Hardware Observability Explained
Transform sensor data into actionable insights to drive innovation
The tools to manage complex machines weren't keeping pace with the machines themselves. Our founders saw an opportunity to revolutionize how engineers work with data, paving the way for faster, safer innovation across industries. To understand the full story behind our mission, read "Why We Left SpaceX" and discover how we're transforming the landscape of hardware engineering.
What is a hardware observability stack?
A hardware observability stack is a toolset that helps engineers make sense of the data generated by complex hardware. Managing this data is crucial for mission success and scalability. These tools are indispensable for building, operating, and scaling the machines of the future.
To fully understand the performance of intricate hardware, engineers need to collect and analyze data from various sensors and transmitters. Sift streamlines this process by providing teams with the ability to ingest, analyze, review, and store this data, eliminating arduous manual work.
Data Review Process
To ensure rigorous testing of human spaceflight rockets and capsules, industry-leading aerospace firms employ a unified system for telemetry data management. (Read about our SpaceX heritage.) This integrated approach stores and visualizes telemetry from all tests while applying consistent, automated checks across HOOTL (hardware out of the loop), HITL (hardware in the loop), and vehicle data. Streamlining the review process through integrated software tools ensures high standards and comprehensive analysis across all testing phases. Read this blog to learn more about the data review process.
Why does hardware observability matter?
An advanced hardware observability system provides real-time data on your system's health, allowing you to spot and fix potential problems before they lead to expensive downtime or disasters.
For machines operating in inaccessible locations, a hardware observability stack is the sole means of precisely monitoring performance and resolving issues. As companies scale their fleets, hardware observability becomes a vital tool for innovation and optimization throughout the entire lifecycle, from R&D to launch.
Hardware observability systems can also provide necessary data for compliance and certification with third parties. The right tools reduce costs and accelerate production, enabling companies to build machines quickly and safely.
How are current monitoring solutions different from hardware observability?
Monitoring solutions like Grafana fall short when it comes to troubleshooting the unknown. Engineers are forced to anticipate issues and anomalies in advance, preconfiguring dashboards for every conceivable scenario. In the uncharted waters of modern hardware development, this is an impossible task.
Without the ability to surface and explore unanticipated data patterns, engineers are left flying blind, unable to spot critical issues before they escalate into catastrophic failures.
Modern observability tools utilize logs, metrics, and traces to provide comprehensive insight, so teams can adapt to ongoing events and troubleshoot new and novel scenarios. They go further than common monitoring tools to include metadata, user actions, system structure, network configuration, and access to granular code information.
How legacy systems can lead to disaster
Building the revolutionary machines of tomorrow demands more than the outdated software of the past. Engineers need reliable, purpose-built tools to develop and operate complex hardware with confidence.
Companies still relying on legacy systems or in-house infrastructure are flying blind, risking costly errors and engineer burnout. Sift provides the modern hardware observability stack these visionaries need to bring their groundbreaking inventions to life.
Should you build in-house?
Building a hardware observability stack in-house is a resource-intensive endeavor that pulls critical engineering talent away from your primary objectives. These homegrown systems are not only costly to maintain, but they often struggle to provide the comprehensive visibility needed for efficient collaboration and risk mitigation.
Open-source tools and generic monitoring solutions fall short when it comes to the unique demands of complex hardware systems. They lack the scalability and flexibility required to handle the high volume and variety of data generated by cutting-edge machines. Relying on these limited tools leaves your hardware vulnerable to critical failures that can result in billions of dollars in losses and indefinite project delays.
Unified Hardware Observability
Sift's hardware observability infrastructure empowers machine development by streamlining the release process with automated data review and anomaly detection. Our platform goes beyond traditional monitoring, leveraging AI and machine learning to proactively identify and predict potential issues before they manifest.
With Sift's open-source, unbundled database architecture, data access is democratized, eliminating silos and preventing engineer bottlenecks. Our fully managed service allows your engineers to focus on innovation, while benefiting from the expertise of a highly specialized team dedicated to your success.
Sift provides a centralized data access point and enables intuitive visualization, giving your team a single source of truth for your hardware's performance. By offloading operational overhead and leveraging advanced AI capabilities, Sift helps you drive innovation and stay ahead of the competition.
Learn more about SiftDB and Sift Observability