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세계의 대규모 언어 모델(LLM) 옵저버빌리티 플랫폼 시장 보고서(2025년)
Large Language Model (LLM) Observability Platform Global Market Report 2025
상품코드 : 1888309
리서치사 : The Business Research Company
발행일 : On Demand Report
페이지 정보 : 영문 250 Pages
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한글목차

대규모 언어 모델(LLM)의 옵저버빌리티 플랫폼 시장 규모는 최근 급격히 확대되고 있습니다. 2024년 14억 4,000만 달러로 평가되었고, 2025년에는 19억 7,000만 달러에 달할 것으로 추정되며, CAGR 36.5%로 성장이 전망되고 있습니다. 이러한 성장은 기업의 인공지능(AI) 및 머신러닝 모델의 도입 증가, 모델 리스크 및 바이어스에 대한 인식 증가, 확장 가능한 모델 감시 툴에 대한 수요 증가, AI 워크플로우에서 운영 효율화의 필요성 증대, 데이터 품질 및 모델 정밀도에 대한 주목 증가 등이 요인으로 생각됩니다.

대규모 언어 모델(LLM)의 옵저버빌리티 플랫폼 시장 규모는 향후 수년간 급성장할 것으로 전망됩니다. 2029년에는 68억 달러에 달할 것으로 예측되며, CAGR 36.3%로 성장할 전망입니다. 예측 기간의 성장요인으로는 산업 횡단적인 생성형 인공지능의 채용 확대, 대규모 언어 모델의 투명성 및 책임에 대한 수요 증가, 모델 성능 최적화에 대한 수요 증가, 인공지능 거버넌스에 관한 규제 프레임워크 확충, AI 인프라에 대한 기업 투자 증가 등이 있습니다. 예측 기간 주요 동향으로는 대규모 언어 모델의 퍼포먼스를 실시간으로 감시하는 기술의 진보, 모델 동작 추적을 위한 통합 가관성 대시보드의 개발, 대규모 언어 모델용 이상 감지 및 드리프트 분석의 혁신, 대규모 언어 모델 파이프라인의 데이터 프라이버시 및 컴플라이언스 감시 기술 향상, 대규모 언어 모델의 신뢰성 및 최적화를 향한 예측 분석 기술 개발 등을 들 수 있습니다.

클라우드 기반의 옵저버빌리티 플랫폼의 채용 급증은 복잡한 클라우드 환경에서의 고도의 감시 및 분석의 필요성이 높아지고 있기 때문에 대규모 언어 모델 옵저버빌리티 플랫폼 시장의 성장을 견인하고 있습니다. 클라우드 기반 옵저버빌리티 플랫폼은 클라우드 환경을 실시간으로 모니터링, 분석 및 시각화하는 통합 솔루션으로, 문제를 신속하게 감지하고 해결할 수 있어 성능 및 안정성을 향상시킵니다. 그 채택은 분산 환경에서 원활한 운영을 유지하기 위해 고급 모니터링 및 분석을 필요로 하는 클라우드 네이티브 애플리케이션과 인공지능 워크로드의 복잡화가 진행되고 있기 때문입니다. 대규모 언어 모델 모니터링 플랫폼은 복잡한 클라우드 인프라 내에서 인공지능 언어 모델의 성능을 모니터링, 디버깅 및 최적화하기 위한 전용 도구를 제공하여 클라우드 기반 모니터링 기능을 강화합니다. 예를 들어, 2023년 12월에 유로스타트가 발표한 보고서에 따르면 유럽 연합(EU) 지역 내 기업의 42.5%가 클라우드 컴퓨팅 서비스를 채택하고 있으며, 클라우드 도입의 광범위한 동향을 반영하고 있습니다. 따라서 클라우드 기반 옵저버빌리티 플랫폼의 채용 증가는 대규모 언어 모델 옵저버빌리티 플랫폼 시장의 성장을 가속할 것으로 예측됩니다.

대규모 언어 모델 옵저버빌리티 플랫폼 시장에서 사업을 전개하는 주요 기업은 엔드 투 엔드의 인공지능 스택 옵저버빌리티와 같은 기술적 진보에 주력하여, 인공지능 라이프사이클 전체에서 퍼포먼스의 가시성, 운용 효율 및 신뢰성의 향상을 도모하고 있습니다. 엔드 투 엔드 인공지능 스택 옵저버빌리티는 인공지능 라이프사이클 내의 모든 구성요소를 종합적으로 모니터링, 분석, 시각화하고, 통일된 가시성, 신속한 문제 검출, 시스템 전체의 최적 성능 확보를 실현하는 개념입니다. 예를 들어, 2025년 1월에는 미국 소프트웨어 기업인 Dynatrace Inc.가 대규모 언어 모델 및 생성형 AI에 대한 AI 옵저버빌리티를 발표하여 조직이 AI 구동 애플리케이션의 성능, 정확성 및 신뢰성에 대한 자세한 지식을 얻을 수 있도록 했습니다. 이 릴리스는 대규모 언어 모델 인사이트를 기존의 옵저버빌리티 및 보안 분석과 통합하여 인공지능 워크로드의 실시간 모니터링, 근본 원인 분석 및 최적화를 가능하게 했습니다. 이러한 진보를 통해 기업은 인공지능 워크로드를 책임지고 모니터링 및 최적화하며, 운영 효율성을 높이고, 생성된 인공지능 시스템 전체의 신뢰성을 향상시킬 수 있습니다.

목차

제1장 주요 요약

제2장 시장 특징

제3장 시장 동향 및 전략

제4장 시장 : 금리, 인플레이션, 지정학, 무역전쟁 및 관세, 그리고 코로나 및 회복이 시장에 미치는 영향을 포함한 거시경제 시나리오

제5장 세계의 성장 분석 및 전략 분석 프레임워크

제6장 시장 세분화

제7장 지역별 및 국가별 분석

제8장 아시아태평양 시장

제9장 중국 시장

제10장 인도 시장

제11장 일본 시장

제12장 호주 시장

제13장 인도네시아 시장

제14장 한국 시장

제15장 서유럽 시장

제16장 영국 시장

제17장 독일 시장

제18장 프랑스 시장

제19장 이탈리아 시장

제20장 스페인 시장

제21장 동유럽 시장

제22장 러시아 시장

제23장 북미 시장

제24장 미국 시장

제25장 캐나다 시장

제26장 남미 시장

제27장 브라질 시장

제28장 중동 시장

제29장 아프리카 시장

제30장 경쟁 구도 및 기업 프로파일

제31장 기타 주요 기업 및 혁신 기업

제32장 세계 시장 경쟁 벤치마킹 및 대시보드

제33장 주요 인수합병(M&A)

제34장 최근 시장 동향

제35장 시장의 잠재력이 높은 국가, 부문 및 전략

제36장 부록

AJY
영문 목차

영문목차

A large language model observability platform refers to a specialized system developed to monitor, analyze, and optimize the performance of large language models throughout their lifecycle. It offers real time visibility into model behavior, latency, token usage, and error patterns to ensure reliability and operational efficiency. These platforms enable developers to trace interactions, identify anomalies, and enhance model outputs through comprehensive analytics and visualization.

The primary components of a large language model observability platform are software and services. A large language model observability platform is specialized software designed to oversee, analyze, and manage the behavior and performance of large language models in practical applications. The deployment modes include on premises and cloud based solutions, catering to small and medium enterprises as well as large enterprises. The key applications include model performance monitoring, bias and fairness detection, security and compliance, data drift detection, and other related functions.

Note that the outlook for this market is being affected by rapid changes in trade relations and tariffs globally. The report will be updated prior to delivery to reflect the latest status, including revised forecasts and quantified impact analysis. The report's Recommendations and Conclusions sections will be updated to give strategies for entities dealing with the fast-moving international environment.

The rapid escalation of U.S. tariffs and the resulting trade tensions in spring 2025 are significantly impacting the information technology sector, particularly in hardware manufacturing, data infrastructure, and software deployment. Higher duties on imported semiconductors, circuit boards, and networking equipment have raised production and operational costs for tech firms, cloud service providers, and data centers. Companies relying on globally sourced components for laptops, servers, and consumer electronics are facing longer lead times and increased pricing pressures. In parallel, tariffs on specialized software tools and retaliatory measures from key international markets have disrupted global IT supply chains and reduced overseas demand for U.S.-developed technologies. To navigate these challenges, the sector is accelerating investments in domestic chip fabrication, diversifying supplier bases, and adopting AI-driven automation to enhance operational resilience and cost efficiency.

The large language model (LLM) observability platform market research report is one of a series of new reports from The Business Research Company that provides large language model (LLM) observability platform market statistics, including large language model (LLM) observability platform industry global market size, regional shares, competitors with a large language model (LLM) observability platform market share, detailed large language model (LLM) observability platform market segments, market trends and opportunities, and any further data you may need to thrive in the large language model (LLM) observability platform industry. This large language model (LLM) observability platform market research report delivers a complete perspective of everything you need, with an in-depth analysis of the current and future scenario of the industry.

The large language models (LLM) observability platform market size has grown exponentially in recent years. It will grow from $1.44 billion in 2024 to $1.97 billion in 2025 at a compound annual growth rate (CAGR) of 36.5%. The growth in the historic period can be attributed to increasing deployment of artificial intelligence and machine learning models in enterprises, growing awareness of model risks and biases, rising demand for scalable model monitoring tools, increasing need for operational efficiency in artificial intelligence workflows, and growing focus on data quality and model accuracy.

The large language models (LLM) observability platform market size is expected to see exponential growth in the next few years. It will grow to $6.80 billion in 2029 at a compound annual growth rate (CAGR) of 36.3%. The growth in the forecast period can be attributed to increasing adoption of generative artificial intelligence across industries, rising need for large language model transparency and accountability, growing demand for model performance optimization, expansion of regulatory frameworks for artificial intelligence governance, and increasing enterprise investments in AI infrastructure. Key trends in the forecast period include advancement in real-time monitoring of large language model performance, development of unified observability dashboards for model behavior tracking, innovation in anomaly detection and drift analysis for large language models, advancement in data privacy and compliance monitoring for large language model pipelines, and development of predictive analytics for large language model reliability and optimization.

The surge in adoption of cloud-based observability platforms is driving the growth of the large language model observability platform market due to the increasing need for advanced monitoring and analytics in complex cloud environments. Cloud-based observability platforms are integrated solutions that monitor, analyze, and visualize cloud environments in real time, enabling faster issue detection and resolution for improved performance and reliability. Their adoption is being driven by the growing complexity of cloud-native applications and artificial intelligence workloads, which require advanced monitoring and analytics to maintain seamless operations in distributed environments. Large language model observability platforms enhance cloud-based observability by providing specialized tools for monitoring, debugging, and optimizing artificial intelligence language model performance within complex cloud infrastructures. For instance, in December 2023, according to a report published by Eurostat, 42.5% of enterprises across the European Union adopted cloud computing services, reflecting the broader trend of cloud adoption. Therefore, the increasing adoption of cloud-based observability platforms is expected to drive the growth of the large language model observability platform market.

Key companies operating in the large language model observability platform market are focusing on technological advancements, such as end-to-end artificial intelligence stack observability, to enhance performance visibility, operational efficiency, and reliability across the entire artificial intelligence lifecycle. End-to-end artificial intelligence stack observability refers to the comprehensive monitoring, analysis, and visualization of all components within the artificial intelligence lifecycle, providing unified visibility, faster issue detection, and ensuring optimal performance across the system. For instance, in January 2025, Dynatrace Inc., a United States-based software company, launched artificial intelligence observability for large language models and generative artificial intelligence, enabling organizations to gain detailed insights into the performance, accuracy, and reliability of artificial intelligence-driven applications. The launch integrates large language model insights with existing observability and security analytics, allowing real-time monitoring, root-cause analysis, and optimization of artificial intelligence workloads. This advancement helps enterprises monitor and optimize artificial intelligence workloads responsibly, enhance operational efficiency, and improve the overall trustworthiness of generative artificial intelligence systems.

In March 2025, Arize AI Inc., a United States-based private company, acquired Velvet Inc. for an undisclosed amount. Through this acquisition, Arize AI Inc. aims to strengthen its position in the artificial intelligence observability market by integrating Velvet's advanced large language model observability and evaluation capabilities. This integration enables deeper insights into model performance, reliability, and transparency across large language models while enhancing Arize's end-to-end artificial intelligence monitoring solutions for enterprise-scale generative artificial intelligence systems. Velvet Inc. is a United States-based technology company that provides large language model observability platforms.

Major players in the large language model (llm) observability platform market are Montecarlo Limited, Datadog Inc., Dynatrace Inc., Elastic N.V., New Relic Inc., Coralogix Ltd., Arize AI Inc., Apica AB, Groundcover Ltd., Fiddler Labs Inc., ArthurAI Inc., Ensemble Labs Inc., Evidently AI Inc., Honeyhive Inc, Portkey Ai Software India Private Limited, Laminar Inc., Comet ML Inc., Braintrust Data Inc., GISKARD AI SAS, Magniv Inc.

North America was the largest region in the large language model (LLM) observability platform market in 2024. Asia Pacific is expected to be the fastest-growing region in the forecast period. The regions covered in large language model (LLM) observability platform report are Asia-Pacific, Western Europe, Eastern Europe, North America, South America, Middle East and Africa.

The countries covered in the large language model (LLM) observability platform market report are Australia, Brazil, China, France, Germany, India, Indonesia, Japan, Russia, South Korea, UK, USA, Canada, Italy, Spain.

The large language model (LLM) observability platform market consists of revenues earned by entities by providing services such as real-time latency monitoring services, token usage analytics services, error detection and logging services, performance metrics dashboard services, and trace and span visualization services. The market value includes the value of related goods sold by the service provider or included within the service offering. The large language model (LLM) observability platform market also consists of sales of products including langsmith, arise artificial intelligence, langfuse, braintrust, comet opik, and traceLoop. Values in this market are 'factory gate' values, that is, the value of goods sold by the manufacturers or creators of the goods, whether to other entities (including downstream manufacturers, wholesalers, distributors, and retailers) or directly to end customers. The value of goods in this market includes related services sold by the creators of the goods.

The market value is defined as the revenues that enterprises gain from the sale of goods and/or services within the specified market and geography through sales, grants, or donations in terms of the currency (in USD unless otherwise specified).

The revenues for a specified geography are consumption values that are revenues generated by organizations in the specified geography within the market, irrespective of where they are produced. It does not include revenues from resales along the supply chain, either further along the supply chain or as part of other products.

Large Language Model (LLM) Observability Platform Global Market Report 2025 from The Business Research Company provides strategists, marketers and senior management with the critical information they need to assess the market.

This report focuses on large language model (llm) observability platform market which is experiencing strong growth. The report gives a guide to the trends which will be shaping the market over the next ten years and beyond.

Reasons to Purchase

Where is the largest and fastest growing market for large language model (llm) observability platform ? How does the market relate to the overall economy, demography and other similar markets? What forces will shape the market going forward, including technological disruption, regulatory shifts, and changing consumer preferences? The large language model (llm) observability platform market global report from the Business Research Company answers all these questions and many more.

The report covers market characteristics, size and growth, segmentation, regional and country breakdowns, competitive landscape, market shares, trends and strategies for this market. It traces the market's historic and forecast market growth by geography.

The forecasts are made after considering the major factors currently impacting the market. These include the technological advancements such as AI and automation, Russia-Ukraine war, trade tariffs (government-imposed import/export duties), elevated inflation and interest rates.

Scope

Table of Contents

1. Executive Summary

2. Large Language Model (LLM) Observability Platform Market Characteristics

3. Large Language Model (LLM) Observability Platform Market Trends And Strategies

4. Large Language Model (LLM) Observability Platform Market - Macro Economic Scenario Including The Impact Of Interest Rates, Inflation, Geopolitics, Trade Wars and Tariffs, And Covid And Recovery On The Market

5. Global Large Language Model (LLM) Observability Platform Growth Analysis And Strategic Analysis Framework

6. Large Language Model (LLM) Observability Platform Market Segmentation

7. Large Language Model (LLM) Observability Platform Market Regional And Country Analysis

8. Asia-Pacific Large Language Model (LLM) Observability Platform Market

9. China Large Language Model (LLM) Observability Platform Market

10. India Large Language Model (LLM) Observability Platform Market

11. Japan Large Language Model (LLM) Observability Platform Market

12. Australia Large Language Model (LLM) Observability Platform Market

13. Indonesia Large Language Model (LLM) Observability Platform Market

14. South Korea Large Language Model (LLM) Observability Platform Market

15. Western Europe Large Language Model (LLM) Observability Platform Market

16. UK Large Language Model (LLM) Observability Platform Market

17. Germany Large Language Model (LLM) Observability Platform Market

18. France Large Language Model (LLM) Observability Platform Market

19. Italy Large Language Model (LLM) Observability Platform Market

20. Spain Large Language Model (LLM) Observability Platform Market

21. Eastern Europe Large Language Model (LLM) Observability Platform Market

22. Russia Large Language Model (LLM) Observability Platform Market

23. North America Large Language Model (LLM) Observability Platform Market

24. USA Large Language Model (LLM) Observability Platform Market

25. Canada Large Language Model (LLM) Observability Platform Market

26. South America Large Language Model (LLM) Observability Platform Market

27. Brazil Large Language Model (LLM) Observability Platform Market

28. Middle East Large Language Model (LLM) Observability Platform Market

29. Africa Large Language Model (LLM) Observability Platform Market

30. Large Language Model (LLM) Observability Platform Market Competitive Landscape And Company Profiles

31. Large Language Model (LLM) Observability Platform Market Other Major And Innovative Companies

32. Global Large Language Model (LLM) Observability Platform Market Competitive Benchmarking And Dashboard

33. Key Mergers And Acquisitions In The Large Language Model (LLM) Observability Platform Market

34. Recent Developments In The Large Language Model (LLM) Observability Platform Market

35. Large Language Model (LLM) Observability Platform Market High Potential Countries, Segments and Strategies

36. Appendix

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