Best Free Observability Tools of 2025 - Page 2

Discover an all-encompassing observability platform designed to provide insights, safeguard assets, and resolve issues in your decentralized applications. Our robust SDK, which is both type-safe and user-friendly, allows you to gather and convert data derived from smart contract events, transactions, traces, and states seamlessly. The data you collect is organized into versions for swift and efficient iteration. Create low-code, real-time dashboards in mere moments, utilizing powerful functions for transformation and aggregation. You can visualize metrics and easily navigate through different time spans to gain deeper insights. Additionally, set up real-time alerts to keep your team informed via platforms like Slack, Telegram, Email, and webhooks, enabling prompt reactions to urgent events. Generate structured logs that are searchable and can be linked to real-time dashboards for enhanced accessibility. Sentio is dedicated to fostering the growth of decentralized applications by providing top-notch developer tools, infrastructure, and a guiding philosophy tailored for the crypto landscape. We invite you to leave your email to stay informed about our launch and secure early access to our beta version, ensuring you’re among the first to experience our innovative solutions.

Open source continuous profiling allows you to identify and resolve your most critical performance challenges across code, infrastructure, and CI/CD pipelines. It offers the ability to tag data based on dimensions that are significant to your organization. This solution facilitates the economical and efficient storage of vast amounts of high cardinality profiling data. With FlameQL, users can execute custom queries to swiftly select and aggregate profiles, making analysis straightforward and efficient. You can thoroughly examine application performance profiles using our extensive suite of profiling tools. Gain insights into CPU and memory resource utilization at any moment, enabling you to detect performance issues before your customers notice them. The platform also consolidates profiles from various external profiling tools into a single centralized repository for easier management. Moreover, by linking to your OpenTelemetry tracing data, you can obtain request-specific or span-specific profiles, which significantly enrich other observability data such as traces and logs, ensuring a comprehensive understanding of application performance. This holistic approach fosters proactive monitoring and enhances overall system reliability.

SigNoz serves as an open-source alternative to Datadog and New Relic, providing a comprehensive solution for all your observability requirements. This all-in-one platform encompasses APM, logs, metrics, exceptions, alerts, and customizable dashboards, all enhanced by an advanced query builder. With SigNoz, there's no need to juggle multiple tools for monitoring traces, metrics, and logs. It comes equipped with impressive pre-built charts and a robust query builder that allows you to explore your data in depth. By adopting an open-source standard, users can avoid vendor lock-in and enjoy greater flexibility. You can utilize OpenTelemetry's auto-instrumentation libraries, enabling you to begin with minimal to no coding changes. OpenTelemetry stands out as a comprehensive solution for all telemetry requirements, establishing a unified standard for telemetry signals that boosts productivity and ensures consistency among teams. Users can compose queries across all telemetry signals, perform aggregates, and implement filters and formulas to gain deeper insights from their information. SigNoz leverages ClickHouse, a high-performance open-source distributed columnar database, which ensures that data ingestion and aggregation processes are remarkably fast. This makes it an ideal choice for teams looking to enhance their observability practices without compromising on performance.

Observability platforms that utilize distributed tracing, like Jaeger, play a crucial role in the functioning of contemporary software applications designed with a microservices architecture. By tracking the movement of requests and data through a distributed system, Jaeger provides visibility into how these requests interact with various services, which can often lead to delays or errors. This platform adeptly links these different elements, enabling users to pinpoint performance issues, diagnose errors, and enhance the overall reliability of applications. Furthermore, Jaeger stands out as a fully open source solution that is designed to be cloud-native and capable of scaling indefinitely. Its ability to provide deep insights into complex systems makes it an invaluable tool for developers aiming to optimize application performance.

ElastiFlow stands out as a comprehensive solution for network observability tailored for contemporary data platforms, delivering exceptional insights across various scales. This powerful tool enables organizations to attain remarkable levels of network performance, reliability, and security. ElastiFlow offers detailed analytics on network traffic flows, capturing critical data such as source and destination IP addresses, ports, protocols, and the volume of transmitted data. Such detailed information equips network administrators with the ability to thoroughly assess network performance and swiftly identify potential problems. The tool proves invaluable for diagnosing and resolving network challenges, including congestion, elevated latency, or packet loss. By scrutinizing network traffic patterns, administrators can accurately determine the root cause of issues and implement effective solutions. Utilizing ElastiFlow not only enhances an organization's security posture but also facilitates prompt detection and response to threats, ensuring adherence to regulatory standards. Consequently, organizations can achieve a more robust and responsive network environment, ultimately leading to improved operational efficiency and user satisfaction.

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.

OpenLIT serves as an observability tool that is fully integrated with OpenTelemetry, specifically tailored for application monitoring. It simplifies the integration of observability into AI projects, requiring only a single line of code for setup. This tool is compatible with leading LLM libraries, such as those from OpenAI and HuggingFace, making its implementation feel both easy and intuitive. Users can monitor LLM and GPU performance, along with associated costs, to optimize efficiency and scalability effectively. The platform streams data for visualization, enabling rapid decision-making and adjustments without compromising application performance. OpenLIT's user interface is designed to provide a clear view of LLM expenses, token usage, performance metrics, and user interactions. Additionally, it facilitates seamless connections to widely-used observability platforms like Datadog and Grafana Cloud for automatic data export. This comprehensive approach ensures that your applications are consistently monitored, allowing for proactive management of resources and performance. With OpenLIT, developers can focus on enhancing their AI models while the tool manages observability seamlessly.

Langtrace is an open-source observability solution designed to gather and evaluate traces and metrics, aiming to enhance your LLM applications. It prioritizes security with its cloud platform being SOC 2 Type II certified, ensuring your data remains highly protected. The tool is compatible with a variety of popular LLMs, frameworks, and vector databases. Additionally, Langtrace offers the option for self-hosting and adheres to the OpenTelemetry standard, allowing traces to be utilized by any observability tool of your preference and thus avoiding vendor lock-in. Gain comprehensive visibility and insights into your complete ML pipeline, whether working with a RAG or a fine-tuned model, as it effectively captures traces and logs across frameworks, vector databases, and LLM requests. Create annotated golden datasets through traced LLM interactions, which can then be leveraged for ongoing testing and improvement of your AI applications. Langtrace comes equipped with heuristic, statistical, and model-based evaluations to facilitate this enhancement process, thereby ensuring that your systems evolve alongside the latest advancements in technology. With its robust features, Langtrace empowers developers to maintain high performance and reliability in their machine learning projects.

Eliminate delays, pinpoint inefficiencies, and troubleshoot problems effectively. Become a part of a swiftly growing network of global businesses that are realizing up to 20 times the value and return on investment by utilizing KloudMate, far exceeding other observability platforms. Effortlessly track essential metrics, relationships, and identify irregularities through alerts and tracking issues. Swiftly find critical 'break-points' in your application development process to address problems proactively. Examine service maps for each component within your application while revealing complex connections and dependencies. Monitor every request and operation to gain comprehensive insights into execution pathways and performance indicators. Regardless of whether you are operating in a multi-cloud, hybrid, or private environment, take advantage of consolidated Infrastructure monitoring features to assess metrics and extract valuable insights. Enhance your debugging accuracy and speed with a holistic view of your system, ensuring that you can detect and remedy issues more quickly. This approach allows your team to maintain high performance and reliability in your applications.

Pydantic Logfire serves as an observability solution aimed at enhancing the monitoring of Python applications by converting logs into practical insights. It offers valuable performance metrics, tracing capabilities, and a comprehensive view of application dynamics, which encompasses request headers, bodies, and detailed execution traces. Built upon OpenTelemetry, Pydantic Logfire seamlessly integrates with widely-used libraries, ensuring user-friendliness while maintaining the adaptability of OpenTelemetry’s functionalities. Developers can enrich their applications with structured data and easily queryable Python objects, allowing them to obtain real-time insights through a variety of visualizations, dashboards, and alert systems. In addition, Logfire facilitates manual tracing, context logging, and exception handling, presenting a contemporary logging framework. This tool is specifically designed for developers in search of a streamlined and efficient observability solution, boasting ready-to-use integrations and user-centric features. Its flexibility and comprehensive capabilities make it a valuable asset for anyone looking to improve their application's monitoring strategy.

Tetragon is an adaptable security observability and runtime enforcement tool designed for Kubernetes, leveraging eBPF to implement policies and filtering that minimize observation overhead while enabling the tracking of any process and real-time policy enforcement. With eBPF technology, Tetragon achieves profound observability with minimal performance impact, effectively reducing risks without the delays associated with user-space processing. Building on Cilium's architecture, Tetragon identifies workload identities, including namespace and pod metadata, offering capabilities that exceed conventional observability methods. It provides a selection of pre-defined policy libraries that facilitate quick deployment and enhance operational insights, streamlining both setup time and complexity when scaling. Furthermore, Tetragon actively prevents harmful actions at the kernel level, effectively closing off opportunities for exploitation while avoiding vulnerabilities related to TOCTOU attack vectors. The entire process of synchronous monitoring, filtering, and enforcement takes place within the kernel through the use of eBPF, ensuring a secure environment for workloads. This integrated approach not only enhances security but also optimizes performance across Kubernetes deployments.

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

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

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.

Chaos Genius serves as a DataOps Observability platform specifically designed for Snowflake, allowing users to enhance their Snowflake Observability, thereby minimizing costs and improving query efficiency. By leveraging this platform, organizations can gain deeper insights into their data operations and make more informed decisions.

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 allows you to consolidate continuous profiling data while ensuring high availability, multi-tenancy, and reliable storage solutions, which enhances your insight into application resource usage at a granular level. As an open-source database, Grafana Phlare offers rapid, scalable, and efficient storage alongside querying capabilities for profiling data. The inception of Phlare took place during a company-wide hackathon at Grafana Labs, and the project was officially introduced in 2022 at ObservabilityCON. Its primary objective is to facilitate large-scale continuous profiling for the open-source community, empowering developers with a deeper comprehension of their code's resource consumption. This initiative ultimately aids users in evaluating their application performance and fine-tuning their infrastructure expenditures, leading to more efficient application management.

Enhance the security of your OpenAI interactions by implementing enterprise-grade features tailored for robust oversight. While OpenAI's LLM APIs offer remarkable capabilities, they often fall short in providing the detailed control and transparency that larger organizations require. Usage Panda addresses these shortcomings effectively. It scrutinizes security protocols for each request prior to submission to OpenAI, ensuring compliance. Prevent unexpected charges by restricting requests to those that stay within predetermined cost limits. Additionally, you can choose to log every request, along with its parameters and responses, for thorough tracking. The platform allows for the creation of an unlimited number of connections, each tailored with specific policies and restrictions. It also empowers you to monitor, censor, and block any malicious activities that seek to manipulate or expose system prompts. With Usage Panda's advanced visualization tools and customizable charts, you can analyze usage metrics in fine detail. Furthermore, notifications can be sent to your email or Slack when approaching usage caps or billing thresholds, ensuring you remain informed. You can trace costs and policy breaches back to individual application users, enabling the establishment of user-specific rate limits to manage resource allocation effectively. This comprehensive approach not only secures your operations but also enhances your overall management of OpenAI API usage.

Pinghome stands out as the foremost provider of top-tier cloud-based uptime monitoring solutions. Our straightforward mission is to equip you with essential tools and insights that guarantee your websites and APIs operate seamlessly at all times. We prioritize delivering outstanding service, beginning with our talented team of skilled and enthusiastic developers. Their commitment and expertise allow us to address all your website monitoring requirements, ensuring you receive unmatched assistance and direction throughout the entire process. Furthermore, we continually strive to innovate and enhance our offerings to better serve our clients in an ever-evolving digital landscape.

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!

HTCD is an AI-driven cloud security SaaS designed to significantly enhance your security posture. HTCD offers centralized visibility with over 500 pre-built policies covering cloud security, infrastructure, networks, SaaS, and compliance. You retain full control of your data while benefiting from seamless integration and extensive protection. Detect - No-Code Detection Engineering Eliminate the need for complex coding. With HTCD, create detections without code, using plain English as your programming language. Quickly identify and mitigate potential threats with queries like: "Which CVEs are exploitable in my Azure environment?" "Show me S3 costs over the past two weeks." Hunt - Proactive Internal Threat Hunting Track activities across all your Cloud (Azure, AWS) and SaaS (M365, GitHub, HubSpot, Slack, etc.) tools with ease. Empower your security analysts and internal threat detection teams with one-click hunting for rapid detection and resolution. Respond - Address What Matters Most Gain a risk-based perspective on security misconfigurations and vulnerabilities, prioritized by AI specifically for you. HTCD helps you address the most critical issues, drastically reducing response times and operational risk.

Identify and resolve performance issues and errors within your microservices by analyzing root causes through traces, logs, and metrics. Leverage Aspecto's built-in remote sampling to reduce your OpenTelemetry trace costs effectively. The way OTel data is displayed significantly influences your ability to troubleshoot; with exceptional visualization, you can seamlessly transition from an overarching view down to intricate details. Easily correlate logs with their corresponding traces, allowing you to navigate back and forth with a single click. Maintain context throughout the process to expedite issue resolution. Utilize filters, free-text search, and grouping features to sift through your trace data, enabling you to swiftly identify the location of problems within your system. Optimize expenses by sampling only the necessary data, targeting traces by languages, libraries, routes, and errors. Implement data privacy measures to obscure sensitive information within trace data or specific routes. Additionally, integrate your everyday tools into your workflow, including logs, error monitoring, and external events APIs, to enhance your operational efficiency. This comprehensive approach ensures that your troubleshooting process is not just effective, but also streamlined and cost-efficient.

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.

Security and observability tailored for Kubernetes environments. Implementing security and observability as code is essential for modern cloud-native applications. This approach encompasses cloud-native security as code for various elements, including hosts, virtual machines, containers, Kubernetes components, workloads, and services, ensuring protection for both north-south and east-west traffic while facilitating enterprise security measures and maintaining continuous compliance. Furthermore, Kubernetes-native observability as code allows for the gathering of real-time telemetry, enhanced with context from Kubernetes, offering a dynamic view of interactions among components from hosts to services. This enables swift troubleshooting through machine learning-driven detection of anomalies and performance issues. Utilizing a single framework, organizations can effectively secure, monitor, and address challenges in multi-cluster, multi-cloud, and hybrid-cloud environments operating on either Linux or Windows containers. With the ability to update and deploy security policies in mere seconds, businesses can promptly enforce compliance and address any emerging issues. This streamlined process is vital for maintaining the integrity and performance of cloud-native infrastructures.

Linkerd enhances the security, observability, and reliability of your Kubernetes environment without necessitating any code modifications. It is fully Apache-licensed and boasts a rapidly expanding, engaged, and welcoming community. Constructed using Rust, Linkerd's data plane proxies are remarkably lightweight (under 10 MB) and exceptionally quick, achieving sub-millisecond latency for 99th percentile requests. There are no convoluted APIs or complex configurations to manage. In most scenarios, Linkerd operates seamlessly right from installation. The control plane of Linkerd can be deployed into a single namespace, allowing for the gradual and secure integration of services into the mesh. Additionally, it provides a robust collection of diagnostic tools, including automatic mapping of service dependencies and real-time traffic analysis. Its top-tier observability features empower you to track essential metrics such as success rates, request volumes, and latency, ensuring optimal performance for every service within your stack. With Linkerd, teams can focus on developing their applications while benefiting from enhanced operational insights.