Digma is a company offering products designed to act on pre-production observability data. It has announced the launch of its preemptive observability analysis (POA) engine. The engine is designed to check and identify issues. It provides ‘fix’ suggestions. This helps to balance systems and reduces issues found in codebases as their complexity increases.
The application of preemptive observability in pre-production may be more important as AI code generators become more common. The company claims this trend is significant. A 2023 Stanford University study found that developers using AI coding assistants were more likely to introduce bugs. Despite this, major companies like Google are increasing their reliance on AI-generated code. Over 25% of Google’s new code is AI-created.
Nir Shafrir, CEO and Co-founder of Digma, commented on the growing resources dedicated to ensuring systems perform well. He said, “We’re seeing a lot of effort invested in assuring optimal system performance. However, many issues are still discovered in complex code bases late in production.”
“Beyond this, scaling has often remained a rough estimation. Organisations anticipating growth frequently hit barriers. These barriers in technology growth arise precisely during periods of significant organisational expansion. Engineering teams may spend between 20-40% of their time addressing issues discovered late in production environments. Some organisations use up to 50% of engineering resources on fixing production problems.”
Preemptive observability is expected to become a key factor helping companies gain competitive advantage. It has several potential benefits for AI-generated code, including speed increases and improvements to the reliability of human-written code. According to Digma, preemptive observability helps ensure manually written code is more trustworthy, and reduces risk in the final product.
Digma’s preemptive observability analysis engine tackles bugs introduced by AI code generation. It also combats issues related to human-made code. These issues are common and long-established in some companies. They may result in service level agreement (SLA) violations and performance issues. For high transactional establishments, like retail, fintech, and e-commerce, this technology could become valuable.
Digma’s algorithm uses pattern matching techniques. It also employs anomaly detection techniques to analyse data. These techniques help find specific behaviours or issues. It can predict an application’s response times. It can also estimate resource usage. This capability helps identify possible issues before they can cause any noticeable damage. Digma specifically detects the part of the code that is causing an issue by analysing tracing data.
Preemptive observability analysis prevents problems rather than dealing with the aftermath of the issues. Teams can monitor holistically, and address potential issues in areas that are frequently ignored once in production.
Roni Dover, CTO and Co-founder of Digma, highlighted a key differentiation of Digma’s preemptive observability analysis engine. “We understand runtime behaviour. We suggest fixes for performance issues, scaling problems, and team conflicts. We’re helping enterprises prevent problems and reduce risks proactively rather than putting out fires in production.”
Application performance monitoring (APM) tools are used to identify service issues, monitor production statuses, and highlight SLA errors. APMs are practical for sending alerts when services fail or slow during production. But unlike preemptive observability, APMs are limited in non-production settings, and can’t provide analysis of problems’ sources.
By identifying performance and scaling issues early on in the production process, observability is enhanced. Even when data volumes are low, preemptive action helps prevent major problems. This approach also reduces cloud costs.
Digma recently completed a successful $6 million seed funding round, indicating a growing confidence in the technology.
Image source: “Till Bechtolsheimer’s – Alfa Romeo Giulia Sprint GT No.40 – 2013 Donington Historic Festival” by Motorsport in Pictures is licensed under CC BY-NC-SA 2.0.
Leave a Reply