Opengear, a provider of solutions that deliver secure, resilient network access and automation to critical IT infrastructure, announced the general availability of the Opengear NetOps AutomationTM platform. Today’s release provides enterprises with a complete and centralised management solution for achieving vendor-neutral automation of NetOps workflows.

The NetOps Automation platform is built on a network of distributed Opengear management devices that enable presence and proximity at each of an organisation’s network locations. Enterprises can automate critical workflows via the Lighthouse centralised management system, running containerised NetOps modules that provide specialised functionality for making business processes even easier to abstract, implement, and automate. A Secure Provisioning module and a LogZillaTM module for event management are now available, with additional modules under development.

Automating configuration management

The Secure Provisioning NetOps Module utilises Opengear’s new OM2200 Operations Manager

The NetOps Automation platform is driven by the desire of our enterprise customers to automate repetitive and error-prone activities both in the data centre and at remote locations,” said Gary Marks, CEO, Opengear. “It’s a natural progression from our existing presence in the network infrastructure, where they rely on us to provide always-on access with smart out-of-band management. This innovative new solution provides that same level of resilience and convenience beyond out-of-band, as these organisations embrace the NetOps philosophy to streamline their processes and reduce human intervention.

The Secure Provisioning NetOps Module utilises Opengear’s new OM2200 Operations Manager to completely automate the initial provisioning, configuration management, re-provisioning, and disaster recovery of remote infrastructure. The OM2200 is built into the initial rack shipped to a branch office or other remote site and, once powered on, will call home using its embedded cellular module (which is secured and protected from tampering by TPM safeguards).

Centralised network management

We’re excited to have LogZilla as our first NetOps Automation platform ecosystem partner"Lighthouse 5 then automatically pushes image, configuration, and script files to the OM2200, which in turn provisions other hardware devices at the location. This completes the secure, zero-touch provisioning of local network infrastructure from a single appliance – and with no IT intervention required.

The automated provisioning and centralised network management capabilities offered by the NetOps Automation platform serve an increasingly critical need, as enterprises scale and expand their infrastructure to meet ever-increasing demands on network capacity,” said Marcio Saito, CTO, Opengear. “We’re excited to have LogZilla as our first NetOps Automation platform ecosystem partner, with its powerful event data management and analytics module proving the platform’s incredible potential. We look forward to future opportunities to add modules alongside further partners as well.

Real-time network intelligence and analytics

The LogZilla NetOps Module – a second module releasing today for use with Opengear’s NetOps Automation platform – was produced through a new partnership between Opengear and LogZilla. The module offers integration with LogZilla’s flagship event management solution to deliver real-time network intelligence and analytics, always-on monitoring, and forensics (even during network outages). Coupled with Opengear’s local appliances, this module improves enterprises’ network resiliency and reduces the mean-time-to-repair and total cost of ownership across network equipment.

The LogZilla event preduplicationTM and forwarding engine can run locally at remote sitesLogZilla’s solution allows organisations to consolidate multiple servers traditionally required to maintain effective management system logs, and instead run them solely through Opengear’s NetOps Automation platform. Additionally, the LogZilla event preduplicationTM and forwarding engine can run locally at remote sites when deployed onto OM2000 appliances.

Reducing cost of ownership

This partnership between Opengear and LogZilla delivers a Network Operations module perfectly aligned to the current needs of enterprise customers and industries we serve,” said Clayton Dukes, CEO, LogZilla. “We remain committed to reducing the total cost of ownership of network equipment by fostering a natural synergy with what Opengear’s accomplished through its NetOps Automation system. We’re excited by the possibilities of this offering, and see this as the first of many collaborations with Opengear.

The Opengear NetOps Automation platform includes the OM2200 appliance, along with a subscription-based license for Lighthouse 5 and individual NetOps modules, and is available through Opengear’s reseller partners

Download PDF version

In case you missed it

What is the changing role of training in the security industry?
What is the changing role of training in the security industry?

Even the most advanced and sophisticated security systems are limited in their effectiveness by a factor that is common to all systems – the human factor. How effectively integrators install systems and how productively users interface with their systems both depend largely on how well individual people are trained. We asked this week’s Expert Panel Roundtable: What is the changing role of training in the security and video surveillance market?

What is AI Face Search? Benefits over facial recognition systems
What is AI Face Search? Benefits over facial recognition systems

When a child goes missing in a large, crowded mall, we have a panicking mom asking for help from the staff, at least a dozen cameras in the area, and assuming the child has gone missing for only 15 minutes, about 3 hours’ worth of video to look through to find the child. Typical security staff response would be to monitor the video wall while reviewing the footage and making a verbal announcement throughout the mall so the staff can keep an eye out for her. There is no telling how long it will take, while every second feels like hours under pressure. As more time passes, the possible areas where the child can be will widen, it becomes more time-consuming to search manually, and the likelihood of finding the child decreases. What if we can avoid all of that and directly search for that particular girl in less than 1 second? Artificial neural networks are improving every day and now enable us to search for a person across all selected camera streamsWith Artificial Intelligence, we can. Artificial neural networks are improving every day and now enable us to search for a person across all selected camera streams in a fraction of a second, using only one photo of that person. The photo does not even have to be a full frontal, passport-type mugshot; it can be a selfie image of the person at a party, as long as the face is there, the AI can find her and match her face with the hundreds or thousands of faces in the locations of interest. The search result is obtained in nearly real time as she passes by a certain camera. Distinguishing humans from animals and statues The AI system continuously analyses video streams from the surveillance cameras in its network, distinguishes human faces from non-human objects such as statues and animals, and much like a human brain, stores information about those faces in its memory, a mental image of the facial features so to speak. When we, the system user, upload an image of the person of interest to the AI system, the AI detects the face(s) in that image along with their particular features, search its memory for similar faces, and shows us where and when the person has appeared. We are in control of selecting the time period (up to days) and place (cameras) to search, and we can adjust the similarity level, i.e., how much a face matches the uploaded photo, to expand or fine-tune the search result according to our need. Furthermore, because the camera names and time stamps are available, the system can be linked with maps to track and predict the path of the person of interest. AI Face Search is not Face Recognition for two reasons: it protects people’s privacy, and it is lightweight Protecting people’s privacy with AI Face Search  All features of face recognition can be enabled by the system user, such as to notify staff members when a person of interest is approaching the store AI Face Search is not Face Recognition for two reasons: it protects people’s privacy, and it is lightweight. First, with AI Face Search, no names, ID, personal information, or lists of any type are required to be saved in the system. The uploaded image can be erased from the system after use, there is no face database, and all faces in the camera live view can be blurred out post-processing to guarantee GDPR compliance. Second, the lack of a required face database, a live view with frames drawn around the detected faces and constant face matching in the background also significantly reduces the amount of computing resource to process the video stream, hence the lightweight. Face Search versus Face Recognition AI Face Search Face Recognition Quick search for a particular person in video footage Identify everyone in video footage Match detected face(s) in video stream to target face(s) in an uploaded image Match detected face(s) in video stream to a database Do not store faces and names in a database Must have a database with ID info Automatically protect privacy for GDPR compliance in public places May require additional paperwork to comply with privacy regulations Lightweight solution Complex solution for large-scale deployment Main use: locate persons of interest in a large area Main use: identify a person who passes through a checkpoint Of course, all features of face recognition can be enabled by the system user if necessary, such as to notify staff members when a person of interest is approaching the store, but the flexibility to not have such features and to use the search tool as a simple Google-like device particularly for people and images is the advantage of AI Face Search.Because Face Search is not based on face recognition, no faces and name identifications are stored Advantages of AI Face Search Artificial Intelligence has advanced so far in the past few years that its facial understanding capability is equivalent to that of a human. The AI will recognise the person of interest whether he has glasses, wears a hat, is drinking water, or is at an angle away from the camera. In summary, the advantages of Face Search: High efficiency: a target person can be located within a few seconds, which enables fast response time. High performance: high accuracy in a large database and stable performance, much like Google search for text-based queries. Easy setup and usage: AI appliance with the built-in face search engine can be customised to integrate to any existing NVR/VMS/camera system or as a standalone unit depending on the customer’s needs. The simple-to-use interface requires minimal training and no special programming skills. High-cost saving: the time saving and ease of use translate to orders of magnitude less manual effort than traditionally required, which means money saving. Scalability: AI can scale much faster and at a wider scope than human effort. AI performance simply relies on computing resource, and each Face Search appliance typically comes with the optimal hardware for any system size depending on the customer need, which can go up to thousands of cameras. Privacy: AI Face Search is not face recognition. For face recognition, there are privacy laws that limits the usage. Because Face Search is not based on face recognition, no faces and name identifications are stored, so Face Search can be used in many public environments to identify faces against past and real-time video recordings. AI Face Search match detected face(s) in video stream to target face(s) in an uploaded image Common use cases of AI Face Search In addition to the scenario of missing child in a shopping mall, other common use cases for the AI Face Search technology include: Retail management: Search, detect and locate VIP guests in hotels, shopping centres, resorts, etc. to promptly attend to their needs, track their behaviour pattern, and predict locations that they tend to visit. Crime suspect: Quickly search for and prove/disprove the presence of suspects (thief, robber, terrorist, etc.) in an incident at certain locations and time. School campus protection: With the recent increase in number of mass shootings in school campuses, there is a need to identify, locate and stop a weapon carrier on campus as soon as possible before he can start shooting. Face Search will enable the authorities to locate the suspect and trace his movements within seconds using multiple camera feeds from different areas on campus. Only one clear image of the suspect’s face is sufficient. In the race of technology development in response to business needs and security concerns, AI Face Search is a simple, lightweight solution for airports, shopping centres, schools, resorts, etc. to increase our efficiency, minimise manual effort in searching for people when incidents occur on site, and actively prevent potential incidents from occurring. By Paul Sun, CEO of IronYun, and Mai Truong, Marketing Manager of IronYun

What technology will impact security most in the rest of 2018?
What technology will impact security most in the rest of 2018?

Where does the time go? Before you know it, here we are at mid-year reflecting on an eventful first half of 2018 in the physical security market. It’s also a good time for our Expert Panel Roundtable to pause and look ahead at what we might expect in the second half of the year. We asked this week’s Expert Panel Roundtable: What technology development will have the greatest impact in the second half of 2018?