Nokia Siemens Networks, the specialists in mobile broadband, is a large networking and telecommunications equipment company with headquarters in Finland. The company has revenues in excess of €14 billion and operates in 150 countries serving many thousands of customers. The company helps operators enable their end users to do more than ever before with the world’s most efficient mobile networks. Nokia Siemens Networks is one of the world’s leading CEM (Customer Experience Management) vendors with a wide offering that brings together pre-integrated software, and related professional services, across the network, IT and the entire customer lifecycle.
Today’s consumers use a variety of mobile devices (e.g., smart phones, tablets) on a daily basis. This activity generates traffic on several systems in telecom networks, leaving a “breadcrumb trail” of information at each network component. Information such as the services they were accessing, at what time, at what speed the data packets were travelling and more. This unstructured data accumulates to large volumes and can serve as an indicator for the health of the network. These indicators, when analysed, can give operators insight to their networks that can be leveraged to provide a better service back to their end users. This type of big data analysis is central to the CEMoD service and requires serious computing power to crunch the numbers and produce meaningful analytics.
Markku Lepistö, Principal Cloud Architect at Nokia Siemens Networks, describes the challenge of handling the volume of data that CEMoD provides. “Running at capacity, CEMoD will be moving, acquiring and analyzing data in the range of 5 to 200 billion attributes (200GB to 2TB of data) servicing upward of 50 million subscribers.” In addition, CEMoD data is relevant to many functions within the operator organization, from operations to marketing to customer care. Therefore, all these functions need to be able to access and share CEMoD information.
Rather than acquiring and managing the necessary hardware, Nokia Siemens Networks chose Amazon Web Services (AWS) to develop and deliver CEMoD via the cloud. Nokia Siemens Networks is using AWS for storing and analyzing the unstructured network data in an efficient way and shares the big data analytics via an innovative user-friendly online portal, a web GUI and an iPad application.
Launched at Mobile World Congress in Barcelona 2012 the Nokia Siemens Networks CEMoD solution provides a way for the operator to gain insights into their networks: Identifying bottlenecks, need for maintenance and knowledge as to the most popular services at any given time, etc. In addition, operators can use CEMoD to take actions to improve the customer experience for their mobile broadband subscribers.
The requirement to scale up and down quickly and efficiently led Nokia Siemens Networks to choose AWS. Using Amazon Elastic Compute Cloud (Amazon EC2) instance types, Nokia Siemens Networks can add compute resources (memory, CPUs and storage), as needed. With Amazon Simple Storage Service (Amazon S3), Nokia Siemens Networks can inexpensively store and retrieve any amount of data, at any time, from anywhere on the web. Amazon Elastic Block Store (Amazon EBS) provides consistent access to data and databases as well as temporary storage for high-speed analysis of run-time data gathered by CEMoD. Leveraging AWS Regions and Availability Zones, NSN follows cloud architecture best practices and “designs for failure.” In a critical fault situation, the applications are able to run in a reduced mode rather than shutting down completely. If one virtual machine fails, the machine is isolated within a region or zone, preventing a ‘domino effect’ of failure meaning the end user remains almost completely unaffected.
Lepistö describes the business agility that AWS brings to both Nokia Siemens Networks and its customers as a critical benefit: "Our developers and testers can now self-service provision environments from AWS, and AWS-compatible on-premise clouds within NSN data centers on-demand. This brings tremendous time and cost savings as waste is eliminated in agile R&D programs. Utilizing the same processes and tools at customer deployments, we can bring down the time-to-revenue for our customers, from several months, to just days or even hours."
The elastic nature of AWS combined with Nokia Siemens Networks CEMoD architecture allows them to work efficiently without additional hardware purchases and server maintenance costs. Lepistö lists other beneficial impacts of AWS for Nokia Siemens Networks:
- No hardware investment, no procurement cycles, no server maintenance costs
- Ease-of-use eliminates barriers to access and facilitates operator subscription sign-up
- Provides self-service provisioning of full environments that are fast and secure
- Immediate value to operators through automated responses to customer
- Designed for failure with fault isolation during a critical event, preventing a ‘domino effect’
Overall, says Lepistö, “AWS is the best example of a programmable data center. In addition to the already-released CEMoD solution, we are using AWS to unleash innovation within Nokia Siemens Networks. Using AWS services such as Amazon EC2 and Amazon S3 throughout the development process, from testing to production, teaches us how to ‘cloudify’ new innovations as well as parts of our existing portfolio offerings. We intend then to offer these to operators in the near future in public, on-premise, and multi-cloud models. For on-premise, NSN supports and builds solutions that follow the AWS IaaS services, their semantics and deterministic performance characteristics as closely as possible. This enables workload and associated data replication, migration or expansion flexibly between AWS, and operator on-premise data centers.”
Satisfied with their AWS solution, Lepistö concludes: "AWS has led the way in revolutionizing how IT is architected and consumed. AWS is disrupting the established enterprise-computing model with its true self-service, on-demand utility computing offering."
To learn more about how you can use AWS to help solve Big Data problems, visit: http://aws.amazon.com/big-data/.