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Latency

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Apa itu Latency?

Latency is the time delay between initiating a request and receiving a response, measured in milliseconds. In automation, lower latency means faster workflow execution and more responsive interactions with websites and APIs.

What is Latency?

Latency measures the time it takes for a request to travel from the sender to the receiver and back. In web and automation contexts, it is the delay between clicking a button (or sending an API call) and seeing the result. Latency is typically measured in milliseconds (ms) and is distinct from bandwidth, which measures data volume capacity.

Types of Latency

Several factors contribute to total latency:

  • Network latency — The time for data to travel across the network. Affected by physical distance, routing hops, and network congestion.
  • Processing latency — The time the server takes to process the request and generate a response.
  • Queuing latency — The time a request spends waiting in a queue before being processed, common in high-traffic systems.
  • Rendering latency — In browser automation, the time for a page to render after receiving HTML, CSS, and JavaScript.

    • Latency in Automation

    Latency directly impacts automation performance:

  • Browser automation — Each page navigation, element interaction, and JavaScript execution adds latency. A workflow with 50 page interactions at 500ms each adds 25 seconds of latency alone.
  • API calls — External API requests typically add 100-500ms per call. Workflows chaining multiple API calls accumulate significant delays.
  • Geographic distance — Automating a website hosted in Europe from a server in the US adds ~100-150ms per request just from network transit.
  • Database operations — Reading from and writing to databases introduces latency that compounds across workflow steps.

    • Reducing Latency

    Common strategies for minimizing latency in automation:

  • Geographic proximity — Run automation servers close to target websites or APIs.
  • Connection reuse — Keep HTTP connections alive (keep-alive) to avoid TCP handshake overhead on every request.
  • Parallel execution — Run independent steps simultaneously rather than sequentially.
  • Caching — Store frequently accessed data locally to avoid redundant network requests.
  • CDN usage — For serving results, use content delivery networks to reduce delivery latency to end users.

    • Mengapa Ini Penting

    Latency determines how fast your automations execute and how many tasks you can complete in a given time window. High latency in workflow steps compounds across a pipeline, turning a 5-minute job into a 30-minute job and limiting the scalability of your automation.

    Bagaimana Autonoly Menyelesaikannya

    Autonoly minimizes latency by running browser automation and SSH sessions in cloud containers close to target services. The platform reuses connections, executes independent workflow steps in parallel, and optimizes browser interactions to reduce unnecessary page loads and network round-trips.

    Pelajari lebih lanjut

    Contoh

    • Measuring 200ms average latency per API call and restructuring a workflow to batch 50 individual calls into 5 bulk requests, reducing total latency from 10 seconds to 1 second.

    • Choosing a US-East execution region for a workflow that scrapes US-hosted websites, cutting network latency from 150ms to 15ms per request.

    • Running three independent data extraction steps in parallel instead of sequentially, reducing total workflow time from 45 seconds to 15 seconds.

    Pertanyaan yang Sering Diajukan

    Latency is the time delay for a single request-response cycle (measured in milliseconds). Bandwidth is the maximum data volume that can be transferred per unit of time (measured in Mbps or Gbps). A connection can have high bandwidth but high latency (satellite internet) or low bandwidth but low latency (local network). For automation, latency usually matters more than bandwidth because most requests are small.

    For real-time applications, under 100ms is ideal. For automation workflows, 100-500ms per API call is typical and acceptable. Anything over 1 second per call should be investigated — it may indicate server issues, network problems, or the need for geographic optimization.

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