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AI monitoring technologies have the potential to introduce significant cost savings for CSPs. Based on machine learning and fully autonomous, these monitoring solutions provide high ROI by dramatically reducing Time to Detection (TTR), Time to Resolution (TTR), the total number of alerts, and the number of false positives and negatives. Forward thinking CSPs who rely on AI-based monitoring drive operational efficiency, deliver a better customer experience, and prevent critical performance and quality of service issues across the network. 

However, for most CSPs, successful adoption and implementation rates of AI monitoring are still low. The main hurdles faced by CSPs are the complexity of the network, limited resources and internal knowledge, and an overwhelming number of potential use cases. In most cases, AI monitoring solutions require heavy investment in setup, data integration, use case development, operation and maintenance — as well as specialized skills typically provided by pricey professional services firms. This results in significantly higher TCO, longer time to value, and slower use case implementation when compared to out-of-the-box solutions.

That’s why Anodot is built from the ground up to deliver AI-based network monitoring with the shortest time to value. It does so by providing a fast and simple integration process, streamlined on-boarding and ongoing use, and completely autonomous monitoring and correlation that requires no manual intervention.

Anodot is built to deliver value fast, so implementation time — including technical integration, data validation and on-boarding —  takes weeks instead of months compared to alternative solutions that rely heavily on outsourced professional services. Data integration is fast and simple using one of Anodot’s many turn-key integrations or agents and open source collectors. The platform also has a robust REST API, so CSPs can stream their measures and dimensions from anywhere. There are no lengthy professional services projects, and no data scientists required. This short integration process enables users to seamlessly send data to the platform, deriving immediate value and new efficiencies. 

More info: ericsson careers

Before signing a contract and partnering up with an MSSP, or if you are looking for a new MSSP to partner with, make sure that they deliver the following seven elements. That way, regardless of what services are used, you can be sure that your overall security needs will be met.

While your team may work the usual Monday to Friday, 9-5 hours, your networks, data, and everything that goes into your business requires 24/7 security. Which is why it is necessary that your MSSP provides full security 24/7, every day of the year, regardless of holidays, working schedules or natural disasters. 24/7 means supported by humans, not automated machines. You should be able to call the SOC at 4am, and someone should be there to answer your call. Watch out for any automated services, these do not bring the same level of care, nor will they answer your specific security needs.

Once you ensure that your MSSP is available 24/7, find out what their speed of response is for requirements and queries of different severity. Your MSSP should have a hotline number if you suspect an incident, or indeed for anything urgent. They should also have an App you can contact the team directly on, and a designated service delivery manager to call upon once signed up.

Your provider must have an SLA agreement, and that must detail the speed of response and the commitment to that.

It is also worth checking testimonials and accreditations. If an MSSP has won awards for their services or platform from a reputable source, it is likely that they have in place processes to guide and support their clients throughout all eventualities.

More info: it support engineer

The protocol that controls data transfer is called Transmission Control Protocol (TCP). After the connection is established, it starts the data transfer and when the transfer process is completed, it terminates the connection by closing the established virtual circuit. Extensive errors are easily found thanks to the error-checking feature of TCP. During peak network periods, transmission is delayed and unsent data is retransmitted. In short, TCP checks whether the data has reached the destination where it should be sent. It notifies with feedback whether data is transferred or not. The data transmission of the internet’s most popular protocols such as HTTP, HTTPS, POP3, SSH and FTP is done by TCP.

It collectively transmits the data to the other party without establishing a connection. It is used in real-time data transfer such as voice and video transmission in wide area networks (WAN). In addition, UDP is more preferred for games. UDP is an untrusted and generally not preferred protocol because it only transmits data according to the speed of the data generated by the application, the capability of the computer and the transmission bandwidth limit. UDP doesn’t think that every packet needs to reach the receiving end, so the network load is smaller than TCP. At the same time, the transmission speed is faster than TCP, but the congested the network the more risk it loses the packet sent. So what are the other differences between TCP and UDP?

It is very important that communication be effective and secure in the business world. Sharing the information in the right place at the right time facilitates the distribution of business processes. Some database services provide error-free management of IP phones and call decisions. With the given configuration commands, the nature of the communication is preserved and is not broken. The Linux-based communication server supported by Cisco Systems that maps IP numbers to phone numbers and integrates voice, video, data and mobile applications is called Cisco Unified Communications (CUCM) or Cisco Call Manager (CCM).

More info: telecom sector

Smart energy grids are deployed to reduce energy consumption and offer more flexibility and reliability than traditional grids. These grids help in supplying energy to millions of households by integrating multiple energy sources. In order to supply, optimize, and maintain energy efficiency for multiple cities and neighborhoods, a huge volume of data is captured from millions of devices, including individual meters and consumption devices. These devices can generate exabytes of data, for which enormous computing power is needed for processing. Traditional servers cannot fulfill this need. However, with HPC, a huge volume of data can be processed and analyzed with efficiency in real-time.

Manufacturing Excellence

Large manufacturing enterprises have already begun to make use of the power of HPC, which is used for IoT and Big Data analysis. Based on the analysis results, real-time adjustments are possible in processes and tools to ensure an improved design of a product, increased competitiveness, and faster lead times.

High Performance Computing is capable of running large simulations, rapid prototyping, redesigns, and demonstrations. An example could be a manufacturing unit that would improve its manufacturing flow with insights from the processing of 25,000 data points from customer intelligence. The first-ever autonomous shipping project of the world is making use of HPC computing, which involves processing a large amount of data collected from sensors. The data includes details of weather conditions, wave points, tidal data, and conditions of various systems installed.

High Performance Computing offers significant benefits over traditional computing for manufacturing enterprises. It can help an automobile unit vehicle maintenance. A wholesaler could optimize the supply chain as well as stock levels. HPC is also used in R&D. The innovative design of the 787 Dreamliner Aircraft by Boeing is a result of HPC-based modeling and simulation that helped the company conduct live tests on the aircraft to test the prototype.

More info: jncia

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