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Making networks greener doesn’t have to hurt

Contributed by Andrew Burrell, Head of Marketing & Communications, Nokia.

One of the reasons for the world’s glacially slow response to the dangers of climate change is the sheer difficulty of taking effective action. Most people accept that dramatic reductions in greenhouse gas (GHG) emissions are needed, but the high costs and often severe lifestyle changes needed are daunting barriers.

We could cite many examples, but let’s look at just two:

  • The aviation industry must reduce carbon emissions, but means people flying less
  • Reducing the carbon footprint of buildings is essential, but means substantial spending on new heating and insulating systems.

Fortunately, it’s a different story when it comes to mobile telecom networks. While such networks may account for just over 1% of global electricity consumption, that 1% adds up to a significant volume of GHG emissions. Unsurprisingly, customers, investors, regulators and governments are urging communications service providers (CSPs) to take action.

While CSPs may be keen to reduce their network energy consumption (and thus costs), the challenge is to do it without compromising network performance, customer satisfaction or the bottom line.

Target the radio network

So how can it be done without forcing CSPs into large-scale hardware redeployments, comprehensive network modernization or architecture redesigns? And how can network carbon footprints be reduced without degrading the user experience?

CSPs aiming to cut the largest possible chunk of energy consumption at the fastest possible pace need to focus on the radio access network (RAN). That’s because the RAN accounts for around 80% of all mobile network energy consumption.  “Waste” is an issue because only 15% of that energy is used to transmit data. The other 85% goes into secondary systems such as heating and cooling, lighting, uninterruptible and other power supplies, and running idle resources.

Modernizing network infrastructure can help but is hindered by slow upgrade cycles and requires high upfront CAPEX investments. If we want to have an immediate impact, there are two main strategies to reduce network energy use: dynamic network shutdowns and full-site power management.

Dynamically shutting down unused network elements during low-traffic periods can save much energy. Artificial intelligence (AI) maximizes the potential savings by using all sorts of data to precisely predict when to shut down infrastructure and perfectly balance energy savings, network performance and customer experience.

Using AI to control dynamic shutdowns can extend sleep times by several hours compared to statically scheduled shutdowns. AI can further boost energy savings by another 50% by eliminating the need to keep resources on standby ready to serve a sudden uplift in demand.

Managing passive equipment

Yet dynamic shutdowns only account for network elements, not power-hungry auxiliary components such as fans, cooling systems, lighting and power supplies. To ensure maximum energy efficiency, AI-powered energy consumption management must cover both active radio and passive equipment. The key is to benchmark energy trends to spot performance anomalies in historically “invisible” passive equipment that could be draining energy and might need to be reconfigured or replaced. Implementing such AI-based energy management can reduce energy costs by 20-30%.

The best news is that, because it is software, AI-based energy efficiency can be deployed in just a few weeks without major upfront investment. Software as a Service business models can also mean that CSPs pay their vendors only for the outcomes that are actually achieved. Implementing the technology over a public cloud can make it even more convenient by easing the processing and analysis of the large volume and velocity of network data.

Maintaining the customer experience

The question that now arises is how can CSPs guarantee that network performance and customer experience don’t suffer when parts of the network are powered down? How do they ensure resources are powered up again in time for traffic peaks? In other words, how to ensure network performance requirements and energy consumption are precisely aligned?

A problem of such complexity calls for AI-based energy solutions that can predict precisely the right time to power off resources and power them on again. Just-in-time waking is hard to achieve with static or rules-based methods, usually requiring extensive wake-up windows or the use of standby mode to shorten response times.

China Mobile adopts an AI-based solution

This was the situation facing China Mobile which wanted a to cut energy consumption and control costs without compromising the customer experience. The CSP realized it needed a comprehensive energy efficiency plan to reduce emissions and lower costs without affecting the customer experience or compromising network performance.

China Mobile decided to use the Nokia AVA Energy Efficiency solution for:

  • Predictive and dynamic management of passive and active components to gain much finer-grained control over energy consumption
  • Predictive closed loop actions for faster, automated responses to changing conditions instead of relying on manual interventions that cause delayed responses
  • Automated remote antenna control to adjust coverage dynamically according to shifting capacity requirements.

China mobile was able to permanently balance energy savings and performance requirements, allowing key performance indicators (KPIs) to be pre-set, with savings calculated by the AI system.

Contrary to most areas of daily life, energy savings in telecoms do not require massive lifestyle changes and do not have an impact on the services and the experiences customers are used to. That has to be good news for people and the planet.

Andrew is speaking on the ‘Energy efficiency and sustainability by design’ panel discussion at FutureNet World on the 11th of May. Register here.

The “March of Time” Requires Intelligent Service Assurance as part of AIOps

Contributed by Mark Geere, Product Marketing, Teoco

I am lucky enough to own an old MGB sports car, and it has been sitting in my garage for the winter. As is typical with these older British cars, it wouldn’t start after a couple of months “rest.” But once I opened the bonnet and applied some simple manual human intelligence, fault finding, and diagnostics, with a little bit of coaxing it eventually started up. I thought of this as I was driving around the next day in my more modern Jaguar XF; I opened the bonnet on this car and realized I had no chance of even trying to understand what was going on in there. Even the Jaguar specialists at my local garage often comment that they must send some faults back to the franchise dealers, as they have the specialist tools, diagnostics, and processes to fix and mend a difficult issues.

I have seen the same march of time impact technology within the telecommunications sector. I previously worked for a software vendor as an engineer on mobile telecoms networks, where we helped design, manage, and assure the relatively simple physical-based networks of 2G/3G. I’ve seen these networks grow in complexity over the years. Through the 4G era of internet and video streaming capabilities to the 5G era of today, virtual/cloud-based networks are becoming a reality, along with new services and the added intricacies of network slicing and MEC capabilities.

Let’s face it. All this innovation is towards achieving the ultimate goal of CSPs to increase their bottom line for their shareholders. However, as part of this they need to ensure that their operational OPEX costs do not rise as fast as the complexity of their network. On the other side of the equation, CSPs have learnt, from painful history, that if they do not provide a dedicated focus on the consumer/Enterprise experience and service declines, it soon translates into a significant loss in revenue. At this point AI/ML and automation within operations become critical tools for balancing both sides of the equation, and it’s why CSPs are looking to AIOps for help.

To gain real benefits within operations, the CSP needs to intelligently automate many previously manual tasks and ensure their service assurance solution seamlessly integrates within their BSS and OSS architectures. As service automation becomes more of a reality (especially at the Enterprise level), Service Assurance solutions will need “talk” to the orchestration and fulfilment solutions with a far tighter, nearer to real-time integration, so that they can translate the intent-based requirements into measurable parameters. This will not always result in predictable outputs from specific inputs, but it will create intelligently-derived performance indicators that impact the intent of service level agreements.

At TEOCO, one of our key capabilities is our ability to integrate multi-technology and multi-vendor network equipment into a single independent view across an entire network. However, even though this remains a unique selling proposition, it is not enough. We recognize the impacts of the “march of time,” and over the years we have worked with industry bodies such as TM Forum, along with our customers, to constantly upgrade our HELIX Service Assurance solution to meet the new challenges of each era. As CSPs move towards zero-touch service operations, TEOCO has focused on providing two key aspects for Service Maintenance & Operations:

  • Providing intelligence within our solution through the introduction of Machine Learning: This reduces the time required to locate faults, the ability to intelligently find the right metrics to manage SLAs, and to drastically reduce the number of alarms across multiple technologies and vendor equipment into those that matter.
  • Seamlessly integrating into operators’ BSS/OSS architectures by being cloud-ready and the use of Open APIs.

AIOps is still immature within CSP operations. It envisions a high level of AI­-assisted or AI­-driven automation in IT and network operations. Though zero-touch is a radical leap, it is an essential part of CSPs’ drive towards operational automation. The introduction of intelligent, integrated service assurance is key to its success.

To learn more about Helix and TEOCO’s full line of service assurance solutions, please visit our website or contact us for more information.

Mark is a panelist in the session: Applying AIOps for Zero Touch Automation through intelligent Service Assurance, at Futurenet World in May. Register today to join him.

Cloudifying the network infrastructure

Contributed by Teresa Monteiro, Director of Marketing, Infinera

In recent years network automation has evolved past SDN and NFV, with the cloud emerging as a major player. Networks that once extended from physical to virtual are now moving to cloud. Cloud-native network functions are helping service providers expand beyond connectivity, and multi-cloud and hybrid cloud architectures are core to meet the distributed computing requirements for scale and agility imposed by 5G and IoT.

In this blog I will also discuss the role of cloud in network automation – but I will do it from a different perspective: that of cloudifying the embedded network infrastructure.

Cloud-native down to the infrastructure

When we think of optical network automation, we typically think of the network management and control layer, and of centralized automation applications enabled by an optical domain controller – automation applications such as network discovery and inventory, path computation, or service restoration.

But let’s not forget that there are also important automation applications implemented in the network operating system (NOS), the operating system running on the individual network elements. The adoption of a cloud-native architecture at the NOS facilitates agile delivery and deployment of such applications.

By cloud-native architectures and technologies, we specifically mean a NOS that is microservices-based and can be deployed in containers with the support of a container management system. This choice of software architecture has many well-known benefits; today, I will focus on the fact that it allows for software modules, developed, and compiled elsewhere, to run autonomously in a network element environment, deployed in what is called a guest container.

In simple words, a guest container is an isolated component within the NOS that can host and execute a software agent. This software agent has access to open, exposed interfaces, but not to any other internal NOS parameters.

The deployment of software agents within guest containers enables the extension of NOS features, accelerates the introduction of innovative automation applications, and supports the development of customized functionality.

A NOS-agnostic software agent can be implemented and compiled independently, in a foreign development environment, by an operator or a third-party supplier, and, once downloaded, will run smoothly in a cloud-native NOS.

Furthermore, since a containerized architecture offers a variety of deployment options, the same agent can be deployed on the fly and run locally on a network element, on a server, or in the cloud. It can be ported easily across platforms: to the cloud, when an application needs to scale, to the network element processor when there are latency constraints.

An example: adaptive streaming telemetry

Let me describe a concrete example, that of an automation application named adaptive streaming telemetry that extends and improves the standard streaming telemetry mechanism and has been successfully implemented as a NOS-agnostic software agent.

Streaming telemetry is a network monitoring methodology where an external system subscribes to a specific network element data stream, among all the monitoring data that the equipment is able to expose. From there on, the network element pushes all corresponding data, in an almost continuous manner, to the server that subscribed it. Streaming telemetry ensures low-latency, high-performance data collection, enabling near real-time access to large volumes of network data.

However, standard streaming telemetry can still be improved. In a modern network, there are plenty of network parameters available to be streamed; under normal operation, many are redundant and monitoring them does not add meaningful information, while also imposing an unnecessary load on the system. This is where adaptive streaming telemetry, a solution that adjusts dynamically to the network status and evolves with the network’s needs, is useful:

  • Under normal network operations, a fixed, limited set of parameters is included in each data stream and pushed to the data collectors at a moderate frequency. These are the parameters that best summarize the network status.
  • Upon network status change, the streaming frequency and the content of the data stream are adjusted: the push frequency may be increased, or more parameters can be added to the telemetry stream, for further insight.

The power of adaptive streaming telemetry

This approach decreases the load on the data communication network compared to standard telemetry, but it continues to support fine-grained visibility when and where needed. It also contributes to better overall data quality, which, in turn, allows for better compliance to SLAs, improves characterization of a network element’s health, and unleashes the predictive power of analytics and machine learning.

Infinera has worked jointly with Oracle and Microsoft in adaptive solutions that extend the standard gRPC-based streaming telemetry. We have successfully demonstrated adaptive streaming using a NOS-agnostic software agent implemented in the Go open source programming language, running in a NOS guest container. The same agent was seamlessly deployed and tested in Infinera’s optical network operating systems as well as in in SONiC, an open-source network operating system that includes strong support for routing protocols. The use of the same software across various technologies and equipment vendors ensures that the behavior of adaptive streaming telemetry is uniform and consistent.

Leveraging cloud towards autonomous networking

Automation applications like adaptive streaming telemetry, that intelligently observe the network, are key ingredients for implementing intent-based cognitive networking. Adaptive streaming telemetry is one example of a fast-growing ecosystem of embedded network automation applications that are also leveraging cloud technologies to bring operators closer to the vision of a network that is self-adapting, self-healing, and self-optimizing.

This content has been adapted from Infinera blogs, published in 2021/2022.

The Growth of CI/CD in Network Automation

Contributed By: Morgan Stern, VP Automation Strategy, Itential

Among the more enjoyable tasks that my job affords me is the opportunity to discuss both goals and challenges CSP network and orchestration teams face as they relate to network automation.

While these conversations typically span several different topics, trends do emerge; and while some of the ideas we discuss never materialize, others do gain traction and become the standard approach for those teams.

Last year, one trend that saw huge momentum was the intersection of network automation and CI/CD. Several CSPs I met with were developing pipelines to manage their network lifecycle activities. This made sense as the practices that changed the way software was developed, tested, and deployed could yield the same types of benefits to the processes for integrating and deploying network automations and orchestration.

While it felt like everyone wanted to discuss CI/CD, the focus of their pipelines varied significantly across different CSPs. For example, some wanted to create pipelines for the specific configs in an “Infrastructure as Code” (IaC) model. Others, wanted to create pipelines for their automation artifacts – the scripts, workflows, templates, etc. – seeking a more structured process for development, testing and deployment now that automation activities were evolving from task-centric to end-to-end process focused. . And in other cases, some CSPs wanted to develop pipelines for managing the automation platforms themselves, to provide the capability to automate the testing, integration, and deployment of the automation/orchestration engines through the version upgrade and patch processes.

After much investigation, which included talking with CSPs around the world, as well as with engineers and SMEs across a few different disciplines, three common themes emerged:

 

  1. The desire for implementing orchestration/automation CI/CD pipelines was in response to the growing dependency and complexity of automation activities within the CSPs.

Automation has graduated from small scripts used by individual engineers to solve specific problems, to automation architectures that solve for end-to-end activities. During this evolution, the limitations of some approaches became obvious. Certain practices did not scale well and created an enormous amount of technical debt in the attempt to take tools that were designed to solve one problem (automate a single task) and apply them to a much larger and more complex problem (automate a business/technical process).

 

  1. The problem set that any given CSP was trying to solve with CI/CD was a reasonably accurate indicator of where that CSP was in their automation and orchestration journey.

Infrastructure as Code (IaC) was the starting point for most organizations, but as the infrastructure required to execute automations became more complex, teams realized that they needed to address the complexity of developing, testing, and deploying the automation assets themselves to ensure interoperability, versioning, and security of assets like new scripts, workflows, and templates. The next challenge was how to create pipelines to ensure that, without disruption to the production environment, the automation tools and platforms were integrated, tested, and upgraded securely..

 

  1. Pipeline development created additional opportunities for automation, particularly for testing activities.

Multiple CSPs wanted the ability to dynamically instantiate working environments to improve the quality of their testing efforts. This created the need for capability to replicate portions of the production network and network services within the lab on demand, and then to have mechanisms for storing and managing network snapshots that could be accessed, versioned, and automatically updated to reflect architectural or vendor changes in production.

I’m excited to observe the best practices that emerge from these activities, and the new tools CSPs employ to manage their automation pipelines. As a network automation vendor, we are always looking for features to simplify pipeline development, and we expect other vendors and the Open-Source community to do the same. With these new capabilities, automation activities should accelerate dramatically, driving significant incremental business benefits for productivity and agility and opening the door for new service offerings made possible through these innovations.

 

 

 

 

Automate everything at cloud scale with Oracle’s Unified Operations portfolio

Contributed by: Anil Rao, Senior Director of Product Marketing and Strategy, Oracle Communications

Many of us in the communications industry remember a time when nearly all operations were manual. Order fulfillment was done by moving paper files from one desk to another, communications networks were made up of boxes into which people plugged cables, and network operations employees handled monitoring manually, and escalated with phone calls or onsite fixes.

Today, Communications Service Providers (CSPs) face a rapidly changing set of technology and business drivers that are fundamental to how they run their operations. Cloud and programmable networks are replacing physical networks, 5G and edge are driving new complexity and requirements, consumer and enterprise customers demand one-click self-service experiences, and business models to monetize networks are in flux.

As a result of these changes, service providers face many challenges. They must reduce operating expenses to improve profitability in increasingly commoditized markets. Siloed tools and fractured operations make it difficult to move beyond the manual, swivel chair operations in an era of ever-increasing network complexity. A lack of technical agility hinders the ability to exploit the benefits of cloud technology, and a lack of business agility constrains the ability to capitalize on new business models and B2B2X relationships enabled by 5G. In short, traditional telcos must transform to become “techcos” – See the recent white paper here – modern service providers that embrace automation and cloud native solutions to deploy innovative business models and deliver high value experiences to their customers.

Service providers today are looking to automate everything that can be automated to reduce costs, tackle complexity, and exploit emerging business opportunities. This includes “north-south” automation whereby customer intent is captured during the self-serve ordering process, then modeled and seamlessly implemented in downstream systems from business operations to service operation, to resource operations at the network level. Intent-based automation is then complemented by “east-west” automation in a closed loop fashion with end-to-end service automation spanning service orchestration, inventory, and assurance.

Introducing Oracle Unified Operations

Oracle’s Unified Operations portfolio is designed to help service providers automate everything at cloud scale. It unifies silos and abstracts complexity across multi-domain networks and services while also unifying multi-vendor networks and tools to provide a ‘single pane of glass’ visibility. Additionally, the unification of orchestration, assurance, and inventory functions across the operations environment provides automated lifecycle management. Cloud native, dynamic, and highly scalable, Unified Operations is architected for the communications needs and networks of today and the future.

The portfolio is comprised of four cloud native solutions, all aligned with TM Forum Open APIs

  1. Unified Assurance. Unifying network and service monitoring across diverse network technologies, generations, and domains, to drive ML-based automated fault and event management, root cause analysis, and performance monitoring.
  2. Unified Orchestration. Bringing together domain specific configuration systems and orchestration platforms with a multi-domain service orchestration platform to drive intent-driven automation
  3. Unified Inventory and Topology. Unifying service, network, and resource visibility across diverse network technologies, generations, and domains, aiding with real time views for automated orchestration and assurance.
  4. Unified Orchestration and Assurance. Bringing together all the components of Unified Operations, this composite solution drives closed loop automation for mobile, fixed line, digital services.

 

Built upon a rich portfolio of Oracle’s proven OSS products together with those of our recent acquisition of Federos , Unified Operations is already helping hundreds of service providers around the world to automate their assurance, orchestration, and inventory processes to improve profitability, deliver a positive customer experience, and capitalize on the opportunity to monetize 5G.

About Oracle Communications:

Oracle Communications provides integrated communications and cloud solutions for Service Providers and Enterprises to accelerate their digital transformation journey in a communications-driven world from network evolution to digital business to customer experience. To learn more about Oracle Communications industry solutions, subscribe to our blog and visit: Oracle Communications LinkedIn, or join the conversation at Twitter @OracleComms.

 

Monetizing 5G SA = ML-Infused Automation + New Operational Methods 

Contributed by B-YOND.

Recovering from the Covid-19 pandemic, the importance of seamless telecommunication services delivering high-speed, ultra-low latency, differentiated network services is more pronounced and significant than ever. As a result, a Telco paradigm shift towards 5G Standalone (5G SA) is imperative to deliver differentiated, highly valuable services, potentially rendering 4G LTE and 5G non-standalone (5G NSA) technologies futile.

Beyond Telco, other Vertical Enterprises (aka Smart Enterprises), such as the health care and automotive industry, are leveraging the benefits of 5G SA. The diverse applicability of 5G SA is attributed to its distinctive dynamic individuality & its ability to deliver:

  • Massive Machine-Type Communications
  • Simplified Network Architecture
  • Ultrareliable, low latency comms
  • Network Slicing (hence new Monetizable Services)
  • Network Cost Optimization

 

ML-Infused Automation

5G SA needs ML-infused automation of a disaggregated and reaggregated full stack solution. Though 5G Standalone technology promises numerous advantages, its induction has proven challenging. 5G SA is complex because it demands the disaggregation and reaggregation of the vertical (full) stack. The technology entails multiple and diverse horizontal layers provided by different vendors, hence disaggregation. Afterward, the reaggregation of the vertical (full) stack delivers a flexible comprehensive architecture that combines all the distinctive (and differentiated capabilities) chosen from the individual horizontal layers. This full stack architecture requires at least five different vendors (one from each horizontal row, see Figure 1).

It is arduous to judiciously select five vendors horizontally only to reintegrate the chosen ones vertically for an optimized monetizable architecture. Achieving this requires a scientific selection process to incorporate the layers in a lab environment & verify their homogenized functionality. The scattered nature of these layers not being pre-integrated and validated necessitates ML-infused automated blueprint validation to deliver an optimal architectural implementation. This blueprint needs to be configurable and, more importantly, repeatable. Accordingly, an automated method for blueprint delivery is essential as 5G SA demands automated segregation and reintegration.

Figure 1: Blueprints for Disaggregation and Reaggregation

Ideally, 5G SA services need to be conceptualized and delivered in minutes or hours through self-service accounts that allow users to create services from a catalog. 5G SA’s capabilities, such as network slicing, support the creation of differentiated services that provide innovative monetizable value to consumers and Smart (vertical) Enterprises. For example, a sliced network can address the needs of crucial communications like e911 while another slice of the same network handles V2V or V2I & another handles IIoT (monitoring gas pipeline leaks). In this example, each slice requires ultra-low latency at the sub-milliseconds level to address new B2B2C models. These 5G SA network sliced latencies are lower than those typically used in 4G LTE (and even 5G NSA) networks. Therefore, it is essential to test end-to-end precision, speed, and latency to ensure that the quality grade is suitable for mission-critical M2M, health sector & Autonomous Driving (ADAS) tasks.

 

End-to-End Validation Required for New Operational Methods

5G SA capabilities, such as network slicing, uLLC (ultra-low latency), and eMBB (improved broadband services), facilitate many new differentiated services. However, developing new end-to-end services designed for rapid operationalization (in hours, days, or seconds) is immensely difficult. Presently, simple, preliminary network services take months, quarters, or up to a year to enable! Nonetheless, rapid rollouts for new premium differentiated services are crucial for the operation and monetization of 5G SA and the realization of its full potential.

New differentiated services as required by B2B customers and Smart Enterprises (aka vertical industries) need ubiquitous end-to-end network services (from app to UE to Tower to RAN to Core/IMS through S1 to internet/server) with value generation enabled for Private Wireless. Facilitating these universal services requires all network parts (from app/UE to Core to app/server/internet) to be provisioned using an amalgamation of service catalogs of sub-systems dynamically strung together and tested on an almost real-time basis.

Additionally, operational needs require Zero Touch Service Provisioning (ZTSP) (not just ZTP as defined by TM Forum). Service creation needs to happen end-to-end horizontally (across the X-Axis) from App/UE to Core, along with configuring and setting up the vertically reaggregated (full) stack, (across the Y-Axis) to deliver the complete solution. Creating dynamic services using approaches such as BPM (Business Process Models) is paramount to competing in the modernization of telecommunications service delivery.

 

In conclusion, a mix of ML-infused automation and ZTSP enabled SDx (Service Delivery Experience) is required to monetize and offer new services, at an exponentially accelerated pace, using new operational models that address the needs of B2B and B2B2C ecosystems. While there may appear to be a multitude of “buzz” solutions available from various vendors, one that delivers both (a) ML-infused automation and (b) ZTSP that enables (c) integration across a broad ecosystem is needed to monetize 5G SA’s value.

B-Yond’s product AGILITY provides an ML-infused approach with ZTSP to realize the value of delivering SDx (Service Delivery Experience) and monetize 5G SA’s value. The new 5G standalone technology era brings advanced capabilities and challenges juxtaposed against its predecessors. Though the configuration of the 5G SA blueprints is rugged, the demand for this new wave of standalone technology is far too significant to ignore. The introduction of 5G SA blueprints will pioneer new and accelerated means of monetization across the telco industry. B-Yond aims to expand on the usage of 5G SA and is currently already using ML-infused automation to provide solutions such as Continuous Assurance (CA) via Anomaly Detection and Continuous Validation (CV) via Root Cause Analysis (RCA). RCA applies machine learning to automate test analyses & troubleshooting & predicts root cause for failures, decreasing the test life cycle and accelerating time-to-market. Anomaly Detection provides service assurance through continuous monitoring, prediction, & impact analysis, thus, accelerating the transformation to a low touch network with ML-based automation.

 

B-Yond’s ML-infused automation solution using our product, AGILITY, enables these much-needed capabilities. Refer to our website or ask for a demo/presentation for more details.

Website: https://bit.ly/B-YOND
Contact Email: contact@b-yond.com

Header image from the B-YOND website

 

 

Evolve network monitoring by combining fault management with performance management

Contributed by Amir Kupervas, Managing Director, Anodot.

Today’s telecom environments and networks are complex, presenting greater challenges than ever for those charged with monitoring the network, assuring continuous service, and driving customer experience.

To prevent customer complaints, the high cost for care, and ultimately – churn, operators need to be able to focus on how services are performing and what their customers are experiencing. To achieve this, it’s critical that they understand not only which technical issues had occurred, but what their impact is, and to resolve them before they turn into customer-impacting problems, instead of focusing on technical alarms.

This is why the traditional network monitoring framework, which relies on fault management for issue awareness, requires a more innovative approach.

Let’s take a closer look at how service providers can evolve network monitoring by combining network fault management with autonomous network performance management to profoundly improve service experience, reduce costs, and protect revenues.

 

The value of fault management

Network fault management systems detect and alert users to technical faults, i.e., events that result from malfunctions and which interfere with the correct functioning of the network.

The key benefits of network fault management include:

  • Detecting technical issues in real-time
  • Alerting incident handlers to the issue detected
  • Driving incident resolution for the restoration of service

 

Yet, alongside these benefits, there is also a limit to how much fault management alone can do for optimal service delivery and application availability:

  1. Fault alarms do not provide insights into what is the impact on service and customer experience.
  2. Fault alarms are de facto reactive, particularly with regards to service degradation, coming in after the fact and lacking the data and insights required for handling issues before they turn into customer-impacting problems.
  3. Prioritization is not possible since these alarms provide no input on the actual impact on customers and their service experience, nor on how many customers are being impacted.
  4. Root cause understanding is compromised since it requires fault alarm correlations that can only be executed by experts with hard to find and often costly skill sets.
  5. The sheer number of alarms coming in the millions, often results in alarm fatigue and with critical alarms being overlooked.
  6. Alerts are generated as based on pre-defined static thresholds, whose efficacy primarily depends on the skill-set and technical knowhow of the individual who defined them.

 

What is network performance management

Where fault management is focused on detecting and alerting to technical failures, performance management is focused on detecting service experience degradations and on correlating issues and alerts.

Performance management enables operators to go beyond knowing that a technical fault has occurred. It monitors all the elements that make up a service, delivers an understanding of what is the impact of the issue, how many customers are being impacted, and enables the operator to resolve them before they turn into customer-impacting problems.

 

Why PM needs to be autonomous

It’s not just any performance management approach that can fully complete fault management. This is because performance management offerings typically do not:

  • Monitor each network domain, layer, and type
  • Collect data from the entire network in one place
  • Correlate all data and prioritize by significance

 

As a result, operators are too often finding themselves still having to cope with alert noise, a prolonged time to resolve, low rates of root cause understanding, and rising customer complaints.

Autonomous network performance management eliminates these issues by:

  • Continually monitoring and correlating network and service anomalies across the entire telco stack
  • Monitoring cross-layer network performance and service experience.
  • Preemptively identifying trends and sending predictive alerts that point to the root cause of faults before they become problems.
  • Providing real-time actionable alerts for the next best action in their context.

 

A powerful combination

The combination of network fault management with autonomous network performance management constitutes a powerful framework for end-to-end service experience monitoring.

Fault management delivers strategic input about whether there was or wasn’t a malfunction, autonomous performance management delivers the strategic insights on the impact.

It lets the operator see the service degradation, understand what the root cause is, and dramatically reduce time to resolve through alerts that are in their context and actionable.

Moreover, autonomous performance management enables operators to be preemptive. For example, if there is a fault between a certain DNS that leaves subscribers unable to connect to Facebook, the issue will be alerted immediately, along with insights into why and what the next best action should be for accelerating resolution, before customers start calling into the contact center to complain.

 

How Anodot can help

Anodot is an autonomous network monitoring platform that completes the network fault management value proposition with real time detection of service-impacting incidents.

Anodot collects and analyzes data across the entire telco stack. Patented big data machine-learning algorithms detect outliers in time series data and make correlations among related anomalies. As a result, there is a 90% reduction in alert noise, 80% faster time to detect, 90% improved root cause analysis, and 30% faster time to resolve.

 

In conclusion

The telecoms business, operations, and network are in flux. And while it can sometimes be a great challenge to keep up, monitoring the network in a modernized and ever evolving ecosystem doesn’t have to be.

When combining the strengths of network fault management with autonomous network performance management, operators have the power to evolve network monitoring and improve service experience, reduce customer complaints, prevent churn, and protect revenues.

Now, that’s one powerful combination!

 

Drive down 5G complexity with automation

Contributed by Olivier Daures, Strategic Marketing, Communications Technology Group (CTG) at Hewlett Packard Enterprise

Why is automation a must-have requirement for emerging 5G services? And how can HPE help you enable it? Let’s take a closer look.

Imagine you run a successful restaurant kitchen, managing a busy team of station chefs and assistants. At any moment, your team is working on a dozen different tasks, but you manage to keep everything tightly coordinated and on schedule. Now, imagine your restaurant expands—by a lot. Now, you’re asked to serve dozens more dishes to 1,000x more diners. Suddenly you’re managing a staff of hundreds, with thousands of tasks happening simultaneously. You still need to keep everything coordinated and on schedule. One thing becomes immediately clear: the way you used to run things—all the systems and tools you had developed over the years—won’t work anymore.

To succeed at this scale, you need to completely rethink your operations.

Fortunately, this is just a hypothetical situation. But if you’re part of a service provider organization preparing for 5G standalone (5G SA) networks, it might sound familiar. 5G brings amazing new capabilities, with the ability to tailor services for enterprise and industrial customers and differentiate your offerings. But that flexibility comes with enormous new operational complexity. In a world of cloud-native infrastructure and microservices, your network has exponentially more moving parts—and yesterday’s operational approaches will no longer get the job done. There’s only one option: automate. And Hewlett Packard Enterprise (HPE), a global leader in service provider orchestration and assurance, can help you do it.

A driving need to automate

The next evolution of 5G networks rewrites the rules for service providers, breaking free from the “one-size-fits-all” connectivity models of the past. With the move to 5G SA, you can use network slicing to customize services for diverse enterprise use cases. You can configure slices to meet disparate requirements – for latency, resiliency, and other attributes – under different service-level agreements (SLAs), over a single infrastructure. 3GPP[1] has already identified 74 distinct consumer and business-to-business (B2B) service scenarios that 5G enables.

This is great news from a business perspective, allowing you to tap into new markets and use cases where you never played before. But operationally? Life just got a lot more complicated. If you’re responsible for provisioning and managing 5G services, you now have to contend with:

  • IT-based software models. 5G SA brings software methodologies from the IT world to service provider environments for the first time. Concepts like DevOps and automated Continuous Integration/Continuous Deployment (CI/CD) pipelines can help you be more agile by continually adding and optimizing network capabilities much quicker. But if you’re not used to working this way—and most Ops teams aren’t—it can feel like a totally different world.
  • Exponential increase in network entities. 5G also brings cloud-native architectures and disaggregation principles from hyperscale cloud environments to operator networks. Instead of using mostly monolithic, single-vendor network appliances, you’re now managing hundreds of virtualized and containerized network functions (VNFs/CNFs) from multiple vendors, and thousands of containers. Here again, you can benefit from agile and flexible cloud models, provided you can handle the massive increase in volume, dynamicity, and complexity of service elements.
  • Complex multi-layer, multi-vendor operations. To provision network slices, you need to apply consistent service characteristics end-to-end across all network layers and subnets such as RAN, core, transport, and enterprise, as well as VNFs/CNFs from multiple vendors.

If you’re wondering how you’ll navigate these requirements using manual processes, handcrafted workflows, and aging service assurance tools, you can’t. There are just too many discrete components, with too much happening at once. Somehow, you have to automate and abstract away that complexity, and enable zero-touch provisioning and management.

Automating 5G operations with tools from HPE

As a longtime leader in service provider network automation, and one of the first to offer a fully cloud-native 5G SA solution with the HPE 5G Core Stack, HPE is the ideal partner to help solve this complexity problem. With our 5G automation software, we can help you automate the end-to-end operation of 5G networks and slices and provide consistently excellent customer experiences.

We can help you:

  • Automate the management of 5G networks and services with intent-based orchestration and zero-touch operations
  • Accelerate your network slicing implementation to start offering customized enterprise services
  • Respond to ongoing network and service changes in dynamic 5G environments in a simple, codeless way
  • Deliver consistently superior 5G services with automated assurance, driven by artificial intelligence and machine learning (AI/ML)

You can enable these capabilities with two recent additions to the HPE portfolio:

  • 5G capabilities for HPE Service DirectorYou can now orchestrate 5G infrastructure and services in a simple, codeless way to optimize operations across your environment. With intent-based modeling, you can design service models and policies at the level of business processes and orchestrate their end-to-end implementation across your hybrid network. You can use zero-touch, profile-driven 5G network slicing orchestration and fully automate lifecycle management of slices across domains.
  • HPE 5G Automated Assurance. Building on our industry-leading service assurance platform, we offer an ML-based solution to collect and monitor vast amounts of information from 5G networks. You can automatically detect, predict, and remediate network and service issues, including triggering healing actions. And you can use analytics tools and dashboards designed specifically for dynamic multi-vendor 5G networks.

How to maximize 5G network investment ROI and deliver on business KPIs

Contributed by Andrew Baldock, Product Marketing Director, Infovista

5G network rollout is creating complexity for operators planning networks and services like never before. Not only are the RF technologies involved in in 5G network roll-outs new; the revenue streams that will pay for them are new too – supported in many cases by as yet untried business models.

Against this backdrop, there’s no room for waste when rolling out, densifying and expanding 5G networks. Planning must not only maximize today’s addressed revenue; it must also be ready to accommodate potential revenue growth.

Whether it’s a greenfield network or an expansion and densification of a live network, operators have long been faced with the need to control CAPEX. But, the fact is that these days the business side of an operator is just as invested in the success of network planning as the technical side. Network performance is increasingly directly connected to revenue, with the increasing prevalence of service level agreements (SLAs). However, the ability to quickly deploy and scale 5G network infrastructure with the highest revenue potential is hindered by legacy siloed processes.

A new agile way of working is needed, combining traditionally separate disciplines.

There needs to be a shift in focus in network planning, from network KPI optimization to business outcomes optimization, and on combining diverse network and business predictions within a single vendor-neutral software application.

Senior stakeholders – including the CTO and CMO organizations – need accurate, predictive views of how their network plans will deliver against the business KPIs, including TCO, additional revenue, churn and ROI. They need to answer questions like how to prioritize the allocation of budget in different geographies so as to capture the larges revenue upside at the lowest cost; or how to target high churn probability hotspots in the network which exist today or will pop-up in the future.

This means data. Data that supports this decision-making must of course include things like the targeted number of sites; download and upload performance; coverage targets; throughput; capacity targets; traffic growth areas, RAN products performance; antenna propagation; latency; interference. The list goes on.

But it’s not enough to just understand the physical network, it’s vital that the teams can understand how the network is being used – the end-users’ experience. The population density in different areas, the dwell time around different cell sites, what kinds of content users consume, even the price plans the customers are on, can be useful for planners. That means live performance management (PM) traffic data, crowdsourced data, social media usage, high resolution geodata and geolocated call traces as examples.

Then to round things off, there’s financial data: TCO, cell-level revenue, regional ARPU.

All this is required to enable decision makers to answer questions like: will demand increase over time? To what extent does this vary? Are we missing areas of demand? How sensitive is predicted revenue to capacity availability? What is the optimum trade-off between throughput capacity and customer experience if, say, a certain area experiences heavy social media usage for only a very short time?

In short, operators need to marry together network planning and business outcomes in a systematic way, using advanced analytics to optimize predicted ROI and then quickly act on the information.

Network planning is a learning process. In an environment where more and more data points can be incorporated into planning, it isn’t a task human teams can manage unassisted. Artificial intelligence (AI) and machine learning (ML) have an increasingly important role to play in the automation of complex decision-making.

Our approach – Smart CAPEX – supports engineering and network planning teams to optimize their efforts in radio network evolution planning for densification and expansion including multiple what-if scenarios simulation in a systematic, repeatable, and continuous way. It leverages fully automated business-driven planning algorithms along with rich geospatial views that provide ‘at-a-glance’ information about the current and predicted network performance, areas, and hotspots with poor QoE or capacity bottlenecks. On top of that, the solution automates the design of the network optimized for TCO, revenue and the resulting ROI.

Smart CAPEX enables CSPs to intelligently optimize traffic and revenue potential against deployment costs and then invest where it matters most to increase the return on investment from their networks. It ends the problem of siloes, enabling the senior team right across the organization to work from a single dashboard, modeling prioritized cell site deployments based on their traffic and revenue potential and making smart investments that address the business KPIs.

In short, Smart CAPEX allows 5G operators to effectively and efficiently plan, optimize and model to deliver next generation networks with the maximum return on investment. It then continues to do so through the network’s lifecycle as adjustments and improvements are highlighted, costed, and implemented.

As 5G rolls out, operators will need to apportion costs with more precision, based on their network’s needs and revenue. The result will improve not just the networks of tomorrow, but the ROI they generate.

 

Register for the 22nd February, Webinar: Smart CapEx investment: Optimizing for RoI featuring C-Level execs from Infovista, BT, Telus, T-Mobile Netherlands, Rakuten Mobile & STL Partners

How Telcos can Prepare for 5G Monetization

Contributed by Marcin Nowak, Senior Solutions Manager, Comarch.

The global rollout of 5G networks represents a true revolution in telecommunications technology. Operators have invested heavily in upgrading and replacing physical and virtual elements of their networks – so the big question for them is how to monetize 5G and maximize the return on their investment.

Without a doubt, network slicing will be at the center of 5G monetization efforts. In fact, almost all operators (95%) believe that the broader concept of network as a service (NaaS), encompassing network slicing, will drive 5G monetization. If they are to take the full benefits of NaaS, telcos will need to focus strongly on automation driven by artificial intelligence (AI) and machine learning (ML) in key areas.

This will mostly impact network maintenance and management processes, neither of which can be optimized in a 5G network without automation. Zero-touch AI/ML-driven network management means networks and network slices can be scaled to meet demand at any given time, without human intervention. In terms of automated 5G network maintenance, automating predictive, preventive and corrective processes means that the network can self-monitor, self-heal, and even predict potential issues – thus avoiding problems and ensuring a high level of customer service. What’s more the time and financial investment required to implement such a solution do not need to be high.

Another area in which telecommunications network operators can monetize 5G deployment and see a return on their investments involves the Internet of Things (IoT), in the business to business (B2B) and business to consumer (B2C) fields. We are already familiar with IoT-enabled services such as smart homes, factories and cities – not to mention driverless cars and e-health services – but this is just the start. In each of these areas, technology is expected to continue evolving at an increasingly rapid pace, and we can also expect new 5G/IoT use cases to emerge in the near future, which will present yet more monetization opportunities for telcos in B2B and B2C.

With technological advances happening so quickly, it’s difficult to predict what is just over the horizon. In this respect, operators need to ensure their 5G networks are future-proof, so they are ready to take advantage of new opportunities as they develop. Those who are not at least planning a strategy along these lines risk being left behind.

For more on these subjects and others related to monetizing and preparing for 5G services, see the four-episode “Telecoms Journey Towards 5G Monetization” campaign from Comarch.

Marcin is a panelist at FutureNet Middle East & Africa on the 26th of January. CSPs register free here.

Why end-to-end service orchestration is a must for conducting network symphonies

Contributed by Ofer Farkash, Product and Solutions Marketing Director, Amdocs.

Why does an orchestra need a conductor? With their prominent position at the front of the stage, and everyone’s eyes fixed upon them, they certainly look important. But if the musicians already have scores guiding them what to play, shouldn’t they be able to manage on their own?

An orchestra comprises a group of individual, highly skilled musicians, each of whom has learned and practiced their instrument for years. But while each musician knows their own piece of the score, if you leave them together to play without common guidance, you’ll have no single voice of the music’s speed, volume or expression. The conductor is the one who unifies all of these variables, weaving the individual players and their sections into a cohesive unit and giving life to the music on the page.

Modern telecommunication networks are much like orchestras, with network services being the symphonies. They are “composed” by chaining specialized siloed capabilities across a hybrid network that spans multiple domains and technologies, as well as a mix of physical, virtual and cloud network functions that spread all the way from the network access and edge to the core, telco cloud – and now, also public clouds.

Just as the challenge of an orchestra is to get all musicians to perform the same piece for a harmonized symphony/outcome, operators must overcome the challenge and complexities of multi-vendor, multi-technology networks and cloud siloes so their services meet their committed performance and customers’ needs and expectations.

Communication service providers (CSPs) are slowly progressing in their network virtualization journeys by gradually introducing network functions virtualization (NFV) and software-defined networking (SDN). Until the journey is complete, over the coming years, many parts of the network will continue to rely on traditional physical appliance-based network elements. This mix of siloed virtual, physical network domains and clouds, which are managed by specific domain orchestrators, controllers or other management systems, expose critical multi-vendor and multi-domain complexities, while diminishing end-to-end visibility, control and the ability to run operational processes efficiently.

While some operators are trying to bridge these siloes with highly disjointed manual processes, such an approach does not scale. Trying to manage today’s highly complex services such as secure SD-WAN, NaaS, edge and 5G services using manual processes that span multiple system silos is increasingly difficult and undermines the ability of CSPs to not only innovate and meet their customers’ emerging needs, but also to deliver and operate services in a timely manner that comply with service-level agreements.

Moreover, almost every service today must operate across a network that spans multiple domains and technologies, traversing all the way from fixed or mobile access to the edge and core, and accessing the telco and public clouds. One such service is 5G network slicing.

5G network slicing enables CSPs to move away from the rigid ‘one size fits all’ business model to offer differentiated connectivity services such as ultra-low latency and massive IoT services with varying network performance characteristics. But to deliver on this promise, they need an end-to-end network slice orchestration and operations solution that can create, provision and manage the lifecycle of network slices spanning the RAN, edge, transport and core network domains.

An end-to-end network slice orchestration solution monitors the performance of each individual network slice, ensuring it meets its SLAs by triggering the various underlying domain controllers to make corrective actions to resolve service degradation.

For all these reasons, many service providers are now looking to implement a solution for end-to-end network and service orchestration that enables them to obtain efficient and effective service lifecycle management of network and cloud services across multiple siloed domains, vendor technologies and hybrid networks.

 

 

Just as a conductor acts as the orchestra’s quality control manager – unifying the musicians, setting the tempo, listening critically, calling out errors and anticipating potential ones – when it comes to networks, this is the job of the end-to-end service and network orchestration solution. It ensures that service intent and quality of experience are maintained by executing continuous service fulfilment and dynamic closed-loop assurance and enforcement of services, xNFs, as well as network and cloud resources policies.

For CSPs, an intelligent, standards-based end-to-end service and network orchestration solution has today become a necessity. In partnership with the right vendor, such a solution provides the empowerment to fully exploit their investments in best-of-breed specialized network technologies, while unleashing the huge potential of cross-domain 5G and other modern services, as well as programmable and cloud-native networks to create new revenue streams.

Read the solution overview to learn more.

Ofer is a panelist at FutureNet Middle East & Africa on the 26th of January. CSPs register free here.