Are you looking for an observability solution to streamline your software deployment operations and maintenance on the cloud ? This post is a roundup of the best observability tools and platforms available in 2025.
What is an Observability Platform?
An observability platform provides a view of the internal workings of the application runtime and the associated infrastructure deployed within cloud environments. It equips developers and operations teams with runtime stack-level data, enabling them to monitor, troubleshoot, and optimize their applications with unprecedented precision.
Observability platforms are the heartbeat of modern software systems. They provide crucial data on application health, user behavior, and cloud resources. They rely on specific datasets, such as logs, traces, metrics, and events, to observe a runtime software application and gain insights about application health and performance. They observe the internal state and control flow of the application stack to unearth unknown anomalies. This approach supersedes the traditional monitoring approaches, which can only track previously known anomalies.
Therefore, observability platforms offer a robust methodology for tracing and diagnosing software applications. Given the highly distributed and microservice-based architecture of modern cloud-hosted applications, observability extends from runtime software observability to service and cloud observability. It also covers the underlying infrastructure and third-party components of a software system.
Types of Observability Platforms
Observability platforms cover the entire depth of an application tech stack. The scope and need for observability differ as you delve deeper into the stack. Therefore, it is important to categorize a platform based on the stack level where it delivers the maximum value. Based on that, you can broadly have three types of observability.
- 1Application observability - This applies to the topmost level of the stack, where observability tools help developers track the application runtime, processes and associated parameters.
- 2Service observability - This applies to the underlying service layers comprising the cloud services or other middleware for hosting and orchestrating the application runtime.
- 3Infrastructure observability - This applies to the bottom-most layer of the stack. It covers the cloud infrastructure, such as the compute, database, and network elements that provide the foundational base for deploying the entire application.
Let’s take a look at the top observability platforms for each category.
The Top Application Level Observability Platforms
Also known as developer observability, these platforms assist developers and DevOps teams in instrumenting and applying dynamic logging and tracing facilities to the runtime processes or containers hosting the application-level business logic.
Lightrun
Lightrun excels in real-time debugging, enabling developers to add logs, metrics, and traces to live applications without stopping them. This unique capability significantly reduces debugging time, from days to under an hour. The platform supports on-demand metrics, aiding developers in performing root cause analysis on bugs reported directly in production.
Lightrun’s developer observability capabilities offer real-time data observability analysis for immediate insights into application source code and runtime performance. It supports plugins for the major IDEs available under these programming language ecosystems.
SigNoz
SigNoz stands out as an exemplary open-source observability tool. It offers a comprehensive view of software system behaviors through support for various telemetry signals, including logs, metrics, and traces. It also supports distributed tracing across services, advanced dashboards, and custom alerts for infrastructure monitoring. Therefore, SigNoz is an ideal solution for an open-source, full-stack observability platform.
At the application level, SigNoz supports many programming languages for code instrumentation. The captured data is compatible with OpenTelemetry. It is stored in the ClickHouse database, which offers fast and resource-efficient data storage for real-time analytics. SigNoz also supports out-of-the-box charts for service and infrastructure-level metrics.
The Top Service Level Observability Platforms
Service-level observability maintains observability on underlying services. This includes standard services offered by public cloud providers, such as AWS Lambda, or a self-hosted middleware service layer based on popular platforms such as Kubernetes. One of the key capabilities of observability platforms operating at this level is their ability to monitor application performance metrics to maintain baseline performance for critical services.
That's why these platforms are also referred to as application performance monitoring. In many cases, this also includes security observability for capturing security-specific data to establish consistent cloud service and application security postures.
Edge Delta
Edge Delta specializes in observability solutions based on custom telemetry pipelines. It offers a visual interface to build complex telemetry pipelines, including the data source, data processing functions, and streaming destinations. It monitors and transforms the data through the pipeline to analyze logs, metrics, and traces for anomaly detection. The entire pipeline is augmented with an observability co-pilot to assist in generating anomaly summaries and speeding up troubleshooting.
Edge Delta observability pipeline can also orchestrate security data to standardize, enrich, and stream data to security platforms. It leverages pipeline features to analyze patterns derived from logs for real-time threat monitoring and gain an immediate understanding of user behavior and risk.
Logz.io
Logz.io offers an AI-powered observability platform for distributed log and trace management. Its AI agent-assisted analysis and investigation covers the service layers down to the infrastructure. The Logz.io App 360 platform takes an AI-led approach to APM to unify the key signals across apps and infrastructure to provide conclusive visibility and insight into complex applications.
Logz.io supports all the major public cloud service providers and Kubernetes. It also supports application-level instrumentation for JavaScript, Java, Node.js, Go, Python, Ruby on Rails, and many other languages.
Chronosphere
Chronosphere is a scalable observability platform specializing in high volume of telemetry data generated by microservices. The platform is designed for containers and cloud-native environments. It significantly reduces observability data volumes and associated costs. It follows an observability data optimization cycle, which reduces data volume and cost to improve performance and deliver more business value.
Chronosphere features an observability pipeline for routing and processing telemetry data via Prometheus. It also supports existing OpenTelemetry compatible sources of observability data.
Honeycomb
Honeycomb offers an observability platform designed to process highly diverse data. It efficiently stores and queries high-cardinal and high-dimensional data, which traditional databases usually find challenging. This capability allows unlimited dimensionality when storing, querying, and correlating data. Additionally, it expedites the observability analysis to answer questions covering the relevant context and fix issues in less time.
Honeycomb supports integration with Kubernetes and OpenTelemetry compatible SDKs for code-level instrumentation. It collects logs and metrics from public cloud services, such as AWS. It can perform various levels of data transformation and enrichment for incident investigation and outlier analysis.
The Top Infrastructure Level Observability Platforms
Infrastructure level observability platforms offer a complete suite of tools and interventions to observe cloud software deployments that are massively distributed and operate at a scale, covering millions of customer interactions. These platforms combine application and service performance management with capacity planning and business-level observability based on technical and business metrics measurement.
Dynatrace
Dynatrace uses AI to provide deep insights into application performance, making it ideal for managing complex environments. The platform integrates advanced analytics, automation, and predictive features to make observability actionable. It aids in the interpretation of complex telemetry data and improves application availability. Its AI-driven cause analysis pinpoints the root causes of operational and quality issues, significantly enhancing the management of complex environments.
Dynatrace supports real-time monitoring of the entire infrastructure and service health. It includes tools for tracking security threats, digital experiences, compliance, and audit trails. The Dynatrace Davis is the industry’s first observability co-pilot. It leverages generative AI on telemetry and system log data to predict anomalies and simplify analytics.
Datadog
Datadog is renowned for supporting hundreds of third-party integrations. It is the top-notch choice for building observability functionalities around a large and distributed software system supporting complex business workflows. The platform architecture integrates seamlessly with open-source telemetry standards. It enables flexible data collection and transformation. Overall, all these capabilities make Datadog the ideal platform for a full-stack view of observability in distributed systems.
Incorporating machine learning technologies, Datadog provides insights that improve application performance and monitoring. This is backed by features for infrastructure, network monitoring, and security. It also offers synthetic monitoring for simulated user testing to assess the resulting impact on system performance. Although Datadog can be complex to set up and configure, and the costs can be higher for extensive integrations, the depth of functionality it offers is unparalleled.
New Relic
New Relic is an intelligent observability platform covering the entire span of tech stack. This extends into business observability, security analytics, and the emerging vertical of AI observability. The platform offers comprehensive monitoring across applications and infrastructure, including Kubernetes, browser, mobile, network, and synthetic monitoring.
From performing traditional monitoring to enabling observability for every part of the stack, New Relic is an excellent choice for a unified observability platform. It also features several innovations around observability, such as AIOps for enabling observability on AI models, and NRQL, the New Relic Query Language for querying data. With hundreds of third-party and developer-friendly integrations and AI-powered insights, New Relic significantly enhances the observability experience for large enterprises.
Sumo Logic
Sumo Logic offers an integrated platform for application observability, infrastructure monitoring, and cloud security analytics. It effectively monitors cloud-native applications, providing real-time analytics tailored to microservices and containerized environments. The platform also has SecOps capabilities and integrates with SIEM systems to enhance threat detection and streamline security response in cloud settings. It integrates seamlessly with cloud services, allowing users to maintain visibility across diverse cloud environments.
Sumo Logic features proprietary AI/ML algorithms with co-pilot assistance for enhancing security and faster data-driven decisions. This helps overcome complex challenges across IT operations, security, and application deployment. The platform also features advanced log analysis for SLOs to be defined based on log searches and queries to monitor golden signals like latency and errors.
Frequently Asked Questions?
The pillars of observability are metrics, logs, and traces, which provide crucial telemetry data for understanding and monitoring system performance. Ensuring a robust implementation of these pillars enhances your ability to diagnose issues effectively.
Real-time debugging is crucial as it enables developers to add logs, metrics, and traces to live applications without interruption, greatly minimizing debugging time. This efficiency leads to faster problem resolution and improved application performance.
Various observability platforms offer features to assist developers, DevOps, site reliability and security teams to track and monitor internal system functionality and performance of software systems. Based on the features, these platforms operate at different levels of the application tech stack, and can be categorized as application level, service level, and infrastructure level observability platforms.
