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Ai for it operations (aiops) on cloud platforms: Reviews, opportunities and challenges
Artificial Intelligence for IT operations (AIOps) aims to combine the power of AI with the big
data generated by IT Operations processes, particularly in cloud infrastructures, to provide …
data generated by IT Operations processes, particularly in cloud infrastructures, to provide …
Log parsing with prompt-based few-shot learning
Logs generated by large-scale software systems provide crucial information for engineers to
understand the system status and diagnose problems of the systems. Log parsing, which …
understand the system status and diagnose problems of the systems. Log parsing, which …
Automatic root cause analysis via large language models for cloud incidents
Ensuring the reliability and availability of cloud services necessitates efficient root cause
analysis (RCA) for cloud incidents. Traditional RCA methods, which rely on manual …
analysis (RCA) for cloud incidents. Traditional RCA methods, which rely on manual …
Unifying the perspectives of nlp and software engineering: A survey on language models for code
Z Zhang, C Chen, B Liu, C Liao, Z Gong, H Yu… - arxiv preprint arxiv …, 2023 - arxiv.org
In this work we systematically review the recent advancements in software engineering with
language models, covering 70+ models, 40+ evaluation tasks, 180+ datasets, and 900 …
language models, covering 70+ models, 40+ evaluation tasks, 180+ datasets, and 900 …
Llmparser: An exploratory study on using large language models for log parsing
Logs are important in modern software development with runtime information. Log parsing is
the first step in many log-based analyses, that involve extracting structured information from …
the first step in many log-based analyses, that involve extracting structured information from …
Divlog: Log parsing with prompt enhanced in-context learning
Log parsing, which involves log template extraction from semi-structured logs to produce
structured logs, is the first and the most critical step in automated log analysis. However …
structured logs, is the first and the most critical step in automated log analysis. However …
A literature review and existing challenges on software logging practices: From the creation to the analysis of software logs
Software logging is the practice of recording different events and activities that occur within a
software system, which are useful for different activities such as failure prediction and …
software system, which are useful for different activities such as failure prediction and …
Brain: Log parsing with bidirectional parallel tree
Automated log analysis can facilitate failure diagnosis for developers and operators using a
large volume of logs. Log parsing is a prerequisite step for automated log analysis, which …
large volume of logs. Log parsing is a prerequisite step for automated log analysis, which …
Log parsing: How far can chatgpt go?
Software logs play an essential role in ensuring the reliability and maintainability of large-
scale software systems, as they are often the sole source of runtime information. Log …
scale software systems, as they are often the sole source of runtime information. Log …
Robust multimodal failure detection for microservice systems
Proactive failure detection of instances is vitally essential to microservice systems because
an instance failure can propagate to the whole system and degrade the system's …
an instance failure can propagate to the whole system and degrade the system's …