
Can we develop our own incident response tools?
February 12, 2026
Author of this article
President and CEO
Takaaki Kanetsuki
The Reality of "Technical Debt" and "Operational Costs" in In-House Tool Development
The more talented an engineering team is, the more likely it is to conclude, “For a feature of this complexity, it would be faster and cheaper to build it ourselves.” However, building tools in-house involves not only the visible development effort but also enormous hidden costs and operational risks.
We have outlined three key considerations to ensure that essential business growth is not hindered.
1. "Opportunity Cost" of Development Resources: Focusing on Differentiation
Engineering man-hours are one of the most scarce resources for any company. Allocating man-hours to in-house tools means putting off development that directly contributes to customer value.
Avoiding Undifferentiated, Labor-Intensive Work: No matter how much you refine your internal infrastructure and operational tools, they rarely contribute directly to increased product sales or customer satisfaction (CS).
Maximizing ROI: The biggest advantage of adopting SaaS is that it allows engineers to focus 100% on "work that creates a competitive advantage," such as developing "proprietary algorithms" and "new features."
2. Discrete costs during the "operational phase"
There is a huge gap between “getting a prototype up and running in two weeks” and “continuing to operate it as a mission-critical service.”
24/7/365 uptime monitoring: Operational tools must function properly precisely when your own services are down. Maintaining the necessary redundancy and monitoring infrastructure in-house is extremely costly.
Security and Compliance: Non-core "defensive development" tasks—such as adhering to SOC 2-equivalent security standards, responding immediately to vulnerabilities, and implementing identity and access management (IAM)—are an ongoing necessity.
The burden of keeping up with technological advancements: For example, tools that utilize LLMs or RAG require dedicated man-hours to continuously keep pace with updates to the underlying models and changes to library specifications.
3. Cost Simulation for In-House Development vs. SaaS Implementation
In fact, if we estimate the cost of developing the system in-house with two engineers, the figures would look like this.
Item | Estimated figures (based on two engineers with an annual income of 8 million yen) | Amount (estimate) |
|---|---|---|
Initial development costs | Three months of full-time development (including social insurance premiums, etc.) | Approximately 5.2 million yen |
Monthly maintenance fee | Allocate 20% of operating man-hours to maintenance | Approximately 350,000 yen per month |
Infrastructure costs | Database, monitoring, log storage, API usage fees, etc. | Approximately 500,000 yen per month |
Total Cost | First year: Approximately 15.4 million yen |
This figure does not include the business profits that the engineer could have generated (opportunity cost). It is also necessary to consider risks such as "reliance on individual expertise" and "outdated documentation" resulting from the employee's departure.
Conclusion: Incident Response Must Become a "Specialized Foundation"
While the goal of in-house tools is often simply to "work," the true value of an incident response tool lies in its ability to "continue operating with optimal settings, remaining calmer than anyone else, even in the worst-case scenario when the company is in a state of panic. "
As the saying goes, “Leave it to the experts.” Outsourcing your operational infrastructure to a specialized service (Incident Lake) is more than just a cost-saving measure. It is a strategic investment designed to free your engineers from “back-end maintenance” and redeploy them to “proactive engineering.”
Author of this article
President and CEO
Takaaki Kanetsuki
After graduating from Kumamoto University, he joined Money Forward, Inc. as a new graduate. He worked in management and development roles at various development sites, both domestically and internationally, including a secondment to the company’s Vietnam office. In 2022, he joined Plaid, Inc., where he oversaw Platform Engineering and was involved in the development of large-scale distributed data systems. In 2024, he founded SIGQ, Inc. Currently, in addition to managing the company, he is conducting research on databases at the University of Tsukuba Graduate School.
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