B: Identify Cloud Network Infrastructure Components Securing and Troubleshooting Networks in the Cloud Topic 6A: Secure a Network in a Cloud Environment Topic 6B: Troubleshooting Cloud Connectivity Managing Cloud Migrations and Troubleshooting Cloud Deployments Topic 7A: Manage Cloud Migrations Topic 7B: Troubleshoot Cloud Deployment and Migration Issues Managing Cloud Automation and Orchestration Topic 8A: Understand Cloud Automation and Orchestration Techniques Topic 8B: Troubleshoot Automation and Orchestration in the Cloud Understanding Cloud Security Concepts Topic 9A: Administer Identity and Access Management in the Cloud Topic 9B: Manage Cloud Operating System and Application Security Topic 9C: Manage Data Security and Compliance in the Cloud Managing Cloud Security Topic 10A: Implement Security Measures in the Cloud Domain Topic 10B: Troubleshoot Cloud Security Managing Cloud Performance Topic 11A: Operate Efficiently in the Cloud Topic 11B: Accomplish Cloud Operations Tasks Topic 11C: Optimize Cloud Resources Topic 11D: Troubleshoot Common Cloud Performance Problems Managing Maintenance in the Cloud Topic 12A: Configure Logs, Monitoring, and Alerting for Cloud Services Topic 12B: Manage Backup and Restore in the Cloud Implementing High Availability and Disaster Recovery in the Cloud Topic 13A: Understand High Availability and Scaling in the Cloud Topic 13B: Manage Disaster Recovery in the Cloud Topic 13C: Incident Response Additional course details: Nexus Humans Cloud Fundamentals 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 Fundamentals 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 is an intermediate course for experienced DBAs and technical individuals, with experience on other relational database platforms, who plan, implement, and maintain Db2 11.1 for Linux, UNIX, and Windows databases. These skills can also be utilize to support cloud based databases using Db2 on Cloud or Db2 Hosted environments. Overview Please refer to course overview This course teaches you to perform, basic and advanced, database administrative tasks using Db2 11.1. These tasks include creating and populating databases and implementing a logical design to support recovery requirements. The access strategies selected by the Db2 Optimizer will be examined using the Db2 Explain tools. Various diagnostic methods will be presented, including using various db2pd command options. Students will learn how to implement automatic archival for database logs and how to plan a redirected database restore to relocate either selected table spaces or an entire database. The REBUILD option of RESTORE, which can build a database copy with a subset of the tablespaces, will be discussed. We will also cover using the TRANSPORT option of RESTORE to copy schemas of objects between two Db2 databases. The selection of indexes to improve application performance and the use of SQL statements to track database performance and health will be covered. This course provides a quick start to Db2 database administration skills for experienced relational Database Administrators (DBA). Overview of Db2 11Command Line Processor (CLP) and GUI UsageThe Db2 EnvironmentCreating Databases and Data PlacementCreating Database ObjectsMoving DataBackup and RecoveryLocks and ConcurrencyDatabase Maintenance, Monitoring and Problem DeterminationSecurityDatabase Rebuild SupportDb2 Database and Table Space RelocationUsing Explain ToolsUsing Indexes for PerformanceAdvanced Monitoring

Duration 5 Days 30 CPD hours This course is intended for Data Warehouse Administrator Database Administrators Database Designers Support Engineer Technical Administrator Overview Back up, restore, and patch DBCS database deployments Describe the DBaaS and on-premises Oracle Database architectures Manage database instances Manage UNDO data Move data between databases Implement basic backup and recovery procedures Monitor and tune database performance Tune SQL to improve performance Manage resources with Oracle Database Resource Manager Create pluggable databases (PDBs) Configure the Oracle network environment Administer user security and implement auditing Create and manage tablespaces Manage storage space Create and manage Database as a Cloud Service (DBCS) database deployments Register databases and manage performance with Enterprise Manager Cloud Control The Oracle Database 12c R2: Administration Workshop Ed 3 course is designed to provide students with a firm foundation in administration of an Oracle Database. In this course students will gain a conceptual understanding of Oracle Database architecture and learn how to manage an Oracle Database in an effective and efficient manner. Exploring Oracle Database Architecture Introducing Oracle Database Relation Database Models Oracle SQL and PL/SQL Oracle Database Server Architecture Connecting to Oracle Databases Oracle Database Tools Oracle-Supplied User Accounts Querying the Oracle Data Dictionary Managing Database Instances Initialization Parameter Files Starting Up Oracle Databases Shutting Down Oracle Databases Opening and Closing PDBs Working with the Automatic Diagnostic Repository (ADR) Querying Dynamic Performance Views Creating PDBs Methods and Tools to Create PDBs Creating PDBs from Seed with SQL*Plus Cloning PDBs with SQL*Plus Unplugging and Pluggin In PDBs with SQL*Plus Dropping PDBs with SQL*Plus Configuring the Oracle Network Environment Oracle Net Services How Listeners Work Configuring Listeners for Dynamic Service Registration Configuring Listeners for Static Service Registration Configuring Local Naming for Connections Testing Oracle Net Connectivity with tnsping Configuring Communication Between Databases Dedicated Versus Shared Server Configurations Administering User Security Creating Users Granting Privileges Creating and Granting Roles Revoking Privileges and Roles Creating and Assigning Profiles Authenticating Users Assigning Quotas to Users Applying the Principal of Least Privilege Creating and Managing Tablespaces How Table Data is Stored Creating Tablespaces in SQL*Plus Altering and Dropping Tablespaces in SQL*Plus Viewing Tablespace Information in SQL*Plus Implementing Oracle Managed Files Moving and Renaming Online Data Files in SQL*Plus Managing Storage Space Oracle Database Space Management Features Block Space Management Row Chaining and Migration Free Space Management Within Segments Types of Segments Allocating Extents Understanding Deferred Segment Creation Space-Saving Features Managing UNDO Data Undo Data: Overview Transactions and Undo Data Storing Undo Information Comparing Undo Data and Redo Data Managing Undo Local Undo Mode Versus Shared Undo Mode Configuring Undo Retention Categories of Undo Moving Data Moving Data: General Architecture Oracle Data Pump: Overview Oracle Data Pump: Benefits Data Pump Export and Import Clients Data Pump Utility: Interfaces and Modes Data Pump Import: Transformations SQL*Loader Overview Loading Methods Backup and Recovery Concepts DBA Responsibilities Categories of Failure Understanding Instance Recovery Understanding Types of Backups Comparing Complete and Incomplete Recovery Oracle Data Protection Solutions Flashback Technology Monitoring and Tuning Database Performance Managing Performance Activities Performance Planning Considerations Database Maintenance Automatic Workload Repository (AWR) Automatic Database Diagnostic Monitor Performance Monitoring Performance Tuning Methodology Database Server Statistics and Metrics SQL Tuning SQL Tuning Process Oracle Optimizer Optimizer Statistics SQL Plan Directives Adaptive Execution Plans SQL Tuning Advisor SQL Access Advisor SQL Performance Analyzer Oracle Database Resource Manager Oracle Database Resource Manager: Overview Resource Manager Elements Using Resource Manager to Allocate Resources Creating a Simple Resource Plan Creating a Complex Resource Plan Using the Active Session Pool Feature Limiting CPU Utilization at the Database Level Limiting CPU Utilization at the Server Level Enterprise Manager Cloud Control Controlling the Enterprise Manager Cloud Control Framework Starting the Enterprise Manager Cloud Control Framework Stopping the Enterprise Manager Cloud Control Framework Introduction to Oracle Database Cloud Service Oracle Cloud: Overview Database Cloud Service Offerings DBCS Architecture Features and Tooling Additional Database Configuration Options Creating DBCS Database Deployments Automated Database Provisioning Creating a Database Deployment How SSH Key Pairs are Used Creating an SSH Key Pair Storage Used for Database Files Managing DBCS Database Deployments Cloud Tooling Accessing Tools and Features from the DBCS Console Managing the Compute Node Associated With a Database Deployment Managing Network Access to DBCS Enabling Access to a Compute Node Port Scaling a Database Deployment Backing Up and Restoring DBCS Database Deployments Backing Up and Recovering Databases on DBCS Backup Destination Choices Backup Configuration Creating an On-Demand Backup Customizing the Backup Configuration Performing Recovery by Using the Console Performing Recovery by Using the dbaascli Utility Patching DBCS Database Deployments Patching DBCS Using the DBCS Console to Manage Patches Using the dbaascli Utility to Manage Patches Creating Master Encryption Keys for PDBs CDB and PDB Master Encryption Keys Determining Whether You Need to Create and Activate and Encryption Key for a PDB Creating and Activating an Encryption Key Tablespace Encryption by Default Tablespace Encryption by Default in DBCS Transparent Data Encryption (TDE) Overview Components of TDE Using TDE Defining the Keystore Location Controlling Tablespace Encryption by Default Managing the Software Keystore and Master Encryption Key Managing the Keystore in CDBs and PDBs Additional course details: Nexus Humans Oracle Database 12c R2 - Administration Workshop Ed 3 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 Oracle Database 12c R2 - Administration Workshop Ed 3 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 Administrator Architect Database Administrator Overview To provide an acceptable response time to users and manage resources effectively, you learn how to monitor performance and manage resources within the multitenant container database and its pluggable databases, and within each pluggable database. Another important aspect is the data movement between non-CDBs and pluggable databases, and between pluggable databases. It is also important to understand the procedures of upgrading an Oracle Database multitenant container database or an Oracle Database pluggable database. Finally, students discover the way multitenant container database and pluggable databases are created and monitored in the Cloud. This course covers all aspects of the multitenant architecture, providing detailed information on the components of an Oracle multitenant container database and its regular and application pluggable databases. You learn why and how to create and manage a multitenant container database and its regular and application pluggable databases, with storage structures appropriate for the business applications. You practice cold and hot cloning, plugging unplugged pluggable databases in multitenant container databases using various methods. CDB BasicsCDB and Regular PDBsApplication PDBs and Application InstallationPDB CreationCDB and PDB ManagementStorageSecurityBackup and DuplicateRecovery and FlashbackPerformance MonitoringResources AllocationData MovementUpgrade methods

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

Duration 1 Days 6 CPD hours This course is intended for This course is intended for: Solutions architects, cloud engineers, including security engineers, delivery and implementation engineers, professional services, and Cloud Center of Excellence (CCOE) Overview In this course, you will learn to: Design and implement a secure network infrastructure Design and implement compute security Design and implement a logging solution Currently, the average cost of a security breach can be upwards of $4 million. AWS Security Best Practices provides an overview of some of the industry best practices for using AWS security and control types. This course helps you understand your responsibilities while providing valuable guidelines for how to keep your workload safe and secure. You will learn how to secure your network infrastructure using sound design options. You will also learn how you can harden your compute resources and manage them securely. Finally, by understanding AWS monitoring and alerting, you can detect and alert on suspicious events to help you quickly begin the response process in the event of a potential compromise. Module 1: AWS Security Overview Shared responsibility model Customer challenges Frameworks and standards Establishing best practices Compliance in AWS Module 2: Securing the Network Flexible and secure Security inside the Amazon Virtual Private Cloud (Amazon VPC) Security services Third-party security solutions Module 3: Amazon EC2 Security Compute hardening Amazon Elastic Block Store (EBS) encryption Secure management and maintenance Detecting vulnerabilities Using AWS Marketplace Module 4: Monitoring and Alerting Logging network traffic Logging user and Application Programming Interface (API) traffic Visibility with Amazon CloudWatch Enhancing monitoring and alerting Verifying your AWS environment Additional course details: Nexus Humans AWS Security Best Practices 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 AWS Security Best Practices 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.