top of page
Streamops.png

StreamOps

Reducing Incident Resolution Time Through a Unified Observability Dashboard

When critical outages occur, engineers must piece together alerts, metrics, logs, and traces across multiple tools. StreamOps unifies observability signals into a single investigation workspace, helping teams identify root causes faster and reduce downtime.

During a high-traffic live streaming event, error rates spike and users begin experiencing buffering issues. Engineers must quickly determine the cause, but key observability data is spread across multiple tools. This fragmented workflow slows investigation, increases context switching, and delays resolution.

Objectives & Goals

  • Reduce incident investigation time.

  • Unify alerts, metrics, logs, and traces into one workflow.

  • Surface relevant context at the right moment.

  • Guide engineers through root cause analysis.

Screenshot 2026-05-29 at 2.56.22 PM.png

WIREFRAMES

View Protoype

  • 01

    Provides engineers with a high-level overview of active incidents, severity, impacted services, and key system health indicators to accelerate initial triage.

    Incident dashboard

    Screenshot 2026-06-01 at 6.26.02 PM.png

  • 02

    A shared timeline that visualizes error rates and latency spikes, helping engineers quickly identify anomalies and focus investigations on the most critical time windows.

    Error & Latency Timeline

  • 03

    Combines health metrics, dependencies, deployments, and configuration updates in a single view to help engineers assess service impact and identify potential causes faster.

    Service detail

    Screenshot 2026-06-01 at 6.48.27 PM.png

  • 04

    Groups related errors into meaningful patterns, surfaces likely root causes, and automatically connects logs to relevant traces to reduce investigation time.

    Logs panel

    Screenshot 2026-06-01 at 6.48.43 PM.png

  • 05

    Visualizes request paths and service interactions, helping engineers pinpoint where failures occur and identify performance bottlenecks.

    Trace view

  • 06

    Automatically correlates observability signals across tools, reducing manual analysis and helping engineers validate root causes with confidence.

    Correlated signals

  • 07

    Summarizes findings, affected services, and recommended next steps to improve communication and accelerate resolution.

    Resolution & escalation

RESEARCH

  • 01

    A review of common patterns in engineering incident response workflows and existing observability platforms.

    Quantitative research

    Observations:
    1. Around half of incident resolution time is spent figuring out what’s wrong, not fixing it.
    2. Multiple alerts frequently point to the same issue.
    3. Engineers often switch between multiple tools during an incident.

  • 02

    Competitor analysis

  • 03

    User Needs

  • 04

    Product user challenges

  • 05

    This system is used by engineers who are responsible for keeping large-scale systems running reliably. This includes SREs, Backend/Platform Engineers and On-call Engineers. These users often work under pressure during live incidents, where fast decision-making is critical.

    User Persona

  • 06

    Task Mapping

  • 07

    Root cause analysis (RCA)

  • 08

    5 why Analysis

  • 09

    Eisen Hover Matrix

  • 10

    Constraints

  • 11

    To resolve user needs

    Features & Functionalities

    1. A single screen that brings together alerts, metrics, logs, and traces related to an incident. This helps engineers understand what is happening without switching between tools.

    2. Automatically groups related alerts into one incident instead of showing multiple separate notifications. This reduces noise and helps engineers focus on the actual issue.

bottom of page