Announcing the availability of IBM Telco Network Cloud Manager Performance (TNC-P) 1.4.5 – GA Feb 29, 2024

Description

Telco Network Cloud Manager - Performance includes the following capabilities:

• Flexible and robust capability to ingest performance metrics, including metrics from streaming platforms, such as Apache Kafka and Pulsar.
• True cloud native deployment that offers the ease and low overhead of centralized management and horizontal scaling.
• Support for network performance reporting use cases of 5G network engineers to provide the flexibility to model the network object hierarchy and update network KPI formulas on both present and past performance data, as required.
• Streaming analytics to support close loop automation use case.
• REST APIs for upstream integration and multi-tenant access.
• Low-code automated data source integration.

Summary of New features included in Telco Network Cloud Manager - Performance 1.4.5: 

• User-configurable automatic threshold baselining.
• More than one threshold evaluation profile can be supported for the same metric and resource scope.
• Python execution engine for machine learning use cases.
• Auto microservice pod scale out based on sizing inputs.
• New dashboards for data ingestion health observability.

Capabilities added in Telco Network Cloud Manager - Performance 1.4.5:

• Insights: Automatic threshold alert
  • Anomaly detection: User configurable baseline thresholding. Allows users to fine tune algorithm by executing test runs against TNCP historical data. Benefit: This trial-and-error approach will reduce occurrence of false positives.
  • Multiple threshold rules for pair of resource & KPI. It helps in meeting diverse operational requirements of users from different business units. 
• Automation: Python runtime environment for machine learning use cases
  • Allow advanced users to deploy Python scripts for machine learning use cases such as anomaly detection and link to auto threshold alert.
• Scalability: Increase pods automatically based on system sizing inputs
  • Simplify task of cluster administrator: By entering projected data load volume in sizing input sheet, TNCP automatically calculates the pods required for each microservice and starts up the number of pods required.
• Resilience: Surveillance of incoming data flow - 3 views of Ingestion Health are available:
  • Data Collection Overview: Is TNCP parsing key KPI groups for each source?
  • Priority Metric Group Coverage: Is TNCP parsing key KPIs?
  • TNCP Application Health: Is File Collector running well - no backlog?
• Resilience: Increased system uptime
  • High availability for Kafka and Zookeeper services: 3 instances.
  • Apply threshold configuration changes dynamically without restarting.