
Statseeker is a powerful network performance monitor solution. It's fast, scalable, and cost-effective.
Statseeker requires only one server or virtual machine to be up and running in minutes. It can also discover your entire network in under an hour without any significant impact on your bandwidth availability.
It can monitor networks of all sizes, polling upto one million interfaces every sixty second, and collecting network data like SNMP, ping, NetFlow (sFlow, and J-Flow), sylog and trap messages, SDN configuration, and health metrics.
Statseeker performance data are never averaged or rolled up. This eliminates the guesswork when it comes to identifying over- and underestimated infrastructure, root cause analysis, capacity planning, and other tasks.
Statseeker's complete data retention means the in-built analytic engine can accurately detect anomalies in performance and forecast network behaviour months in advance. This allows network admins to plan and perform cost-effective, preventative maintenance, instead of fire-fighting problems as they occur.
Statseeker's dashboards and out-of-the box reports allow you to troubleshoot and fix problems in your network before users are aware.
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Log360 is a SIEM or security analytics solution that helps you combat threats on premises, in the cloud, or in a hybrid environment. It also helps organizations adhere to compliance mandates such as PCI DSS, HIPAA, GDPR and more. You can customize the solution to cater to your unique use cases and protect your sensitive data.
With Log360, you can monitor and audit activities that occur in your Active Directory, network devices, employee workstations, file servers, databases, Microsoft 365 environment, cloud services and more. Log360 correlates log data from different devices to detect complex attack patterns and advanced persistent threats. The solution also comes with a machine learning based behavioral analytics that detects user and entity behavior anomalies, and couples them with a risk score. The security analytics are presented in the form of more than 1000 pre-defined, actionable reports. Log forensics can be performed to get to the root cause of a security challenge.
The built-in incident management system allows you to automate the remediation response with intelligent workflows and integrations with popular ticketing tools.
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SolarWinds Log Analyzer
You can quickly and easily examine machine data to identify the root cause of IT problems faster. Log aggregation, filtering, filtering, alerting, and tagging are all part of this intuitive and powerfully designed system. Integrated with Orion Platform products, it allows for a single view of IT infrastructure monitoring logs. Because we have experience as network and system engineers, we can help you solve your problems. Log data is generated by your infrastructure to provide performance insight. Log Analyzer log monitoring tools allow you to collect, consolidate, analyze, and combine thousands of Windows, syslog, traps and VMware events. This will enable you to do root-cause analysis. Basic matching is used to perform searches. You can perform searches using multiple search criteria. Filter your results to narrow down the results. Log monitoring software allows you to save, schedule, export, and export search results.
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Splunk IT Service Intelligence
Safeguard business service-level agreements by utilizing dashboards that enable monitoring of service health, troubleshooting alerts, and conducting root cause analyses. Enhance mean time to resolution (MTTR) through real-time event correlation, automated incident prioritization, and seamless integrations with IT service management (ITSM) and orchestration tools. Leverage advanced analytics, including anomaly detection, adaptive thresholding, and predictive health scoring, to keep an eye on key performance indicators (KPIs) and proactively avert potential issues up to 30 minutes ahead of time. Track performance in alignment with business operations through ready-made dashboards that not only display service health but also visually link services to their underlying infrastructure. Employ side-by-side comparisons of various services while correlating metrics over time to uncover root causes effectively. Utilize machine learning algorithms alongside historical service health scores to forecast future incidents accurately. Implement adaptive thresholding and anomaly detection techniques that automatically refine rules based on previously observed behaviors, ensuring that your alerts remain relevant and timely. This continuous monitoring and adjustment of thresholds can significantly enhance operational efficiency.
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