Alternatives to Monte Carlo

Auvik Network Management is a network management and monitoring software designed to empower IT professionals with deep visibility, automation, and control over their network infrastructure. This innovative platform is trusted by businesses of all sizes to streamline network operations, enhance security, and optimize performance. One of Auvik's standout features is its real-time network mapping and discovery capabilities. It automatically generates interactive, visual maps of your network topology, allowing you to easily identify devices, connections, and potential bottlenecks. This invaluable insight helps in planning and optimizing network architecture for maximum efficiency.

LogicMonitor is the leading SaaS-based, fully-automated observability platform for enterprise IT and managed service providers. Cloud-first and hybrid ready. LogicMonitor helps enterprises and managed service providers gain IT insights through comprehensive visibility into networks, cloud, applications, servers, log data and more within one unified platform. Drive collaboration and efficiency across IT and DevOps teams, in a fully secure, intelligently automated platform. By providing end-to-end observability for enterprise businesses, LogicMonitor connects coders to consumers, customer experience to the cloud, infrastructure to applications and business insights into instant actions. Maximize uptime, optimize end-user experience, predict what comes next, and keep your business fearlessly moving forward.

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.

Big Data Quality must always be verified to ensure that data is safe, accurate, and complete. Data is moved through multiple IT platforms or stored in Data Lakes. The Big Data Challenge: Data often loses its trustworthiness because of (i) Undiscovered errors in incoming data (iii). Multiple data sources that get out-of-synchrony over time (iii). Structural changes to data in downstream processes not expected downstream and (iv) multiple IT platforms (Hadoop DW, Cloud). Unexpected errors can occur when data moves between systems, such as from a Data Warehouse to a Hadoop environment, NoSQL database, or the Cloud. Data can change unexpectedly due to poor processes, ad-hoc data policies, poor data storage and control, and lack of control over certain data sources (e.g., external providers). DataBuck is an autonomous, self-learning, Big Data Quality validation tool and Data Matching tool.

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.

Coralogix is the most popular stateful streaming platform, providing engineering teams with real-time insight and long-term trend analysis without relying on storage or indexing. To manage, monitor, alert, and manage your applications, you can import data from any source. Coralogix automatically narrows the data from millions of events to common patterns, allowing for faster troubleshooting and deeper insights. Machine learning algorithms constantly monitor data patterns and flows among system components and trigger dynamic alarms to let you know when a pattern is out of the norm without the need for static thresholds or pre-configurations. Connect any data in any format and view your insights anywhere, including our purpose-built UI and Kibana, Grafana as well as SQL clients and Tableau. You can also use our CLI and full API support. Coralogix has successfully completed the relevant privacy and security compliances by BDO, including SOC 2, PCI and GDPR.

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.

Datadog is the cloud-age monitoring, security, and analytics platform for developers, IT operation teams, security engineers, and business users. Our SaaS platform integrates monitoring of infrastructure, application performance monitoring, and log management to provide unified and real-time monitoring of all our customers' technology stacks. Datadog is used by companies of all sizes and in many industries to enable digital transformation, cloud migration, collaboration among development, operations and security teams, accelerate time-to-market for applications, reduce the time it takes to solve problems, secure applications and infrastructure and understand user behavior to track key business metrics.

Splunk Observability Cloud provides a comprehensive real-time monitoring platform that helps organizations gain visibility into their cloud native environments, infrastructures, applications, and service. It combines metrics with logs and traces to create a unified platform that provides seamless visibility from end-to-end across complex architectures. Splunk Observability helps teams identify and resolve performance problems, reduce downtime and improve system reliability with its powerful analytics and AI-driven insights. It provides real-time data in high resolution and supports a variety of integrations. This allows IT and DevOps to detect anomalies, optimize the performance, and ensure that their cloud and hybrid environment is healthy and efficient.

You can prevent data outages by identifying data quality issues and fixing them before they reach production. In less than a day, you can increase your test coverage for data pipelines from 0 to 100%. Automatic regression testing across billions upon billions of rows allows you to determine the impact of every code change. Automate change management, improve data literacy and compliance, and reduce incident response times. Don't be taken by surprise by data incidents. Automated anomaly detection allows you to be the first to know about them. Datafold's ML model, which can be easily adjusted by Datafold, adapts to seasonality or trend patterns in your data to create dynamic thresholds. You can save hours trying to understand data. The Data Catalog makes it easy to search for relevant data, fields, or explore distributions with an intuitive UI. Interactive full-text search, data profiling and consolidation of metadata all in one place.

ServiceNow Cloud Observability provides real-time visibility and monitoring of cloud infrastructure, applications and services. It allows organizations to identify and resolve performance problems by integrating data from different cloud environments into a single dashboard. ServiceNow Cloud Observability's advanced analytics and alerting features help IT and DevOps departments detect anomalies, troubleshoot issues, and ensure optimal performance. The platform supports AI-driven insights and automation, allowing teams the ability to respond quickly to incidents. Overall, the platform improves operational efficiency while ensuring a seamless user-experience across cloud environments.

Anomalo helps you get ahead of data issues by automatically detecting them as soon as they appear and before anyone else is impacted. -Depth of Checks: Provides both foundational observability (automated checks for data freshness, volume, schema changes) and deep data quality monitoring (automated checks for data consistency and correctness). -Automation: Use unsupervised machine learning to automatically identify missing and anomalous data. -Easy for everyone, no-code UI: A user can generate a no-code check that calculates a metric, plots it over time, generates a time series model, sends intuitive alerts to tools like Slack, and returns a root cause analysis. -Intelligent Alerting: Incredibly powerful unsupervised machine learning intelligently readjusts time series models and uses automatic secondary checks to weed out false positives. -Time to Resolution: Automatically generates a root cause analysis that saves users time determining why an anomaly is occurring. Our triage feature orchestrates a resolution workflow and can integrate with many remediation steps, like ticketing systems. -In-VPC Development: Data never leaves the customer’s environment. Anomalo can be run entirely in-VPC for the utmost in privacy & security

Digna is a solution powered by AI that addresses the challenges of data quality management in modern times. It is domain agnostic and can be used in a variety of sectors, including finance and healthcare. Digna prioritizes privacy and ensures compliance with stringent regulations. It's also built to scale and grow with your data infrastructure. Digna is flexible enough to be installed on-premises or in the cloud, and it aligns with your organization's needs and security policies. Digna is at the forefront of data quality solutions. Its user-friendly design, combined with powerful AI analytics, makes Digna an ideal solution for businesses looking to improve data quality. Digna's seamless integration, real time monitoring, and adaptability make it more than just a tool. It is a partner on your journey to impeccable data quality.

Sumo Logic is a cloud-based solution for log management and monitoring for IT and security departments of all sizes. Integrated logs, metrics, and traces allow for faster troubleshooting. One platform. Multiple uses. You can increase your troubleshooting efficiency. Sumo Logic can help you reduce downtime, move from reactive to proactive monitoring, and use cloud-based modern analytics powered with machine learning to improve your troubleshooting. Sumo Logic Security Analytics allows you to quickly detect Indicators of Compromise, accelerate investigation, and ensure compliance. Sumo Logic's real time analytics platform allows you to make data-driven business decisions. You can also predict and analyze customer behavior. Sumo Logic's platform allows you to make data-driven business decisions and reduce the time it takes to investigate operational and security issues, so you have more time for other important activities.

With today's complex IT environment and applications, which can span traditional data centers, SaaS and IaaS clouds, it can be difficult to gain visibility into performance. When companies use a traditional, siloed management approach, they have a fragmented and incomplete view of performance. IT spends a great deal of time analyzing the data, but often comes to different and sometimes conflicting conclusions about the cause of performance issues. Riverbed Portal integrates telemetry data to create a dynamic, centralized view of performance. This holistic view provides IT Ops teams with a single source for truth to accelerate troubleshooting, and provide meaningful data for all stakeholders across the enterprise. IT can control and optimize data, applications, and traffic on the hybrid network as a whole, allowing key resources to focus on strategic projects.

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.

Monitor your data health, and monitor your pipeline performance. Get unified visibility for all pipelines that use cloud-native tools such as Apache Spark, Snowflake and BigQuery. A platform for Data Engineers that provides observability. Data engineering is becoming more complex as business stakeholders demand it. Databand can help you catch-up. More pipelines, more complexity. Data engineers are working with more complex infrastructure and pushing for faster release speeds. It is more difficult to understand why a process failed, why it is running late, and how changes impact the quality of data outputs. Data consumers are frustrated by inconsistent results, model performance, delays in data delivery, and other issues. A lack of transparency and trust in data delivery can lead to confusion about the exact source of the data. Pipeline logs, data quality metrics, and errors are all captured and stored in separate, isolated systems.

SigNoz can be used as an open-source alternative to Datadog or New Relic. A single tool that can handle all your observability requirements, including APM, logs and metrics, exceptions and alerts, dashboards, and dashboards. You don't have to manage multiple tools. You can use the powerful query builder and great charts that come with the software to dig deeper into data. By using an open-source standard, you are not locked into a vendor. OpenTelemetry's auto-instrumentation libraries can help you get started quickly and with minimal code changes. OpenTelemetry provides a single-stop solution to all your telemetry requirements. A single standard for telemetry signals increases developer productivity and consistency within teams. Write queries for all telemetry signals. Apply filters and formulas and run aggregates to gain deeper insights. SigNoz uses ClickHouse, a fast open source distributed columnar database. Ingestion and aggregates are lightning fast.

Logit.io are a centralized logging and metrics management platform that serves hundreds of customers around the world, solving complex problems for FTSE 100, Fortune 500 and fast-growing organizations alike. The Logit.io platform delivers you with a fully customized log and metrics solution based on ELK, Grafana & Open Distro that is scalable, secure and compliant. Using the Logit.io platform simplifies logging and metrics, so that your team gains the insights to deliver the best experience for your customers.

After a few late-night code fires, we set out to find application performance management tools that would help us stop them. We were able to identify what was wrong, but it didn't tell us why or how to prevent future failures. Retrace was created to do just that. We believe that when our 1300+ customers spend less of their time fighting technology, they spend more time releasing it. This makes the world a better place.

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.

Your enterprise's self-healing IT solution. HEAL's unique cognitive capabilities prevent IT system failures from ever happening, allowing you to focus your energy on other areas of your business. It's not enough to flag incidents after they happen in a fast-paced world. HEAL, a self-healing tool that predicts and prevents instead of fixing what's broken is a new age IT tool. It uses AI algorithms and machine learning to help enterprises run smoothly. HEAL uses a patented technique called workload-behavior correlation'. It analyzes all aspects that contribute to the smooth running an IT system (the cumulative volumes, composition, and payload) and responds to any abnormal behavior. This action can either be a healing or scaling action depending on the root cause.

OK, it’s not that big a secret. Companies that get ahead will remain focused on Continuous Experience Optimization. More than just a process, Continuous Experience Optimization becomes a deeply ingrained culture. A driving force built around constantly optimizing the digital experience. While other platforms alert you to user friction, only Blue Triangle helps you prioritize solutions with website monitoring software rooted in business outcomes.

You can add logs, metrics, and traces to production or staging directly from your IDE/CLI, in real time and on-demand. Lightrun can help you increase productivity and ensure 100% code-level observability. Lightrun allows you to insert logs and metrics even when the service is in progress. You can debug monolith microservices like Kubernetes and Docker Swarm, ECS and Big Data workers, as well as serverless. Quickly add a logline, instrument a measurement, or place a snapshot that can be taken on-demand. There is no need to recreate the production environment or redeploy. Once instrumentation has been invoked, data is printed to your log analysis tool, your editor, or an APM of choice. To analyze code behavior and find bottlenecks or errors, you can stop the running process. You can easily add large numbers of logs and snapshots, counters or timers to your program. The system won't be stopped or broken. Spend less time debugging, and more time programming. Debugging is done without the need to restart, redeploying, or reproduce.

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.

Are you having trouble processing all those tickets and alerts? Moogsoft AIOps reduces the noise and helps you detect issues earlier. Don't let a flood alerts slow down your day. We automatically remove all the annoying alerts that could distract you. Never look at another ticket. Instead of sending you tickets, we only send you "Situations" which are actionable work items that you can use to solve problems quickly before your customers complain. Stop wasting your time switching between tools. We bring all your tools together so that you can manage any incident regardless of its source.

Kensu monitors data usage throughout the day in real-time. This allows your team to prevent data incidents. It is important to understand how you use your data, not just the data. A single comprehensive view allows you to analyze data quality and lineage. Real-time insight into data usage across all of your systems, projects, or applications. Instead of relying on ever-increasing numbers of repositories, monitor data flow. With catalogs, glossaries and incident management systems, share lineages, schemas, and quality information. To prevent data catastrophes from spreading, identify the root causes of complex data issues at a glance. You can generate notifications about specific data events and their context. Learn how data was collected, copied, and modified by any application. Analyze historical data information to detect anomalies. Use historical data information and leverage lineage to determine the cause.

AI-powered cloud observation platform. Middleware platform helps you identify, understand and resolve issues across your cloud infrastructure. AI will detect and diagnose all issues infra, application and infrastructure and provide better recommendations for fixing them. Dashboard allows you to monitor metrics, logs and traces in real time. The best and fastest results with the least amount of resources. Bring all metrics, logs and traces together into a single timeline. A full-stack platform for observability will give you complete visibility into your cloud. Our AI-based algorithms analyze your data and make suggestions for what you should fix. Your data is yours. Control your data collection, and store it in your cloud to save up to 10x the cost. Connect the dots to determine where the problem began and where it ended. Fix problems before users report them. The users get a comprehensive solution for cloud observability at a single location. It's also too cost-effective.

IBM®, Instana®, is the gold-standard of incident prevention. It offers automated full-stack transparency, 1-second granularity, and 3-second notification. In today's highly complex and dynamic cloud environments, an hour of downtime could cost you six figures or more. Traditional application performance monitoring tools (APMs) are not fast enough to keep pace or comprehensive enough to contextualize issues identified. They are also typically only available to super users, who must undergo months of training. IBM Instana Observability is a solution that goes beyond traditional APM by democratizing observability. Anyone in DevOps or SRE, Platform Engineering, ITOps, and Development can access the data they need with the context needed. Instana delivers high-fidelity data with a 1-second granularity, and end-toend traces, as well as the context of logical, physical, and mobile dependencies, across applications, web, and infrastructure.

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.

No downtime required to deploy existing containerized apps to the Edge Your apps will be more accessible to your users, delivering exceptional digital experiences. Dynamic edge adapts to your users to optimize performance and cost efficiency. Automated, optimized placement and scaling globally distributed edge application deployments for the best resource consumption and highest performance. Control cost, placement, performance and scale at the edge. A heterogeneous multicloud and edge computing network, delivered as a configurable and homogenous edge cloud. Section's GEN is a global network of top infrastructure providers that is vendor-agnostic. This gives you the best in flexibility, reach and scale as well as reliability.

Automate the automatic coverage of thousands of tables using ML-based anomaly detection. 50+ custom metrics are also available. Monitoring of metadata and data. Comprehensive mapping of all dependencies between assets from ingestion to reporting. Collaboration between data consumers and data engineers is enhanced and productivity is increased. Sifflet integrates seamlessly with your data sources and preferred tools. It can run on AWS and Google Cloud Platform as well as Microsoft Azure. Keep an eye on your data's health and notify the team if quality criteria are not being met. In a matter of seconds, you can set up the basic coverage of all your tables. You can set the frequency, criticality, and even custom notifications. Use ML-based rules for any anomaly in your data. There is no need to create a new configuration. Each rule is unique because it learns from historical data as well as user feedback. A library of 50+ templates can be used to complement the automated rules.

With a single AI-powered platform, you can control costs, optimize performance, monitor and drive uptime across your infrastructure in public and private clouds. Enterprises face the most difficult challenges when attempting to leverage public cloud services. How to know which workloads to migrate, how to avoid unexpected costs and performance degradation after workloads have been moved to the cloud. The Virtana unified observability system allows you to migrate and optimize across hybrid, private, and public cloud environments. This modular hybrid-cloud infrastructure optimization platform gathers high-fidelity data and then applies AIOps technologies including machine learning and advanced analytics to provide intelligent observation of single workloads to make better decisions regarding what to move and where, while still meeting performance requirements.

When organizations invest in a platform that unifies data and insights across IT, they can solve problems faster and eliminate data silos. They can also eliminate resource-intensive warrooms and alert fatigue. Riverbed IQ unified observability enables rapid, effective decision making across business and IT. It codifies expert troubleshooting skills so junior staff members can achieve more first level resolutions. Broad-based Telemetry provides a unified view on performance and insights. This is the foundation for unified observability, upon which all other capabilities can be delivered. Riverbed IQ’s approach to unified observability starts with our full-fidelity telemetry – across the network and infrastructure, and including end-user experiences metrics.

Observability allows you to detect data issues and ML problems faster, to deliver continuous improvements and to avoid costly incidents. Start with reliable data. Monitor data in motion for quality issues. Pinpoint data and models drift. Identify the training-serving skew, and proactively retrain. Monitor key performance metrics continuously to detect model accuracy degradation. Identify and prevent data leakage in generative AI applications. Protect your generative AI apps from malicious actions. Improve AI applications by using user feedback, monitoring and cross-team collaboration. Integrate in just minutes with agents that analyze raw data, without moving or replicating it. This ensures privacy and security. Use the proprietary privacy-preserving technology to integrate the WhyLabs SaaS Platform with any use case. Security approved by healthcare and banks.

Bigeye is a data observability platform that allows teams to measure, improve and communicate data quality at any scale. A data quality problem can cause an outage that causes trust in the data. Bigeye starts with monitoring to rebuild trust. Before executives see it in a dashboard, find missing or broken reporting data. Before models are retrained, be aware of potential issues in training data. You need to get rid of that uncomfortable feeling that most data is correct most of the time. The status of a pipeline job doesn't tell the entire story. Monitoring the actual data is the best way to make sure data is available for use. Monitoring data-level freshness will ensure that pipelines run on schedule even when ETL orchestrators are down. Learn about any changes in event names, region codes or product types and other categorical data. To ensure that everything is working as it should, detect drops or spikes of row counts, nulls, or blank values.

The most comprehensive network observability solution available for modern data platforms. Provides unprecedented insights at any size. ElastiFlow enables organizations to achieve unprecedented levels in network performance, availability and security. ElastiFlow gives detailed information about network traffic, including IP addresses, ports and protocols, as well as the amount of data sent. This information allows network administrators gain a deeper understanding of the network's performance, and identify potential problems. ElastiFlow can be used to diagnose and troubleshoot network issues, such as congestion, packet loss, or high latency. Administrators can identify the root cause of a problem by analyzing network traffic and taking appropriate action. ElastiFlow allows organizations to improve their security posture and detect and respond more effectively to threats, while maintaining compliance with regulatory requirements.

Predicting and avoiding downtime is the first step to increasing service and support efficiency, and business satisfaction. EV Observe provides an end-toend service experience with its monitoring platform that includes network, IoT and IT infrastructure monitoring, cloud monitoring, and application monitoring. We make it simple for organizations to adopt a proactive and predicative approach to service delivery, support, and observability. This includes collaborative self-help and self-healing as well as comprehensive performance and availability insight. This allows teams to focus on innovation and value delivery that drives business outcomes. The result is higher employee engagement, improved customer experience, increased productivity and improved resilience. Cloud-based SaaS monitoring for multi-clients and multi-sites. Software production tool that integrates the entire spectrum of software development processes and incorporates DevOps.

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.

You can innovate faster in the cloud, improve user experience and future-proof applications. Splunk is designed for cloud-native enterprises and helps you solve current problems. Splunk helps you detect any problem before it becomes a customer problem. Our AI-driven Directed Problemshooting reduces MTTR. Flexible, open-source instrumentation eliminates lock-in. Optimize performance by seeing all of your application and using AI-driven analytics. You must observe everything in order to deliver an excellent end-user experience. NoSample™, full-fidelity trace ingestion allows you to leverage all your trace data and identify any anomalies. Directed Troubleshooting reduces MTTR to quickly identify service dependencies, correlations with the underlying infrastructure, and root-cause errors mapping. You can break down and examine any transaction by any dimension or metric. You can quickly and easily see how your application behaves in different regions, hosts or versions.

InsightFinder Unified Intelligence Engine platform (UIE) provides human-centered AI solutions to identify root causes of incidents and prevent them from happening. InsightFinder uses patented self-tuning, unsupervised machine learning to continuously learn from logs, traces and triage threads of DevOps Engineers and SREs to identify root causes and predict future incidents. Companies of all sizes have adopted the platform and found that they can predict business-impacting incidents hours ahead of time with clearly identified root causes. You can get a complete overview of your IT Ops environment, including trends and patterns as well as team activities. You can also view calculations that show overall downtime savings, cost-of-labor savings, and the number of incidents solved.

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/

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.

Get a complete picture of your app's performance in production. A continuous profiling will ensure that you never miss any important data. You never know when you will need profiling information, so collect it with low overhead. Many organizations waste 20-30% of their resources on code paths that can be easily optimized. The Parca Agent is designed to lower the bar for profiling by requiring zero instrumentation of the entire infrastructure. Start by deploying in your infrastructure! Parca can determine (with confidence and statistical significance), hot paths to optimize, using profiling data collected throughout time. It can also show differences in any query, whether it's comparing software versions or any other dimension. Profiling data can provide unique insight into the code that a process executed. Memory leaks and momentary spikes in CPU, I/O, or both, which cause unexpected behavior, are situations that are difficult to troubleshoot.

CtrlStack manages many operational activities and sources for changes to reduce risk, track change impact, find root causes of production problems fast, and reduce risks. Relationship mapping is a way to find meaningful connections and interactions among data, such as logs, events, and traces. This "data between data" is represented using a native graph database at speed and scale. In one click, you can see all changes across commits and configuration files. To avoid reverting other's changes, capture all context surrounding an incident as it happens. Get insight into the context of an incident, including who, what, and when it occurred and how it affects operations. Use a DevOps diagram to collaborate across teams and share data knowledge.

Our pre-built dashboards work and allow you to monitor your cluster's health and troubleshoot problems faster. Our clear pricing makes it easy for you to get started right away. ContainIQ deploys three agents inside your cluster. One replica deployment collects metrics and events using Kubernetes API. Two additional daemon sets collect logs from all your pods/containers. The second collects latency information for each pod on that node. Monitor latency by microservice or by path, including p95 and p99, average and RPS. It works instantly without the need for middleware or application packages. Set up alerts for significant changes. You can search functionality, filter by date range and view data over time. View all incoming and outgoing requests along with metadata. Graph P99,P95, average latency and error rate over time for each URL. For debugging problems when they arise, correlate logs are useful.

Helios gives security teams context and actionable insights at runtime that reduce alert fatigue. This is done by providing real-time visibility of app behavior. We provide accurate insights into the software components that are in use and their data flow, providing an accurate assessment of the risk profile. Save time by prioritizing fixes according to the unique context of your application - focusing on its real attack surface. Security teams can identify which vulnerabilities need to be fixed by using the applicative context. Once the proof is in hand, it is not necessary to convince the development team that a particular vulnerability exists.

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

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.

WISdom connects database, technical, and financial teams, enabling a healthy, optimized environment, reduced data costs and all on one platform. View your entire data ecosystem from one location, unifying code, and uncovering performance potential. WISdom provides you with a comprehensive view of your environment, while also providing recommendations and context about server health. Enterprise dashboards will show you what are the most important issues and opportunities to address in your environment today. Most DBAs spend 90 percent of their time proactively identifying issues, fixing them, and optimizing systems. This is why WISdom is built around workload optimization. WISdom is a workload optimization tool that allows users to analyze code, identify statements with the most expensive code and optimize their workload. WISdom provides improved monitoring and alerting of SQL Server environments. Machine learning is used to minimize false positives, and focus on critical issues.