The High-Stakes Decision of Observability Tools
When building mission-critical machines, like planes and spacecraft, where precision and reliability are non-negotiable, telemetry and observability tools play a crucial role in ensuring safety, performance, and compliance. These tools provide real-time insights into complex systems, enabling engineers to detect anomalies, predict failures, and optimize operations. However, the decision to build or buy observability tools has far-reaching implications, especially when in-house solutions are considered.
The allure of custom-built tools lies in their promise of control and cost savings. Yet, the reality is that these tools often fail to scale, leading to inefficiencies, knowledge silos, and operational risks that jeopardize long-term success. According to Sift’s 2024 Aerospace report, 77% of respondents identified inefficiencies and loss of expertise as significant consequences of fragmented telemetry systems—a clear indicator of the hidden pitfalls of in-house development.
Take JetZero, for example. Tasked with meeting ambitious net-zero carbon emission goals, they avoided the in-house trap by adopting Sift’s unified telemetry platform. This decision allowed them to focus on their core competency of building planes, not maintaining tools, ensuring scalable, reliable data insights at every stage.
The allure of custom-built tools lies in their promise of control and cost savings. Yet, the reality is that these tools often fail to scale, leading to inefficiencies, knowledge silos, and operational risks that jeopardize long-term success.
The Challenges of Unscalable Solutions
In-house telemetry systems built using various tools such as Influx and Grafana might work for smaller projects or limited use cases but often crumble under the weight of growing demands. These tools struggle to:
- Handle increasing data volumes and real-time data needs
- Adapt to evolving system requirements
- Provide consistent visibility across teams and projects
- Capture institutional knowledge
This stagnation leads to abandoned projects and mounting technical debt. For example, 63% of aerospace professionals in Sift’s survey cited data management challenges, such as ingestion and migration, as major issues. Fragmented tools exacerbate these problems, often leaving critical data inaccessible or underutilized.
At Mach Industries, reliance on bespoke systems delayed field testing, increasing operational inefficiencies. By switching to Sift’s observability platform, they reduced these delays and accelerated their development cycles, demonstrating the transformative power of scalable solutions.
This ongoing maintenance not only diverts talent away from core innovation but also introduces points of failure that compound under pressure.
Engineering Impact and Resource Allocation
Maintaining in-house observability tools places an undue burden on engineering teams, often disrupting their ability to scale and innovate effectively. Instead of fostering resilience and adaptability, these tools require constant updates, troubleshooting, and reconfiguration to meet new demands. This ongoing maintenance not only diverts talent away from core innovation but also introduces points of failure that compound under pressure.
- Key Insight: In Sift’s Observability Aerospace Report, 81% of respondents highlighted the value of redirecting resources from tool maintenance to mission-critical tasks, emphasizing the inefficiencies of in-house solutions.
Systems that can evolve under stress and complexity ensure greater operational efficiency, but in-house tools often fail to scale or adapt without significant manual intervention. The result is a cycle of firefighting—where engineers are bogged down by reactive maintenance rather than proactive innovation. This misallocation of resources is particularly costly for mission-critical industries, where time-to-market and reliability define success. Every hour spent patching or scaling an internal tool is an hour not spent developing the next breakthrough technology or ensuring product performance in high-stakes environments. (Read Next: Antifragile Engineering)
In contrast, in-house tools often struggle to adapt, leaving organizations exposed to escalating inefficiencies and accumulating technical debt.
Financial Implications: The Long-Term Cost of In-House Tools
Building telemetry tools in-house may appear cost-effective at first glance, but the hidden financial burdens are substantial—and they tend to grow as systems scale. Internal tools often lack transparency in cost projection, which leads to surprises as the system scales and adapts. Companies consistently underestimate expenses in areas such as:
- Maintenance Costs: Regular updates, bug fixes, licensing fees for dependencies, and scaling efforts demand ongoing investment, often exceeding initial budgets.
- Technical Debt: Legacy code and architectures accumulate over time, requiring costly overhauls to keep pace with evolving operational demands.
- Operational Inefficiencies: Fragmented tools increase storage costs, delay anomaly detection, and hinder compliance efforts, driving up indirect costs.
Well-designed systems are built to handle complexity and uncertainty, improving their performance as demands grow. In contrast, in-house tools often struggle to adapt, leaving organizations exposed to escalating inefficiencies and accumulating technical debt. According to Sift’s 2024 Aerospace report, rising storage costs and inefficiencies were identified as critical pain points, particularly as telemetry data volumes grow exponentially.
Moreover, in industries like aerospace, where regulatory compliance budgets are already stretched thin, maintaining fragile in-house tools consumes resources that could otherwise be invested in innovation or risk mitigation. Purpose-built platforms like Sift automate compliance, streamline anomaly detection, and reduce operational overhead, enabling organizations to allocate resources more strategically.
Operational Risks and Long-Term Impact
Bespoke solutions introduce operational risks that can undermine reliability and adaptability. Knowledge silos develop when key expertise resides with a few individuals, creating vulnerabilities during attrition or organizational changes. 77% of aerospace respondents highlighted knowledge silos as a major concern, leading to inefficiencies and increased risk of failures. 1
Additionally, traditional tools often struggle with slow anomaly detection and false alerts, as noted by 62% of survey respondents. These delays disrupt operations, increase costs, and compromise safety.
Scalability as a Strategic Imperative
In fast-paced, high-stakes industries, scalability is not just a technical necessity—it’s a strategic imperative. Scalable observability tools enable organizations to:
- Manage large volumes of telemetry data without oversight or additional headcount
- Ensure accessibility by all users of varying software fluency from technicians on the factory floor, to program managers working with regulators
- Collaborate on workflows designed around thousands of users
For example, Sift DB’s architecture is designed to scale infinitely, keeping costs low while managing massive telemetry datasets. This ensures compliance and agility, positioning companies for sustained success.
Making The Case for Scalable Observability Platforms
In industries where stakes are high, scalability is not just a technical requirement—it’s a strategic necessity. Sift’s observability solutions enable organizations to:
- Handle Exponential Data Growth: Sift DB scales effortlessly, managing massive telemetry datasets without increasing personnel.
- Simplify Certification: Automated reporting simplifies adherence to rigorous standards, allowing for agility even under strict regulatory constraints.
- Support Innovation: By consolidating data and streamlining workflows, scalable solutions free resources for breakthroughs instead of maintenance.
The risks of building in-house telemetry tools—from operational inefficiencies to escalating costs—are substantial. As industries like aerospace continue to evolve, scalability, reliability, and long-term viability must guide observability decisions.
Sift’s purpose-built platform addresses these challenges, empowering organizations to prioritize innovation and operational excellence. With 78% of professionals citing data visibility as a critical issue, now is the time to invest in scalable solutions.
Informed decision-making today ensures operational excellence tomorrow. Sift’s Forward Deployed Engineers (FDEs) help transform organizations to be more scalable, ensuring their systems and workflows are built to adapt and grow with future demands. Grab 30 mins with Sift’s FDE team here.
Check out more on this topic: Avoiding the In-house Sinkhole, Evolving Past the In-house Model
