Traditional network architectures are inherently fragile, often relying on a single transport type to connect branches, production facilities, and data centres. The imperative for networks to maintain resilience has grown significantly, particularly due to the delivery of customer-facing services at branches and the increasing reliance on interconnected machines in operational environments. The cost of network downtime can now be quantified in terms of both lost customers and reduced production.
Distributed Enterprises Face New Challenges
As the importance of maintaining resiliency grows, so does the complexity of network management. Distributed enterprises must provide connectivity under challenging conditions, such as:
- Remote access for employees using video conferencing
- Local breakout for cloud services to avoid backhauling
- IoT devices left unattended in public places
- Customers accessing digital services at the branch or home
- Sites in remote areas requiring the same quality of service
Network managers require intelligent tools to remain in control without adding any unnecessary burden to end users. The number of endpoints and speed of change has made it impossible for human operators to manage without assistance from AI.
AI-Enhanced Network Management
Modern network operations centres are enhancing their visibility by aggregating data from diverse systems and consolidating them within a unified management platform. Machine learning (ML) and AI are employed to analyse data originating from enterprise networks, telecom Points of Presence (PoPs), IoT devices, cloud service providers, and user experience monitoring. These technologies enable the early identification of network issues before they reach critical levels. Intelligent networks can suggest strategies to enhance network resilience, forecast how modifications may impact performance, and are increasingly capable of autonomous responses to evolving conditions.
Here are some critical ways that AI/ML can help build resilient networks.
- Alert Noise Reduction. Network operations centres face thousands of alerts each day. As a result, operators battle with alert fatigue and are challenged to identify critical issues. Through the application of ML, contemporary monitoring tools can mitigate false positives, categorise interconnected alerts, and assist operators in prioritising the most pressing concerns. An operations team, augmented with AI capabilities could potentially de-prioritise up to 90% of alerts, allowing a concentrated focus on factors that impact network performance and resilience.
- Data Lakes. Networking vendors are building their own proprietary data lakes built upon telemetry data generated by the infrastructure they have deployed at customer sites. This vast volume of data allows them to use ML to create a tailored baseline for each customer and to recommend actions to optimise the environment.
- Root Cause Analysis. To assist network operators in diagnosing an issue, AIOps can sift through thousands of data points and correlate them to identify a root cause. Through the integration of alerts with change feeds, operators can understand the underlying causes of network problems or outages. By using ML to understand the customer’s unique environment, AIOps can progressively accelerate time to resolution.
- Proactive Response. As management layers become capable of recommending corrective action, proactive response also becomes possible, leading to self-healing networks. With early identification of sub-optimal conditions, intelligent systems can conduct load balancing, redirect traffic to higher performing SaaS regions, auto-scale cloud instances, or terminate selected connections.
- Device Profiling. In a BYOD environment, network managers require enhanced visibility to discover devices and enforce appropriate policies on them. Automated profiling against a validated database ensures guest access can be granted without adding friction to the onboarding process. With deep packet inspection, devices can be precisely classified based on behaviour patterns.
- Dynamic Bandwidth Aggregation. A key feature of an SD-WAN is that it can incorporate diverse transport types, such as fibre, 5G, and low earth orbit (LEO) satellite connectivity. Rather than using a simple primary and redundant architecture, bandwidth aggregation allows all circuits to be used simultaneously. By infusing intelligence into the SD-WAN layer, the process of path selection can dynamically prioritise traffic by directing it over higher quality or across multiple links. This approach guarantees optimal performance, even in the face of network degradation.
- Generative AI for Process Efficiency. Every tech company is trying to understand how they can leverage the power of Generative AI, and networking providers are no different. The most immediate use case will be to improve satisfaction and scalability for level 1 and level 2 support. A Generative AI-enabled service desk could provide uninterrupted support during high-volume periods, such as during network outages, or during off-peak hours.
Initiating an AI-Driven Network Management Journey
Network managers who take advantage of AI can build highly resilient networks that maximise uptime, deliver consistently high performance, and remain secure. Some important considerations when getting started include:
- Data Catalogue. Take stock of the data sources that are available to you, whether they come from network equipment telemetry, applications, or the data lake of a managed services provider. Understand how they can be integrated into an AIOps solution.
- Start Small. Begin with a pilot in an area where good data sources are available. This will help you assess the impact that AI could have on reducing alerts, improving mean time to repair (MTTR), increasing uptime, or addressing the skills gap.
- Develop an SD-WAN/SASE Roadmap. Many advanced AI benefits are built into an SD-WAN or SASE. Most organisations already have or will soon adopt SD-WAN but begin assessing the SASE framework to decide if it is suitable for your organisation.
Cyber threats are growing in volume, intensity, and complexity and are here to stay. Basic endpoint attacks are becoming intricate, multi-stage operations. Cybercriminals are launching highly coordinated and advanced attacks. This evolving threat landscape affects businesses of all sizes, jeopardising data, operations, and finances.
In the face of massive data leaks, costly ransomware payments, and an ever-expanding and complex threat landscape, the need to strengthen digital defences has driven significant advancements in cybersecurity.
Read on to find out how organisations, governments, industry associations and technology providers are evolving ways to combat cybercrime.
Download ‘Securing the Future: Cyber Resiliency in the Digital World’ as a PDF
Organisations in Asia Pacific are no longer only focused on employing a cloud-first strategy – they want to host the infrastructure and workloads where it makes the most sense; and expect a seamless integration across multiple cloud environments.
While cloud can provide the agile infrastructure that underpins application modernisation, innovative leaders recognise that it is only the first step on the path towards developing AI-powered organisations. The true value of cloud is in the data layer, unifying data around the network, making it securely available wherever it is needed, and infusing AI throughout the organisation.
Cloud provides a dynamic and powerful platform on which organisations can build AI. Pre-trained foundational models, pay-as-you-go graphics superclusters, and automated ML tools for citizen data scientists are now all accessible from the cloud even to start-ups.
Organisations should assess the data and AI capabilities of their cloud providers rather than just considering it an infrastructure replacement. Cloud providers should use native services or integrations to manage the data lifecycle from labelling to model development, and deployment.
In this Ecosystm Byte, sponsored by Oracle, Ecosystm Principal Advisor, Darian Bird presents the top 5 trends for Cloud in 2023 and beyond. Read on to find out more.
Download ‘The Top 5 Cloud Trends for 2023 & Beyond’ as a PDF
Technology has been reshaping the Real Estate industry landscape. Advancements in manufacturing technologies, digital tools, AI & analytics, and IoT – coupled with customer and employee expectations – are revolutionising how properties are built, bought, sold, managed, and experienced.
The evolution of RealTech and PropTech has a far-reaching impact on the industry, streamlining processes, improving customer experiences, and driving innovation across the entire sector.
Read on to find out how technology impacts the entire value chain; the key drivers of Real Estate evolution; the strong influence of “smart consumers”; and what Ecosystm VP Industry Insights Sash Mukherjee thinks where the industry is headed.
Download ‘The Future of Real Estate’ as a PDF
Since officially separating from IBM in November last year, Kyndryl has been busy cementing some heavyweight partnerships. The alliances with Microsoft, Google, and VMware demonstrate its intention to build hybrid cloud solutions with whoever it needs to, rather than favouring the Big Blue or Red Hat. The SAP tie-up hints at a future of migrating ERP workloads to the cloud and even an eye on moving up the application stack. Last week Kyndryl announced it is working with Nokia to provide private 5G and LTE networks to enable Industry 4.0 solutions. The first customer reference for the partnership is Dow, deploying both real-world and proof-of-concept applications for worker safety and collaboration and asset tracking.
The Partnership
Kyndryl has a competitive networking services unit, particularly in partnership with Cisco. Its focus has been on SD-WAN, campus networks, and network management as part of broader cloud services deals. This 5G partnership with Nokia is its first serious effort to work with one of the major carrier-grade vendors using cellular technology. It creates an opportunity for Kyndryl to position itself as a provider of services that underpin IoT and edge applications, rather than only cloud, which has until now been its main strength.
Prior to the Kyndryl announcement, Nokia was already developing private 5G solutions under the moniker Digital Automation Cloud (DAC). A key customer is Volkswagen, using the network to connect robots and wireless assembly tools. Over-the-air vehicle updates are also tested over the private network. Volkswagen operates in a dedicated 3.7-3.8 GHz band, which was allocated by the Federal Network Agency in Germany. This illustrates a third option for accessing spectrum, which will become an important consideration in private 5G rollouts.
Private 5G Use Cases
Private 5G has several benefits such as low latency, long-range, support for many users per access point, and provision for devices that are mobile due to handover. It is unlikely that it will completely replace other technologies, like wireless LAN, but it is very compelling for certain use cases.
Private 5G is useful on large sites, like mines, ports, farms, and warehouses where connected machines are moving about or some devices – like perimeter security cameras – are just out of reach. Utilities, like power, gas, and water, with infrastructure that needs to be monitored over long distances, will also start looking at it as a part of their predictive maintenance and resiliency systems. Low latency will become increasingly important as we see more and more customer-facing digital services delivered on-site and autonomous robots in the production environment.
Another major benefit of private 5G compared to operating on public service is that data can remain within the organisation’s own network for as long as possible, providing more security and control.
Private 5G Gaining Popularity
There has been a lot of activity over the last year in this space, with the hyperscalers, telecom providers and network equipment vendors developing private 5G offerings.
Last year, the AWS Private 5G was announced, a managed service that includes core network hardware, small-cell radio units, SIM cards, servers, and software. The service operates over a shared spectrum, like the Citizens Broadband Radio Service (CBRS) in the US, where the initial preview will be available. CBRS is considered a lightly licenced band. This builds on AWS’s private multi-access edge compute (MEC) solution, released in conjunction with Verizon to integrate AWS Outposts with private 5G operating in licenced spectrum. A customer reference highlighted was low latency, high throughput analysis of video feeds from manufacturing robots at Corning.
Similarly, Microsoft launched a private MEC offering last year, a cloud and software stack designed for operators, systems integrators, and ISVs to deploy private 5G solutions. The system is built up of components from Azure and its acquisition of Metaswitch. AT&T is an early partner bringing a solution to the market built on Microsoft’s technology and the operator’s licenced spectrum. Microsoft highlighted use cases such as asset tracking in logistics, factory operations in manufacturing, and experiments with AI-infused video analytics to improve worker safety.
The Future
Organisations are likely to begin testing private 5G this year for Industry 4.0 applications, either at single sites in the case of factories or in select geographic areas for Utilities. Early applications will mostly focus on simple connectivity for mobile machines or remote equipment. In the longer term, however, the benefits of private 5G will become more apparent as AI applications, such as video analysis and autonomous machines become more prevalent. This will require the full ecosystem of players, including telecom providers, network vendors, cloud hyperscalers, systems integrators, and IoT providers.
It is an incredible time of change for the city and regional governments where every strategic activity – especially in these globally challenging times – presents a significant opportunity for transformation. To continue to meet the changing needs of the communities they serve, every modern city government’s technology story is a work in progress. While this is the mantra for successful continuous improvement it also describes the best strategic approach for how municipalities should manage their corporate application replacement programs.
Unfortunately, significant systems upgrade and replacement programs are regularly approached as complex, multi-tasking activities that have a hard start, a defined program, and a date-stamped end. In taking this traditional project implementation approach, intuitively, many organisations believe that doing as much as possible, in as quick a time as possible, ultimately helps to achieve twice as much within the same time. The result is more likely to be half as much, and at lower levels of quality and enjoyment for all involved. This manifests as project scope creep and budget overruns.
Aside from these big bang approaches, thanks to large implementation costs and stringent regulatory oversight, local governments are also forced to think upfront about the potential future value created by a significant core system technology change. The pressure of moving at high speed, and with a dominant technology focus, can obscure both the true organisational cost and ultimate value of the program. This mentality prevails even when it is acknowledged that activities associated with a transformation program will eventually usher in a period of significant change – that is not limited to the changing core corporate applications environment itself.
The 4-Part ERP Transformation Trap is All Too Common in City Government
An over-reliance on technology to deliver business transformation outcomes. Local governments everywhere continue to pursue strategic plans that are either wholly defined or implicitly reliant on world-class customer experience (CX), employee experience (EX), and digital transformation (DX) capabilities. Despite these being business-oriented strategies, organisations then pursue an over-reliance on technology – usually winner-take-all ERP led procurements – to achieve them.
Choosing an industry solution focused on the wrong business model. The chance of achieving these digital transformation outcomes is further obscured when the customer is not central to the data model. The core corporate application technology underpinning the sector’s leading ERP programs is largely based on a property-centric model – where the customer is a subordinate attribute of a property, and the property asset defines the business process and individual. It is a challenge for any council to deliver contemporary customer-first digital transformation with a property-centric approach. To realise customer and employee-centric outcomes, councils must therefore rethink their project’s business methodology and ask themselves, “what is our primary focus here?”. This is never more important than when replacing legacy systems.
Inability to realise that a winner-take-all ERP solution is not an architectural choice. ERP is important but it is not everything. The traditional council ERP is just one important part of an overall capability that allows authorities to longitudinally manage the impacts and opportunities of change across their organisation, communities, and stakeholder ecosystems. Having chosen a sector specific ERP solution, city governments realise too late that no single technology vendor has a best-of-breed solution to achieve the desired DX outcomes. That requires a more sophisticated architectural approach.
Failure to acknowledge there is no finish line to transformation. Like many worthwhile activities, the prize in DX is in the journey, not in the cup. While there can be an end to “project scope”, there should be no “end point” for an ERP transformation program. Only once these challenges are acknowledged and accepted, can transformation be assimilated into the organisation to ensure the council is technically capable of delivering the implicit outcome for the organisation. This could simply be defined as ‘a contemporary business approach to managing the money, the assets, the community, the customers, and the staff of regional government.’
A Better Way: Re-Architecting for Project Success
Where opportunities to meet increasing CX and EX demands arise, especially through ERP and corporate application renewal programs, successful projects in contemporary councils require a service-oriented architecture not found in contemporary or legacy ERP systems alone.
Beyond the property-centric challenges already outlined, even contemporary systems and suppliers can be among the least flexible to the changing data management requirements of many organisations which call for significantly more robust data, integration and application friendly infrastructure management environments.
Customer centricity, data management, integration and software infrastructure capabilities must take precedent over an aging view of single-vendor dominance in the city government sector, especially in middle- and back-office functions, which are typically void of true differentiation opportunities and prone to confining organisations to technology-led and locked projects.
Rather than tendering for a single software provider or platform, contemporary city governments must ditch the old approach to procuring a winning ERP vendor and take steps to establish the following Big 5 platform capabilities (Figure 1). And then foster the contemporary workforce to support them.
For several decades now many organisations have attempted to short-circuit the city government ERP challenge. Fundamentally, technology transformation is not possible without technology change. A non-negotiable part of that change is a shift away from the psychology of brand-based procurement towards a new architectural approach which, like all businesses, is adaptable to change over a long period of time.
The Internet of Things (IoT) solutions require data integration capabilities to help business leaders solve real problems. Ecosystm research finds that the problem is that more than half of all organisations are finding integration a key challenge – right behind security (Figure 1). So, chances are, you are facing similar challenges.
This should not be taken as a criticism of IoT; just a wake-up call for all those seeking to implement what has long been test-lab technology into an enterprise environment. I love absolutely everything about IoT. IT is an essential technology. Contemporary sensor technologies are at the core of everything. It’s just that there are a lot of organisations not doing it right.
Like many technologists, I was hooked on IoT since I first sat in a Las Vegas AWS re: invent conference breakout session in 2015 and learned about MQTT protocols applied to any little thing, and how I could re-order laundry detergent or beer with an AWS button, that clumsy precursor to Alexa.
Parts of that presentation have stayed with me to this day. Predict and act. What business doesn’t want to be able to do that better? I can still see the room. I still have those notes. And I’m still working to help others embrace the full potential of this must-have enterprise capability.
There is no doubt that IoT is the Cinderella of smart cities. Even digital twinning. Without it, there is no story. It is critical to contemporary organisations because of the real-time decision-making data it can provide into significant (Industry 4.0) infrastructure and service investments. That’s worth repeating. It is critical to supporting large scale capital investments and anyone who has been in IT for any length of time knows that vindicating the need for new IT investments to capital holders is the most elusive of business demands.
But it is also a bottom-up technology that requires a top-down business case – a challenge also faced by around 40% of organisations in the Ecosystm study – and a number of other architectural components to realise its full cost-benefit or capital growth potential. Let’s not quibble, IoT is fundamental to both operational and strategic data insights, but it is not the full story.
If IoT is the belle of the smart cities ball, then integration is the glass slipper that ties the whole story together. After four years as head of technology for a capital city deeply committed to the Smart City vision, if there was one area of IoT investment I was constantly wishing I had more of, it was integration. We were drowning in data but starved of the skills and technology to deliver true strategic insights outside of single-function domains.
This reality in no way diminishes the value of IoT. Nor is it either a binary or chicken-and-egg question of whether to invest in IoT or integration. In fact, the symbiotic market potential for both IoT and integration solutions in asset-intensive businesses is not only huge but necessary.
IoT solutions are fundamental contemporary technologies that provide the opportunity for many businesses to do well in areas they would otherwise continue to do very poorly. They provide a foundation for digital enablement and a critical gateway to analytics for real-time and predictive decision making.
When applied strategically and at scale, IoT provides a magical technology capability. But the bottom line is that even magic technology can never carry the day when left to do the work of other solutions. If you have already plunged into IoT then chances are it has already become your next data silo. The question is now, what you are going to do about it?
Cities worldwide have been facing unexpected challenges since 2020 – and 2022 will see them continue to struggle with the after-effects of COVID-19. However, there is one thing that governments have learnt during this ongoing crisis – technology is not the only aspect of a Cities of the Future initiative. Besides technology, Cities of the Future will start revisiting organisational and institutional structures, prioritise goals, and design and deploy an architecture with data as its foundation.
Cities of the Future will focus on being:
- Safe. Driven by the ongoing healthcare crisis
- Secure. Driven by the multiple cyber attacks on critical infrastructure
- Sustainable. Driven by citizen consciousness and global efforts such as the COP26
- Smart. Driven by the need to be agile to face future uncertainties
Read on to find out what Ecosystm Advisors, Peter Carr, Randeep Sudan, Sash Mukherjee and Tim Sheedy think will be the leading Cities of the Future trends for 2022.
Click here to download Ecosystm Predicts: The Top 5 Trends for Cities of the Future in 2022
One of the biggest impacts of the pandemic has been the uptick in cloud adoption. Ecosystm research shows that more than half the organisations are either building cloud native applications or have a Cloud-First strategy. Cloud infrastructure, platforms and software became a key enabler of the business agility and innovation that organisations needed to survive and succeed.
However, as organisations look to become data-driven and digital, they will require seamless access to their data, irrespective of where they are generated (enterprise systems, IoT devices or AI solutions) and where they are stored (public cloud, Edge, on-premises or data centres) to unlock the full value of the data and deliver the insights needed. This will shape the Cloud and Data Centre ecosystem in 2022.
Read on to find out what Ecosystm Analysts, Claus Mortensen, Darian Bird, Peter Carr and Tim Sheedy think will be the leading Cloud & Data Centre trends in 2022.
Click here to download Ecosystm Predicts: The Top 5 Trends for Cloud & Data Centre in 2022 as PDF