Arize AI Alternatives

Build. Test. Automate. Empower your whole team to build and maintain automated tests, not just developers. Meet your testing demands fast. Get full test coverage in days, not months. Our natural-language tests are extremely stable to code changes. When tests break our AI will repair it in minutes. Go Agile/DevOps by setting up Continuous Testing. Push features in production the same day. Boozang supports the following test approaches: - Codeless Record/Replay interface - BDD / Cucumber - API testing - Model-based testing - HTML Canvas testing The following features makes your testing a breeze - In-browser console debugging - Screenshots to show where test fails - Integrate to any CI server - Test with unlimited parallel workers to speed up tests - Root-cause analysis reports - Trend reports to track failures and performance over time - Test management integration (Xray / Jira)

Sematext Cloud is an innovative, unified platform with all-in-one solution for infrastructure monitoring, application performance monitoring, log management, real user monitoring, and synthetic monitoring to provide unified, real-time observability of your entire technology stack. It's used by organizations of all sizes and across a wide range of industries, with the goal of driving collaboration between engineering and business teams, reducing the time of root-cause analysis, understanding user behaviour and tracking key business metrics. The main capabilities range from log monitoring to APM, server monitoring, database monitoring, network monitoring, uptime monitoring, website monitoring or container monitoring Find complete details on our website. Or better: start a free demo, no email address required.

Epsagon enables 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. Increase development velocity and reduce application downtime with Epsagon.

We solve your most urgent business challenges with straightforward, flexible and scalable packages built to make your digital transformation a reality. Get started with our leading business observability platform, today. Get full-stack observability with a business lens from AppDynamics and Cisco. Prioritize what’s most important to your business and your people so you can see, share and take action in real-time. Turn performance into profit with a deeper understanding of user and application behavior. Correlate full-stack performance with key business metrics like conversions and quickly resolve issues before they impact the bottom line. Confidently face the unknowns in today’s technology landscape with easy-to-implement solutions that fuel growth, delight your customers and keep your people engaged in driving your business success. Connect app performance to customer experience and business outcomes, helping you prioritize the most critical issues before they affect your customers.

Netreo is the most comprehensive full stack IT infrastructure management and observability platform. We provide a single source of truth for proactive performance and availability monitoring for large enterprise networks, infrastructure, applications and business services. Our solution is used by: - IT Executives to have full visibility from the business service right down into the infrastructure and network that supports it. - IT Engineering departments as a decision support system for capacity planning, and architecting modern solutions. - IT Operations teams for real time visibility into what is failing in their environment, what bottlenecks exist and who it is affecting. We provide all of these insights for systems and vendor mixes in large heterogeneous and constantly evolving environments. We have an extensive and growing list of supported vendors (over 350 integrations) including network vendors, servers, storage, virtualization, cloud platforms and others.

Get scores for factual accuracy, context retrieval quality, guideline adherence, tonality, and many more. You can’t improve what you can’t measure. UpTrain continuously monitors your application's performance on multiple evaluation criterions and alerts you in case of any regressions with automatic root cause analysis. UpTrain enables fast and robust experimentation across multiple prompts, model providers, and custom configurations, by calculating quantitative scores for direct comparison and optimal prompt selection. Hallucinations have plagued LLMs since their inception. By quantifying degree of hallucination and quality of retrieved context, UpTrain helps to detect responses with low factual accuracy and prevent them before serving to the end-users.

Get the full picture of your model's performance. Log inputs and outputs and seamlessly enrich them with metadata and user feedback. Figure out how your model is really working, and where you can improve. Monitor for errors and discover underperforming cohorts and use cases. The best models are built on user data. Programmatically gather unusual or underperforming examples to retrain your model. Stop manually reviewing thousands of outputs when changing your prompt or model. Evaluate your LLM-powered apps programmatically. Detect and fix degradations quickly. Monitor new deployments in real-time and seamlessly edit the version of your app your users interact with. Connect your self-hosted or third-party model and your existing data sources. Process enterprise-scale data with our serverless streaming dataflow engine. Gantry is SOC-2 compliant and built with enterprise-grade authentication.

The open-source ML observability platform. Evaluate, test, and monitor ML models from validation to production. From tabular data to NLP and LLM. Built for data scientists and ML engineers. All you need to reliably run ML systems in production. Start with simple ad hoc checks. Scale to the complete monitoring platform. All within one tool, with consistent API and metrics. Useful, beautiful, and shareable. Get a comprehensive view of data and ML model quality to explore and debug. Takes a minute to start. Test before you ship, validate in production and run checks at every model update. Skip the manual setup by generating test conditions from a reference dataset. Monitor every aspect of your data, models, and test results. Proactively catch and resolve production model issues, ensure optimal performance, and continuously improve it.

Langfuse is an open source LLM engineering platform to help teams collaboratively debug, analyze and iterate on their LLM Applications. Observability: Instrument your app and start ingesting traces to Langfuse Langfuse UI: Inspect and debug complex logs and user sessions Prompts: Manage, version and deploy prompts from within Langfuse Analytics: Track metrics (LLM cost, latency, quality) and gain insights from dashboards & data exports Evals: Collect and calculate scores for your LLM completions Experiments: Track and test app behavior before deploying a new version Why Langfuse? - Open source - Model and framework agnostic - Built for production - Incrementally adoptable - start with a single LLM call or integration, then expand to full tracing of complex chains/agents - Use GET API to build downstream use cases and export data

Enable observability to detect data and ML issues faster, deliver continuous improvements, and avoid costly incidents. Start with reliable data. Continuously monitor any data-in-motion for data quality issues. Pinpoint data and model drift. Identify training-serving skew and proactively retrain. Detect model accuracy degradation by continuously monitoring key performance metrics. Identify risky behavior in generative AI applications and prevent data leakage. Protect your generative AI applications are safe from malicious actions. Improve AI applications through user feedback, monitoring, and cross-team collaboration. Integrate in minutes with purpose-built agents that analyze raw data without moving or duplicating it, ensuring privacy and security. Onboard the WhyLabs SaaS Platform for any use cases using the proprietary privacy-preserving integration. Security approved for healthcare and banks.

The Robust Intelligence Platform integrates seamlessly into your ML lifecycle to eliminate model failures. The platform detects your model’s vulnerabilities, prevents aberrant data from entering your AI system, and detects statistical data issues like drift. At the core of our test-based approach is a single test. Each test measures your model’s robustness to a specific type of production model failure. Stress Testing runs hundreds of these tests to measure model production readiness. The results of these tests are used to auto-configure a custom AI Firewall that protects the model against the specific forms of failure to which a given model is susceptible. Finally, Continuous Testing runs these tests during production, providing automated root cause analysis informed by the underlying cause of any single test failure. Using all three elements of the Robust Intelligence platform together helps ensure ML Integrity.

Protect business service-level agreements with dashboards to monitor service health, troubleshoot alerts and perform root cause analysis. Reduce MTTR with real-time event correlation, automated incident prioritization and integrations with ITSM and orchestration tools. Use advanced analytics like anomaly detection, adaptive thresholding and predictive health scores to monitor KPI data and prevent issues 30 minutes in advance. Monitor performance the way the business operates with pre-built dashboards that track service health and visually correlate services to underlying infrastructure. Use side-by-side displays of multiple services and correlate metrics over time to identify root causes. Predict future incidents using machine learning algorithms and historical service health scores. Use adaptive thresholding and anomaly detection to automatically update rules based on observed and historical behavior, so your alerts never become stale.

Reimagined observability for context and performance in one place, across all stacks and any scale. Gain comprehensive end-to-end visibility by monitoring applications, infrastructure, databases, and more seamlessly on a single, intuitive dashboard. Effortlessly trace and analyze digital journeys in just a few clicks, right from the browser and applications to infrastructure. Uncover valuable insights into user journeys, understand dropouts, and pinpoint critical points in business transactions through deep user analytics and real user monitoring (RUM). Quickly adapt, optimize and innovate with real-time visibility and rapid root-cause analysis. Access our team of experts round-the-clock, 365 days a year to ensure you receive timely assistance and personalized support to address your specific needs.

Deploy all major ML frameworks such as Pytorch, Onnx, XGBoost etc with 1 line of code. Don't have your own models? Deploy our prebuilt models that have been optimised to run with sub-second latency. Fine-tune smaller models on particular tasks in order to decrease costs and latency while increasing performance. It takes just a few lines of code and don't worry about infrastructure, we got it. Integrate with top ML observability platforms in order to be alerted about feature or prediction drift, compare model versions and resolve issues quickly. Discover the root causes for prediction and feature drift to resolve degraded model performance. Understand which features are contributing most to the performance of your model.

Drive transformation with 360° observability over your whole IT environment. VirtualMetric is a completely agentless solution that is easy to deploy, easy to use and easy to scale. VirtualMetric is an all-in-one infrastructure monitoring suite ensuring the health and reliability of your IT environment. Get 360 ° observability, smart alarms, predictive analysis and AI capabilities to ensure the stress-free management of your infrastructure. VirtualMetric is a full stack monitoring and reporting software for your bare metal servers and virtualization. The all-in-one monitoring suite covers fully your whole IT stack and monitoring needs. Fast root-cause analysis of infrastructure issues, improved performance and infrastructure health. Centralized management suite, which is easy to use and will save you time and money. VirtualMetric’s performance counters are in real-time and provide you with full visibility over your servers, virtual machines and inventory.

Monitor your data health and pipeline performance. Gain unified visibility for pipelines running on cloud-native tools like Apache Airflow, Apache Spark, Snowflake, BigQuery, and Kubernetes. An observability platform purpose built for Data Engineers. Data engineering is only getting more challenging as demands from business stakeholders grow. Databand can help you catch up. More pipelines, more complexity. Data engineers are working with more complex infrastructure than ever and pushing higher speeds of release. It’s harder to understand why a process has failed, why it’s running late, and how changes affect the quality of data outputs. Data consumers are frustrated with inconsistent results, model performance, and delays in data delivery. Not knowing exactly what data is being delivered, or precisely where failures are coming from, leads to persistent lack of trust. Pipeline logs, errors, and data quality metrics are captured and stored in independent, isolated systems.

Reduce your hardware costs while improving performance with Opster’s AutoOps platform by optimizing mapping, stabilizing operations and improving resource utilization. You need more than orchestration, management capabilities and ticket-based support. AutoOps covers everything you need in real-time, with hands-on support. AutoOps diagnoses issues across all aspects of Elasticsearch operations. Once diagnosed, the system not only provides precision root cause analysis, but also resolves the issue. The AutoOps platform can perform advanced optimizations such as: shard rebalancing, blocking heavy searches, optimizing templates and more. These optimizations will ensure that your cluster will operate at peak performance and maximum resiliency. By optimizing mapping, stabilizing operations and improving resource utilization, Opster’s AutoOps platform allows customers to significantly downsize the needed hardware for their deployment.

Get accurate failure alerts weeks or months in advance with real-time data and predictive analytics. Leverage the combination of prescriptive maintenance, root cause analysis, RAM analysis and more to address issues at the equipment, process and system levels. Quickly deploy automated Asset Performance Management solutions through low-touch machine learning to predict asset failures and reduce downtime — plant-wide, system-wide or across multiple locations.

Create customized monitors for your machine learning models with our magically-simple monitor builder, and get alerts for issues like concept drift, model performance degradation, bias and more. Aporia integrates seamlessly with any ML infrastructure. Whether it’s a FastAPI server on top of Kubernetes, an open-source deployment tool like MLFlow or a machine learning platform like AWS Sagemaker. Zoom into specific data segments to track model behavior. Identify unexpected bias, underperformance, drifting features and data integrity issues. When there are issues with your ML models in production, you want to have the right tools to get to the root cause as quickly as possible. Go beyond model monitoring with our investigation toolbox to take a deep dive into model performance, data segments, data stats or distribution.

IBM® Z® Operations Analytics is a tool that enables you to search, visualize and analyze large amounts of structured and unstructured operational data across IBM Z environments, including log, event and service request data and performance metrics. Leverage your analytics platform and machine learning to gain enterprise visibility, identify issues in your workloads, locate hidden problems and perform root cause analysis faster. Use machine learning to baseline normal system behavior and detect operational anomalies. Detect emerging issues across services, so you can proactively alert and cognitively adjust to changes. Gain expert advice for corrective actions and greater service assurance. Identify unusual workload behaviors. Locate common issues hidden in operational data. Reduce time required for root cause analysis. Harness the domain expertise of IBM Z. Leverage IBM Z insights on your analytics platform.

Gain unprecedented insight into sales performance with Sugar Discover—A time-aware approach to revenue analytics that tracks extensive metrics and historical performance to alert you proactively to issues or opportunities. Going a step further, Discover provides root cause analysis for its findings without you having to do anything. Sugar is the only CX platform built on a cutting-edge event stream database that records every change in the customer journey to rewind the past and predict the future. Sugar Discover comes with key metrics and commonly used KPIs out-of-the-box to eliminate the need to build your own analytical database, learn a complicated tool, or hire a data scientist. Unlike standard reporting, Sugar Discover gives you historical perspective—it leverages data from every point in time to enable more informed decisions. Discover’s time-aware technology helps you understand past performance to make accurate predictions about the future.

Know before you go to the public cloud with a single AI-powered observability platform to migrate, control cost, optimize performance, monitor, and drive uptime for your infrastructure across data centers, private and public clouds. The most difficult challenges facing enterprises as they seek to leverage public clouds are how to “know before you go” which workloads to migrate and how to avoid unexpected costs and performance degradation once workloads are operating in the cloud. With the Virtana unified observability platform, you can migrate and optimize across hybrid, public, and private cloud environments. This modular hybrid-cloud infrastructure optimization platform collects high-fidelity data — then apply AIOps technologies, including machine learning and advanced data analytics to to provide intelligent observability of singular workloads to make better decisions about what to move and where to move it while still meeting performance requirements.

Kubernetes-native security and observability. Security and observability as code for cloud-native applications. Cloud-native security as code for hosts, VMs, containers, Kubernetes components, workloads, and services to secure north-south and east-west traffic, enable enterprise security controls, and ensure continuous compliance. Kubernetes-native observability as code to collect real-time telemetry, enriched with Kubernetes context, for a live topographical view of interactions between components from hosts to services. Rapid troubleshooting with machine-learning powered anomaly and performance hotspot detection. Single framework to centrally secure, observe, and troubleshoot multi-cluster, multi-cloud, and hybrid-cloud environments running Linux or Window containers. Update and deploy policies in seconds to enforce security and compliance or resolve issues.

Censius is an innovative startup in the machine learning and AI space. We bring AI observability to enterprise ML teams. Ensuring that ML models' performance is in check is imperative with the extensive use of machine learning models. Censius is an AI Observability Platform that helps organizations of all scales confidently make their machine-learning models work in production. The company launched its flagship AI observability platform that helps bring accountability and explainability to data science projects. A comprehensive ML monitoring solution helps proactively monitor entire ML pipelines to detect and fix ML issues such as drift, skew, data integrity, and data quality issues. Upon integrating Censius, you can: 1. Monitor and log the necessary model vitals 2. Reduce time-to-recover by detecting issues precisely 3. Explain issues and recovery strategies to stakeholders 4. Explain model decisions 5. Reduce downtime for end-users 6. Build customer trust

The most complete network observability solution for use with modern data platforms, providing unprecedented insights at any scale. ElastiFlow allows organizations to achieve unprecedented levels of network performance, availability, and security. ElastiFlow provides granular information about network traffic flows, including source and destination IP addresses, ports, protocols, and the amount of data transmitted. This information allows network administrators to gain deep insights into the network's performance and identify potential issues. ElastiFlow is highly valuable for diagnosing and troubleshooting network issues such as congestion, high latency, or packet loss. By analyzing the network traffic, administrators can pinpoint the cause of the problem and take appropriate action to resolve it. By leveraging ElastiFlow, organizations can improve their security posture, detect and respond to threats more effectively, and maintain compliance with regulatory requirements.

Sensai provides AI based anomaly detection, root cause analysis and prediction tool, enabling real time resolution of issues. Sensai AI solution significantly improves uptime & time to root cause. Empowers IT leaders to manage SLAs for improved performance and profitability. Streamlines & automates anomaly detection, prediction, root cause analysis (RCA) & resolution. Holistic view & integrated analytics through integration w/3rd party tools. Pre-trained algorithms & models from day one.

InsightFinder Unified Intelligence Engine (UIE) platform provides human-centered AI solutions for identifying incident root causes, and predicting and preventing production incidents. Powered by patented self-tuning unsupervised machine learning, InsightFinder continuously learns from metric time series, logs, traces, and triage threads from SREs and DevOps Engineers to bubble up root causes and predict incidents from the source. Companies of all sizes have embraced the platform and seen that business-impacting incidents can be predicted hours ahead with clearly pinpointed root causes. Survey a comprehensive overview of your IT Ops ecosystem, including patterns, trends, and team activities. Also view calculations that demonstrate overall downtime savings, cost of labor savings, and number of incidents resolved.

Nazar was created from our own needs to manage multiple databases in multi-cloud or hybrid environments. It is production ready for the main database engines and completely eliminates the need for using multiple tools. It saves one a lot of time by making a standard and easy way to setup new servers in the platform. Get a normalized view of your database's behavior on a single dashboard without having to use multiple tools with completely different views and metrics from one another. Setting up, tracing and investigating logs and querying data dictionaries every time is not where the race is won. Nazar uses the resources already available in the DBMS for monitoring and does not need to rely on agents. NAZAR automates anomaly detection and root-cause analysis, reducing mean time to resolution (MTTR) and detecting issues to avoid incidents for peak application and business performance.

Aurea Monitor delivers the system monitoring, root-cause analysis, and issue identification tools you need to run your business in real time. Find and fix system issues before they impact your customers with real-time monitoring. You can’t afford delays in identifying and fixing the application issues that affect your customers. Aurea Monitor speeds your ability to detect potential pitfalls and gaps in system operations and performance and swiftly correct them to improve customer experience. Automatically discover all the systems in your infrastructure involved in a business process, so you have total visibility as changes or additions happen over time. Move the needle to 100% uptime. Aurea Monitor continually tracks and monitors all processes with proactive issue identification and notifications so you can respond to and resolve issues even faster.

OPUS is a leading industrial no-code AI platform that allows users to model processes and equipment to identify opportunities for optimization and predictive maintenance. Without any programming or coding experience teams can analyze their data, predict future performance, identify opportunities to reduce power consumption, improve productivity, and make adjustments to settings which can drastically improve operational outcomes. Dive deeper into your asset's data than ever before. Discover unexpected correlations that existed unnoticed, and root cause analysis into individual components so you can focus your efforts. Improve safety, compliance and environmental outcomes through artificial intelligence predictive insights, allowing you to plan interventions and make informed business decisions. With rapid deployment & AI model results in just minutes, you can unleash the power of your operational data and experience ROI. Optimize your entire facility, plant or worksite.

Sightline Enterprise Data Manager™ (EDM) is a powerful IT monitoring and performance analytics solution that provides real-time visibility across today’s modern cloud, virtual and hybrid IT environments. Sightline leverages big data visualization, predictive analytics and machine learning to deliver root cause analysis, real-time anomaly detection, automated forecasting and capacity planning to help organizations identify infrastructure problems.

StackState's Topology and Relationship-Based Observability platform lets you manage your dynamic IT environment more effectively by unifying performance data from your existing monitoring tools into a single topology. Enabling you to: 1. 80% Decreased MTTR: by identifying the root cause and alerting the right teams with the correct information. 2. 65% Fewer Outages: through real-time unified observability and more planful planning. 3. 3x Faster Releases: by giving time back to developers to increase implementations. Get started today with our free guided demo: https://www.stackstate.com/schedule-a-demo

Easily investigate machine data to help identify the root cause of IT issues faster. Powerfully designed and intuitive log aggregation, tagging, filtering, and alerting for effective troubleshooting. Fully integrated with Orion Platform products, enabling a unified view of IT infrastructure monitoring and associated logs. We’ve worked as network and systems engineers, so we understand your problems and how to solve them. Your infrastructure is constantly generating log data to provide performance insight. Collect, consolidate, and analyze thousands of syslog, traps, Windows, and VMware events to perform root-cause analysis with log monitoring tools from Log Analyzer. Perform searches using basic matching. Execute searches using multiple search criteria and apply filters to narrow results. Save, schedule, and export search results within the log monitoring software.

Innovate faster in the cloud, elevate user experience and future-proof your applications. Built for the cloud-native enterprise, Splunk helps you solve modern issues. Detect any issue before it turns into a customer problem. Reduce MTTR with our real-time, AI-driven Directed Troubleshooting. Flexible, open-source instrumentation eliminates lock-in. Maximize performance by seeing everything in your application, and act on AI-driven analytics. To deliver a flawless end-user experience, you need to observe everything. With NoSample™ full-fidelity trace ingestion, leverage all your trace data to identify any anomaly. Reduce MTTR with Directed Troubleshooting to quickly understand service dependencies, correlation with underlying infrastructure and root-cause error mapping. Breakdown and explore any transaction by any metric or dimension. Quickly and easily understand how your application behaves for different regions, hosts, versions or users.

BMC Helix Operations Management is a fully integrated, cloud-native, observability and AIOps solution designed to tackle challenging hybrid-cloud environments. Take a service-centric approach to observability data for truly effective AIOps. Combine 3rd party observability data such as metrics, events, logs, incidents, changes and topologies into a central IT data store. See service health and enable best-in-class root cause isolation via auto-generated dynamic business service models. Improve signal-to-noise ratio with AI event suppression, de-duplication, and correlation to create actionable situations. Gain immediate root cause isolation through AI probability assignments to causal nodes using data and service models. Prevent issues before they occur with Business Service Health monitoring and AI outage prediction. Troubleshoot rapidly with log enrichment and analytics. Easily request and execute automations from BMC or 3rd party tools.

Autointelli Inc, an AIOps company, provides solutions that handle modern IT operations (ITOps) with a duo of automation and machine learning. With a solution-oriented approach, we thrive in developing an AIOps platform that simplifies data center automation. Automate them with Autointelli AIOps platform – reduce alert noise, identify root causes and free your resources for high-value IT tasks. Build a better digital workplace with us. Autointelli AIOps Platform automatically correlates the events faster and escalates the tedious incidents to respective engineers. Autointelli AIOps Platform comes with a self-service automation feature that allows you to create any number of workflows to automate. Root cause analysis helps to identify the underlying cause of a problem in hardware and software. Analytics should enhance your business performance and provide possible insights from all major data sources.

The only Data Observability platform that provides complete control of enterprise data systems. Provides comprehensive, cross-sectional visibility into complex, interconnected data systems. Synthesizes signals across workloads, data quality, infrastructure and security. Improves data processing and operational efficiency. Automates end-to-end data quality monitoring for fast-changing, mutable datasets. Acceldata provides a single pane of glass to help predict, identify, and fix data issues. Fix complete data issues in real-time. Observe business data flow from a single pane of glass. Uncover anomalies across interconnected data pipelines.

VictoriaMetrics Anomaly Detection is a service that continuously scans time series stored in VictoriaMetrics and detects unexpected changes within data patterns in real time. It does so by utilizing user-configurable machine learning models. In the dynamic and complex world of system monitoring, VictoriaMetrics Anomaly Detection, a part of our Enterprise offering, is a pivotal tool for achieving advanced observability. It empowers SREs and DevOps teams by automating the intricate task of identifying abnormal behavior in time-series data. It goes beyond traditional threshold-based alerting, utilizing machine learning techniques to detect anomalies and minimize false positives, thus reducing alert fatigue. Providing simplified alerting mechanisms atop unified anomaly scores enables teams to spot and address potential issues faster, ensuring system reliability and operational efficiency.

Monitor, analyze, and manage multi-cloud applications and infrastructure environments with full-stack visibility, prebuilt analytics, and automation using Oracle Cloud Observability and Management Platform. Complete visibility through infrastructure monitoring, real user experience, synthetic monitoring, and distributed tracing. Monitor and troubleshoot issues faster by analyzing data from any source using interactive, intuitive dashboards. Unified monitoring, capacity planning, and database administration capabilities for on-premises and cloud databases. Deploy and manage Oracle Cloud resources using Terraform-based automation and manage data exchanges. Complete app performance visibility through real user experience, synthetic monitoring, and distributed tracing. Unified database monitoring and administration capabilities for on-premises and cloud databases. Easily review log data, diagnose issues, and generate notifications using predefined triggers.

IBM® Instana® is the gold standard of incident prevention with automated full-stack visibility, 1-second granularity and 3 seconds to notify. With today’s highly dynamic and complex cloud environments, the average cost of an hour of downtime can reach six figures and beyond1. Traditional application performance monitoring (APM) tools simply aren’t fast enough to keep up or thorough enough to contextualize the issues identified. Also, they are typically limited to super users who must complete months of training to learn. IBM Instana Observability goes beyond traditional APM solutions by democratizing observability so anyone across DevOps, SRE, platform engineering, ITOps and development can get the data they want with the context they need. Instana automatically delivers continuous high-fidelity data at 1-second granularity and end-to-end traces with the context of logical and physical dependencies across mobile, web, applications and infrastructure.

Bigeye is the data observability platform that helps teams measure, improve, and communicate data quality clearly at any scale. Every time a data quality issue causes an outage, the business loses trust in the data. Bigeye helps rebuild trust, starting with monitoring. Find missing and busted reporting data before executives see it in a dashboard. Get warned about issues in training data before models get retrained on it. Fix that uncomfortable feeling that most of the data is mostly right, most of the time. Pipeline job statuses don't tell the whole story. The best way to ensure data is fit for use, is to monitor the actual data. Tracking dataset-level freshness ensures pipelines are running on schedule, even when ETL orchestrators go down. Find out about changes to event names, region codes, product types, and other categorical data. Detect drops or spikes in row counts, nulls, and blank values to ensure everything is populating as expected.

Bridging observability with automated orchestration for self-managed, resilient applications at scale. Every second, huge volumes of data are generated by observability and monitoring tools, capturing metrics, logs, and traces about all aspects of complex, dynamic applications. Yet it’s still up to humans to troubleshoot and make sense of all this data. They are locked in a never-ending cycle of responding to alerts, identifying root causes, and determining the best action for remediation. The process hasn’t changed fundamentally in decades, and it’s still labor-intensive, reactive, and costly. Causely removes the need for human troubleshooting by capturing causality in software, closing the gap between observability and action. For the first time, the entire lifecycle of detection, root cause analysis, and remediation of defects in applications is fully automated. With Causely, defects are identified and resolved in real-time, so applications can scale with high performance.

Nucleus helps ML teams build better datasets. Bring together your data, ground truth, and model predictions to effortlessly fix model failures and data quality issues. Optimize your labeling spend by identifying class imbalance, errors, and edge cases in your data with Scale Nucleus. Significantly improve model performance by uncovering and fixing model failures. Find and label high-value data by curating unlabeled data with active learning and edge case mining. Curate the best datasets by collaborating with ML engineers, labelers, and data ops on the same platform. Easily visualize and explore your data to quickly find edge cases that need labeling. Check how well your models are performing and always ship the best one. Easily view your data, metadata, and aggregate statistics with rich overlays, using our powerful UI. Nucleus supports visualization of images, videos, and lidar scenes, overlaid with all associated labels, predictions, and metadata.

The complete self-healing IT solution for your enterprise. Thanks to its unique cognitive capabilities, HEAL prevents IT system failures before they even happen, letting you focus your time and energy on other aspects of your business. In a fast paced world where every second counts, it’s no longer good enough to detect and flag incidents after they have happened. A self-healing solution that predicts and prevents rather than just fix what’s broken, HEAL is a new age IT tool that uses AI algorithms and machine learning models to help enterprises run without a hitch. Using a patented technique called ‘workload-behavior correlation’, HEAL analyses all the aspects that go into the smooth running of an IT system (the cumulative volume, composition and payload), and reacts every time an abnormal behavior occurs, triggering either a healing action or a scaling action depending on the root cause of the problem.

Sumo Logic offers a cloud solution for log management and metrics monitoring for IT and security teams of organizations of all sizes. Faster troubleshooting with integrated logs, metrics and traces. One platform. Many use cases. Increase your troubleshooting effectiveness. Sumo Logic helps you reduce downtime and move from reactive to proactive monitoring with cloud-based modern analytics powered by machine learning. Quickly detect Indicators of Compromise (IoCs), accelerate investigation, and ensure compliance using Sumo Logic Security Analytics. Enable data-driven business decisions and predict and analyze customer behavior using Sumo Logic’s real-time analytics platform. The Sumo Logic platform helps you make data-driven decisions and reduce the time to investigate security and operational issues so you can free up resources for more important activities.

Onboard your data and models to Openlayer and collaborate with the whole team to align expectations surrounding quality and performance. Breeze through the whys behind failed goals to solve them efficiently. The information to diagnose the root cause of issues is at your fingertips. Generate more data that looks like the subpopulation and retrain the model. Test new commits against your goals to ensure systematic progress without regressions. Compare versions side-by-side to make informed decisions and ship with confidence. Save engineering time by rapidly figuring out exactly what’s driving model performance. Find the most direct paths to improving your model. Know the exact data needed to boost model performance and focus on cultivating high-quality and representative datasets.

Deepen your understanding of your organization with workforce analytics, deep-dive visualization and org charts, and reporting capabilities. Leverage machine learning in HR to automate problem detection and root cause analysis. Predict the outcome and impact of organizational changes to stay proactive and responsive in the face of change. Modernize the way you do organizational design and build the future state of your organization by embracing change as a way of life with continuous AI-driven organizational design. The business team successfully builds a well-designed organization that scales and adapts quickly to change, while retaining talent and hiring more effectively. Finance teams have visibility into forecasted HR budgets through predictive reporting.

ExtraView is an enterprise software platform implementing business process management, global quality management systems for CAPA, adverse event reporting, food safety, bug and defect tracking, change management, customer support, helpdesk, field audit, and other workflow or issue management systems. Use out-of-the-box solutions or implement a custom requirement. Available as a service in the cloud or on your own servers. Simple to configure, yet provides a quality platform on which to implement fully validated systems such as incident management, CAPA, adverse event reporting, & root cause analysis, clinical trial data management and food safety. Implement bug-tracking, customer support, requirements management, change management and other issue-tracking systems. Many customers can take advantage of the full-featured, free, downloadable version! Learn how financial companies implement systems that regulate and control audit systems, provide corporate governance and risk management.

Deploy an end-to-end service assurance solution with automated root cause analysis using event correlation, machine learning (ML), and topology. Oracle Unified Assurance can be deployed as an overlay platform to unify monitoring across existing assurance tools or as a standalone assurance solution. Integrate the solution into multivendor networks and management systems, or deploy it in a hybrid mode. Oracle’s Unified Assurance solution is helping customers automate assurance and implement assisted and full closed-loop automation. Provide dynamic, end-to-end assurance for 5G solutions at scale while ensuring optimal quality of service and customer experience with machine learning (ML) analytics. Automate operations with end-to-end network and service assurance by federating across existing tools. Leverage existing investments with a roadmap to rationalize the tools and build the basis for autonomous operations.

AI-powered anomaly detection and root cause analysis for the metrics that matter to your business. Using machine learning, Avora autonomously monitors your business metrics 24/7 and alerts you to critical events so that you can take action in hours, rather than days or weeks. Continuously analyze millions of records per hour for unusual behavior, uncovering threats and opportunities in your business. Use root cause analysis to understand what factors are driving your business metrics up or down so that you can make changes quickly, and with confidence. Embedded Avora’s machine learning capabilities and alerts into your own applications, using our suite of APIs. Get alerted about anomalies, trend changes and thresholds via email, Slack, Microsoft Teams, or to any other platform via Webhooks. Share relevant insights with other team members​. Invite others to track existing metrics and receive notifications in real-time.