Application: DBALite Oracle Database Performance Summary App Application Purpose: Provide Oracle host and database performance info suitable for non-dbas. Target users are Non-dba performance engineers, testers, prod support staff and application team members who want to proactively and reactively monitor their databases. Licensing: Because this App queries the dba_hist_sqlstat AWR data, a license must exist for the Oracle Diagnostic Pack. Most facilities running Oracle databases have this license. Application Basic Structure: Four stored procedures run in the Oracle database. They read performance data tables and write it out to datafiles which are consumed by Splunk. Oracle Scheduler jobs execute the stored procedures at configurable intervals. The app also uses the Splunk Add-on for Unix and Linux to get host metrics. Dependencies: Splunk Add-on for Unix and Linux (http://docs.splunk.com/Documentation/UnixAddOn/latest/User/InstalltheSplunkAdd-onforUnixandLinux) Stored procedures and scheduler jobs running in Oracle Database 11.1 or higher (procedures scripts included in the setup files.) Index creation: Splunk Add-on For Unix and Linux will create the 'unix_metrics' index. This DBALite app will create the 'database' index. Sourcetypes: om:oracle:locks -- snapshot information about blocking locks om:oracle:memory -- Oracle sga and pga memory statistics om:oracle:osstat -- Operating System stats from v$osstat table om:oracle:sql -- top resource consuming sqls from dba_hist_sqlstat om:oracle:sqltext -- sqltext for the top resource consuming sqls om:oracle:sysevent -- wait event information om:oracle:sysstat -- performance statistics from v$sysstat table Installation: Oracle Setup: Copy all the sql scripts from the Oracle_Performance_Summary_For_Splunk/bin directory to your database server or run them in SQL Developer or other tool. Connect to your database. As sysdba, create the splunk sch_spl user. (Sysdba is required for this one script in order to grant privileges on DBMS_LOCK and UTL_FILE: @cr_sch_spl.sql Create a unix directory where you want Oracle to write the output files. Splunk will pick up the data from these output files created by the stored procedures. If the owner of the directory is not the ORACLE user, then make the ORACLE user a member of the Unix group for the directory so that Oracle can write to the directory. Make the permissions on the directory 774. Note: For a RAC database, just create the directory on one node. The app is not elaborate enough to provide failover capabilities, so in case of an outage of its node, the data would just not be written until the node came back online. Create an Oracle Directory called 'DIR_SPLUNK' using the above unix directory. Example: CREATE DIRECTORY dir_splunk as '/u01/perf/dbdashboard/data'; grant read,write on directory dir_splunk to sch_spl; As the splunk user SCH_SPL, create the stored procedures and scheduler jobs that will run them: @cr_procs_and_jobs.sql After 10 minutes, check the data files to confirm there is data being written to them. These data files should exist: dbd_locks.txt dbd_memory.txt dbd_osstat.txt dbd_sysevents.txt dbd_sysstat.txt dbd_top_sql_text.txt dbd_top_sql.txt To check the scheduler jobs, as SCH_SPL user, execute: 'SELECT job_name, actual_start_date, status, additional_info from user_scheduler_job_run_details order by actual_start_date;'

A monitoring plugin for icinga/nagios/nsca, that reports basic system metrics of a linux host: cpu, load, threads, openfiles, procs, diskio, disku, memory, swap, network

A MySQL plugin to export linux performance metrics as status variables, including CPU/network/memory/disk space/disk IO, also some metrics of InnoDB internal data structure.

Ansible Role to install CloudWatchMonitoringScripts and Monitor Memory and Disk Metrics for Amazon EC2 Linux Instances

a .NET Core library designed to track process resource usage (CPU, memory, and more) over specified intervals. It allows you to store collected metrics in various formats, including JSON and CSV, facilitating easy monitoring and analysis of application performance. It works on Windows, macOs and Linux.

Collects Linux memory metrics from /proc/meminfo

Cross-platform system metrics collector - Gathers CPU, memory, disk usage & uptime on Windows/macOS/Linux with automatic server backup. Uses psutil when available, falls back to native OS commands.

Beowulf Clustering is formed with regular computers, sharing paralleling process among them, thus are scalable performance cluster wich can be ussed as data mining, data processing, internet server. In each of these computer are installed a open software linux distribuiton arranged into a dedicate lan area network, coneccted with a mesh swicht with fastethernet . While Beowulf are used to develop parallel programming it has to be monitored to maintain efficient infrastructure and troubleshooting in cluster system. Thus, monitoring is fundamental not only to software operations but to optimize system. The implementation of monitoring dashboard and configuration of software streaming tool require the identification of the network parameters, wich is done using linuxs networking mapping open tools. Thus a remote SSH client ussing settings, like tunneling and port fowarding can manage cluster. This work is motivated by monitoring real-time metrics of memory usage, cpu thermal, fan speed, networking bandwidth, disk write rate, remotely from outside of localhost network. display those actions in a same monitoring and by troubleshooting directives thus dashboard can be used for watching entire systems, maintaining health and performance of systems services and applications.

These scripts automate the collection and publishing of custom metrics for Amazon EC2 instances running on Windows and Linux operating systems. They are IMDSv2 enabled and provide an easy way to collect and publish custom metrics to CloudWatch, including automatic creation of alarms with thresholds of 75% and 90% for Memory and Disk metrics.

Monitoring Memory and Disk Metrics for Amazon EC2 Linux Instances

RAM usage, and 53 other memory-related metrics on Linux systems.

Custom metrics plugin for mackerel-agent to get available memory on Linux.

Script to automate the installation of "Monitoring Memory and Disk Metrics for Amazon EC2 Linux Instances" script from AWS.

Per-process statistics (taskstats) from the Linux kernel for .NET Core and Mono for x64, arm, and arm64. The metrics include CPU Usage, counters and delays caused by IO, swap-in, memory reclaim, and memory trashing.

PyLinuxGuard: Linux System Behavior Monitoring & Anomaly Detection | A Python tool to monitor Linux system metrics like CPU, memory, and network usage. It detects anomalies based on historical data and sends email alerts when something unusual is detected.

A Linux-based system monitoring toolkit that provides real-time reports on CPU, GPU, memory, disk usage, and system metrics. It supports HTML report generation, optional graphical interface (GUI), and Docker containerization. Advanced features include optional Python-based charts and InfluxDB integration for time-series data storage.

A lightweight Node.js linux server monitoring API that provides real-time system metrics (CPU monitoring, memory monitoring, disk used percentage, system load) with systemd integration. 一个轻量级的实时 linux 服务器系统监控指标（CPU 监控、内存监控、存储已用百分比、负载）的 API 服务，支持 systemd 服务管理。

Sending AWS EC2 Linux Instances Memory and Disk Metrics to CloudWatch

How accurate is Linux's MemUsed compared to MemTotal - MemAvailable?

Create and send custom metric data for disk and memory util on EC2 Linux instances

This Web API in its first phase, tries to provide the metrics of a Linux system of CPU, Memory and Disks.

Ultra-lightweight Linux system monitor with CPU/memory/disk/GPU metrics, SQLite history tiers, and a built-in Flask dashboard/API.

A short, framework-agnostic PHP status agent that exposes a /status JSON endpoint with Linux host metrics (uptime, load, CPU, memory, swap and disk).

Ansible playbook to collect Linux server performance metrics (CPU, memory, disk, processes, users) and generate a clean HTML report — simple, agentless, no Prometheus/Grafana required.

It installs AWS monitoring scripts for Amazon CloudWatch. These sample Perl scripts comprise a fully functional example that reports memory, swap, and disk space utilization metrics for an EC2 Linux instance.

A Bash script that analyzes and displays essential server performance statistics on Linux systems, including CPU usage, memory usage, disk usage, top processes, and additional metrics like OS version, uptime, and failed login attempts.

This project involves setting up a comprehensive system health monitoring dashboard for Linux servers using Grafana and Prometheus. The goal is to monitor key metrics (CPU), memory, disk, and network usage), configure alerts for high resource utilization, and provide a user-friendly real-time dashboard.

Develop a script that monitors the health of a Linux system. It should check CPU usage, memory usage, disk space, and running processes. If any of these metrics exceed predefined thresholds (e.g., CPU usage > 80%), the script should send an alert to the console or a log file.

This agent provides extended memory metrics based on /proc/meminfo on linux kernels. The provided metrics are : MemTotal: MemFree: Buffers: Cached: SwapCached: Active: Inactive: HighTotal: HighFree: LowTotal: LowFree: SwapTotal: SwapFree: Dirty: Writeback: AnonPages: Mapped: Slab: SReclaimable: SUnreclaim: PageTables: NFS_Unstable: Bounce: CommitLimit: Committed_AS: VmallocTotal: VmallocUsed: VmallocChunk: HugePages_Tot HugePages_Fre HugePages_Rsv Hugepagesize: Prerequisites: Kernel 2.6 (both x86 and x64)   Implementation: * Standard SP Studio packages, ready to install * SP Studio sources

A Linux-based project in C that implements CPU scheduling (HPF, SRTN, RR) and buddy memory allocation. It manages process execution using IPC, tracks performance metrics, and dynamically allocates memory.