205 Mac courses in Crawley

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

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.

Cloud deployment training course description This course covers the important topics every cloud professional needs, including, configuration and deployment, security, maintenance, management, and troubleshooting. It covers all aspects of cloud computing infrastructure and administration, with a practical focus on real-world skills. It will help you to master the fundamental concepts, terminology, and characteristics of cloud computing. Deploy and implement cloud solutions, manage the infrastructure, and monitor performance. You will also be able to install, configure, and manage virtual machines. What will you learn Cloud services, models, and characteristics. Virtualization components, installation, and configuration. Infrastructure configurations and optimization. Resource management and specific allocations. IT security concepts, tools, and best practices. Recovery, availability and continuity in the cloud. Cloud deployment training course details Who will benefit: IT professionals looking to deploy and implement cloud solutions, manage the infrastructure, and monitor performance, Install, configure, and manage virtual machines. Prerequisites: Introduction to virtualization. Duration 5 days Cloud deployment training course contents Preparing to Deploy Cloud Solutions Deploying a Pilot Project Testing Pilot Project Deployments Designing a Secure and Compliant Cloud Infrastructure Designing and Implementing a Secure Cloud Environment Planning Identity and Access Management for Cloud Deployments Determining CPU and Memory Sizing for Cloud Deployments Determining Storage Requirements for Cloud Deployments Analysing Workload Characteristics to Ensure Successful Migration Maintaining Cloud Systems Implementing Backup, Restore, Disaster Recovery, and Business Continuity Measures Analysing Cloud Systems for Performance Analysing Cloud Systems for Anomalies and Growth Forecasting Troubleshooting Deployment, Capacity, Automation, and Orchestration Issues Troubleshooting Connectivity Issues Troubleshooting Security Issues

Level 2 NVQ Diploma in Construction Plant or Machinery Maintenance

Windows clustering training course description This course covers high availability and disaster recovery technologies such as live migration, storage migration and Hyper-V Replica, as well as providing indepth coverage of failover clustering including a detailed implementation of failover clustering of Hyper- V using SoFS. The course also covers System Center Virtual Machine Manager and implementing Network Load Balancing (NLB) and load balancing clusters. What will you learn Plan and implement a failover cluster. Describe managing server roles and clustering resources. Implement and manage virtual machines. Use System Center Virtual Machine Manager. Describe cloud-based storage and high availability solutions. Implement a Network Load Balancing (NLB) cluster. Windows clustering training course details Who will benefit: Technical staff working with Microsoft clusters. Prerequisites: Supporting Microsoft Windows server Duration 3 days Windows clustering training course contents High Availability in Windows Server Defining levels of availability, High Availability and disaster recovery solutions with Hyper-V Virtual Machines, High Availability with failover clustering in Windows Server. Hands on Configuring High Availability and Disaster Recovery. Implementing failover clustering Planning a failover cluster, creating a new failover cluster. Hands on Creating and Administering a Cluster. Server roles and clustering resources Configuring highly available applications and services on a failover cluster, managing and maintaining a failover cluster, troubleshooting a failover cluster, implementing site high availability with multisite failover clusters. Hands on Managing server roles and clustering resources. Failover clustering with Hyper-V Overview of integrating Hyper-V with failover clustering, implementing Hyper-V with failover clustering, managing and maintaining Hyper-V Virtual Machines on failover clusters. Hands on Implementing failover clustering by using Hyper-V Storage Infrastructure Management with Virtual Machine Manager Virtual Machine Manager, managing storage infrastructure with Virtual Machine Manager, provisioning failover clustering in Virtual Machine Manager. Hands on Managing storage infrastructure. Cloud-Based storage and High Availability Azure storage solutions and infrastructure, cloud integrated storage with StorSimple, disaster recovery with Azure Site Recovery. Hands on Managing cloud-based storage and high availability Network Load Balancing Clusters Overview of NLB, configuring an NLB cluster, planning NLB. Hands on Implementing a Network Load Balancing Cluster

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

MPEG training course description This course studies the MPEG standards for video and audio compression. A major focus is on MPEG-4 and MPEG-TS. Hands on includes decoding and analysing MPEG streams. What will you learn Recognise the main MPEG standards. Describe the techniques used in MPEG video and audio compression. Compare MPEG2m MPEG4 and MPEG-H. Describe the MPEG-TS. Analyse MPEG streams. MPEG training course details Who will benefit: Anyone working with MPEG. Prerequisites: None. Duration 2 days MPEG training course contents Introduction What is MPEG? MPEG and VCEG, MPEG 1, MPEG 2, MPEG-3, MPEG-4, MPEG-H, others, codecs and containers, licensing and patents, parts and layers (System, Video, Audio, others). MPEG2 DVD, DVB, characteristics, MPEG2 Part2, audio MPEG2 Part 7 (AAC). MPEG tools Wireshark, vlc, analysers, decoders, ffmpeg, wowzer. MPEG2 Video compression Sampling, bit rates, resolution. Inter and Intra frame coding, I, B, P frames, GOP, slices, blocks, macroblocks. Motion estimation. Hands on Analysing MPEG frames. MPEG4 Profiles and levels, Enhancements, Parts 1,2,3, Part 10 and AVC, Part 14 and mp4. Performance versus MPEG2. MPEG audio Coding, frequencies, bit rates. MPEG-TS PES, Transport Streams, TS elements, packets, PID, Programs, PSI, PAT, PMT, synchronisation, PCR, PTS. MPEG-H Part 2 HEVC, benefits, improvements. Video codecs What is a CODEC, pictures and audio, digitisation, sampling, quantisation, encoding, compressing.

Samba training course description Samba enables UNIX/Linux machines to act as Microsoft File and Print servers. This two day hands on training course progresses from the basics of installing samba and simple configurations through to authentication issues and troubleshooting. What will you learn Install and configure Samba. Administrate file and printer sharing. Secure Samba servers. Troubleshoot Samba Samba training course details Who will benefit: Technical staff working with Samba. Prerequisites: Intro to UNIX Systems Administration TCP/IP Foundation. Duration 2 days Samba training course contents What is Samba? File and print servers, Samba server roles, Windows networking, NetBIOS, SMB. Hands on Microsoft File and Print shares, analysing the network traffic. Installing Samba Source, binaries, where to find samba, building and compiling Samba. Hands on Download and install Samba. Controlling Samba Samba daemons, starting and stopping Samba, smbcontrol, Samba net command, smb.conf. Viewing Samba status, smbclient. Hands on Starting and stopping Samba, testing the server. Samba configuration Simple shares, smb.conf variables, configuration from a web browser, swat, enabling access to swat. Hands on Configuring samba servers and clients. File sharing Basic shares, [homes], locking options, UNIX file permissions, controlling user access, Windows ACLs, virtual samba servers, browsing. Hands on File sharing and browsing. Print sharing Sharing printers, UNIX printing, CUPS, printer drivers, [printers], PRINT$. Hands on Samba print server. Authentication Workgroups, domains, users and passwords, Samba domain security, Samba password backends: smbpasswd, tdbsam, nisplus, mysql, Active Directory. Hands on Securing samba shares. Troubleshooting Logging options, controlling logs, Samba utilities, network protocols, .SMB/CIFS. Performance tuning. Hands on Troubleshooting Samba

Data centre infrastructure course description This course provides a foundation in data centre infrastructure technologies. It begins with a tour of virtualisation and the impact of this on the network before moving on to the spine and leaf design, how it works and how to scale. Layer 2 technologies enabling this architecture are studied in terms of the impact on the data centre. The course then progresses onto how Layer 3 technologies such as BGP, EVPN and VXLAN are used in data centre networks. The course then studies interconnecting data centres finishing with a section on automation and orchestration of both underlay and overlay networks. What will you learn Explain the spine and leaf architecture Recognise the impact of virtualisation, containers and orchestration on the network Describe how the following technologies are used in data centres: Multi port aggregation Overlay networks MBGP, VRFs, EVPN VXLAN COOP Data centre infrastructure course details Who will benefit: Staff involved with Data centres. Prerequisites: Network fundamentals for engineers Duration 2 days Data centre infrastructure course contents What is Ethernet? Data centres versus enterprise networks. Servers, Blades, Racks, Clusters, Storage, Virtual Machines, Hosts, guests, containers, orchestration. Virtual switches. Distributed switches. Live migrations (e.g. vMotion). IP addressing and VM traffic. Data centre network architecture Spine leaf design. North south traffic, East West traffic, Scaling: Ports, bandwidth. N+1 redundancy, ratio East West optimisation, oversubscription. 2 tier versus 3 tier Leaf/Spine. Pods. Underlay, Overlay L2 technologies STP vs link aggregation vs multi link aggregation. LACP, LLDP, CDP. Scalability. VLANs and VLAN pruning. L2 design recommendations. Disabling STP on edge ports. L3 technologies Underlay, Overlay, VXLAN, VTEP, VXLAN overlay forwarding, EVPN, IS-IS, COOP, MP BGP, VRFs, EBGP, IBGP, AS numbers, route reflectors. Anycast gateways. MTU considerations-for data and control planes. BUM traffic. Data centre interconnects Pods, fabrics, multi pods, multi fabric, multi site. VXLAN with BGP/EVPN Data center interconnect. Cloud integration, Inter Site Networks. Automation Automation and orchestration, Zero touch provisioning, Devops, Netops, telemetry automated configuration for underlay and overlay, SDN.