Assuring Scale & Reliability

  • Handle Peak Loads on Limited Infrastructure

    Concerns:

    • “Spikey” traffic profile – intermittent periods of high-volume traffic
    • Data & infrastructure costs can be considerable, even during periods of low connections.
    • Maintain reliability of service regardless of load.

    How Diffusion helps:

    • Offloads responsibility for managing and scaling end-device connections = less back-end infrastructure required
    • Topic caching allows new connections to receive latest data without having to interact with back-end infrastructure
    • Pub/Sub model only sends data when values change for topics that consumers have registered selections for, reducing overall data volume transmitted over the network.
    • Kubernetes support allows dynamic scaling of Diffusion edge-nodes to handle changes in traffic volume
  • Scaling Data Across Limited Bandwidth Networks

    Concerns:

    • Large amounts of messages need to be transmitted over limited bandwidth
    • Performance must be maintained regardless of data volume
    • Data costs can be considerable

    How Diffusion helps:

    • Binary deltas – reduces amount of data that needs to be transmitted, reducing bandwidth costs and ensuring consistently low latency
    • Queue-based server architecture handles high-throughput / high-volume messaging requirements
    • Pub/Sub model only sends data when values change for topics that consumers have registered selections for, reducing overall data volume transmitted over the network.
  • Scaling Mobile & IoT Connections

    Concerns:

    • Mobile & IoT applications need to handle large numbers of connections
    • Must be able to handle unreliable and congested networks
    • Infrastructure costs can be considerable

    How Diffusion helps:

    • Offloads responsibility for managing and scaling end-device connections = less back-end infrastructure
    • Clustering allows easy scaling of Diffusion edge-nodes to handle device connections
    • High-performance server architecture for maintaining low-latencies at scale
  • Extend Messaging Across The Internet

    Concerns:

    • Need to extend traditionally back-end messaging across the internet to web/mobile apps
    • Must be able to handle unreliable and congested networks
    • Need consistent QoS for scaling to large numbers of connections

    How Diffusion helps:

    • 1-to-1 and 1-to-many messaging features across all Client SDKs
    • Reliable reconnect – no lost messages in the case of client disconnection
    • Message delivery acknowledgement and explicit error handling
    • High-performance server architecture for scaling to large numbers of client connections
    • 1st party Client SDKs for web and mobile platforms