Graph and download economic data for Producer Price Index by Industry: Logging (PCU11331133) from Dec 1981 to Jun 2025 about logging, PPI, industry, inflation, price index, indexes, price, and USA.

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Log Management Market Size 2025-2029

The log management market size is forecast to increase by USD 3.23 billion at a CAGR of 14.6% between 2024 and 2029.

The market is experiencing significant growth, driven primarily by the increasing demand from the IT sector for enhanced security and compliance. With the integration of advanced technologies such as artificial intelligence (AI) and machine learning (ML) into log management solutions, organizations are better equipped to analyze vast amounts of data and gain actionable insights. However, this market is not without its challenges. The high deployment costs associated with implementing these sophisticated solutions can be a barrier for entry for some organizations, particularly smaller businesses. Despite this hurdle, the long-term benefits of log management, including improved security, regulatory compliance, and operational efficiency, make it a worthwhile investment for businesses seeking to capitalize on market opportunities and navigate challenges effectively. Companies looking to succeed in this market must stay abreast of emerging technologies and trends while also addressing the cost concerns of potential customers. By doing so, they can differentiate themselves and position themselves as trusted partners to their clients.

What will be the Size of the Log Management Market during the forecast period?

Request Free SampleLog management is a critical aspect of modern business operations, with the market exhibiting significant growth and trends. Log data, including alerts, archives, pipelines, notifications, reports, repositories, forwarders, dashboards, and various performance and cost considerations, plays a pivotal role in ensuring log data's availability, integrity, scalability, security, and compliance. Log data performance and cost are essential factors driving market growth. Log data privacy and masking are becoming increasingly important due to heightened concerns over data security and regulatory compliance. Log data governance and integrity are also key considerations, with organizations seeking to implement effective log data management solutions. Log data security is a major concern, with encryption, redaction, and masking essential for protecting sensitive information. Log event correlation and anomaly detection are critical for identifying and addressing security threats. Log data warehouses and sinks enable organizations to store and analyze log data at scale, while log correlation rules and sinks facilitate efficient log data processing. Log data management solutions must be scalable, secure, and cost-effective to meet the evolving needs of businesses. Market leaders are focusing on developing innovative solutions to address these challenges, including advanced log data analytics, automation, and machine learning capabilities. The market dynamics are influenced by various factors, including increasing data volumes, growing regulatory requirements, and the need for real-time log data analysis. As businesses continue to generate vast amounts of log data, effective log management solutions will become increasingly valuable for ensuring data security, compliance, and operational efficiency.

How is this Log Management Industry segmented?

The log management industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD million' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments. ComponentSolutionServicesDeploymentOn-premisesCloud-basedConsumerLarge enterprisesSMEsEnd-userIT and ITeSBFSIEducationHealthcareTelecomGeographyNorth AmericaUSCanadaEuropeFranceGermanyUKAPACChinaIndiaJapanSouth KoreaSouth AmericaBrazil

By Component Insights

The solution segment is estimated to witness significant growth during the forecast period.The market is segmented into solutions and services based on components. The solution sector is expected to lead the market due to the increasing demand for cost-effective management solutions that enhance SME productivity and ensure security. Log management solutions are utilized by businesses to manage various types of logs, including application, security, and system logs. These logs help identify different events, such as alerts, errors, audit failures, and success information. Moreover, the implementation of compliance regulations, such as PCI DSS, necessitates the use of log management systems to ensure data security and privacy. Log management software enables organizations to collect, retain, and enrich logs using techniques like log normalization, filtering, and parsing. Log data is then analyzed using artificial intelligence, machine learning, and security analytics to detect anomalies and potential threats. Log management solutions also offer features like log indexing, log correlation, and real-time logging to facilitate incident mana

The Geophysical Borehole Log index provides details of all digital geophysical logs available to BGS. The database provides the borehole metadata related to logging and metadata for the logging itself and log data stored in a proprietary hierarchical database system (PETRIS RECALL). Contains most digital geophysically logged bores known to BGS National Geological Records Centre. Scattered distribution of boreholes, locally dense coverage, relatively few logs from Scotland & Central Wales, increasing data density on UK continental Shelf.

Canada Raw Materials Price Index: Logs, Pulpwood, Natural Rubber & Other Forestry Products data was reported at 118.900 2010=100 in Sep 2020. This records an increase from the previous number of 117.100 2010=100 for Aug 2020. Canada Raw Materials Price Index: Logs, Pulpwood, Natural Rubber & Other Forestry Products data is updated monthly, averaging 110.000 2010=100 from Jan 2010 (Median) to Sep 2020, with 129 observations. The data reached an all-time high of 131.200 2010=100 in Apr 2019 and a record low of 98.000 2010=100 in Jul 2010. Canada Raw Materials Price Index: Logs, Pulpwood, Natural Rubber & Other Forestry Products data remains active status in CEIC and is reported by Statistics Canada. The data is categorized under Global Database’s Canada – Table CA.I021: Raw Materials Price Index: 2010=100.

United States - Indexes of Aggregate Weekly Hours of All Employees, Mining and Logging was 87.30000 Index 2007=100 in April of 2025, according to the United States Federal Reserve. Historically, United States - Indexes of Aggregate Weekly Hours of All Employees, Mining and Logging reached a record high of 129.40000 in August of 2014 and a record low of 73.90000 in February of 2021. Trading Economics provides the current actual value, an historical data chart and related indicators for United States - Indexes of Aggregate Weekly Hours of All Employees, Mining and Logging - last updated from the United States Federal Reserve on July of 2025.

A complete list of live websites using the log technology, compiled through global website indexing conducted by WebTechSurvey.

United States - Indexes of Aggregate Weekly Payrolls of All Employees, Mining and Logging was 140.90000 Index 2007=100 in June of 2025, according to the United States Federal Reserve. Historically, United States - Indexes of Aggregate Weekly Payrolls of All Employees, Mining and Logging reached a record high of 157.80000 in August of 2014 and a record low of 82.30000 in March of 2006. Trading Economics provides the current actual value, an historical data chart and related indicators for United States - Indexes of Aggregate Weekly Payrolls of All Employees, Mining and Logging - last updated from the United States Federal Reserve on July of 2025.

Graph and download economic data for Producer Price Index by Commodity: Lumber and Wood Products: Logs, Bolts, Timber and Pulpwood (WPU08510502) from Dec 2011 to Jun 2025 about logging, wood, commodities, PPI, inflation, price index, indexes, price, and USA.

United States - Producer Price Index by Commodity: Lumber and Wood Products: Logs, Bolts, Timber, Pulpwood and Wood Chips was 262.25600 Index 1982=100 in June of 2025, according to the United States Federal Reserve. Historically, United States - Producer Price Index by Commodity: Lumber and Wood Products: Logs, Bolts, Timber, Pulpwood and Wood Chips reached a record high of 278.75900 in July of 2022 and a record low of 90.60000 in February of 1986. Trading Economics provides the current actual value, an historical data chart and related indicators for United States - Producer Price Index by Commodity: Lumber and Wood Products: Logs, Bolts, Timber, Pulpwood and Wood Chips - last updated from the United States Federal Reserve on July of 2025.

United States - Indexes of Aggregate Weekly Payrolls of Production and Nonsupervisory Employees, Mining and Logging was 245.10000 Index 2002=100 in April of 2025, according to the United States Federal Reserve. Historically, United States - Indexes of Aggregate Weekly Payrolls of Production and Nonsupervisory Employees, Mining and Logging reached a record high of 266.70000 in August of 2014 and a record low of 9.80000 in February of 1950. Trading Economics provides the current actual value, an historical data chart and related indicators for United States - Indexes of Aggregate Weekly Payrolls of Production and Nonsupervisory Employees, Mining and Logging - last updated from the United States Federal Reserve on July of 2025.

This repository contains synthetic log data suitable for evaluation of intrusion detection systems. The logs were collected from a testbed that was built at the Austrian Institute of Technology (AIT) following the approaches by [1], [2], and [3]. Please refer to these papers for more detailed information on the dataset and cite them if the data is used for academic publications. Other than the related AIT-LDSv1.1, this dataset involves a more complex network structure, makes use of a different attack scenario, and collects log data from multiple hosts in the network. In brief, the testbed simulates a small enterprise network including mail server, file share, WordPress server, VPN, firewall, etc. Normal user behavior is simulated to generate background noise. After some days, two attack scenarios are launched against the network. Note that the AIT-LDSv2.0 extends this dataset with additional attack cases and variations of attack parameters.

The archives have the following structure. The gather directory contains the raw log data from each host in the network, as well as their system configurations. The labels directory contains the ground truth for those log files that are labeled. The processing directory contains configurations for the labeling procedure and the rules directory contains the labeling rules. Labeling of events that are related to the attacks is carried out with the Kyoushi Labeling Framework.

Each dataset contains traces of a specific attack scenario:

• Scenario 1 (see gather/attacker_0/logs/sm.log for detailed attack log):
  • nmap scan
  • WPScan
  • dirb scan
  • webshell upload through wpDiscuz exploit (CVE-2020-24186)
  • privilege escalation
• Scenario 2 (see gather/attacker_0/logs/dnsteal.log for detailed attack log):
  • DNSteal data exfiltration

The log data collected from the servers includes

• Apache access and error logs (labeled)
• audit logs (labeled)
• auth logs (labeled)
• VPN logs (labeled)
• DNS logs (labeled)
• syslog
• suricata logs
• exim logs
• horde logs
• mail logs

Note that only log files from affected servers are labeled. Label files and the directories in which they are located have the same name as their corresponding log file in the gather directory. Labels are in JSON format and comprise the following attributes: line (number of line in corresponding log file), labels (list of labels assigned to that log line), rules (names of labeling rules matching that log line). Note that not all attack traces are labeled in all log files; please refer to the labeling rules in case that some labels are not clear.

Acknowledgements: Partially funded by the FFG projects INDICAETING (868306) and DECEPT (873980), and the EU project GUARD (833456).

If you use the dataset, please cite the following publications:

[1] M. Landauer, F. Skopik, M. Wurzenberger, W. Hotwagner and A. Rauber, "Have it Your Way: Generating Customized Log Datasets With a Model-Driven Simulation Testbed," in IEEE Transactions on Reliability, vol. 70, no. 1, pp. 402-415, March 2021, doi: 10.1109/TR.2020.3031317.

[2] M. Landauer, M. Frank, F. Skopik, W. Hotwagner, M. Wurzenberger, and A. Rauber, "A Framework for Automatic Labeling of Log Datasets from Model-driven Testbeds for HIDS Evaluation". ACM Workshop on Secure and Trustworthy Cyber-Physical Systems (ACM SaT-CPS 2022), April 27, 2022, Baltimore, MD, USA. ACM.

[3] M. Frank, "Quality improvement of labels for model-driven benchmark data generation for intrusion detection systems", Master's Thesis, Vienna University of Technology, 2021.

The Geophysical Borehole Log index provides details of hardcopy geophysical logs known to BGS. The index provides the storage location of the logs and details of the format they are available in, eg. paper, at a scale of 1:200. The data is updated when new data becomes available. Contains most geophysically logged bores known to BGS National Geological Records Centre. Scattered distribution of boreholes, locally dense coverage, few logs from Scotland.

Graph and download economic data for Export Price Index (End Use): Logs and Lumber (IQ13100) from Dec 1992 to Jun 2025 about end use, logging, wood, exports, price index, indexes, price, and USA.

This layer of the map based index (GeoIndex) shows the location of onshore UK boreholes known to BGS that have digital or paper geophysical borehole logs. The details given for each borehole are, the name of the borehole, the grid reference and the format, ie. paper or digital. Scattered distribution of boreholes, locally dense coverage, few logs from Scotland. The GeoIndex is updated at regular intervals but more information may be available than is shown at any one time.

In 2023, the producer price index of logging in Vietnam amounted to approximately 172.02 index points, indicating an increase from the previous year. In that year, the country's producer price index was at 168.91 points.

PPI: Mining: EO: NM: SQ: CL: Primary Product data was reported at 333.800 Dec1983=100 in Mar 2020. This records an increase from the previous number of 333.100 Dec1983=100 for Feb 2020. PPI: Mining: EO: NM: SQ: CL: Primary Product data is updated monthly, averaging 154.750 Dec1983=100 from Dec 1983 (Median) to Mar 2020, with 436 observations. The data reached an all-time high of 333.800 Dec1983=100 in Mar 2020 and a record low of 100.000 Dec1983=100 in Dec 1983. PPI: Mining: EO: NM: SQ: CL: Primary Product data remains active status in CEIC and is reported by Bureau of Labor Statistics. The data is categorized under Global Database’s United States – Table US.I044: Producer Price Index: By Industry: Logging, Mining, Utilities, & Construction.

PPI: Mining: EO: NM: SC: Kaolin & Ball Clay data was reported at 249.537 Jun1984=100 in Dec 2022. This stayed constant from the previous number of 249.537 Jun1984=100 for Nov 2022. PPI: Mining: EO: NM: SC: Kaolin & Ball Clay data is updated monthly, averaging 121.300 Jun1984=100 from Jun 1984 (Median) to Dec 2022, with 463 observations. The data reached an all-time high of 249.537 Jun1984=100 in Dec 2022 and a record low of 99.300 Jun1984=100 in Oct 1984. PPI: Mining: EO: NM: SC: Kaolin & Ball Clay data remains active status in CEIC and is reported by U.S. Bureau of Labor Statistics. The data is categorized under Global Database’s United States – Table US.I: Producer Price Index: by Industry: Logging and Mining.

Slovakia Exports Price Index: Forestry and Logging data was reported at 135.595 2010=100 in Dec 2017. This records an increase from the previous number of 135.411 2010=100 for Nov 2017. Slovakia Exports Price Index: Forestry and Logging data is updated monthly, averaging 117.062 2010=100 from Jan 2012 (Median) to Dec 2017, with 72 observations. The data reached an all-time high of 135.595 2010=100 in Dec 2017 and a record low of 107.383 2010=100 in Jan 2012. Slovakia Exports Price Index: Forestry and Logging data remains active status in CEIC and is reported by Statistical Office of the Slovak Republic. The data is categorized under Global Database’s Slovakia – Table SK.I026: Exports Price Index: Classification of Products by Activity. Rebased from 2010=100 to 2015=100 Replacement series ID: 402622137

A complete list of live websites using the Debug Log Manager technology, compiled through global website indexing conducted by WebTechSurvey.

United States - Producer Price Index by Commodity: Lumber and Wood Products: Logs, Bolts, Timber and Pulpwood was 110.32700 Index Dec 2011=100 in June of 2025, according to the United States Federal Reserve. Historically, United States - Producer Price Index by Commodity: Lumber and Wood Products: Logs, Bolts, Timber and Pulpwood reached a record high of 118.22800 in July of 2022 and a record low of 100.00000 in December of 2011. Trading Economics provides the current actual value, an historical data chart and related indicators for United States - Producer Price Index by Commodity: Lumber and Wood Products: Logs, Bolts, Timber and Pulpwood - last updated from the United States Federal Reserve on July of 2025.