Best Network Monitoring Software for MongoDB

Transform your network monitoring experience with New Relic's advanced solutions. Effortlessly incorporate SNMP and flow data throughout your system for immediate visibility into performance metrics and traffic trends. Quickly identify anomalies using AI-driven alerts, enhance operational efficiency, and minimize MTTR with insightful data. Designed specifically for large enterprises, New Relic guarantees your network remains effective, dependable, and prepared for any challenge. Discover the benefits of comprehensive, integrated analysis and enhance your IT approach now.

With more than 50,000 customer installations across the five continents, Pandora FMS is a truly all-in-one monitoring solution, covering all traditional silos for specific monitoring: servers, networks, applications, logs, synthetic/transactional, remote control, inventory, etc. Pandora FMS allows you to quickly find and solve problems. It scales them so that they can be derived either from on-premise, multi-cloud, or both. You now have the ability to use your entire IT stack and analytics to solve any problem, even those that are difficult to find. You can control and manage any technology and application with more than 500 plugins, including SAP, Oracle, Lotus or Citrix, Jboss, VMware, AWS and SQL Server.

Sematext Cloud provides all-in-one observability solutions for modern software-based businesses. It provides key insights into both front-end and back-end performance. Sematext includes infrastructure, synthetic monitoring, transaction tracking, log management, and real user & synthetic monitoring. Sematext provides full-stack visibility for businesses by quickly and easily exposing key performance issues through a single Cloud solution or On-Premise.

Better Stack brings all your observability needs under one roof to help you build and ship more reliable software, faster. Handle on-call scheduling, get clear, actionable alerts, and resolve issues quickly – all from a single tool that covers incident response, uptime checks, status pages, log management, and infrastructure monitoring. Designed to scale with your team, Better Stack unifies your alerting and monitoring workflows into a clean, powerful interface that boosts visibility and shortens response times. Key capabilities include an OpenTelemetry-native Kubernetes collector powered by eBPF, instant alerting, and dashboards built for collaboration. Powered by ClickHouse, Better Stack enables rapid-fire queries and seamless ingestion of massive, high-cardinality datasets. It turns your logs into structured, searchable data, giving you the ability to query everything using SQL – just like a single, unified database. With 100+ integrations, it fits right into your existing workflow, no extra effort needed.

Checkmk is an IT monitoring system that allows system administrators, IT managers and DevOps teams, to quickly identify and resolve issues across their entire IT infrastructure (servers and applications, networks, storage and databases, containers, etc. Checkmk is used daily by more than 2,000 commercial customers worldwide and many other open-source users. Key product features * Service state monitoring with nearly 2,000 checks 'outside the box' * Event-based and log-based monitoring * Metrics, dynamic Graphing, and Long-Term Storage * Comprehensive reporting incl. Accessibility and SLAs * Flexible notifications and automated alert handling * Monitoring business processes and complex systems * Software and hardware inventory * Graphical, rule-based configuration and automated service discovery These are the top use cases * Server Monitoring * Network Monitoring * Application Monitoring * Database Monitoring * Storage Monitoring * Cloud Monitoring * Container Monitoring

Enhance your metrics and alerting capabilities using a top-tier open-source monitoring tool. Prometheus inherently organizes all data as time series, which consist of sequences of timestamped values associated with the same metric and a specific set of labeled dimensions. In addition to the stored time series, Prometheus has the capability to create temporary derived time series based on query outcomes. The tool features a powerful query language known as PromQL (Prometheus Query Language), allowing users to select and aggregate time series data in real time. The output from an expression can be displayed as a graph, viewed in tabular format through Prometheus’s expression browser, or accessed by external systems through the HTTP API. Configuration of Prometheus is achieved through a combination of command-line flags and a configuration file, where the flags are used to set immutable system parameters like storage locations and retention limits for both disk and memory. This dual method of configuration ensures a flexible and tailored monitoring setup that can adapt to various user needs. For those interested in exploring this robust tool, further details can be found at: https://ancillary-proxy.atarimworker.io?url=https%3A%2F%2Fsourceforge.net%2Fprojects%2Fprometheus.mirror%2F

NetWatch.ai provides an all-encompassing, AI-powered monitoring and security platform aimed at unifying disparate tools into a cohesive solution tailored for contemporary IT settings. The platform features three main product categories: NetWatch OPS, which delivers real-time monitoring, proactive alerts, and efficient resource management for servers and networks; Secure OPS, a hybrid SIEM that facilitates comprehensive security oversight and compliance for both cloud-based and on-premises systems; and AI OPS, which harnesses machine learning to foresee potential issues, automate resolution processes, and enhance operational efficacy. A unique “AI System Administrator” functions as a virtual operator that oversees customer infrastructures, integrates seamlessly through API with existing workflows, and provides thorough visibility and automation. Additionally, for organizations in need of expert support, NetWatch.ai offers Hive OPS SOC, a tiered Security Operations Center service that includes round-the-clock monitoring, incident response, and various other critical services. This integrated approach not only simplifies management but also significantly strengthens the overall security posture of businesses in an increasingly complex digital landscape.

Centreon is a global provider for business-aware IT monitoring to ensure high performance and continuous operations. The company's AIOps-ready platform, which is holistic and ready for use in today's complex hybrid cloud infrastructures, is designed to meet the needs of these distributed clouds. Centreon monitors all aspects of the IT Infrastructure, from Cloud-to Edge for a clear and comprehensive view. Centreon eliminates blind spots by monitoring all equipment, middleware, and applications that are part modern IT workflows. This includes legacy assets on-premise, private and public clouds, and all the way to edge of the network where smart devices and customers come together to create business value. Centreon is always up-to-date and can support even the most dynamic environments. It has auto-discovery capabilities that allow it to keep track of Software Defined Network (SDN), AWS or Azure cloud assets and Wi-Fi access points, as well as any other component of today’s agile IT infrastructure.

Selector’s software-as-a-service leverages machine learning and natural language processing to deliver self-service analytics that facilitate immediate access to actionable insights, significantly decreasing mean time to resolution (MTTR) by as much as 90%. This innovative Selector Analytics platform harnesses artificial intelligence and machine learning to perform three critical functions, equipping network, cloud, and application operators with valuable insights. It gathers a wide array of data—including configurations, alerts, metrics, events, and logs—from diverse and disparate data sources. For instance, Selector Analytics can extract data from router logs, device performance metrics, or configurations of devices within the network. Upon gathering this information, the system normalizes, filters, clusters, and correlates the data using predefined workflows to generate actionable insights. Subsequently, Selector Analytics employs machine learning-driven data analytics to evaluate metrics and events, enabling automated detection of anomalies. In doing so, it ensures that operators can swiftly identify and address issues, enhancing overall operational efficiency. This comprehensive approach not only streamlines data processing but also empowers organizations to make informed decisions based on real-time analytics.