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Confluent Telecommunications United States

DISH Wireless

Real-time Analytics

DISH Wireless needed to turn massive 5G network telemetry into developer-accessible data products, but traditional telco infrastructure kept operations and analytics locked in proprietary systems, making it hard to monitor networks in real time, customize connectivity, and support low-latency Industry 4.0 applications at cloud and edge scale.

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an exabyte of data per day
more than 73% of the United States

Reported impact

Business outcome

DISH built a programmable smart network that lets enterprises and developers work with trusted network data in real time, extended cloud-native 5G O-RAN coverage to more than 73% of the United States, and created a foundation for monitoring, predictive analytics, mobility, and smart-factory applications across heterogeneous edge environments.

  • Customer Experience
  • Scalability
  • Speed to Market

Solution

DISH Wireless used Confluent Cloud to build an event-driven connectivity platform for its cloud-native 5G O-RAN network. Rather than treat network data as a black box, the company adopted Apache Kafka and data-mesh principles so teams could decentralize ownership, apply federated governance, and expose trusted network data as APIs. Confluent Cloud and its Kora engine provide the streaming layer that ingests log, telemetry, and application data, connects real-time systems with batch consumers and APIs, and keeps connectivity workloads cloud native from core to edge. The platform also supports customer use cases in AWS environments, including Wavelength-based low-latency processing and SageMaker model training for manufacturing and mobility scenarios. By making network signals programmable and shareable, DISH created a flexible developer platform that supports proactive monitoring, predictive analytics, and edge applications without the operational burden of self-managing Kafka.

Data flow

Network logs, telemetry, and application data stream through Confluent Cloud and Kafka, where they are processed in real time, exposed as APIs for developers, and selectively replicated to AWS edge and regional services such as Wavelength and SageMaker for monitoring, analytics, and machine learning.

Solution architecture

5 components · 4 layers
  1. Ingest
    • Confluent Cloud Provides the cloud-native streaming platform that carries DISH network telemetry and exposes programmable data products.
  2. Compute
    • AWS Wavelength Processes low-latency edge workloads for manufacturing and automotive scenarios close to devices.
    • Amazon SageMaker Consumes replicated manufacturing data for ongoing model training and anomaly-detection workflows.
  3. Serving
    • Kora Acts as Confluent Cloud's managed Kafka engine so DISH can scale the platform without self-operating open-source clusters.
  4. Orchestration
    • Apache Kafka Supplies the event-streaming model that connects real-time systems, batch systems, and APIs across the network stack.

Architecture clues

  • DISH exposes network data products as APIs so developers can customize connectivity from any cloud to any device.
  • Manufacturing and automotive patterns replicate edge data into AWS regions for further processing and training.
  • The platform uses data mesh principles with decentralized ownership and federated governance.

Evidence from the source

As of June 2023, DISH Wireless has expanded coverage of its cloud-native 5G O-RAN network—powered by innovative technologies like Confluent—to more than 73% of the United States.
DISH Wireless generates an exabyte of data per day
Using Confluent, DISH Wireless has been able to build a programmable network
With Confluent Cloud, DISH Wireless has built an event-driven connectivity platform from the ground up.
Transparency Evidence & methodology 90/100 reference value · 79% confidence · 1 source

Review how this reference was scored and trace each normalized claim back to its documented source.

01

Scoring methodology

How scores are calculated

Customer Reference Value measures usefulness as a customer reference. Evidence Confidence measures the quality and traceability of available evidence, not independent verification.

Customer reference value90/100
  • Problem clarity20/20
    Measures whether the customer's operational problem is specific enough to compare.
  • Implementation depth25/25
    Rewards named components, data flow, integrations, and architecture detail.
  • Outcome specificity20/20
    Measures whether the reported benefit is concrete rather than a generic claim.
  • Quantified impact15/25
    1 metric describe measurable impact.
  • Deployment scale10/10
    Rewards evidence of a live or scaled deployment and meaningful integration scope.
Evidence confidence79%
  • Source authority20/25
    The main evidence is an official vendor-published customer story.
  • Claim traceability21/25
    10 of 12 key fields link to a named source.
  • Direct evidence20/20
    4 direct source quotes retained.
  • Date provenance0/10
    The publication date has no documented provenance.
  • Source transparency8/10
    1 source reference document publisher, URL, authority, retrieval, and supported fields.
  • Implementation specificity10/10
    Rewards source-backed components, data flow, quantified impact, and a specific outcome.
02

Traceability

Sources & provenance

Field coverage shows which facts each source supports. Dates are shown only when documented by the source.

  1. Confluent

    DISH Wireless customer story

    First-party
    https://www.confluent.io/customers/dish-wireless/
    Source type
    Vendor-published customer story
    Supports
    • Customer
    • Business problem
    • Solution
    • Products
    • Solution components
    • Data flow
    • Integrations
    • technical area
    • use case category
    • Business outcome
    • outcome category
    • Metrics
    • Architecture
    • evidence quotes

Date evidence

  • First archived Dec 5, 2023 · Internet Archive · Independent First Wayback Machine capture; confirms the page existed by this date, not when it was published.
    Open date source
  • Sitemap last modified Oct 11, 2026 · Confluent · Publisher metadata Publisher-reported modification timestamp; not a publication date.
    Open date source
Not separately sourced Industry, Region, Company size. Treat these normalized attributes as lower-confidence until a dedicated source is added.

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