Alternatives to InsightFinder

Around 25 million engineers work across dozens of distinct functions. Engineers are using New Relic as every company is becoming a software company to gather real-time insight and trending data on the performance of their software. This allows them to be more resilient and provide exceptional customer experiences. New Relic is the only platform that offers an all-in one solution. New Relic offers customers a secure cloud for all metrics and events, powerful full-stack analytics tools, and simple, transparent pricing based on usage. New Relic also has curated the largest open source ecosystem in the industry, making it simple for engineers to get started using observability.

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.

Splunk Enterprise delivers an end-to-end platform for security and observability, powered by real-time analytics and machine learning. By unifying data across on-premises systems, hybrid setups, and cloud environments, it eliminates silos and gives organizations full visibility. Teams can search and analyze any type of machine data, then visualize insights through customizable dashboards that make complex information clear and actionable. With Splunk AI and advanced anomaly detection, businesses can predict, prevent, and respond to risks faster than ever. The platform also includes powerful streaming capabilities, turning raw data into insights in milliseconds. Built-in scalability allows enterprises to ingest data from thousands of sources at terabyte scale, ensuring reliability at any growth stage. Customers worldwide use Splunk to reduce incident response time, cut operational costs, and drive better outcomes. From IT to security to business resilience, Splunk transforms data into a strategic advantage.

IT performance monitoring does not just focus on monitoring CPU, memory, and network resources. eG Enterprise makes the user experience the center of your IT management and monitoring strategy. eG Enterprise allows you to measure the digital experience of your users and get deep visibility into the performance of the entire application delivery chain -- from code to user experiences to data center to cloud -- all from a single pane. You can also correlate performance across domains to pinpoint the root cause of problems proactively. eG Enterprise's machine learning and analytics capabilities enable IT teams to make smart decisions about right-sizing and optimizing for future growth. The result is happier users, increased productivity, improved IT efficiency, and tangible business ROI. eG Enterprise can be installed on-premise or as a SaaS service. Get a free trial of eG Enterprise today.

Edge Delta is a new way to do observability. We are the only provider that processes your data as it's created and gives DevOps, platform engineers and SRE teams the freedom to route it anywhere. As a result, customers can make observability costs predictable, surface the most useful insights, and shape your data however they need. Our primary differentiator is our distributed architecture. We are the only observability provider that pushes data processing upstream to the infrastructure level, enabling users to process their logs and metrics as soon as they’re created at the source. Data processing includes: * Shaping, enriching, and filtering data * Creating log analytics * Distilling metrics libraries into the most useful data * Detecting anomalies and triggering alerts We combine our distributed approach with a column-oriented backend to help users store and analyze massive data volumes without impacting performance or cost. By using Edge Delta, customers can reduce observability costs without sacrificing visibility. Additionally, they can surface insights and trigger alerts before data leaves their environment.

Epsagon allows teams to instantly visualize, understand, and optimize their microservice architectures. With our unique lightweight auto-instrumentation, gaps in data and manual work associated with other APM solutions are eliminated, providing significant reductions in issue detection, root cause analysis and resolution times. Epsagon can increase development speed and reduce application downtime.

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.

IBM Instana sets the benchmark for incident prevention, offering comprehensive full-stack visibility with one-second precision and a notification time of just three seconds. In the current landscape of rapidly evolving and intricate cloud infrastructures, the financial repercussions of an hour of downtime can soar into the six-figure range or more. Conventional application performance monitoring (APM) tools often fall short, lacking the speed and depth required to effectively address and contextualize technical issues, and they usually necessitate extensive training for super users before they can be utilized effectively. In contrast, IBM Instana Observability transcends the limitations of standard APM tools by making observability accessible to a wider audience, enabling individuals from DevOps, SRE, platform engineering, ITOps, and development teams to obtain the necessary data and context without barriers. The Instana Dynamic APM functions through a specialized agent architecture, utilizing sensors—automated, lightweight programs specifically designed to monitor particular entities and ensure optimal performance. As a result, organizations can respond to incidents proactively and maintain a higher level of service continuity.

All data sources, including topology, monitoring, change, and observation tools, are aggregated. BigPanda's Open Box Machine Learning will combine the data into a limited number of actionable insights. This allows incidents to be detected as they occur, before they become outages. Automatically identifying the root cause of problems can speed up incident and outage resolution. BigPanda identifies both root cause changes and infrastructure-related root causes. Rapidly resolve outages and incidents. BigPanda automates the incident response process, including ticketing, notification, tickets, incident triage, and war room creation. Integrating BigPanda and enterprise runbook automation tools will accelerate remediation. Every company's lifeblood is its applications and cloud services. Everyone is affected when there is an outage. BigPanda consolidates AIOps market leadership with $190M in funding and a $1.2B valuation

You've adopted cloud architecture, yet its intricate nature poses challenges for effective monitoring. The IBM Cloud Monitoring service offers a fully managed solution designed specifically for administrators, DevOps teams, and developers alike. Anticipate in-depth visibility into containers and an array of comprehensive metrics. By utilizing this service, you can lower costs while empowering your DevOps teams and improving the management of the software lifecycle. Set up a cluster to relay metrics to the IBM Cloud Monitoring service seamlessly within the IBM Cloud environment. This enhancement boosts the productivity of system administrators, DevOps professionals, and developers, providing timely notifications regarding various metrics and events. Leverage intuitive dashboards that allow you to assess the health of your entire infrastructure effortlessly. Moreover, you can dynamically discover applications, containers, hosts, and networks while displaying content and controlling access based on specific users or teams. Additionally, configure an Ubuntu host to send metrics directly to the IBM Cloud Monitoring service, ensuring thorough cloud monitoring and troubleshooting across your infrastructure, cloud services, and applications. Ultimately, this service is essential for maintaining optimal performance and reliability in complex cloud environments.

The Dynatrace software intelligence platform revolutionizes the way organizations operate by offering a unique combination of observability, automation, and intelligence all within a single framework. Say goodbye to cumbersome toolkits and embrace a unified platform that enhances automation across your dynamic multicloud environments while facilitating collaboration among various teams. This platform fosters synergy between business, development, and operations through a comprehensive array of tailored use cases centralized in one location. It enables you to effectively manage and integrate even the most intricate multicloud scenarios, boasting seamless compatibility with all leading cloud platforms and technologies. Gain an expansive understanding of your environment that encompasses metrics, logs, and traces, complemented by a detailed topological model that includes distributed tracing, code-level insights, entity relationships, and user experience data—all presented in context. By integrating Dynatrace’s open API into your current ecosystem, you can streamline automation across all aspects, from development and deployment to cloud operations and business workflows, ultimately leading to increased efficiency and innovation. This cohesive approach not only simplifies management but also drives measurable improvements in performance and responsiveness across the board.

Arize's machine-learning observability platform automatically detects and diagnoses problems and improves models. Machine learning systems are essential for businesses and customers, but often fail to perform in real life. Arize is an end to-end platform for observing and solving issues in your AI models. Seamlessly enable observation for any model, on any platform, in any environment. SDKs that are lightweight for sending production, validation, or training data. You can link real-time ground truth with predictions, or delay. You can gain confidence in your models' performance once they are deployed. Identify and prevent any performance or prediction drift issues, as well as quality issues, before they become serious. Even the most complex models can be reduced in time to resolution (MTTR). Flexible, easy-to use tools for root cause analysis are available.

Amazon CloudWatch serves as a comprehensive monitoring and observability tool designed specifically for DevOps professionals, software developers, site reliability engineers, and IT administrators. This service equips users with essential data and actionable insights necessary for overseeing applications, reacting to performance shifts across systems, enhancing resource efficiency, and gaining an integrated perspective on operational health. By gathering monitoring and operational information in the forms of logs, metrics, and events, CloudWatch delivers a cohesive view of AWS resources, applications, and services, including those deployed on-premises. Users can leverage CloudWatch to identify unusual patterns within their environments, establish alerts, visualize logs alongside metrics, automate responses, troubleshoot problems, and unearth insights that contribute to application stability. Additionally, CloudWatch alarms continuously monitor your specified metric values against established thresholds or those generated through machine learning models to effectively spot any anomalous activities. This functionality ensures that users can maintain optimal performance and reliability across their systems.

Revolutionizing observability brings context and performance into a unified space, suitable for any stack and scale. Achieve thorough end-to-end visibility by effortlessly monitoring applications, infrastructure, databases, and more from a single, user-friendly dashboard. With just a few clicks, trace and analyze digital journeys seamlessly from browsers and applications to the infrastructure layer. Discover invaluable insights into user experiences, identify where dropouts occur, and highlight critical aspects of business transactions through in-depth user analytics and real user monitoring (RUM). This allows for quick adaptation, optimization, and innovation powered by real-time visibility and swift root-cause analysis. Additionally, our dedicated team of experts is available 24/7, 365 days a year, ensuring you receive prompt assistance and tailored support for your unique requirements, which further enhances your operational efficiency. The combination of these features empowers businesses to stay ahead in a rapidly evolving digital landscape.

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.

Obtain scores that assess factual accuracy, context retrieval quality, guideline compliance, tonality, among other metrics. Improvement is impossible without measurement. UpTrain consistently evaluates your application's performance against various criteria and notifies you of any declines, complete with automatic root cause analysis. This platform facilitates swift and effective experimentation across numerous prompts, model providers, and personalized configurations by generating quantitative scores that allow for straightforward comparisons and the best prompt selection. Hallucinations have been a persistent issue for LLMs since their early days. By measuring the extent of hallucinations and the quality of the retrieved context, UpTrain aids in identifying responses that lack factual correctness, ensuring they are filtered out before reaching end-users. Additionally, this proactive approach enhances the reliability of responses, fostering greater trust in automated systems.

Dash0 serves as a comprehensive observability platform rooted in OpenTelemetry, amalgamating metrics, logs, traces, and resources into a single, user-friendly interface that facilitates swift and context-aware monitoring while avoiding vendor lock-in. It consolidates metrics from Prometheus and OpenTelemetry, offering robust filtering options for high-cardinality attributes, alongside heatmap drilldowns and intricate trace visualizations to help identify errors and bottlenecks immediately. Users can take advantage of fully customizable dashboards powered by Perses, featuring code-based configuration and the ability to import from Grafana, in addition to smooth integration with pre-established alerts, checks, and PromQL queries. The platform's AI-driven tools, including Log AI for automated severity inference and pattern extraction, enhance telemetry data seamlessly, allowing users to benefit from sophisticated analytics without noticing the underlying AI processes. These artificial intelligence features facilitate log classification, grouping, inferred severity tagging, and efficient triage workflows using the SIFT framework, ultimately improving the overall monitoring experience. Additionally, Dash0 empowers teams to respond proactively to system issues, ensuring optimal performance and reliability across their applications.

VictoriaMetrics Anomaly Detection, a service which continuously scans data stored in VictoriaMetrics to detect unexpected changes in real-time, is a service for detecting anomalies in data patterns. It does this by using user-configurable models of machine learning. VictoriaMetrics Anomaly Detection is a key tool in the dynamic and complex world system monitoring. It is part of our Enterprise offering. It empowers SREs, DevOps and other teams by automating the complex task of identifying anomalous behavior in time series data. It goes beyond threshold-based alerting by utilizing machine learning to detect anomalies, minimize false positives and reduce alert fatigue. The use of unified anomaly scores and simplified alerting mechanisms allows teams to identify and address potential issues quicker, ensuring system reliability.

Revolutionize your operations across various sectors by leveraging AI and Automation to establish an Autonomous Enterprise that enhances resilience, assures quality, and elevates the customer experience. Digitate’s ignio addresses your operational challenges, enabling the transition to an Agile, Resilient, and Autonomous Enterprise. Organizations can swiftly adapt to changes, embark on digital transformations, and foster innovation to thrive in competitive landscapes. By utilizing ignio, you can shift your IT and business operations from a reactive stance to a proactive one, propelling you toward the ability to ‘Predict, Prescribe, and Prevent.’ Discover how enterprises can enhance their business and IT operational strategies to forge a path into an Autonomous Enterprise. Begin your transformation journey from Traditional to Automated and ultimately to Autonomous Operations. With the power of AI and Machine Learning, Autonomous Operations empower businesses to minimize manual intervention, seamlessly adapt to both business and IT shifts with lower costs, and prioritize innovation as a core focus. This strategic shift not only optimizes efficiency but also positions organizations to thrive in an ever-evolving landscape.

Nazar was developed to address the challenges of managing several databases across multi-cloud or hybrid settings. Fully equipped for the primary database engines, it effectively removes the necessity for juggling multiple tools. By providing a standardized and user-friendly method for establishing new servers on the platform, it significantly reduces setup time. Users can obtain a cohesive overview of their database performance on a singular dashboard, eliminating the hassle of interfacing with various tools that offer inconsistent views and metrics. The real competition lies not in the tedious setup, log tracing, or querying of data dictionaries; rather, Nazar leverages the inherent capabilities of the DBMS for monitoring, thus eliminating the need for additional agents. Furthermore, Nazar automates both anomaly detection and root-cause analysis, which leads to a decrease in mean time to resolution (MTTR) while proactively identifying issues to prevent incidents, ensuring optimal application and business performance. With its comprehensive approach, Nazar not only enhances efficiency but also empowers users to focus on strategic initiatives rather than mundane tasks.

Enhance your observability framework to swiftly identify data and machine learning challenges, facilitate ongoing enhancements, and prevent expensive incidents. Begin with dependable data by consistently monitoring data-in-motion to catch any quality concerns. Accurately detect shifts in data and models while recognizing discrepancies between training and serving datasets, allowing for timely retraining. Continuously track essential performance metrics to uncover any decline in model accuracy. It's crucial to identify and mitigate risky behaviors in generative AI applications to prevent data leaks and protect these systems from malicious attacks. Foster improvements in AI applications through user feedback, diligent monitoring, and collaboration across teams. With purpose-built agents, you can integrate in just minutes, allowing for the analysis of raw data without the need for movement or duplication, thereby ensuring both privacy and security. Onboard the WhyLabs SaaS Platform for a variety of use cases, utilizing a proprietary privacy-preserving integration that is security-approved for both healthcare and banking sectors, making it a versatile solution for sensitive environments. Additionally, this approach not only streamlines workflows but also enhances overall operational efficiency.

Sensai offers a cutting-edge AI-driven platform for detecting anomalies, performing root cause analysis, and forecasting issues, which allows for immediate problem resolution. The Sensai AI solution greatly enhances system uptime and accelerates the identification of root causes. By equipping IT leaders with the tools to effectively manage service level agreements (SLAs), it boosts both performance and profitability. Additionally, it automates and simplifies the processes of anomaly detection, prediction, root cause analysis, and resolution. With its comprehensive perspective and integrated analytics, Sensai seamlessly connects with third-party tools. Users benefit from pre-trained algorithms and models available from the outset, ensuring a swift and efficient implementation. This holistic approach helps organizations maintain operational efficiency while proactively addressing potential disruptions.

Mona is a flexible and intelligent monitoring platform for AI / ML. Data science teams leverage Mona’s powerful analytical engine to gain granular insights about the behavior of their data and models, and detect issues within specific segments of data, in order to reduce business risk and pinpoint areas that need improvements. Mona enables tracking custom metrics for any AI use case within any industry and easily integrates with existing tech stacks. In 2018, we ventured on a mission to empower data teams to make AI more impactful and reliable, and to raise the collective confidence of business and technology leaders in their ability to make the most out of AI. We have built the leading intelligent monitoring platform to provide data and AI teams with continuous insights to help them reduce risks, optimize their operations, and ultimately build more valuable AI systems. Enterprises in a variety of industries leverage Mona for NLP/NLU, speech, computer vision, and machine learning use cases. Mona was founded by experienced product leaders from Google and McKinsey&Co, is backed by top VCs, and is HQ in Atlanta, Georgia. In 2021, Mona was recognized by Gartner as a Cool Vendor in AI Operationalization and Engineering.

Shield34 stands out as the sole web automation framework that ensures complete compatibility with Selenium, allowing users to seamlessly continue utilizing their existing Selenium scripts while also enabling the creation of new ones through the Selenium API. It effectively tackles the notorious issue of flaky tests by implementing self-healing technology, intelligent defenses, error recovery protocols, and dynamic element locators. Furthermore, it offers AI-driven anomaly detection and root cause analysis, which facilitates a swift examination of failed tests to identify what changed and triggered the failure. By eliminating flaky tests, which often present significant challenges, Shield34 incorporates sophisticated defense-and-recovery AI algorithms into each Selenium command, including dynamic element locators, thereby reducing false positives and promoting self-healing alongside maintenance-free testing. Additionally, with its real-time root cause analysis capabilities powered by AI, Shield34 can swiftly identify the underlying reasons for test failures, minimizing the burden of debugging and the effort required to replicate issues. Ultimately, users can relish a more intelligent version of Selenium, as it effortlessly integrates with your existing testing framework while enhancing overall efficiency.

Anodot uses AI to deliver autonomous analytics at enterprise scale across all data types and in real-time. We provide business analysts with the ability to control their business, without the limitations of traditional Business Intelligence. Our self-service AI platform runs continuously to eliminate blind spots and alert incidents, and investigate root cause. Our platform uses machine learning algorithms that are patent-pending to identify issues and correlate them across multiple parameters. This eliminates business insight latency and supports quick, smart business decision-making. Anodot serves over 100 customers in the digital transformation industry, including eCommerce, FinTech and AdTech, Telco and Gaming. This includes Microsoft, Lyft and Waze. Anodot was founded in 2014 in Silicon Valley and Israel. There are also sales offices around the world.

Harness the power of AI for anomaly detection and root cause analysis focused on the key metrics that impact your business. Avora employs machine learning to oversee your business metrics around the clock, promptly notifying you of critical incidents so you can respond within hours instead of waiting for days or weeks. By continuously examining millions of records every hour for any signs of unusual activity, it reveals both potential threats and new opportunities within your organization. The root cause analysis feature helps you identify the elements influencing your business metrics, empowering you to implement swift, informed changes. You can integrate Avora’s machine learning features and notifications into your applications through our comprehensive APIs. Receive alerts about anomalies, shifts in trends, and threshold breaches via email, Slack, Microsoft Teams, or any other platform through Webhooks. Additionally, you can easily share pertinent insights with your colleagues and invite them to monitor ongoing metrics, ensuring they receive real-time notifications and updates. This collaborative approach enhances decision-making across the board, fostering a proactive business environment.

Sightline EDM: Improved Operations, Right Out of the Box Predictive analytics and performance and risk-based monitoring used to be a complicated process. Between endless Excel files and disjointed communication between departments, a lot of information was lost. When you switch to Sightline EDM, you can start making the best decisions for your operations, prepare for the future, and begin saving time and money immediately in one easy-to-use platform. One Easy-to-Use Dashboard Data from multiple monitoring tools can be consolidated into a single display: a uniform, easy-to-use dashboard with drill-down details. Real-Time OT & IT Intelligence With configurable notifications to any errors or anomalies, visualize and analyze production and operations in minutes, not months. Scalable Usability for All Organizations & Teams Proven, enterprise-grade, scalable software solution with role-based access controls, security, and user views that works with all web browsers and mobile devices. Pre-Built Integrations Across Systems Data from PLCs, CNC machines, process equipment, ERP/MES systems, and other vital data sources is gathered in minutes, not months, using open, agent, and agentless interfaces.

Aquarium's innovative embedding technology identifies significant issues in your model's performance and connects you with the appropriate data to address them. Experience the benefits of neural network embeddings while eliminating the burdens of infrastructure management and debugging embedding models. Effortlessly uncover the most pressing patterns of model failures within your datasets. Gain insights into the long tail of edge cases, enabling you to prioritize which problems to tackle first. Navigate through extensive unlabeled datasets to discover scenarios that fall outside the norm. Utilize few-shot learning technology to initiate new classes with just a few examples. The larger your dataset, the greater the value we can provide. Aquarium is designed to effectively scale with datasets that contain hundreds of millions of data points. Additionally, we offer dedicated solutions engineering resources, regular customer success meetings, and user training to ensure that our clients maximize their benefits. For organizations concerned about privacy, we also provide an anonymous mode that allows the use of Aquarium without risking exposure of sensitive information, ensuring that security remains a top priority. Ultimately, with Aquarium, you can enhance your model's capabilities while maintaining the integrity of your data.

BMC Helix Operations Management serves as a comprehensive, cloud-native solution for observability and AIOps, specifically engineered to address the complexities of hybrid-cloud environments. Adopting a service-oriented perspective towards observability data is crucial for achieving effective AIOps results. It facilitates the integration of third-party observability inputs, including metrics, events, logs, incidents, changes, and topologies, into a unified IT data repository. This enables users to monitor service health and enhances the capacity for pinpointing root causes through automatically generated dynamic business service models. The AI-driven features improve the signal-to-noise ratio by employing event suppression, de-duplication, and correlation, all aimed at generating actionable insights. Users can quickly identify root causes with AI probability assignments to key causal nodes based on comprehensive data and service models. Additionally, the platform aids in preventing future incidents through proactive Business Service Health monitoring and AI-driven outage predictions. Troubleshooting is expedited via enriched logs and advanced analytics, while users can conveniently request and implement automations through BMC or other third-party tools, making management seamless and efficient. Ultimately, this solution empowers organizations to enhance their operational resilience and streamline management processes.

Apica offers a unified platform for efficient data management, addressing complexity and cost challenges. The Apica Ascent platform enables users to collect, control, store, and observe data while swiftly identifying and resolving performance issues. Key features include: *Real-time telemetry data analysis *Automated root cause analysis using machine learning *Fleet tool for automated agent management *Flow tool for AI/ML-powered pipeline optimization *Store for unlimited, cost-effective data storage *Observe for modern observability management, including MELT data handling and dashboard creation This comprehensive solution streamlines troubleshooting in complex distributed systems and integrates synthetic and real data seamlessly

A new category of AI. Most AI solutions today are designed using a mathematical and statistical lens. We took a different approach. Intelligent Artifacts' team has created a new type of AI based on information theory. It is a true AGI that eliminates the current shortcomings in machine intelligence. Our framework separates the intelligence layer from the data and application layers, allowing it to learn in real time and allowing it to make predictions down to the root cause. A truly integrated platform is required for AGI. Intelligent Artifacts will allow you to model information, not data. Predictions and decisions can be made across multiple domains without the need for rewriting code. Our dynamic platform and specialized AI consultants will provide you with a tailored solution that quickly provides deep insights and better outcomes from your data.

Full-stack platform for monitoring your hardware and software. InsightCat, a full-stack monitoring solution for infrastructure monitoring, allows you to search, analyze, aggregate and summarize system metrics from one place. The solution was designed to be simple and address the most pressing requests of DevOps and SecOps (System administrators, SecOps and IT specialists) related to infrastructure monitoring, security log management, log management, log management, and other issues. This solution allows you to: Perform infrastructure monitoring. Identify anomalies in your infrastructure and eliminate them as quickly possible. This will also prevent similar problems from happening again. Synthetic monitoring. Monitoring your web services 24 hours a day. Be aware of any critical downtimes in advance. Log management. Log management. Smart alerting and escalation. To keep your team informed of any unusual behavior, spikes or errors, set up the flexible alarming system.

Zenoss Cloud stands out as a pioneering SaaS-based intelligent platform for IT operations management, capable of streaming and normalizing all machine data, which fosters the development of context essential for averting service disruptions in intricate and contemporary IT settings. By utilizing Zenoss, enterprises can redirect their focus towards business growth, alleviating the burdens that hinder their architecture and operations teams. Organizations leveraging Zenoss are empowered to eradicate infrastructure blind spots, anticipate the repercussions on business services prior to outages, and expedite incident resolution, all while scaling to meet the demands of their operations. Designed specifically for today's IT infrastructures, Zenoss Cloud transforms the way businesses manage their systems and services. Together, we can explore potential collaborations to enhance operational efficiency and resilience.

Elevate your log management with Honeycomb, a platform designed specifically for contemporary development teams aiming to gain insights into application performance while enhancing log management capabilities. With Honeycomb’s rapid query functionality, you can uncover hidden issues across your system’s logs, metrics, and traces, utilizing interactive charts that provide an in-depth analysis of raw data that boasts high cardinality. You can set up Service Level Objectives (SLOs) that reflect user priorities, which helps in reducing unnecessary alerts and allows you to focus on what truly matters. By minimizing on-call responsibilities and speeding up code deployment, you can ensure customer satisfaction remains high. Identify the root causes of performance issues, optimize your code efficiently, and view your production environment in high resolution. Our SLOs will alert you when customers experience difficulties, enabling you to swiftly investigate the underlying problems—all from a single interface. Additionally, the Query Builder empowers you to dissect your data effortlessly, allowing you to visualize behavioral trends for both individual users and services, organized by various dimensions for enhanced analytical insights. This comprehensive approach ensures that your team can respond proactively to performance challenges while refining the overall user experience.

Enhancing service and support efficiency, alongside business satisfaction, begins with the ability to foresee and prevent downtime. EV Observe serves as a comprehensive monitoring platform tailored for networks, IoT devices, IT infrastructure, cloud environments, and application monitoring, ensuring a seamless end-to-end service experience. Our solution empowers organizations to adopt a proactive and predictive stance towards service support, delivery, and observability, facilitating collaborative self-help and self-healing capabilities, as well as providing in-depth insights into performance and availability. This approach enables teams to concentrate on delivering value and fostering innovation that propels business success, ultimately leading to greater employee engagement, enriched customer experiences, heightened productivity, and enhanced resiliency. Specifically designed for SaaS monitoring in a multi-client and multi-site environment, it also integrates a comprehensive software production tool that encompasses the entire range of software processes while promoting the implementation of DevOps practices for optimized operational efficiency. The holistic nature of our platform ensures that organizations can adapt swiftly to changing demands in the digital landscape.

Anticipate issues before they arise by utilizing an Azure AI anomaly detection service. This service allows for the seamless integration of time-series anomaly detection features into applications, enabling users to quickly pinpoint problems. The AI Anomaly Detector processes various types of time-series data and intelligently chooses the most effective anomaly detection algorithm tailored to your specific dataset, ensuring superior accuracy. It can identify sudden spikes, drops, deviations from established patterns, and changes in trends using both univariate and multivariate APIs. Users can personalize the service to recognize different levels of anomalies based on their needs. The anomaly detection service can be deployed flexibly, whether in the cloud or at the intelligent edge. With a robust inference engine, the service evaluates your time-series dataset and automatically determines the ideal detection algorithm, enhancing accuracy for your unique context. This automatic detection process removes the necessity for labeled training data, enabling you to save valuable time and concentrate on addressing issues promptly as they arise. By leveraging advanced technology, organizations can enhance their operational efficiency and maintain a proactive approach to problem-solving.

VirtualMetric is a comprehensive data monitoring solution that provides organizations with real-time insights into security, network, and server performance. Using its advanced DataStream pipeline, VirtualMetric efficiently collects and processes security logs, reducing the burden on SIEM systems by filtering irrelevant data and enabling faster threat detection. The platform supports a wide range of systems, offering automatic log discovery and transformation across environments. With features like zero data loss and compliance storage, VirtualMetric ensures that organizations can meet security and regulatory requirements while minimizing storage costs and enhancing overall IT operations.

Autointelli Inc, a leader in AIOps, delivers innovative solutions that revolutionize modern IT operations through a combination of automation and advanced machine learning techniques. Our focus on providing solutions has led us to create an AIOps platform designed to streamline data center automation. By utilizing the Autointelli AIOps platform, you can effectively minimize alert noise, pinpoint root issues, and reallocate your team to focus on more critical IT responsibilities. Partner with us to enhance your digital workplace experience. The Autointelli AIOps platform accelerates event correlation and seamlessly escalates complex incidents to the appropriate engineers. Furthermore, it includes a robust self-service automation feature, enabling users to design countless workflows for automation purposes. The platform's root cause analysis capability allows for the identification of core issues affecting both hardware and software. Additionally, our analytics tools are engineered to boost your business performance by gleaning valuable insights from all significant data sources, ensuring you remain competitive in a rapidly changing landscape. As technology evolves, having an intelligent AIOps solution becomes essential for sustained operational success.

Fiddler is a pioneer in enterprise Model Performance Management. Data Science, MLOps, and LOB teams use Fiddler to monitor, explain, analyze, and improve their models and build trust into AI. The unified environment provides a common language, centralized controls, and actionable insights to operationalize ML/AI with trust. It addresses the unique challenges of building in-house stable and secure MLOps systems at scale. Unlike observability solutions, Fiddler seamlessly integrates deep XAI and analytics to help you grow into advanced capabilities over time and build a framework for responsible AI practices. Fortune 500 organizations use Fiddler across training and production models to accelerate AI time-to-value and scale and increase revenue.

StackPilot is a next-generation incident response solution designed to reduce engineering toil and accelerate bug resolution. Acting as an AI-powered copilot, it plugs into your monitoring and logging ecosystem to immediately act on alerts. When issues occur, StackPilot cross-references code commits, stack traces, and system data to identify root causes with precision. It then auto-generates a pull request containing a recommended fix, saving engineers countless hours of manual debugging. Beyond incident resolution, the platform builds real-time incident timelines and turns troubleshooting steps into standardized runbooks for future use. Setup takes just minutes, requiring only a GitHub and monitoring tool connection. The platform is built with privacy-first principles—your data never leaves your environment and is not used for AI training. Teams using StackPilot benefit from reduced mean time to resolution (MTTR), stronger reliability, and higher developer productivity.

Traversal is an innovative AI-driven Site Reliability Engineering (SRE) solution that functions round the clock, autonomously identifying, addressing, and even preventing production issues. It meticulously analyzes logs, metrics, traces, and your codebase to pinpoint the root causes of errors or delays, quickly highlighting the impacted areas, critical bottleneck services, and potential root causes with relevant evidence in a matter of minutes. Leveraging advancements in causal machine learning, reasoning from large language models, and intelligent AI agents, Traversal proactively resolves problems before alerts are triggered, ensuring seamless operations. Tailored for complex organizations and vital infrastructure, it accommodates diverse data types, supports bring-your-own models, and offers optional on-premises deployment for added flexibility. With its straightforward integration into existing systems requiring only read-only access—without the need for agents, sidecars, or any write operations to production—Traversal guarantees data privacy and control. By effortlessly fitting into your observability framework, it not only accelerates the resolution process but also significantly reduces downtime, further enhancing operational efficiency and reliability. Furthermore, its ability to adapt to various environments makes it a versatile asset for businesses striving for uninterrupted service delivery.

Langfuse is a free and open-source LLM engineering platform that helps teams to debug, analyze, and iterate their LLM Applications. Observability: Incorporate Langfuse into your app to start ingesting traces. Langfuse UI : inspect and debug complex logs, user sessions and user sessions Langfuse Prompts: Manage versions, deploy prompts and manage prompts within Langfuse Analytics: Track metrics such as cost, latency and quality (LLM) to gain insights through dashboards & data exports Evals: Calculate and collect scores for your LLM completions Experiments: Track app behavior and test it before deploying new versions Why Langfuse? - Open source - Models and frameworks are agnostic - Built for production - Incrementally adaptable - Start with a single LLM or integration call, then expand to the full tracing for complex chains/agents - Use GET to create downstream use cases and export the data

You can gain a deeper understanding of your organization by using workforce analytics, deep-dive visualisation, org charts and reporting tools. Use machine learning to automate root cause analysis and problem detection in HR. Predict the impact and outcome of organizational changes in order to remain proactive and responsive. Modernize your organizational design by embracing continuous AI-driven design. This will help you build the future state for your organization. The business team builds a well designed organization that can scale and adapt quickly to change while retaining talent more effectively and hiring more efficiently. The finance teams can see the forecasted budgets for HR through predictive reporting.

The Robust Intelligence Platform is designed to integrate effortlessly into your machine learning lifecycle, thereby mitigating the risk of model failures. It identifies vulnerabilities within your model, blocks erroneous data from infiltrating your AI system, and uncovers statistical issues such as data drift. Central to our testing methodology is a singular test that assesses the resilience of your model against specific types of production failures. Stress Testing performs hundreds of these evaluations to gauge the readiness of the model for production deployment. The insights gained from these tests enable the automatic configuration of a tailored AI Firewall, which safeguards the model from particular failure risks that it may face. Additionally, Continuous Testing operates during production to execute these tests, offering automated root cause analysis that is driven by the underlying factors of any test failure. By utilizing all three components of the Robust Intelligence Platform in tandem, you can maintain the integrity of your machine learning processes, ensuring optimal performance and reliability. This holistic approach not only enhances model robustness but also fosters a proactive stance in managing potential issues before they escalate.

LMOps is a stack that allows you to launch production-ready applications for monitoring, model management and more. Portkey is a replacement for OpenAI or any other provider APIs. Portkey allows you to manage engines, parameters and versions. Switch, upgrade, and test models with confidence. View aggregate metrics for your app and users to optimize usage and API costs Protect your user data from malicious attacks and accidental exposure. Receive proactive alerts if things go wrong. Test your models in real-world conditions and deploy the best performers. We have been building apps on top of LLM's APIs for over 2 1/2 years. While building a PoC only took a weekend, bringing it to production and managing it was a hassle! We built Portkey to help you successfully deploy large language models APIs into your applications. We're happy to help you, regardless of whether or not you try Portkey!