Is Data Integrity Assurance that important?
It happens all too often.
For whatever reason, the nice network engineer may not update the inventory system when making a change to the network.
Perhaps a day or two (or more) passes before a network alarm is triggered!
Operations are now wasting time and money trying to understand the root cause of the problem…
This could easily impact the rollout of new services or prevent the quick restoration of a service outage.
The hybrid and disaggregated nature of 5G networks adds complexity, requires accurate real-time data and topology information if network automation is to be effective.
The list of challenges facing CSPs that rely on outdated and manual inventory processes is long and formidable:
- Unresolved Discrepancy between the deployed network and the inventory database
- Non-automated and tedious handling time of network and OSS data conflicts
- Longer manual process to review new service designs, potential order fallout, spending hours reconciling offline with siloed inventory
- Slow and complicated migration process of customers to new technologies
- Low data quality in OSS Inventory systems, which negatively affects fulfillment and assurance processes
Finding the Invisible Leak in the Ship
In all cases, the results lead to customer frustration and dissatisfaction, costing the CSP money in lost revenues and increased operational expenses.
This scenario is even more likely to occur with the migration to hybrid next-generation networks based on disaggregation, virtualization, and cloudification from the current siloed network architectures.
The challenge of quickly resolving the issue is compounded by the complexity of parsing such a diverse inventory of data from multiple sources.
Atrinet offers CSPs a Data Integrity Assurance solution that is based on Automated Discovery and Reconciliation modules designed to meet the challenges of supporting open virtualized next-generation networks like 5G and next-generation Transport Networks, where resources reside in the physical, virtual, and cloud domains.
Your Multi-Tool of Choice
Atrinet’s NetACE Auto-discovery & Reconciliation modules provide multi-domain federation and auto-discovery.
Including automatic rule-based reconciliation of multi-technology, multi-vendor and multi-layer networks and services.
Our modules are built with a cloud-native approach that uses web-scaled containerized functions, decomposed into scalable and resilient microservices.
Atrinet NetACE Solution & Benefits:
- Accurate multi-layered live view of operator’s networks and services
- Makes sure the inventory database perfectly matches the deployed and functioning network at all times
- Real-time inventory from the ‘live’ network ensures that customers are not impacted during a technology migration
- Auto-Discovery of physical, virtual, and cloud networks feeds data into Next Generation Inventories in real-time via Open REST API and reconciles the data to gain 100% data integrity at all times.
Re-Discover Your Network
“NetACE Auto-discovery & Reconciliation solution assures that your inventory data is 100% accurate, which is the mandatory backbone of any effective process of resource planning, service or resource orchestration and automated assurance use cases,”
says Ohad Kamer, CMO and co-founder of Atrinet.
“Moreover, it can be customized by partners and customers to meet specific CSP requirements.”
Amdocs’ ONI (Open Network Inventory)
“We are excited to be partnering with Amdocs and its Open Network Inventory (ONI) solution to enable CSPs to shorten the service provisioning cycle, prevent costly failures and outages and save CSPs time and money,”
says Yaron Nachman, Director of Pre-Sales, at Atrinet.
“NetACE Auto-discovery & Reconciliation supports all areas of the telecommunication network, including RAN, Transport, Core, Access and IT domains for physical, visualized and cloud-native network functions and applications,”
“It’s vendor-agnostic data models and reconciliation flows are flexible and easily customizable. The Reconciliation operation compares and records differences between actual network data and the intent planned data, resolves discrepancies based on automatic rule-based resolutions, and assure Inventory’s data integrity at all times.”