Search Results for "correlation"
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Showing 14 open source projects for "correlation"
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Plaso
Super timeline all the things
Plaso (Plaso Langar Að Safna Öllu), or "super timeline all the things," is a Python-based engine designed for automatic creation of timelines in digital forensic investigations. It processes various log files and artifacts to generate a chronological sequence of events, aiding analysts in understanding system activities. -
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Grafana k6 Studio
Desktop application for Mac, Windows, and Linux
...The software converts these recordings into executable k6 scripts without requiring manual JavaScript programming. Users can customize generated scripts through predefined rules, correlation handling, and custom JavaScript. It provides configuration options for test scenarios and load profiles. A built-in validator executes test scripts and displays requests, responses, logs, and checks for troubleshooting. Available for Windows, macOS, and Linux, k6 Studio helps developers and quality assurance engineers create, validate, and maintain performance tests through an interactive interface. -
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Sysdig Inspect
A powerful opensource interface for container troubleshooting
Sysdig Inspect is a powerful opensource interface for container troubleshooting and security investigation. Inspect's user interface is designed to intuitively navigate the data-dense sysdig captures that contain granular system, network, and application activity of a Linux system. Sysdig Inspect helps you understand trends, correlate metrics and find the needle in the haystack. It comes packed with features designed to support both performance and security investigations, with deep... -
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Brave
Java distributed tracing implementation compatible with Zipkin backend
...This repository includes dependency-free Java libraries and instrumentation for common components used in production services. For example, this includes trace filters for Servlet and log correlation for Apache Log4J. Brave's dependency-free tracer library works against JRE6+. This is the underlying api that instrumentation use to time operations and add tags that describe them. This library also includes code that parses X-B3-TraceId headers. -
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Go gRPC Middleware
Golang gRPC Middlewares: interceptor chaining, auth, logging, retries
...Especially for observability signals (logging, tracing, metrics) interceptors offer semi-auto-instrumentation that improves the consistency of your observability and allows great correlation techniques (e.g. exemplars and trace ID in logs). Demo-ed in examples. This repository offers ready-to-use middleware that implements gRPC interceptors with examples. In some cases, dedicated projects offer great interceptors, so this repository skips those, and we link them in the interceptors list. -
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Measurements.jl
Error propagation calculator and library for physical measurements
Error propagation calculator and library for physical measurements. It supports real and complex numbers with uncertainty, arbitrary precision calculations, operations with arrays, and numerical integration. Physical measures are typically reported with an error, a quantification of the uncertainty of the accuracy of the measurement. Whenever you perform mathematical operations involving these quantities you have also to propagate the uncertainty, so that the resulting number will also have... -
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Deequ
Deequ is a library built on top of Apache Spark
Deequ is a library built atop Apache Spark that enables defining “unit tests for data” — that is, formal constraints or checks on datasets to ensure data quality along dimensions such as completeness, uniqueness, value ranges, correlations, etc. It can scale to large datasets (billions of rows) by translating those data checks into Spark jobs. Deequ supports advanced features like a metrics repository for storing computed statistics over time, anomaly detection of data quality metrics, and... -
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Bootstrap.jl
Statistical bootstrapping library for Julia
Bootstrapping is a widely applicable technique for statistical estimation. -
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NodeBrain
Rule Engine for State and Event Monitoring
NodeBrain is a rule engine for construction of state and event monitoring applications. It interacts with other monitoring components to perform simple element state monitoring or complex event correlation based on user specified rules. It is extended through the development of node modules (plug-ins) using NodeBrain's C API, and servants (programs written in any language) that interact with the rule engine via stdin, stdout, and stderr. The package includes a small set of plug-in modules to provide capabilities typically required for monitoring applications. -
Build Securely on AWS with Proven FrameworksMoving to the cloud brings new challenges. How can you manage a larger attack surface while ensuring great network performance? Turn to Fortinet’s Tested Reference Architectures, blueprints for designing and securing cloud environments built by cybersecurity experts. Learn more and explore use cases in this white paper.
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math toolkit
A C++ and Python library for finance, statistics and linear algebra.
...Finance features include compound rate present/future value, annuity, various present/future value coefficients ... Statistics features include mean, median, variance, standard deviation, covariance, correlation, linear regression, probabilities and random variates of various distributions ... Linear algebra features include matrix arithmetic, inverse, determinant, rank, linear system solution, lu/qr decomposition, svd, eigen values/vectors ... And some auxiliary features like random number generators, equation solution, numerical integration, permutation/combination and gcd/lcm etc. ... -
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...The latest version supports named fields in the STL files for tagging data parsed in the Prefix Tree and anonymous functions for parsing dynamic message payloads. We now output JSON objects and I'm working on HBase integration. By outputting to JSON it also leaves open the possibility for on the fly in memory correlation between events. Read the included README before starting, it has a quick start guide and info on the constructors.
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The Panopticode project provides a standardized format for describing the structure of software projects and integrates metrics from several tools into that format. Reporting options provide correlation, historic analysis, and visualization.
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Program to performing the complete cycle of neural networks analysis: preparing data, choosing neural network (CasCor, MP, LogRegression, PNN), learning of network, monitoring learning state, ROC-analysis, optimization of network parameters using GA.
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OpenESM project to promote software development of enterprise systems management. Focus areas are (Performance and Availability, Configuration Management, Data Warehousing, Reporting and Correlation).
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