New Azure for Operators solution accelerator offers a fast path to network insights – azure.microsoft.com

New Azure for Operators solution accelerator offers a fast path to network insights – azure.microsoft.com

New Azure for Operators solution accelerator offers a fast path to network insights – azure.microsoft.com 0 0 Alan Dickson

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Posted on September 27, 2022
5G marks an inflection point for operators. The disaggregation of software and hardware in 5G enables operators to move telecommunication workloads to public or hybrid public/private cloud infrastructures, giving them unprecedented agility and flexibility to deliver exceptional customer experiences and realize cost efficiencies. However, the full benefit of running large-scale telecommunication services in the cloud can only be achieved if cloud adoption is accompanied by a comprehensive approach to network analysis and automation supported by cloud-based big data and AI.
Today, Azure for Operators is introducing a network analytics solution accelerator program, providing a standardized approach to data acquisition and visualization that aids operators on their journey toward complete end-to-end AI Operations (AIOps). The solution employs the same operational techniques and capabilities that Microsoft uses to manage Azure, packaged specifically for operator analytics. Our network analytics solution comprises existing Azure services combined with unique capabilities developed specifically for communications service providers, which allows network planners and engineers to visualize performance and troubleshoot service anomalies.
Disaggregated cloud native 5G networks add many new individual elements that must interwork effortlessly. These increasing interdependencies mean management and analytics tools can no longer run in relative isolation. Successfully deploying and managing end-to-end services in such environments requires the ability to analyze network and host platform data simultaneously from numerous sources. Only then can operators reactively and proactively diagnose issues, while ensuring operational costs are kept in check and that customers are always presented with the best user experiences.
With the scale and complexity of such services, network management needs to operate autonomously in a closed loop manner—taking operational insights on the health of network elements and the underlying distributed cloud infrastructure and ensuring a service is configured optimally.
At Microsoft, we understand this journey because Azure went through a similar evolution. In the early days, we recognized the challenges of troubleshooting across disparate services. To solve this, we established a common data analytics infrastructure that gave us a comprehensive view of how our services performed, which resulted in lower engineering overheads and better service quality.
Large operators generate petabytes of data every day—complicating the challenges associated with quickly ingesting, cost-effectively storing, and concisely analyzing the information to gain meaningful insights. Public clouds are ideal for solving these problems because they simplify the ability to aggregate and analyze data, thereby allowing operators to rapidly identify and act on any irregularities or opportunities. Azure excels in this area with a portfolio of trusted storage, machine learning, business intelligence, and automation tools.
Azure Data Lake, for example, can capture and store a wealth of disparate log data generated by communications services. Data lakes are more adept than classic data warehouses at handling the sheer velocity, volume, and variety of information operators will need to store. Lakehouses, such as those enabled using Azure Databricks, provide a mediation layer to enforce data quality and consistency.
Once ingested, Azure has several standardized services for aggregating and analyzing otherwise distinct data streams such as logs, traces, telemetry information, and alerts, from inherently different platforms, network functions, and devices. Azure Data Explorer (ADX) rapidly ingests and analyzes petabytes of unstructured, structured, and semi-structured data formats. Similarly, Power BI provides real-time analytical intelligence through a combination of dynamic visualizations and AI-driven insights.
Azure network analytics empowers operations teams to accelerate root cause analysis, enables capacity planners to understand where to deploy new resources, and allows engineers to improve customer experiences by enhancing network performance and quality of service. Our analytics offerings can also assist business teams in tuning marketing strategies toward reducing customer churn and increasing monetization opportunities.
Ingest and analyze data at scale with existing Azure services.
Naturally, with large companies and many users handing enormous amounts of potentially sensitive information, we must guarantee the governance, integrity, and security of this data, providing role-based access while ensuring relevant compliance standards and policies are followed. Microsoft’s Purview provides a fully managed and centralized unified data governance service that delivers the tools such organizations demand. Purview can even prevent the duplication of analytics dashboards, providing a quick and easy way to search for existing interfaces that meet their immediate needs.
A critical step towards a fully automated network is the ability to identify anomalies and predict issues before they become catastrophic failures. Existing rules-based systems rely on heuristic approaches that will struggle to scale to the quantity and complexity of data they must ingest to pinpoint potential problems within modern network infrastructures. Instead, big data and machine learning–driven inferencing approaches are needed to predict problems hidden within terabytes of disparate logs, error messages, and security alerts with lower severity levels.
Closing the loop from detection to resolution requires a comprehensive vendor and platform-agnostic approach to provisioning standalone network functions and end-to-end services. This evolves to solutions working at the application layer that make choices about how and where to instantiate elements that enable a complete end-to-end service. Such solutions operate across multiple access, edge, core compute, and cloud platforms and are responsible for assigning appropriate resources and tuning configurations within each component to meet the requirements of the service. Underpinning this is multi-cloud and edge lifecycle management systems such as Azure Arc, which provides ongoing governance and management of virtual machines, Kubernetes clusters, and databases.
A closed loop AIOps architectural blueprint.
Ultimately, the goal is that the network operates autonomously based on a loose set of expected outcomes rather than explicit rules defining how to react to specific requests or conditions. Such intent-based management systems will require the application of artificial neural networks which employ deep learning on the vast amounts of real-time data streams that will enable them to train themselves to carry out tasks and perform actions.
There are many scenarios where our network analytics capabilities are needed today. Operators can use the solution to proactively analyze the quality of service in mobile and fixed voice networks, detect issues, prevent outages, and gain insight into infrastructure utilization for capacity planning. The network analytics solution also monitors mobile core performance, looking for underlying platform issues and reporting poor quality of service to accelerate root cause analysis. Furthermore, the solution performs deep packet analysis of end-to-end services, which accelerates deployments and reduces the mean time to repair.
The network management and automation journey can look daunting but, with our network analytics solution accelerator program we offer operators an easier path. With the right technology and the flexibility to handle data from many systems, operators can adopt automation incrementally and at their own pace, meeting business objectives along the way. Azure network analytics allows operations teams to build trust in big data and AI and provides the foundation for closed loop automation.
As part of the Azure for Operators program, Microsoft is making it easy to start discovering the power of Azure’s network analytics offerings. Our solution accelerator enables service providers and systems integrators to take advantage of the Azure tools and services available today as they evolve their longer-term AIOps analytics strategies. Our experts are on hand to guide you through the process of importing, analyzing, and visualizing the massive amounts of data produced by the networks you maintain. Plus, we have resources available to help solve any network issues you are experiencing today or simply understand how your infrastructure is performing. To learn more about participating in our solution accelerator program, contact us here.
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