The telecommunication industry is constantly transforming, increasing operational complexity. Cloud-native network functions (CNFs), decentralization of networks and migrating to the cloud have provided new capabilities  that help service providers better compete. But with the acceleration of new technologies, it's important that service providers implement operations and systems that properly manage and maintain a high quality of service.

This is why observability is crucial for service providers to better maintain network efficiency, security and reliability. It enables service providers to proactively manage and optimize infrastructure, leading to improved performance, reduced downtime and enhanced customer satisfaction.

This article explores the value of combining the critical aspects of V^3 (Volume, Velocity and Variety) and A^3 (Availability, Accessibility and Affordability) within the realm of observability in complex service provider networks, particularly focusing on OSS/BSS (Operational/Business Support Systems) improvements.

  • V^3 are the key dimensions that drive the effectiveness of observability in service provider networks. These dimensions are crucial for comprehensively understanding and optimizing complex telco systems and applications.
  • Simultaneously, we explore the A^3 principles, which are integral for efficient data management and governance in a multi-cloud infrastructure.
Figure 1: Observe - data - act driving the AIOps revolution

Figure 1: Observe - data - act driving the AIOps revolution

The synergy between V^3 and A^3 principles is paramount in modern telco operations, where leveraging large-scale, diverse data in a cost-effective and accessible manner is essential for staying competitive and maintaining optimal network performance and reliability. Such a data stack would be foundational to drive intelligent, automated workflows such as issue remediation, smart-scaling, predictive maintenance and service assurance, and more, such as accelerating the data-driven business (ie AIOPs revolution, see Figure 1).

Observability for OSS/BSS

At its essence, observability in telecommunications and OSS/BSS goes beyond traditional monitoring. It is a holistic approach to understanding and managing complex telecommunication systems and stacks. This approach encompasses the comprehensive collection and analysis of data across multiple dimensions to gain deep insights into these systems' current state, performance, functionality, security and life cycle. Observability for OSS/BSS has characteristics that go beyond traditional monitoring, such as:

  • Multidimensional data collection: observability is not just about gathering basic operational data; it involves collecting a wide range of metrics, events, logs and traces (MELT). This multidimensional data collection provides a 360-degree view of the system (passive outlook), allowing for a clearer understanding of how different components interact and impact overall performance and functionality.
  • Real-time analysis, reactive data for proactive management: by analyzing observability data in real-time, telecommunications operators can better understand and manage their systems. This approach goes beyond reactive troubleshooting in that it enables proactive prediction of potential issues and system performance optimization.
  • Advanced analytics and actionable insights: observability data is the bedrock upon which advanced analytical tools operate. Telecommunications operators can transform raw data into actionable insights by leveraging artificial intelligence and machine learning (AI/ML) algorithms. These insights guide strategic decisions related to network optimization, customer experience enhancement and resource allocation that bring OSS/BSS to ultimate capacity and capability, enabling business continuity through service level agreements (SLA).
Figure 2: OSS/BSS Stages with Observability

Figure 2: OSS/BSS Stages with Observability

  • Lifecycle management and continuous improvement: Observability plays a critical role in the lifecycle management of telecommunication systems. Operators can make informed decisions about upgrades, maintenance, scalability and sustainability by continuously monitoring and analyzing system data. This ongoing process helps make sure that systems are stable and are able to evolve to meet changing demands and technological advancements.
  • Security insights: In an era where cybersecurity is paramount, observability provides vital real-time insights into telecommunication systems. By continuously monitoring data for anomalies, suspicious behavior and potential threats, observability becomes vital in the early detection and mitigation of security incidents.

The impact of V^3

V^3 (VolumeVelocity and Variety) encapsulates the essential characteristics of observability data in the telecommunications industry.

Figure 3: Explanation of V^3

Figure 3: Explanation of V^3

Volume: The scale of data

  • Immense data streams: The service provider industry generates and processes vast quantities of data. This encompasses a wide spectrum from transactional data, such as call logs and billing records, to diverse sensor outputs from network infrastructure and valuable customer interaction data from multiple channels.
  • Strategic utilization: Effectively managing this colossal volume of data is key for achieving strategic objectives such as network optimization, targeted marketing and predictive maintenance. For instance, analyzing patterns in data generated from cell towers can lead to network improvements and a better customer experience.

Velocity: The pace of data

  • Rapid data generation and processing: In today's digital era, the velocity with which data is produced and needs to be processed in telecommunications is astonishing. The sector requires capabilities for handling data at high speed, including real-time or near-real-time processing for operational agility.
  • Operational impact: High-velocity data handling facilitates instantaneous responses to network challenges, enables real-time customer interaction and support and permits dynamic allocation of resources. Example use cases are adopting real-time analytics for dynamic pricing strategies or swift identification and resolution of network disruptions.

Variety: The diversity of data

  • Multifaceted data types: Service providers encounter a broad spectrum of data types, ranging from structured data, such as customer information and billing details, to unstructured formats such as social media interactions, emails and transcripts from customer service calls.
  • Analytical advantage: The ability to process and analyze this diverse data landscape is crucial. It enhances the customer experience, informs decision-making and fosters the development of innovative services and products.

Solving today’s data platform challenges

Governance: Data management complexity

  • Decentralized data landscape: The data in the telecommunication networks is often dispersed across various locations and managed by different teams. Establishing effective governance and achieving a coherent, comprehensive dataset can be challenging due to these organizational and geographical complexities.
  • Strategic alignment: Effective data governance enables the alignment of people, processes and technology to help make sure that the right data is collected, managed and utilized while maintaining its integrity and compliance with regulatory standards.

Signal-to-Noise Ratio (SNR) / Avoiding the Bias: Data quality assurance

  • Filtering essential data: With the high velocity of data, telecommunications systems often encounter "noise"–irrelevant or erroneous data elements. Identifying and filtering out these elements is crucial for maintaining data quality.
  • Enhancing data reliability:  Implementing robust mechanisms to detect and address invalid or biased data entries helps make sure that reliable, actionable data is used for decision-making and analytics.

Correlation: Creating a unified data perspective

  • Linking related data: In the vast pool of telco data, identifying and correlating related datasets is essential but challenging. It enables the creation of a comprehensive, interconnected data mesh that supports both operational and business teams.
  • Driving business insights: Observability can correlate data sets that serve as a foundation for developing new business insights, aiding in identifying emerging trends and opportunities and supporting strategic decisions to tap into new revenue streams.

The effect of A^3

A^3 (AvailabilityAccessibility and Affordability) represents key attributes of observability data that are vital for achieving optimal price performance and ease of use in telecommunications.

Figure 4: Explanation of A^3

Figure 4: Explanation of A^3

Availability: Providing constant data presence

  • Critical role in operations: In the telco industry, the continuous availability of data is not just a convenience but a necessity. This underlines the importance of making sure that data is readily available for various purposes, including analysis, decision-making and operational management.
  • Resilience in adverse scenarios: Data availability supports uninterrupted service and operational continuity. This is especially important in disaster recovery or during peak demand periods. Implementing robust data backup and recovery systems is crucial for maintaining this continuous availability.

Accessibility: Streamlining data reach/Can-do

  • Ease of access across the organization: Accessibility entails making sure that data is easily retrievable by authorized personnel, irrespective of their department or geographical location. This includes facilitating seamless integration and compatibility with diverse analytical tools and platforms.
  • Enhancing collaboration and efficiency: By breaking down data silos and providing a unified view of data, telco operators can enhance collaboration across teams, leading to more efficient decision-making and problem-solving.

Affordability: Balancing costs with value/able-to-have

  • Cost-effective data management: With the sheer volume of data handled in the telecommunications industry, managing the costs associated with data storage, processing and analysis is a significant challenge. Developing affordable solutions is essential to maintain profitability while capitalizing on the advantages of big data analytics.
  • Optimizing data storage strategies: Implementing tiered data storage solutions allows categorizing data into hot, warm and cold storage based on access frequency and importance, which can be used as a key strategy in balancing cost and accessibility.

Solving today’s data cost and governance challenges:

Cost management: Economizing data storage

  • Balancing storage types: The cost implications of storing large volumes of data, particularly when dealing with petabyte-scale datasets, can be substantial. Employing a strategic mix of storage solutions — from on-premises to cloud-based and from hot to cold storage — is complex but essential to manage costs effectively.
  • Leveraging emerging technologies: Innovations in data storage technologies, such as compression algorithms and efficient data deduplication methods, offer new opportunities to reduce storage requirements and costs.

Navigating regulations: Compliance and data sovereignty

  • Adhering to regulatory standards: Telecommunications is a highly regulated industry with stringent data handling and privacy requirements. Regulations often dictate where and how data can be stored and accessed. Complying with geo-specific and industry-specific regulations is crucial for lawful operations and business continuity.

The Formula: V^3 x A^3 -> AIOps revolution

Merging the principles of V^3 with A^3 results in a robust and dynamic framework for telecommunications operations. This fusion creates a very beneficial environment for the implementation of artificial intelligence for IT operations (AIOps) and integration for enhanced operations, such as:

  • Data-rich environment: By harnessing the vast volumes (Volume), rapid throughput (Velocity) and diverse types (Variety) of data, telecommunications systems become data powerhouses. This rich data environment is crucial for in-depth analytics and informed decision-making.
  • Optimized data management: The principles of continuous data availability, seamless accessibility and strategic affordability help make sure that this wealth of data is managed efficiently, effectively and cost-consciously. This optimized data management is key for agile and responsive operations.
  • Foundation for AI implementation: The combination of V^3 and A^3 sets the stage for a more impactful application of AI technologies. With a comprehensive and well-managed data infrastructure, AI algorithms can be effectively applied to optimize automation and operations, enhance decision-making and predict future trends and potential issues.
  • Elevating OSS to AIOps: In this enhanced environment, operational support systems can evolve into intelligent platforms where AI-driven insights lead to proactive and predictive operations, transforming how telecommunications networks are managed and optimized.

AIOps necessitates real-time capabilities throughout the process, encompassing the discovery phase and predictive analysis and executing tasks associated with these analyses, such as remediation, changes or updates. In this context, the data-driven methodologies align with the automation journey, aiming to minimize operational time for issue resolution, alerts, remediation and proactive customer configurations.

Conclusion

The enablement and empowerment that V^3 x A^3 brings to observability create better OSS/BSS solutions that can pave the way for advanced AIOps in the telecommunications industry. This integration fosters a richer data environment and optimized data management essential for AI-driven telco operations.

Central to this transformation is the power of open source. Open-source solutions bring innovation, flexibility, cost-effectiveness and enhanced security to telco observability, which is crucial for addressing the unique challenges of V^3 x A^3 (you can read more on open-source observability data projects here). Open source's collaborative and community-driven nature help accelerate technological advancements and customization, aligning with the economic and operational goals of modern, multivendor telco networks and systems.

In essence, the synergy of V^3, A^3 and open-source solutions marks a new era in telecommunications. This era is defined by intelligent, data-driven, adaptable OSS platforms, poised to meet the dynamic demands of the telco industry and its customers, demonstrating that telecom observability's future is reactive but predictive and proactive, driven by the collaborative and innovative spirit of open source.

Remember that the algorithms can only take you as far and as much as your data fuels.


About the authors

Fatih, known as "The Cloudified Turk," is a seasoned Linux, Openstack, and Kubernetes specialist with significant contributions to the telecommunications, media, and entertainment (TME) sectors over multiple geos with many service providers.

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Volker Tegtmeyer develops content strategies that show how Red Hat solutions can help telecommunications service providers meet their business and technology challenges. Solutions that help service providers in their digital transformation and as they evolve from telco to techco. New technologies cover broad areas from 5G, AI/ML, telco cloud, automation to new solutions that help tackling sustainability goals. Volker has more than 20 years of experience in the telecommunications industry having previously worked in various roles at Siemens, Cisco and Akamai.

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With extensive experience in Telco industry I have developed several positions, local and globally, in leading telecommunication and IT Companies, such as Telefonica, Ericsson, Vodafone, Huawei and Ricoh IT Services.

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