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How to view and query your telemetry on site with Sift Edge
REGISTER FOR THE WEBINARWhen a signal drifts or a component spikes during a test out in the Mojave, a bad network connection isn't just an inconvenience—it's a liability. When running high-stakes hardware tests, waiting on cloud latency or fighting a spotty cellular uplink can mean the difference between aborting safely or losing a multi-million-dollar asset and losing months of schedule. You need immediate, high-throughput access to your telemetry right on the test stand so operators can make split-second decisions before a failure escalates.
Sift Edge brings Sift's core analytics power directly to the local hardware. Engineered from the ground up for extreme write throughput and sub-second query speeds, Edge safely ingests live sensor streams locally no matter how remote or air-gapped the site is. Operators get full local visibility through a responsive desktop GUI letting them trace historical trends and spot anomalies as close to real time as possible while the hardware is actively firing.
Once the test concludes and connectivity is restored, team members can selectively sync local telemetry directly to their main Sift tenant giving engineering teams Sift's full suite of deep data review, automated rules, and cross-campaign collaboration tools to verify their hardware.
Stream sensor data with your existing Sift streaming integrations or with Industry Standard Protocols
For teams already using Sift's client libraries, connecting to Sift Edge is as simple as pointing them to the socket address that Edge is listening on; however Sift Edge also supports industry-standard protocols like Arrow Flight for high-throughput data transfer. Once ingested, sensor streams map cleanly into channels within the desktop application, offering an exploration experience familiar to existing Sift users that keeps complex, nested data organized and easily searchable.
View live and historical data with ultra low-latency
Monitoring active hardware requires both real-time visibility and immediate access to past context. The Sift Edge desktop application allows operators to visualize live streams without sacrificing responsiveness.
- Flexible multi-pane layouts: Tabs, split plots, and tabular views can be arranged side by side—such as tracking acceleration waveforms while monitoring live brake torque values concurrently.
- Instant time-range navigation: Operators can scrub through historical runs or jump back to live data instantly. Preset time controls and sub-millisecond custom time ranges let teams isolate anomalies as they happen without interrupting background ingestion.
- Synchronized multi-channel views: Assets, runs, and channel hierarchies stay grouped in the sidebar for rapid discovery. Telemetry streams from multiple sensors render on shared axes to clarify cross-channel relationships during active tests.
Upload data to back to your single source of truth
While Sift Edge handles immediate local monitoring on the test stand, Sift remains the organization's central single source of truth. Once back online, operators can sync local run data up to their Sift tenant, moving telemetry seamlessly from the edge into the main platform for deep data review, cross-team collaboration, and executive decision-making.
- Selective run syncing: Teams choose which local runs to upload, giving control over when and what gets pushed upstream rather than saturating limited networks during live testing.
- Upload tracking and visibility: The integrated sync management view provides real-time upload progress, point counts, and job status to ensure data integrity before clearing local disk space.
- Unified campaign analytics: Once uploaded, local telemetry automatically integrates with existing Sift assets and channels, enabling automated rules, historical trend analysis, and shared reporting across distributed teams.
| The job | A common setup today | With one Sift Edge deployment | What changes for your team |
|---|---|---|---|
| Get custom telemetry into a viewer | Write a converter or export script that reshapes messages into CSV or another format the viewer accepts, then update it every time the schema moves | Register a descriptor with its fully qualified message type name and file descriptor set, then stream raw protobuf messages against it | A schema change becomes a re-registration, and a field the server cannot ingest comes back by name before the run starts |
| Watch the test as it runs and look backward | Stand up a separate time-series database beside the test and keep it running, with recent history living in a different tool from the live view | Current samples in memory and Parquet on local disk, merged by DataFusion inside one query, served by a single binary | One process on the test-stand machine, and one series that runs from the newest sample back through the test |
| Keep the dashboards operators already use | Point Grafana at whatever local store your team stood up, and rebuild panels when that store changes | Point a local Grafana instance at the local server through the Sift Grafana plugin, Edge build | Existing panels and alerts keep working, and the dashboard and the native GUI read the same file on the same disk |
| Get the run to the rest of the team | Move files after the test, or leave the record in a local database that never joins the shared history | Start an upload job for a run, an asset time range, or a selection made in Explore, and track it to completion | The telemetry your team chooses lands in your Sift tenant alongside reports, rules, and campaign history, on a schedule your team sets |
Accelerate Edge integrations with AI Agent Skills
To streamline custom telemetry pipelines, Sift Edge ships with built-in Agent Skills that give AI coding assistants precise context about the Sift Edge environment. Many engineering teams already use AI agents that understand their specific hardware, sensor suites, or internal codebase. Equipping those same agents with Sift Edge skills bridges the gap—combining deep hardware-stack context with accurate platform specs to generate reliable integration code.
- Pre-packaged platform context: The embedded skill covers the full client surface area—from data ingestion and querying to avoiding common pitfalls.
- Broad agent compatibility: Whatever AI coding assistant your team already uses, Sift Edge skills integrate with your assistant of choice.
- Simple CLI installation: Distributed directly within the Sift Edge CLI, skills can be installed or inspected in a single step to immediately upgrade an agent's capabilities without modifying server behavior.
How to view and query your telemetry on site with Sift Edge
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