Sector: Internet performance / network assurance / telecoms
Context: Cisco / ThousandEyes / Internet performance / network assurance / telecoms
Capability area: Event-driven architecture, Kafka, cloud data pipelines, BigQuery, observability, high-scale ingestion
Challenge
Internet performance monitoring requires the collection, processing and analysis of large volumes of measurement data from distributed endpoints. The data must be reliable enough for ISPs, enterprise customers and analysts to understand real-world network performance.
Delivery contribution
Worked on platform engineering and ingestion services handling measurement data using event-driven systems, including Kafka-based pipelines, Spring Boot microservices services and cloud analytics patterns such as BigQuery, ensuring the distributed systems could horizontally and vertically scale across the SME to comglemorate.
Complexity
The environment required high-volume ingestion, pipeline reliability, cloud scaling, data quality, reporting readiness and operational resilience. These are the same engineering concerns found in large government platforms where many departments, services or citizens generate continuous operational data.
Outcome
Cisco completed its acquisition of SamKnows in September 2023, describing SamKnows as a UK-based internet performance monitoring company that helps ISPs and broadband customers measure and troubleshoot last-mile broadband performance. Cisco also stated that SamKnows’ millions of vantage points would expand ThousandEyes’ visibility into last-mile performance.
Relevance to Governement Delivery
Large government platforms increasingly depend on reliable data flows, operational dashboards and service performance monitoring. This experience is relevant to state-level digital services where multiple departments, users or citizen-facing channels generate continuous data that must be processed, monitored and reported accurately.
For MDAs, the same engineering principles apply to service dashboards, revenue activity monitoring, citizen case tracking, SLA reporting and early detection of operational bottlenecks.
Want to understand how this applies to public-sector dashboards and MDA reporting?
