Alternatives to Kensu

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.

OpManager is the ideal end-to-end network monitoring tool for your organization's network. With OpManager, you can keep a close eye on health, performance, and availability levels of all network devices. This includes monitoring switches, routers, LANs, WLCs, IP addresses and firewalls. Insights into your hardware health and performance; monitor CPU, memory, temperature, disk usage, and more to improve efficiency. Seamlessly manage faults and alerts with instant notifications and detailed logs. Streamlined workflows facilitate easy set-up to execute quick diagnosis and corrective measures. The solution also comes with powerful visualization tools such as business views, 3d data center views, topology maps, heat maps, and customizable dashboards. Get proactive in capacity planning and decision-making with over 250 predefined reports covering all important metrics and areas in your network. Overall, OpManager's detailed management capabilities make it the ideal solution for IT administrators to achieve network resiliency and efficiency.

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.

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.

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

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.

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.

Do you struggle to manage all those alerts and tickets that come in? Dell APEX AIOps can reduce noise, detect incidents sooner, and fix issues faster. Do not let a flood alerts slow you. We remove these annoying alerts automatically so that you can enjoy your day without distraction. Never look at a ticket again. We send you "Situations" instead of tickets so you can fix problems faster before your customers complain. Stop wasting your time switching between tools. We bring all the tools together in one place, so you can manage any incident regardless of its origin. Use AI and ML to identify patterns and prevent them from happening again. Continuous delivery means continuous changes. Dell APEX AIOps automates the incident management workflow to provide continuous improvement. This gives you more time for other important and enjoyable tasks.

BMC Helix Operations Management, a cloud-native, fully integrated, observability, and AIOps system, is designed to address hybrid-cloud environments. For truly effective AIOps, adopt a service-centric approach for observability data. Combine third-party observability data, such as metrics, events logs, incidents and changes, into a central IT storage data store. Service health can be viewed and root cause isolation can be achieved using dynamic business service models that are auto-generated. Increase signal-to-noise ratio through AI event suppression, deduplication and correlation to create actionable circumstances. With data and service models, AI probability assignments to causal nosdes using data and models allow for root cause isolation. Business Service Health monitoring and AI outage prediction can help you prevent problems from ever happening. Log enrichment and analytics make it easy to troubleshoot quickly. Automate your tasks with BMC or third-party tools.

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.

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.

The Observer Platform provides a comprehensive network performance monitoring (NPMD) solution that is ideal for maintaining high performance of all IT services. The Observer Platform is an integrated offering that provides visibility into critical KPIs via pre-defined workflows, starting at high-level dashboards and ending at service anomaly root cause. It is ideal for achieving business goals and solving challenges across the entire IT enterprise lifecycle, including deploying new technologies, managing existing resources, solving service anomalies, and optimizing IT asset use. The Observer Management Server UI (OMS UI) is a cyber security tool. It features simple navigation that allows you to authenticate security threats, manage user access and password data, upgrade web applications, and streamline management tools from a single location.

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.

BindPlane is a unique IT operations data management platform which can deliver a relationship-aware stream real-time logs and metrics. This is the best way to ensure that your performance monitoring platform always has the most accurate data across your entire stack. All your stack data in one place. More than 150 high-fidelity technology connections for apps, infrastructure, and cloud resources are instantly connectable to your favorite monitoring software. Dimensional data can help you identify the root cause of performance problems up to 33% quicker than traditional methods. It allows you to see the inter and intra relationships among different layers of your IT stack. Get immediate insight using our best-practice-based KPIs, data visualizations, and other tools. Share full-stack dashboards and standardize deployment automation using rich APIs. Access to the most popular enterprise technologies and a constantly updated library of plugins will improve analytics accuracy.

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.

Enterprise observability for all of your teams at scale Traditional tools only detect simple threshold-based anomalies. This makes it difficult to distinguish between real issues and false alarms. VMware Tanzu Observability from Wavefront allows you to create smart alerts that dynamically filter out noise and capture true anomalies. It is difficult to troubleshoot distributed cloud applications because of many moving parts, dependencies on other applications, and frequent code changes. Wavefront tracks all metrics from your cloud applications, infrastructure, and clouds. It can be difficult to find the right needle when dealing with thousands of metrics from containerized microservices and distributed cloud applications. AI Genie™, which automatically identifies "unknown unknowns", allows you to quickly find the root cause of an incident - isolate applications, infrastructure, and cloud.

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.

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.

Log management. Upgraded Honeycomb. Honeycomb is designed for modern developers to help them understand and improve their log management. You can quickly query system logs, metrics, and traces to find unknown unknowns. Interactive charts provide the most detailed view against raw, high-cardinality data. You can set Service Level Objectives (SLOs), based on what users are most interested in, to reduce noise alerts and prioritize work. Customers will be happy if you reduce on-call time, ship code faster, and minimize the amount of work required. Find the cause. Optimize your code. View your prod in high-res.

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.

Get a deep understanding of your cloud-native applications, from microservices architectures to serverless architectures, and quickly identify the root causes of problems. APM can be used to identify anomalies, map dependencies and simplify investigations of outliers. Optimize your code with support for popular programming languages, OpenTelemetry and distributed tracing. Identify performance issues using an automated and curated visual representation that includes all dependencies including cloud, messaging and data stores, as well as third-party services, and their performance data. Drill down into anomalies, transactional details, and metrics to perform a deeper analysis.

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.

Zenoss Cloud, the first SaaS-based intelligent IT operation management platform, streams and normalizes all machine information. This unique feature allows for the creation of context to prevent service disruptions in complex, modern IT environments. Zenoss allows enterprises to focus on their business growth by removing the burden of managing operations and architecture. Zenoss helps organizations eliminate infrastructure blindspots, predict business service impacts before they cause outages, and respond faster to incidents -- whatever size the business requires.

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.

VictoriaMetrics Enterprise, a commercial product designed by the creators VictoriaMetrics, is a solution for monitoring and observability in complex environments. It's perfect for organizations with large or rapidly scaling monitoring environments. The Enterprise edition includes all of the features in the Community Edition plus additional enhancements like Downsampling Automated backups / Backup manager Data Retention Per Label/Tenant Multi Tenant Statistic & Anomaly detection. It provides stable releases and long-term support to ensure critical bug fixes, security patches, and other enhancements. The package also includes enterprise security compliance and prioritised feature requests. We can help you reduce storage costs while improving performance of historical data queries. Multiple retentions allow different storage durations for various datasets. Automatic discovery of storage updates the list without restarting services at insert and vmselect.

Only Data Observability platform that allows complete control over enterprise data systems. Comprehensive, cross-sectional visibility of complex, interconnected data systems. Synthesizes signals across workloads and data quality, security, infrastructure, and security. Data processing and operational efficiency are improved. Automates data quality monitoring from start to finish for rapidly changing and mutable datasets. Acceldata offers a single window to identify, predict, and fix data problems. Complete data issues can be fixed in real-time. You can observe the flow of business data from one pane of glass. Find anomalies in interconnected data pipelines.

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.

StackState's Topology & Relationship-Based Observability platform allows you to manage your dynamic IT environment more effectively. It unifies performance data from existing monitoring tools and creates a single topology. This platform allows you to: 1. 80% Reduced MTTR by identifying the root cause of the problem and alerting the appropriate teams with the correct information. 2. 65% Less Outages: Through real-time unified observation and more planned planning. 3. 3.3.2. 3x faster releases: Developers are given more time to implement the software. Get started today with our free guided demo: https://www.stackstate.com/schedule-a-demo

Middleware Observability & management software for Messaging, event processing, and Streaming Across Hybrid Clouds (MESH). - 360 degree situational awareness® with complete observability of Integration MESH - Manage configuration, administration and deployment in a secure manner and automate them. - Track and trace transactions, messages, and flows - Collect data, monitor performance, and benchmark it meshIQ provides granular controls for managing configurations in the MESH, reducing downtime and allowing quick recovery after outages. It allows you to search, browse, track and trace messages in order to detect bottlenecks, speed up root cause analysis, and detect bottlenecks. Unlocks integration blackbox for visibility across MESH infrastructure in order to visualize, analyse, report and predict. Delivers the capability to trigger automated action based on predefined criteria or intelligent AI/ML actions.

Reimagined observability in one place for context and performance, across all stacks at any scale. Monitor applications, infrastructure, databases and more on a single intuitive dashboard to gain comprehensive end-toend visibility. With just a few mouse clicks, you can easily track and analyze digital journeys from the browser to applications and infrastructure. Deep user analytics and real-user monitoring (RUM) can help you gain valuable insights about user journeys, identify dropouts and pinpoint critical business points. Real-time visibility, rapid root-cause analyses and quick adaptations will help you to optimize and innovate. You can reach our team of experts 24/7, 365 days per year to receive timely assistance.

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.

IBM Instana sets the gold standard for incident prevention, offering automated full-stack visibility, 1-second data granularity, and 3-second notifications. In today’s complex and ever-changing cloud environments, even an hour of downtime can lead to six-figure losses or more. Traditional application performance monitoring (APM) tools often fall short—they’re too slow to keep up, lack the breadth to provide actionable context, and are typically reserved for super users who require extensive training to operate them. IBM Instana Observability goes beyond traditional APM by democratizing access to observability. Teams across DevOps, SRE, Platform Engineering, ITOps, and Development can seamlessly access the data they need, enriched with contextual insights. Instana delivers high-fidelity data with 1-second granularity, end-to-end tracing, and comprehensive visibility into logical, physical, and mobile dependencies spanning applications, web services, and infrastructure. At its core, Instana Dynamic APM leverages an agent-based architecture that uses sensors—lightweight, automated programs designed to monitor specific entities. A single agent per host, deployed either as a standalone process or a container.

The cloud-native apps you use today have an order of magnitude higher number of dependencies, ephemerality and releases. APM and proprietary monitoring were created in the era monolithic apps and static infrastructure. They are costly, intrusive, siloed and generate more noise than their value. Although open source and cloud-based monitoring tools provide a solid foundation, they require highly skilled engineers to integrate and maintain the data. Your journey to modern infrastructure is pushing the boundaries of your monitoring framework. It's time to try a new approach. OpsCruise is here! OpsCruise's deep knowledge of Kubernetes combined with our unique ML-based behavior profiling allows your entire team to instantly spot performance degradations and predict their cause. It's a third the cost of current monitoring and you don't have to instrument code, deploy agents or maintain open-source software.

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.

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.

Open source continuous profiling. Find and debug the most painful performance issues in code, infrastructure, and CI/CD pipelines. You can tag your data according to the dimensions that are important to your organization. You can store large volumes of high-cardinality profiling information efficiently and cheaply. FlameQL allows you to create custom queries that select and aggregate profiles quickly for easy analysis. Our suite of profiling software allows you to analyze application performance profiles. Understand CPU and memory resource usage at any time to identify performance issues before your customers do. Store, analyze, and collect profiles from external profiling tools. Link to your OpenTelemetry trace data and get request specific or span specific profiles to enhance other observability information like traces and logs

Application Performance Management Get complete visibility into the health and performance of applications. Detect and resolve performance issues no matter where they occur in the entire stack. No sampling. No blindspots. Log Analytics Search and analyze event data across your applications, infrastructure, security, or business without worrying about indexing, data tiers, retention policies, or cost. Keep all log data always hot. Infrastructure Monitoring Capture metrics across your infrastructure – cloud, Kubernetes, serverless, applications or from over 400 pre-built integrations. Visualize the entire stack and troubleshoot performance issues in real-time. O11y AI Investigate and resolve incidents faster with O11y Investigator. Use natural language to explore observability data with O11y Copilot, generate Regular Expressions effortlessly with O11y Regex, and obtain precise answers with O11y GPT. Observe for Snowflake Comprehensive observability into Snowflake workloads. Optimize performance and resource utilization. Deliver secure and compliant operations.

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.

Grafana Phlare aggregates continuous profiling data while providing high availability, multitenancy and durable storage. This allows you to understand resource usage down to the line numbers in your applications. Grafana Phlare, an open-source database, provides a fast, scalable and highly available storage and querying system for profiling data. Phlare's idea was born during a hackathon held by Grafana Labs. The project was announced at ObservabilityCON in 2022. The project's mission is to enable continuous profiler at scale for the Open Source community, giving developers an understanding of resource usage in their code. It allows users to optimize their infrastructure and understand their application performance.

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.

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.

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.

SolarWinds Observability self-hosted (formerly known by the name Hybrid Cloud Observability), is a comprehensive and integrated full-stack observability tool designed to help organizations increase visibility, intelligence and productivity in on-premises or multi-cloud environments. It integrates data across the IT ecosystem including networks, servers and applications, databases and more. This provides a unified view on service delivery and component dependency. The platform includes features such as network monitoring, flow analysis and monitoring, network device configuration, IP address management and monitoring, user and device tracking and server and application management. It also offers virtualization monitoring and managing, log monitoring and analytics, server configuration management and VoIP and network assurance.

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!

The only real-time, analytics driven multicloud monitoring solution (formerly SignalFx). Monitor any environment using a highly scalable streaming architecture. Open, flexible data collection and quick visualizations of services in seconds. This purpose is for dynamic and ephemeral cloud-native environments of any size (e.g. Kubernetes containers, serverless, container). Identify, visualize, and resolve issues immediately. Predictive streaming analytics allows you to monitor infrastructure performance at cloud scale in real-time. More than 200 pre-built cloud integrations and out-of the-box dashboards allow for quick visualization of your entire stack. Autodiscover, break down, group, and explore cloud, services, and systems. You can quickly and easily see how your infrastructure behaves in relation to different availability zones, Kubernetes Clusters, and other services.

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.

No more data catalog ghost cities. Acryl Cloud accelerates time-to-value for data producers through Shift Left practices and an intuitive user interface for data consumers. Continuously detect data-quality incidents in real time, automate anomaly detecting to prevent breakdowns, and drive quick resolution when they occur. Acryl Cloud supports both pull-based and push-based metadata ingestion to ensure information is reliable, current, and definitive. Data should be operational. Automated Metadata Tests can be used to uncover new insights and areas for improvement. They go beyond simple visibility. Reduce confusion and speed up resolution with clear asset ownership and automatic detection. Streamlined alerts and time-based traceability are also available.

Get a clear view of your data assets: popularity, usage, and schema coverage. Get important insights into your data assets, such as popularity and utilization. Find and filter data based on tags and descriptions in metadata. Get valuable insights about your data assets, such as popularity, usage, quality, and schema cover. Drive data governance and ownership throughout your organization. Stream-lake-warehouse lineage to facilitate data ownership and collaboration. Lineage maps are automatically generated at the field level to help understand the entire data ecosystem. Anomaly detection is based on your data and seasonality patterns. It uses automatic backfilling from historical data. Machine learning thresholds are trained for each data segment and not just metadata.

Add enterprise-level security to your OpenAI usage. OpenAI LLM APIs may be powerful, but lack the visibility and control that enterprises require. Usage Panda fixes this. Usage Panda checks the security policies of requests before they are sent to OpenAI. Avoid unexpected bills by only allowing those requests that are below a certain cost threshold. Opt-in for a log of the entire request, parameters and response to every OpenAI request. Create an unlimited number connections, each with their own custom policies and limitations. Monitor, redact and block malicious attempts at altering or revealing system prompts. Usage Panda's visualizations and custom charts allow you to explore usage in great detail. Receive notifications via email or Slack when you reach a usage threshold or billing limit. Assign costs and policy violations to the end application users, and implement rate limits per user.

Enhancing business performance through the identification and resolution high-priority incidents. The WatchTower Platform, an observability tool, simplifies incident resolution for mainframe environments. It does this by integrating events, data flows and metrics from across IT silos. It provides a unified and user-friendly interface for operations teams, allowing them to streamline workflows. WatchTower, built on familiar AIOps, detects potential problems early, facilitating proactive prevention. OpenTelemetry is used to stream mainframe data to observability software, allowing enterprise SREs identify bottlenecks and improve operational efficiency. WatchTower adds context to alerts, eliminating the need to log into multiple tools in order collect critical information. WatchTower workflows simplify problem identification, investigation and incident resolution. They also streamline problem handover, escalation and problem handover.