212 Mac courses in Walkden

UNIX Virtualization and High Availability course description This course covers administering UNIX enterprise-wide with an emphasis on virtualization and high availability. What will you learn Manage Virtual Machines. Manage containers. Manage HA clusters. Manage HA cluster storage. UNIX Virtualization and High Availability course details Who will benefit: Enterprise-level UNIX professional. UNIX professionals working with virtualization and/or High availability. Prerequisites: Linux network administration 2 (LPIC-2) Duration 5 days UNIX Virtualization and High Availability course contents VIRTUALIZATION Virtualization concepts and theory Terminology, Pros and Cons of virtualization, variations of Virtual Machine monitors, migration of physical to VMs, migration of VMs between host systems, cloud computing. Xen Xen architecture, networking and storage, Xen configuration, Xen utilities, troubleshooting Xen installations, XAPI, XenStore, Xen Boot Parameters, the xm utility. KVM KVM architecture, networking and storage, KVM configuration, KVM utilities, troubleshooting KVM installations. Other virtualization solutions OpenVZ and LXC, other virtualization technologies, virtualization provisioning tools. Libvirt and Related Tools libvirt architecture, networking and storage, basic technical knowledge of libvirt and virsh, oVirt. Cloud Management Tools Basic feature knowledge of OpenStack and CloudStack, awareness of Eucalyptus and OpenNebula. Containers Containers versus VMs, Docker, Kubernetes. Load balanced clusters of LVS/IPVS, VRRP, configuration of keepalived, configuration of ldirectord, backend server network configuration. HAProxy, configuration of HAProxy. Failover clusters Pacemaker architecture and components (CIB, CRMd, PEngine, LRMd, DC, STONITHd), Pacemaker cluster configuration, Resource classes (OCF, LSB, Systemd, Upstart, Service, STONITH, Nagios), Resource rules and constraints (location, order, colocation), Advanced resource features (templates, groups, clone resources, multi-state resources), Pacemaker management using pcs, Pacemaker management using crmsh, configuration and management of corosync in conjunction with Pacemaker, other cluster engines (OpenAIS, Heartbeat, CMAN). HIGH AVAILABILITY CLUSTER STORAGE DRBD/cLVM DRBD resources, states and replication modes, configuration of DRBD resources, networking, disks and devices, configuration of DRBD automatic recovery and error handling, management of DRBD using drbdadm. drbdsetup and drbdmeta, Integration of DRBD with Pacemaker, cLVM, integration of cLVM with Pacemaker. Clustered File Systems Principles of cluster file systems. Create, maintain and troubleshoot GFS2 file systems in a cluster, create, maintain and troubleshoot OCFS2 file systems in a cluster, Integration of GFS2 and OCFS2 with Pacemaker, the O2CB cluster stack, other commonly used clustered file systems.

Linux virtualization and HA training course description The LPIC-3 certification is the culmination of LPI's multi -level professional certification program. LPIC-3 is designed for the enterprise-level Linux professional and represents the highest level of professional, distribution neutral Linux certification within the industry. LPIC-3 304 covers administering Linux enterprise-wide with an emphasis on virtualization and high availability. At SNT we have enhanced the contents of the course by covering containers. What will you learn Manage Virtual Machines. Manage containers. Manage HA clusters. Manage HA cluster storage. Linux virtualization and HA training course details Who will benefit: Linux professionals working with virtualization and/or High availability. Prerequisites: Linux network administration 2 (LPIC-2) Duration 5 days Linux virtualization and HA training course contents VIRTUALIZATION Virtualization concepts and theory Terminology, Pros and Cons of virtualization, variations of Virtual Machine monitors, migration of physical to VMs, migration of VMs between host systems, cloud computing. Xen Xen architecture, networking and storage, Xen configuration, Xen utilities, troubleshooting Xen installations, XAPI, XenStore, Xen Boot Parameters, the xm utility. KVM KVM architecture, networking and storage, KVM configuration, KVM utilities, troubleshooting KVM installations. Other virtualization solutions OpenVZ and LXC, other virtualization technologies, virtualization provisioning tools. Libvirt and Related Tools libvirt architecture, networking and storage, basic technical knowledge of libvirt and virsh, oVirt. Cloud Management Tools Basic feature knowledge of OpenStack and CloudStack, awareness of Eucalyptus and OpenNebula. Containers Containers versus VMs, Docker, Kubernetes. Load balanced clusters of LVS/IPVS, VRRP, configuration of keepalived, configuration of ldirectord, backend server network configuration. HAProxy, configuration of HAProxy. Failover clusters Pacemaker architecture and components (CIB, CRMd, PEngine, LRMd, DC, STONITHd), Pacemaker cluster configuration, Resource classes (OCF, LSB, Systemd, Upstart, Service, STONITH, Nagios), Resource rules and constraints (location, order, colocation), Advanced resource features (templates, groups, clone resources, multi-state resources), Pacemaker management using pcs, Pacemaker management using crmsh, configuration and management of corosync in conjunction with Pacemaker, other cluster engines (OpenAIS, Heartbeat, CMAN). HIGH AVAILABILITY CLUSTER STORAGE DRBD/cLVM DRBD resources, states and replication modes, configuration of DRBD resources, networking, disks and devices, configuration of DRBD automatic recovery and error handling, management of DRBD using drbdadm. drbdsetup and drbdmeta, Integration of DRBD with Pacemaker, cLVM, integration of cLVM with Pacemaker. Clustered File Systems Principles of cluster file systems. Create, maintain and troubleshoot GFS2 file systems in a cluster, create, maintain and troubleshoot OCFS2 file systems in a cluster, Integration of GFS2 and OCFS2 with Pacemaker, the O2CB cluster stack, other commonly used clustered file systems.

Java training course description A comprehensive introduction of the Java language and environment. It is important to note that the course will assume that the delegates are already familiar with the C language as this enables more advanced features of the Java language to be covered in the course. The course will also give an overview of areas related to programming in Java. What will you learn Describe the Java architecture. Write Java applets and applications. Debug Java programs. Examine existing code and determine its function. Use multimedia extensions, the awt, multithreading, exceptions within Java Java training course details Who will benefit: Those wishing to program in Java. Prerequisites: Complete C programming Duration 5 days Java training course contents Review of UNIX fundamentals What is Java? What Java is, history of Java, reasons for success. The Java Virtual Machine, Bytecodes, getting up and running with Java, Java resources. Simple Java applications. C features in Java Java data structures, Java flow control, differences from C, arrays, strings and packages. OO features in Java Java classes and objects, inheritance, overloading, packages. Differences from C++. Java applets Applications vs. applets, HTML, the applet tag, applet methods, life cycle, testing and debugging. Multimedia applets Images, sounds, fonts, colours and animation. Java products The JDK in detail, other development environments. Javabeans and JDBC overviews. Abstract Window Toolkit JFC and Swing versus AWT. Event handling (JDK 1.1), GUIs, panels, buttons, lists, scrollbars, text areas, frames… Exception handling and multithreading Handling exceptions. Starting, pausing, stopping threads, producers, consumers, monitoring. More standard classes Java file I/O, Streams, The system class. The networking model, java.net classes. Security and Java Types of attack, the security manager, craplets, securing the network. Integrating legacy code with Java

Complete C programming training course description A hands-on introduction to programming in the ANSI C programming language. The course initially moves at a fast pace in order to spend as much time as possible on the subject of pointers - the area which cause the most bugs in C programs. What will you learn Write ANSI C programs Use the C libraries Debug C programs Examine existing code and determine its function. Complete C programming training course details Who will benefit: Programmers wishing to learn C. Programmers wishing to learn C++ or Java. Prerequisites: None, although experience in another high level language would be useful. Duration 5 days Complete C programming training course contents Getting started The compilation process, comments, main(), statement blocks, printf(). C data types and operators char, int, float and double, qualifiers, arithmetic and assignment operators, precedence, Associativity. Basic I/O C libraries, stdin and stdout, getchar(), putchar(), printf() formatting. Flow control if else, dangling elses, else if, while and for loops. switch statements, the null statement, break, continue and gotos. Functions Function calls, arguments and return types, function declarations (prototypes), function definitions, scope of variables. The preprocessor Preprocessor actions, macros, #include. Libraries and their relationship with header files. Conditional compilation. More data types and operators Logical, bitwise and other operators, type conversion, casting, typedefs and access modifiers. Arrays Declaring and handling arrays, common gotchas, multidimensional arrays. Pointers What are pointers? Why they are so important, declaring and using pointers,The three uses of the *,pointer example - scanf, pointers as arguments. More pointers Golden rules of pointers and arrays, pointers to arrays, pointer arithmetic, arrays of pointers, multiple indirection. Character/string manipulation Arrays of characters, string definition, working with strings, String library. Program arguments argc and argv, example uses,char *argv[] versus char ** argv. Program structure and storage classes Globals (externals), multi source programs, the look of a C program. Structures Declaration, the . and - operators, unions and bitfields. Library functions File handling, fopen and fclose, reading from and writing to files, fseek().calloc() and malloc()

Network DevOps course description This course is not a soft skills course covering the concepts of DevOps but instead concentrates on the technical side of tools and languages for network DevOps. Particular technologies focussed on are ansible, git and Python enabling delegates to leave the course ready to starting automating their network. Hands on sessions follow all major sections. More detailed courses on individual aspects of this course are available. What will you learn Evaluate network automation tools. Automate tasks with ansible. Use git for version control. Use Python to manage network devices. Use Python libraries for network devices. Network DevOps course details Who will benefit: Administrators automating tasks. Prerequisites: TCP/IP Foundation Duration 5 days Network DevOps course contents What is DevOps Programming and automating networks, networks and clouds, AWS, OpenStack, SDN, DevOps for network operations. Initial configuration Configuring SSH, ZTP, POAP. Hands on Initial lab configuration. Getting started with ansible The language, the engine, the framework. Uses of ansible, orchestration. The architecture, Controlling machines, nodes, Agentless, SSH, modules. Configuration management, inventories, playbooks, modules, roles. Hands on Installing ansible, running ad hoc commands. Ansible playbooks ansible-playbook, YAML, plays, tasks, handlers, modules. Playbook variables. Register module, debug module. Hands on Running playbooks. Ansible Inventories /etc/ansible/hosts, hosts, groups, static inventories, dynamic inventories. Inventory variables, external variables. Limiting hosts. Hands on Static inventories, variables in inventory files. Ansible modules for networking Built in modules, custom modules, return values. Core modules for network operations. Cisco and/or Juniper modules. ansible_connection. Ansible 2.6 CLI. Hands on Using modules. Ansible templating and roles aConfiguration management, full configurations, partial configurations. The template module, the assemble module, connection: local, Jinja2 templates, variables, if, for, roles. Hands on Generating multiple configurations from a template. Network programming and modules Why use Python? Why use ansible? alternatives, ansible tower, Linux network devices. Programming with Python Python programming Functions. Classes, objects and instances, modules, libraries, packages. Python strings, Python file handling, pip list, pip instal. Hands on Python programming with pyping. More Python programming Functions. Classes, objects and instances, modules, libraries, packages. Python strings, Python file handling, pip list, pip install. Hands on Python programming with pyping. Git Distributed version control, repositories, Git and GitHub, Alternatives to GitHub, Installing git, git workflows, creating repositories, adding and editing files, branching and merging, merge conflicts. Hands on working with Git. Python and networking APIs, Sockets, Telnetlib, pysnmp, ncclient, ciscoconfparse. Paramiko SSH and Netmiko Integrating Python and network devices using SSH. Netmiko, Netmiko methods. Hands on Netmiko. NAPALM What is NAPALM, NAPALM operations, getters, Replace, merge, compare, commit, discard. Hands on Configuration with NAPALM. Integrating ansible and NAPALM. Python and REST REST APIs, enabling the REST API. Accessing the REST API with a browser, cURL, Python and REST, the request library. Hands on Using a REST API with network devices.

Network automation course description This course is not a soft skills course covering the concepts of DevOps but instead concentrates on the technical side of tools and languages for network DevOps. Particular technologies focussed on are ansible, git and Python enabling delegates to leave the course ready to starting automating their network. Hands on sessions follow all major sections. More detailed courses on individual aspects of this course are available. What will you learn Evaluate network automation tools. Automate tasks with ansible. Use git for version control. Use Python to manage network devices. Use Python libraries for network devices. Network automation course details Who will benefit: Network engineers. Prerequisites: TCP/IP foundation for engineers. Duration 5 days Network automation course contents What is DevOps Programming and automating networks, networks and clouds, AWS, OpenStack, SDN, DevOps for network operations. Initial configuration Configuring SSH, ZTP, POAP. Hands on Initial lab configuration. Getting started with ansible The language, the engine, the framework. Uses of ansible, orchestration. The architecture, Controlling machines, nodes, Agentless, SSH, modules. Configuration management, inventories, playbooks, modules, roles. Hands on Installing ansible, running ad hoc commands. Ansible playbooks ansible-playbook, YAML, plays, tasks, handlers, modules. Playbook variables. Register module, debug module. Hands on Running playbooks. Ansible Inventories /etc/ansible/hosts, hosts, groups, static inventories, dynamic inventories. Inventory variables, external variables. Limiting hosts. Hands on Static inventories, variables in inventory files. Ansible modules for networking Built in modules, custom modules, return values. Core modules for network operations. Cisco and/ or Juniper modules. ansible_connection. Ansible 2.6 CLI. Hands on Using modules. Ansible templating and roles Configuration management, full configurations, partial configurations. The template module, the assemble module, connection: local, Jinja2 templates, variables, if, for, roles. Hands on Generating multiple configurations from a template. Network programming and modules Why use Python? Why use ansible? alternatives, ansible tower, Linux network devices. Programming with Python Scripting versus application development, Python interactive mode, Python scripts, Python 2.7 vs Python 3. A simple Python script. Variables, loops, control statements, operators. PEP style guide. Python IDEs. Hands on Simple Python programs. More Python programming Functions. Classes, objects and instances, modules, libraries, packages. Python strings, Python file handling, pip list, pip install, Hands on Python programming with pyping. Git Distributed version control, repositories, Git and GitHub, Alternatives to GitHub, Installing git, git workflows, creating repositories, adding and editing files, branching and merging, merge conflicts. Hands on working with Git. Python and networking APIs, Sockets, Telnetlib, pysnmp, ncclient, ciscoconfparse. Paramiko SSH and Netmiko Integrating Python and network devices using SSH. Netmiko, Netmiko methods. Hands on Netmiko. PyEZ Juniper, NETCONF, installing PyEZ, a first pyEZ script, pyEZ configuration management. Hands on Juniper configuration management with pyEZ. NAPALM What is NAPALM, NAPALM operations, getters, Replace, merge, compare, commit, discard. Hands on Configuration with NAPALM. Integrating ansible and NAPALM. Python and REST REST APIs, enabling the REST API. Accessing the REST API with a browser, cURL, Python and REST, the request library. Hands on Using a REST API with network devices.

Network management technologies course description A comprehensive tour of the available network management technologies available for todays networks. The course starts with basic tools such as syslog along with Python network automation. SNMP is then covered with the *flow technologies and streaming telemetry. Configuration management with ansible, Python, NETCONF and RESTCONF is then studied. The final part of the course looks at SDN. Hands on sessions are used throughout to reinforce the theory rather than teach specific manufacturer equipment. Note that sections are available as individual courses. What will you learn Evaluate network management technologies. Evaluate network management technologies. Recognise the weaknesses of SNMP versus NETCONF and streaming telemetry. Explain the role of NETCONF and RESTCONF. Compare & contrast *flow and streaming telemetry. Explain the role of SDN in network management. Automate network configuration with ansible and Python. Network management technologies course details Who will benefit: Those wishing to manage networks. (Previous Python experience is NOT needed) Prerequisites: Intro to data comms Duration 5 days Network management technologies course content Basic network management Network management What is network management? Benefits, issues. FCAPS model. Fault management, Configuration management, accounting, performance, security. What to manage, what not to manage. Managing network devices, managing servers. Monitoring networks Traditional network tools Ping..., SSH, syslog, TFTP for configurations. nmap. Wireshark. CLI. Web based management. Splunk. Nessus, snort, Kali. Hands on syslog, network inventories. Network automation using the CLI Programming and automating networks, netOps. Python, Git. Python network modules, SSH, paramiko, netmiko. EVE-NG. Hands onPython network modules. Structured versus unstructured data Problems with automation and unstructured data. XML, JSON, YAML. The role of YANG. Hands on Parsing data. SNMP SNMP architecture, SNMP MIBs, SMI, the SNMP protocol, polling security. Configuring SNMP. SNMPv1, v2, v3, SNMP security. Which version should you use? MIBs and MIB structure. mib-2, extra parts of mib-2, Private enterprise MIBs. Summary: What SNMP is good/bad at. Hands on Configuring agents and a NMS. MIB browsing. Server management Microsoft, Linux, application polling. WMI vs SNMP. Hands on: Application polling. Performance management *flow Polling, push vs pull, netflow, sflow, IPFIX, *flow. Flows. Where to monitor traffic. Comparing *flow with SNMP. Architecture: Generators and collectors. When flows are exported. NetFlow reporting products. SolarWinds. Hands on Netflow configuration. Collectors. Streaming telemetry Model driven telemetry, periodic/on change. Structured data. Telemetry protocol stack. gRPC and gNMI. Protobuf. gNMI operations. Telemetry architecture. Telegraf, databases, Grafana. Hands on Telemetry example. Configuration management Configuration management tools Chef, puppet, ansible, saltstack. Ansible architecture, controlling machines, nodes, agentless, SSH, modules. Inventories, playbooks, modules, network modules, jinja2 templates. Hands on Network configuration with ansible. NETCONF What is NETCONF? Protocol stack, Data stores, traffic flows, validating configurations, rollback. YANG data models and how YANG is used by NETCONF. XML. Explorers and other tools. Hands on anx, Python and NETCONF. RESTCONF The REST API, HTTP, What is RESTCONF? Tools including Postman. Comparison with NETCONF. Hands on Configuration with RESTCONF. Python network automation: configuration SSH issues. Using structured data. Jinja2. ncclient, requests, NAPALM, Nornir. Automated testing. Hands on Python network device configuration with nornir. Software Defined Networks and orchestration Classic SDN What is SDN? benefits. SDN architecture. SDN applications, SDN switches, SDN controllers, Network Operating Systems. Control plane, data plane. Northbound interfaces. SDN components. Southbound interfaces. OpenFlow. ONF, OpenFlow ports, Flow tables. Network virtualization Virtual networks, virtual switches, NfV. Service chaining. NfV and SDN. SDN implementations Classic SDN, Hybrid SDN, SDN via APIs, SDN via overlays. Data centre SDN, VXLAN, Service Provider SDN, SD WAN, Enterprise SDN, WiFi. SDN and open source OpenDaylight, OpenVSwitch, Open Networking Forum, Open Network Operating System. Hands onOpenStack. SD-WAN What is SD-WAN? Architecture: Edge, gateway, orchestrator, controller. Overlay and underlay. Use of MPLS, 4G/5G. Benefits and features. Secure Access Service Edge (SASE).

OpenStack for NFV and SDN course description OpenStack is predominately a cloud management technology. This course looks at how OpenStack can be used in a NFV and SDN environment. What will you learn Describe the architecture of NFV. Explain the relationship between NFV and SDN. Implement NFV VIM using OpenStack. Explain how OpenStack as VNFM and orchestrator works. OpenStack for NFV and SDN course details Who will benefit: Anyone wishing to implement NFV using OpenStack. Prerequisites: Introduction to Virtualization Duration 3 day OpenStack for NFV and SDN course content What is NFV? What is NFV? What are network Functions? NFV benefits, NFV market drivers. ETSI NFV framework. ETSI documents, Architecture overview, compute domain, hypervisor domain, infrastructure network domain. What is OpenStack? Virtual machines, clouds, management. OpenStack architecture, OpenStack modules. Why OpenStack for NFV? Hands on OpenStack installation. OpenStack Virtualization and NFV Server, storage and network virtualization and NFV. Where OpenStack fits in the ETSI framework. Virtual machines, containers and docker. Data centres, clouds, SaaS, IaaS, PaaS. Hands on OpenStack Iaas, OpenStack Nova. The virtualization layer VM centric model, containers versus hypervisors, FD.io. Hands on OpenStack as the VIM. OpenStack Neutron VXLAN, Networks, subnets, ports. Security groups. Routers. Service and component hierarchy. Hands on Implementing a virtual network with OpenStack Neutron. Virtualization of Network Functions Network virtualization versus Network Function virtualization. NFV MANO Management and Orchestration. Where OpenStack fits. MANO descriptors, Open orchestration. OpenStack Tacker, Open MANO, OpenBaton, other orchestrators. OpenStack Tacker Installation, getting started, configuration. SFC and OpenStack. Hands on Deploying a VNF. OPNFV What is OPNFV, Where OpenStack fits into OPNFV. SDN What is SDN? Control and data planes. SDN controllers. Classic SDN versus real SDN. Hybrid SDN, network automation, SDN with overlays. Northbound, southbound, SDN protocols, OpenFlow, OpenDaylight, ONOS, SDN with NFV. SDN and OpenStack. Summary Deploying NFV, performance, testing. Futures

About this training course Artificial lift systems are an important part of production operations for the entire lifecycle of an asset. Often, oil and gas wells require artificial lift for most of the life cycle. This 5-day training course offers a thorough treatment of artificial lift techniques including design and operation for production optimization. With the increasing need to optimize dynamic production in highly constrained cost environments, opportunities and issues related to real-time measurements and optimization techniques needs to be discussed and understood. Artificial lift selection and life cycle analysis are covered. These concepts are discussed and reinforced using case studies, quizzing tools, and exercises with software. Participants solve examples and class problems throughout the course. Animations and videos reinforce the concepts under discussion. Understanding of these important production concepts is a must have to exploit the existing assets profitably. Unique Features: Hands-on usage of SNAP Software to solve gas-lift exercises Discussion on digital oil field Machine learning applications in gas-lift optimization Training Objectives After the completion of this training course, participants will be able to: Understand the basics and advanced concepts of each form of artificial lift systems including application envelope, relative strengths, and weaknesses Easily recognize the different components from downhole to the surface and their basic structural and operational features Design and analyze different components using appropriate software tools Understand challenges facing artificial lift applications and the mitigation of these challenges during selection, design, and operation Learn about the role of digital oilfield tools and techniques and their applications in artificial lift and production optimization Learn about use cases of Machine learning and artificial intelligence in the artificial lift Target Audience This training course is suitable and will greatly benefit the following specific groups: Production, reservoir, completion, drilling and facilities engineers, analysts, and operators Anyone interested in learning about selection, design, analysis and optimum operation of artificial lift and related production systems will benefit from this course. Course Level Intermediate Advanced Training Methods The training instructor relies on a highly interactive training method to enhance the learning process. This method ensures that all participants gain a complete understanding of all the topics covered. The training environment is highly stimulating, challenging, and effective because the participants will learn by case studies which will allow them to apply the material taught in their own organization. Course Duration: 5 days in total (35 hours). Training Schedule 0830 - Registration 0900 - Start of training 1030 - Morning Break 1045 - Training recommences 1230 - Lunch Break 1330 - Training recommences 1515 - Evening break 1530 - Training recommences 1700 - End of Training The maximum number of participants allowed for this training course is 20. This course is also available through our Virtual Instructor Led Training (VILT) format. Prerequisites: Understanding of petroleum production concepts. Each participant needs a laptop/PC for solving class examples using software to be provided during class. Laptop/PC needs to have a current Windows operating system and at least 500 MB free disk space. Participants should have administrator rights to install software. Trainer Your expert course leader has over 35 years' work-experience in multiphase flow, artificial lift, real-time production optimization and software development/management. His current work is focused on a variety of use cases like failure prediction, virtual flow rate determination, wellhead integrity surveillance, corrosion, equipment maintenance, DTS/DAS interpretation. He has worked for national oil companies, majors, independents, and service providers globally. He has multiple patents and has delivered a multitude of industry presentations. Twice selected as an SPE distinguished lecturer, he also volunteers on SPE committees. He holds a Bachelor's and Master's in chemical engineering from the Gujarat University and IIT-Kanpur, India; and a Ph.D. in Petroleum Engineering from the University of Tulsa, USA. Highlighted Work Experience: At Weatherford, consulted with clients as well as directed teams on digital oilfield solutions including LOWIS - a solution that was underneath the production operations of Chevron and Occidental Petroleum across the globe. Worked with and consulted on equipment's like field controllers, VSDs, downhole permanent gauges, multiphase flow meters, fibre optics-based measurements. Shepherded an enterprise-class solution that is being deployed at a major oil and gas producer for production management including artificial lift optimization using real time data and deep-learning data analytics. Developed a workshop on digital oilfield approaches for production engineers. Patents: Principal inventor: 'Smarter Slug Flow Conditioning and Control' Co-inventor: 'Technique for Production Enhancement with Downhole Monitoring of Artificially Lifted Wells' Co-inventor: 'Wellbore real-time monitoring and analysis of fracture contribution' Worldwide Experience in Training / Seminar / Workshop Deliveries: Besides delivering several SPE webinars, ALRDC and SPE trainings globally, he has taught artificial lift at Texas Tech, Missouri S&T, Louisiana State, U of Southern California, and U of Houston. He has conducted seminars, bespoke trainings / workshops globally for practicing professionals: Companies: Basra Oil Company, ConocoPhillips, Chevron, EcoPetrol, Equinor, KOC, ONGC, LukOil, PDO, PDVSA, PEMEX, Petronas, Repsol, , Saudi Aramco, Shell, Sonatrech, QP, Tatneft, YPF, and others. Countries: USA, Algeria, Argentina, Bahrain, Brazil, Canada, China, Croatia, Congo, Ghana, India, Indonesia, Iraq, Kazakhstan, Kenya, Kuwait, Libya, Malaysia, Oman, Mexico, Norway, Qatar, Romania, Russia, Serbia, Saudi Arabia, S Korea, Tanzania, Thailand, Tunisia, Turkmenistan, UAE, Ukraine, Uzbekistan, Venezuela. Virtual training provided for PetroEdge, ALRDC, School of Mines, Repsol, UEP-Pakistan, and others since pandemic. POST TRAINING COACHING SUPPORT (OPTIONAL) To further optimise your learning experience from our courses, we also offer individualized 'One to One' coaching support for 2 hours post training. We can help improve your competence in your chosen area of interest, based on your learning needs and available hours. This is a great opportunity to improve your capability and confidence in a particular area of expertise. It will be delivered over a secure video conference call by one of our senior trainers. They will work with you to create a tailor-made coaching program that will help you achieve your goals faster. Request for further information post training support and fees applicable Accreditions And Affliations

Ansible for engineers training course description An introduction to automation using ansible. Ansible is a general purpose IT automation platform that can be use for a number of purposes. The course covers configuration management, cloud provisioning and application deployment with ansible. Hands on sessions follow all major sections. What will you learn Install ansible. Automate tasks with ansible. Write ansible playbooks. Ansible for engineers training course details Who will benefit: Administrators and developers automating tasks. Prerequisites: Linux administration skills Duration 3 days Ansible for engineers training course contents What is ansible? The language, the engine, the framework. Uses of ansible, orchestration. Hands on Installing ansible. Ansible architecture ible architecture Controlling machines, nodes, Agentless, SSH, modules, JSON protocol. Configuration management, inventories, playbooks, modules, roles. Hands on Getting started, running ad hoc commands. Ansible and Vagrant Prototyping and testing. Hands on Using ansible with Vagrant. Ad hoc commands Parallelism, shell commands, managing files and directories, file transfer, package management, manage user and groups, deploying applications, service management, background jobs, checking log files, managing cron jobs. Hands on Using ansible with Vagrant. Playbooks ansible-playbook, users, sudo, YAML, plays, tasks, handlers, modules. Hands on Running playbooks. More playbooks Handlers, variables, environmental variables, playbook variables, inventory variables, variable scope and precedence, accessing variables, facts, ansible vault. Conditionals, wait_for. Hands on Using variables and conditions in playbooks. Roles and includes Dynamic includes, Handler includes, playbook includes. Roles, role parts: handlers, files, templates, cross platform roles, ansible galaxy. Hands on includes example, building roles. Inventories /etc/ansible/hosts, inventory variables, static inventories, dynamic inventories. Hands on Inventories and variables. Miscellanea Individual server cookbooks, Main playbook for configuring all servers. Hands onPlaybooks.