GCP – Autonomous Network Operations framework: Unlock predictable and high-performing networks

Over the past year, an exponential surge in data, the widespread rollout of 5G, and heightened customer expectations have placed unprecedented demands upon communications service providers (CSPs). To thrive in this challenging landscape, telecommunications leaders are rethinking traditional network management, embracing digital transformation, and using the power of AI to build smarter, more efficient, and self-managing networks.

Today, to help CSPs address these pressures, we are announcing the Autonomous Network Operations framework — enabling CSPs to enhance service reliability, proactively detect and resolve network issues, and turn fragmented data into value. This new framework takes an AI-first approach, leveraging the latest in Google Cloud AI, infrastructure, and analytics products to understand and make sense of complex network data, risks, and operations. The framework also offers an extensive ecosystem to help deploy these solutions, including partners and Google Cloud Consulting. 

The Autonomous Network Operations framework draws on Google’s extensive expertise in operating its own global network, which has leveraged AI at scale for more than 25 years and is one of the industry’s most advanced and resilient autonomous networks. CSPs are already using the framework to improve service reliability and minimize mean time to repair (MTTR) by 25%, and now we’re making it broadly available to accelerate their autonomous network operations journeys. 

Navigating network complexity in the AI era

Managing complex telecom networks is a costly and resource-intensive undertaking for CSPs. Legacy infrastructure, often built for previous generations of mobile technology, struggles to keep pace with the immense data demands of 5G and beyond. This has led to several challenges:

• Increased operational costs and network demands: Manual tasks like alarm triage, troubleshooting, configuration, and service provisioning across diverse systems consume significant resources for CSPs, hindering innovation and modernization.

• Sub-optimal customer experience: Network operations traditionally focus on technical KPIs (utilization, latency, etc.) without real-time visibility into how specific network events or degradations are actually affecting the quality of experience for individual subscribers or services. Taking action usually happens reactively, leading to eroded customer satisfaction and increased churn.

• Fragmented and siloed data: In many legacy platforms, vital network-performance and customer-experience data reside in separate systems, and often are difficult to integrate. But without a unified view, correlating network events with their impact on the customer experience is hard, and can lead to ineffective resource prioritization and delayed root cause analysis.

• Difficulty implementing advanced technologies: Adopting autonomous networking operations can be resource intensive and costly, presenting challenges such as integration with existing infrastructure, data management, cybersecurity, upskilling talent, and identifying a clear path to a positive return on investment.

Yet, we’ve heard from our customers that successfully embracing autonomous network operations has the potential to dramatically improve service uptime for subscribers, significantly reduce network complexity, and unify fragmented data for actionable insights.

Google Cloud’s Autonomous Network Operations framework

Google Cloud’s Autonomous Network Operations framework supports CSPs’ strategic pathways to achieving true network autonomy, building on our unique strengths in AI, infrastructure, and global expertise.

The framework integrates critical Google Cloud products to transform operations, enhance service reliability, and unlock new value in three key ways:

1. Differentiated building blocks for sophisticated use cases

Google Cloud uniquely helps CSPs build intelligent networks with cutting-edge, AI-powered tools tailored to their specific needs. At its core is Cloud Spanner, Google Cloud’s globally distributed database that acts like a real-time virtual copy (a “digital twin”) of national networks. Spanner tracks billions of changing data points across all network components, providing a single, reliable record that even retains historical network conditions. This is crucial for advanced analysis and quickly pinpointing the root cause of issues. BigQuery then adds data analysis that can handle massive amounts of live network information. Finally, Google’s Gemini, our most capable AI model available through Vertex AI, and specialized Graph Neural Network (GNN) models, deeply understand the network’s complex and evolving connections. 

Together, these tools let CSPs move beyond simple automation to tackle advanced autonomous network operations like finding problems before they happen, linking issues across different network areas, and making quick, precise decisions based on live information, at any scale.

2. Extensive integration to accelerate time-to-value

What truly sets Google Cloud’s framework apart is how smoothly all of its pieces fit together, reducing complexity and helping CSPs get things done much faster. Our services are designed to work hand-in-hand from the start, cutting down on time-consuming data engineering. For instance, BigQuery can directly access data in Cloud Spanner, providing a unified view of current operations and historical trends. Additionally, with BigQuery ML, CSPs can build and deploy AI models using simple SQL commands, leveraging powerful AI capabilities like Gemini through Vertex AI. This tight integration across our data storage, analytics, and AI tools allows CSPs to quickly pilot, launch, and expand their AI initiatives. The entire system is AI-ready from day one, facilitating the ingestion of live network data and even enabling automated problem resolution, unlocking value in days, not months.

3. Google’s AI and network operations expertise through Google Cloud Consulting

Google’s global network, one of the most advanced and resilient networks in the world, has leveraged AI at scale for more than 25 years. Through Google Cloud Consulting, we bring this operational expertise directly to CSPs to help them design and implement their own autonomous network operations frameworks. Our teams work closely with CSPs to tailor the framework to their environments. This includes everything from setting up data pipelines to operationalizing use cases like predictive maintenance, fault correlation, and closed-loop automation — helping to ensure rapid and reliable data activation.

To help ensure these intelligent, automated operations remain secure, we also bring in Mandiant, Google’s frontline cybersecurity team. Mandiant helps CSPs embed security by design into our framework — securing data flows, detecting adversarial AI threats, and protecting automated decision loops from compromise. With this unified approach, CSPs can scale autonomous operations with the same level of resilience, visibility, and protection that underpins Google’s own global infrastructure.

A tightly integrated, open ecosystem

We strengthened the Autonomous Network Operations framework with a deep ecosystem of leading independent software vendors (ISVs) and global system integrators (GSIs), who bring specialized expertise and solutions to accelerate CSPs’ transformation journeys.

For example, Amdocs, Ericsson, and Nokia now offer their own autonomous network solutions as comprehensive offerings built on the Autonomous Network Operations framework’s capabilities, enabling their customers to easily adopt and accelerate their journey toward network autonomy. These partners bring crucial expertise in handling diverse network data from various vendors, facilitating the creation of a unified data model. This unified model is essential for building sophisticated, AI-driven automation.

“As CSPs navigate the complexities of modern networks—ranging from high operational costs to the need for enhanced resiliency and uptime—intelligent automation and the evolution to autonomous networks become essential. By leveraging Google Cloud’s AI infrastructure, our Amdocs Network AIOps solution and the network agents it includes empower CSPs to proactively manage their networks through predictive analytics, automated workflows, and closed-loop operations. This collaboration enables a transformative shift toward autonomous networks, enhancing efficiency and delivering superior customer experiences.” – Anthony Goonetilleke, group president of Technology and head of Strategy, Amdocs

“The transformation to full autonomy will shape the success of CSPs, paving the way for a transition to next-generation technologies. Ericsson and Google Cloud are committed to empowering this transformation. Our collaboration is driving a fundamental shift in how mobile core networks are built and operated on public cloud infrastructure. Ericsson and Google continue to combine their expertise on multiple fronts — technology innovation, streamlined delivery models, and, most importantly, a shared culture of relentless innovation — to empower operators in realizing their vision of autonomous networks.” — Razvan Teslaru, head of Strategy, Cloud Software and Services, Ericsson.

“The industry needs to work together to realize the benefits of Level 4/5 autonomous networks. Nokia has a long history of meaningful innovation in network automation and applied Telco AI. We’re excited about deepening our collaboration with Google Cloud, which is already delivering tangible benefits to CSPs on their own, unique journeys to fully autonomous networks.” – Kal De, senior vice president, Product and Engineering, Cloud and Network Services, Nokia. 

Complementing the ISVs, GSIs including Accenture and Capgemini act as the execution arm for the CSP, playing a pivotal role in helping create the specific autonomous networking deployments, and scaling these autonomous operations across the entire organization.

Customers embracing the framework with Google Cloud

CSPs are already transforming their operations and enhancing customer experiences with the Google Cloud AI, infrastructure, and expertise provided in the Autonomous Network Operations framework:

• Bell Canada achieved a 25% reduction in customer-generated reports and increased software delivery productivity by 75%. By leveraging Autonomous Network Operations framework capabilities such as Spanner Graph to dynamically assess network relationships and changes in traffic and Google Cloud AI to identify and prioritize network issues before they escalate, Bell’s new AI operations (AI Ops) solution enables faster detection and resolution of network problems, improving network performance.
• Deutsche Telekom ensures high service uptime for its customers, even during peak demand, with the RAN Guardian agent built using capabilities from Google Cloud’s Autonomous Network Operations framework. This RAN Guardian is a multi-agentic system that constantly analyzes key network details in real time to predict and detect anomalies. It also prioritizes network issues by combining data from monitoring, inventory, performance, and coverage. Then, it automatically implements fixes, such as reallocating resources or adjusting configurations, to keep service quality high.
• Telstra and Google Cloud are also co-developing a new approach to optimizing its radio access network (RAN) with an AI-powered agent. This agent uses Telstra’s network data to rapidly pinpoint incidents and detect anomalies before they impact service. This project is a key step in Telstra’s ambition for an autonomous network. If successful, it will unlock a future of advanced AI capabilities, enabling dynamic RAN optimization and intelligent capacity management to deliver a more resilient and higher-performing network.
• Customers such as MasOrange and VMO2 have also expressed interest in leveraging advanced autonomous network capabilities to enhance their operations and customer experiences.

“By achieving a 25% reduction in customer-generated reports and boosting software delivery productivity by 75%, we’re transforming our operations into a customer-centric ‘techco’ model. This lean approach, with the customer as our #1 priority, is paving the way for full network autonomy. This future-forward strategy promises not only self-healing and resilient systems but also significant cost efficiencies.” – Mark McDonald, EVP and Chief Technology Officer, Bell Canada

“Transforming our network operations is fundamental to delivering best-in-class connectivity and services. By deeply integrating Google Cloud’s cutting-edge capabilities like Spanner Graph with its robust data and AI tools that we use today — such as BigQuery and Vertex AI — we will better understand network behavior and anticipate service incidents. This integration is key to achieving a truly autonomous operation in our future NOC, ensuring the best experience for MasOrange customers.” – Miguel Santos Fernández, Chief Technology Officer, MasOrange

Unlock autonomous network operations today with Google Cloud

If you are a CSP who is looking to enhance service reliability, proactively detect and resolve network issues, and turn data into value, the Autonomous Network Operations framework can help. Contact a Google Cloud account manager or explore our framework on our telecommunications industry page to learn more about starting a proof-of-concept with the Google Cloud Autonomous Network Operations framework.