Best Observability Tools for MongoDB

New Relic’s enterprise Observability software offers a complete platform for gaining in-depth insights into the performance and behavior of your software systems. Built for large-scale environments, our unified data platform aggregates telemetry data across your entire tech stack, providing powerful full-stack analysis tools that offer detailed insights into system behavior, dependencies, and performance. With real-time monitoring, automated alerts, and customizable dashboards, New Relic empowers you to proactively detect and resolve issues, optimize performance, and deliver outstanding customer experiences. Simplify observability, improve operational efficiency, and drive innovation with New Relic’s advanced Observability solutions.

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.

SolarWinds®, AppOptics™, is a SaaS-based infrastructure and application monitoring tool for custom-built on-premises, hybrid, and cloud systems. AppOptics reduces MTTR by allowing quick identification of performance issues across the stack, from the application to the underlying infrastructure down to the line code. AppOptics was designed to be easy to use and set up by IT professionals. It has powerful features that quickly and automatically identify performance issues, eliminating the guesswork and reducing the time spent on troubleshooting. AppOptics allows you to align infrastructure and performance objectives with business objectives.

Open-source monitoring solutions are able to power your alerting and metrics. Prometheus stores all data in time series. These are streams of timestamped value belonging to the same metric with the same labeled dimensions. Prometheus can also generate temporary derived times series as a result of queries. Prometheus offers a functional query language called PromQL, which allows the user to select and aggregate time series data real-time. The expression result can be displayed as a graph or tabular data in Prometheus’s expression browser. External systems can also consume the HTTP API. Prometheus can be configured using command-line flags or a configuration file. The command-line flags can be used to configure immutable system parameters such as storage locations and the amount of data to be kept on disk and in memory. . Download: https://sourceforge.net/projects/prometheus.mirror/

The most widely used observability platform, built on the ELK Stack, is the best choice. It converges silos and delivers unified visibility and actionable insight. All your observability data must be in one stack to effectively monitor and gain insight across distributed systems. Unify all data from the application, infrastructure, user, and other sources to reduce silos and improve alerting and observability. Unified solution that combines unlimited telemetry data collection with search-powered problem resolution for optimal operational and business outcomes. Converge data silos with the ingesting of all your telemetry data from any source, in an open, extensible and scalable platform. Automated anomaly detection powered with machine learning and rich data analysis can speed up problem resolution.

Troubleshoot performance issues and errors in your microservices. Correlate root cause across traces, metrics, and logs. Aspecto's built-in remote sampler will reduce your OpenTelemetry trace costs. The way OTel data has been visualized can impact your ability to troubleshoot. With the best-in class visualization, you can go from a high level overview to every last detail. Correlate logs with traces. With one click, you can switch from logs to their corresponding traces. Never lose context again and resolve issues faster. Search your trace data using filters, groups, and free-text search to quickly pinpoint the problem. Reduce your costs by only sampling the data that you need. Sample traces according to languages, libraries and routes. Set data privacy rules for sensitive fields to be hidden within trace data or specific routes. Connect your everyday tools to your workflow. Logs, error tracking, external events API and more.

LogIQ.AI's LogFlow allows you to centrally manage your observability data pipes. Data streams are automatically organized and optimized as they arrive for your business teams or knowledge workers. XOps teams can centralize the management of data flows, increase data quality, and relevance. LogFlow's InstaStore, which can be built on any object store allows for infinite data retention and data replay to any target observation platform of your choosing. Analyze operational metrics across applications, infrastructure and gain actionable insight that will help you scale with confidence and maintain high availability. By analyzing and collecting behavioral data from business systems, you can help your business make better business decisions and provide better user experiences. Don't let new attack techniques catch you off guard. Automate threat prevention and remediation by automating the detection and analysis of threat patterns from multiple sources.

DX Unified Infrastructure Management is unique in that it offers an open architecture, full stack observability, zero-touch configuration, and an open architecture for monitoring traditional, hybrid, and public cloud infrastructure environments. This solution is designed to provide an excellent end-user experience. It provides a modern HTML5 operations console which makes it easy for IT teams to implement and use the solution quickly. This reduces time to value. DX Unified Infrastructure Management provides actionable insight for cloud environments such as AWS or Azure and modern architectures associated cloud services such as Nutanix and Hadoop, Mongo and Apache. It combines deep domain expertise across hybrid cloud infrastructure elements to drive digital transformation, automation and innovation. Automatically detect devices based upon their properties and then automatically set policies for each type of device and deploy configurations and alarm policy as required.