Open Source Splunk Alternatives

Apache Superset is a data exploration and visualization platform built for teams who want self-serve analytics without depending on a data engineering team for every report. It works with any SQL-based database, from small Postgres instances to petabyte-scale cloud warehouses, and doesn't require a separate data ingestion layer.

The tool serves two kinds of users at once. Analysts who prefer a visual interface can use the drag-and-drop chart builder to assemble dashboards without writing a line of SQL. Those who want more control get SQL Lab, a full-featured SQL IDE with database metadata browsing, Jinja templating, and the ability to save query results as virtual datasets for further exploration.

Key capabilities include:

• 40+ built-in chart types, from basic line and bar charts to geospatial visualizations
• Virtual and physical datasets with unified metric definitions, so the same numbers appear consistently across dashboards
• Cross-filters, drill-to-detail, and drill-by for interactive data analysis directly in a dashboard
• Data caching to keep dashboards fast without re-querying the database on every load
• CSS templates for matching charts to your brand
• Semantic layer for SQL-based data transformations before visualization
• Plugin architecture for adding custom chart types beyond the built-in set

Compared to lighter tools like Metabase or Redash, Superset leans toward teams that need more customization and are comfortable managing their own deployment. It's self-hostable under the Apache License, which makes it a common choice for organizations that can't send data to a third-party SaaS. Grafana covers similar dashboard territory but focuses heavily on time-series and metrics rather than general SQL exploration.

Superset scales horizontally and is designed to sit on top of your existing data infrastructure rather than replace it.

Grafana is a self-hosted observability platform built on open standards like OpenTelemetry and Prometheus. It brings together metrics, logs, traces, profiles, and business data into a single view, so engineering and SRE teams can troubleshoot across their entire stack without jumping between tools.

It's built for teams that want the flexibility of open source without the overhead of managing infrastructure themselves. Hundreds of plugins and integrations let you connect existing data sources rather than replacing them.

Key capabilities include:

• Adaptive Telemetry automatically identifies high-value data and aggregates the rest, cutting telemetry costs by up to 80% without manual filtering rules
• AI-assisted analysis helps interpret production telemetry and accelerate root cause analysis, plus tooling to evaluate and monitor production AI agents
• Unified signal map correlates metrics, logs, and traces so teams can move from alert to fix without context-switching
• Incident response and synthetic monitoring built in, covering the full reliability workflow rather than just data collection
• Compliance certifications including FedRAMP, PCI DSS, SOC Type II, and GDPR, making it viable for regulated industries

Compared to alternatives like Dynatrace or Coralogix, Grafana's differentiator is its open-source foundation. The core Grafana stack is community-driven, and the cloud product extends it with managed infrastructure, enterprise features, and cost controls. You're not locked into proprietary agents or data formats.

For teams already using OpenObserve or Uptrace and considering a managed path, Grafana Cloud offers a broader feature surface with the same commitment to open standards. A free tier is available with no time limit, and paid plans scale with usage.

Prometheus is the de facto standard for open source infrastructure monitoring. It collects metrics from your applications, systems, and services, stores them as time series data, and lets you query, visualize, and alert on that data. Originally inspired by Google's internal Borgmon system, it's now a graduated CNCF project (the second after Kubernetes) with a large community behind it.

The core model is pull-based: Prometheus scrapes metrics from instrumented targets at configurable intervals. This makes it straightforward to see exactly what's being collected and when. Targets can be defined statically or discovered automatically, which is where its Kubernetes integration shines. It continuously discovers pods, services, and nodes as they come and go, so you don't have to manually update your monitoring config every time your infrastructure changes.

Key capabilities:

• PromQL: a flexible query language for slicing and aggregating time series data across any combination of labels
• Multi-dimensional data model: every metric carries key-value label pairs, letting you filter and group by environment, region, service, or any dimension you define
• Built-in alerting: Alertmanager handles deduplication, grouping, silencing, and routing alerts to your notification channels
• Service discovery: native integrations with Kubernetes, Consul, EC2, and other platforms
• Local storage: an efficient on-disk time series database, purpose-built for high-ingestion workloads

For dashboards, Prometheus pairs naturally with Grafana, which can query it directly. Tools like Uptrace and OpenObserve also support Prometheus as a data source, extending what you can do with the metrics you're already collecting.

Prometheus is self-hosted, which means your metrics stay on your infrastructure. The entire project is Apache-licensed and community-governed under the CNCF.

SigNoz is a powerful, open-source observability platform designed for modern, cloud-native applications. It provides a unified solution for monitoring, troubleshooting, and optimizing your microservices architecture.

Key benefits of SigNoz include:

1. All-in-One Observability: Combine metrics, traces, and logs in a single platform, eliminating the need for multiple tools and reducing context-switching.

2. Cost-Effective: As an open-source solution, SigNoz offers significant cost savings compared to proprietary alternatives, especially for high-volume data ingestion.

3. Easy Setup: Get started quickly with a simple installation process and intuitive UI, making it accessible for teams of all sizes.

4. Customizable Dashboards: Create tailored views of your system's performance with flexible, drag-and-drop dashboard builders.

5. Distributed Tracing: Gain deep insights into request flows across your microservices, helping you identify bottlenecks and optimize performance.

6. Anomaly Detection: Leverage built-in anomaly detection capabilities to proactively identify issues before they impact your users.

7. Scalability: Designed to handle high-volume data ingestion, SigNoz scales effortlessly with your growing infrastructure.

8. Open Standards: Built on OpenTelemetry, ensuring compatibility with a wide range of technologies and future-proofing your observability stack.

By choosing SigNoz, you're not just adopting a monitoring tool; you're embracing a comprehensive observability solution that grows with your needs and empowers your team to maintain high-performing, reliable applications.

ProjectDiscovery delivers enterprise-grade vulnerability management with a focus on detecting only exploitable vulnerabilities to eliminate false positives. The platform features real-time infrastructure monitoring that provides instant visibility into your entire tech stack as teams deploy.

Key capabilities include:

• Zero-noise vulnerability detection that identifies only actual exploitable vulnerabilities
• Comprehensive asset discovery to map and contextualize your complete attack surface
• Custom exploit detection through the open-source Nuclei framework
• Automated workflows for instant organization-wide detection and triage
• Multi-protocol support covering web, network, DNS, and cloud infrastructure

The platform is trusted by over 100,000 security professionals to transform noisy scan results into relevant, actionable alerts that enable 10x faster vulnerability triage and remediation.

Redash is a powerful, open-source data visualization and analytics platform designed to help teams connect, query, visualize, and share their data effectively. Here's what makes Redash stand out:

1. Versatile Data Connectivity:

   • Supports a wide range of data sources, including SQL, NoSQL, Big Data, and APIs
   • Allows querying from multiple sources to answer complex questions

2. Powerful Query Editor:

   • Intuitive SQL editor with schema browsing and click-to-insert functionality
   • Ability to create and reuse query snippets for efficiency

3. Interactive Dashboards:

   • Drag-and-drop interface for creating customizable dashboards
   • Resize and arrange visualizations to suit your needs
   • Schedule automatic refreshes from data sources

4. Collaboration and Sharing:

   • Share dashboards with team members or make them public
   • User management features for access control

5. Visualizations and Alerts:

   • Create various types of visualizations to represent your data
   • Set up alerts to stay informed about important data changes

6. Open-Source Advantage:

   • Customize and add features to suit your specific needs
   • No vendor lock-in
   • Active community for support and contributions

7. API Access:

   • Integrate Redash with other tools and services using its API

Redash is trusted by data-driven companies to make sense of their information, enabling better decision-making and deeper understanding of their data. Whether you're a small startup or a large enterprise, Redash provides the tools you need to turn your data into actionable insights.

OpenObserve is a comprehensive, open-source observability platform designed for logs, metrics, and traces. It offers a modern, scalable architecture built for high performance and significant cost savings. The platform's primary advantage is its efficiency, providing up to 140x lower storage costs when compared to alternatives like Elasticsearch. This is achieved through high data compression and a columnar storage format.

Key features include:

• High Performance: Built in Rust and utilizing the DataFusion query engine for rapid data analysis, even at petabyte scale.
• Scalability: A stateless architecture allows for easy horizontal scaling to handle enterprise-level workloads.
• Cost-Effectiveness: Drastically reduces telemetry costs with high compression and the ability to use your own storage buckets like S3, GCS, and Azure Blob.
• Open Standards: Fully compatible with OpenTelemetry, ensuring seamless integration with existing tools and workflows.

Logstash is a powerful data processing pipeline that allows you to collect, transform, and ship data from various sources to multiple destinations. Here are some key features and benefits:

1. Versatile Input Support:

   • Ingest data from a wide range of sources, including logs, metrics, web applications, data stores, and AWS services.
   • Supports continuous, streaming data ingestion.

2. Powerful Data Transformation:

   • Parse and structure unstructured data using grok patterns.
   • Derive additional information, such as geolocations from IP addresses.
   • Anonymize or exclude sensitive data for compliance and security.
   • Transform data into a common format for easier analysis.

3. Flexible Output Options:

   • Send processed data to various destinations, with Elasticsearch being a primary output.
   • Route data to multiple outputs simultaneously for different use cases.

4. Extensibility:

   • Pluggable framework with over 200 plugins available.
   • Easy-to-build custom plugins for specific needs.

5. Reliability and Security:

   • Guarantees at-least-once delivery with persistent queues.
   • Dead letter queues for handling processing failures.
   • Ability to secure ingest pipelines.

6. Monitoring and Management:

   • Built-in monitoring features for observing performance and availability.
   • Pipeline Viewer for understanding and optimizing data flows.
   • Centralized management through a user-friendly UI.

7. Elastic Stack Integration:

   • Seamless integration with other Elastic Stack components like Elasticsearch and Kibana.
   • Pre-built modules for quick setup with popular data sources.

Logstash is an essential tool for organizations looking to centralize and process their data efficiently, making it ready for analysis and visualization in platforms like Elasticsearch and Kibana.

Open source observability platform that unifies session replays, logs, traces, metrics and errors into a single view - all without the expensive Datadog price tag. Recently acquired by ClickHouse to accelerate open source observability innovation.

Key capabilities include:

• End-to-end correlation - Trace requests from user browsers to backend servers and async workers automatically
• Blazing fast search - Query terabytes of events in seconds, powered by ClickHouse
• Automatic clustering - Condense billions of events into distinctive patterns without manual configuration
• Session replay integration - Automatically link user sessions with backend logs and traces
• Intuitive visualization - Build charts and graphs with simple full-text search, no complex syntax required

Developer-friendly features:

• OpenTelemetry-powered instrumentation prevents vendor lock-in
• Agent-free installation option eliminates infrastructure overhead
• Native JSON parsing for structured logs with zero configuration
• Real-time live tail for immediate log stream monitoring
• Intercom integration for jumping directly from support tickets to user sessions

Transparent pricing at $0.40 per GB with no per-user or per-host fees makes enterprise-grade observability accessible to teams of all sizes. Trusted by high-velocity engineering teams for resolving production issues fast.

Monitor and optimize your LLM applications with comprehensive observability built on OpenTelemetry standards. This open-source platform provides deep insights into your AI systems with minimal setup complexity.

Key capabilities include:

• Performance monitoring - Track response times, throughput, and system health across all LLM interactions
• Cost tracking - Monitor API usage and expenses across different LLM providers in real-time
• Error detection - Identify and debug issues in your AI applications before they impact users
• Request tracing - Follow complete request flows through your LLM pipeline for better debugging
• Multi-provider support - Works seamlessly with various LLM providers and observability platforms

Quick integration requires just 2 lines of code to start collecting telemetry data. Built on OpenTelemetry standards, ensuring compatibility with existing monitoring infrastructure and avoiding vendor lock-in.

Perfect for developers building production LLM applications who need reliable monitoring without complex setup or proprietary dependencies.

Coroot is an innovative open-source observability platform that revolutionizes how developers and operations teams monitor and troubleshoot their systems. Here's what makes Coroot stand out:

1. Zero-instrumentation observability:

   • Utilizes eBPF technology to automatically gather metrics, logs, traces, and profiles without any code changes
   • Provides a comprehensive Service Map covering 100% of your system with no blind spots
   • Offers predefined inspections to audit each application without configuration

2. Comprehensive monitoring features:

   • Application Health Summary for easy status overview of multiple services
   • Distributed tracing to explore outlier requests with a single click
   • Log pattern analysis with out-of-the-box event clustering
   • Continuous profiling to analyze CPU and memory usage down to specific code lines
   • AI-powered root cause analysis for quick anomaly explanations

3. User-friendly interface:

   • Intuitive dashboards for visualizing system performance
   • One-click investigation of anomalies
   • Easy comparison of system behavior against baselines

4. Built-in expertise:

   • Automatically identifies over 80% of issues
   • Sends concise alerts with relevant inspection results when SLOs are not met
   • Customizable inspections for specific applications or entire projects

5. Deployment and cost monitoring:

   • Tracks every application rollout in Kubernetes clusters
   • Compares each release with the previous one to detect performance degradations
   • Provides cloud cost insights down to individual applications

6. Open-source and cloud options:

   • Available as a free, open-source Community Edition
   • Coroot Cloud offering for those who prefer a managed solution

Coroot simplifies the complex task of system observability, making it accessible to teams of all sizes. By leveraging cutting-edge technologies and providing a user-friendly interface, Coroot enables faster debugging, better development practices, and improved system reliability.

GreptimeDB is a cloud-native, real-time observability database that revolutionizes how organizations handle metrics, logs, and traces. Built for OpenTelemetry and modern cloud environments, it delivers sub-second query performance at petabyte scale while dramatically reducing operational complexity.

Key benefits include:

• All-in-One Solution: Process metrics, logs, and traces through a unified database with full SQL, PromQL, and streaming processing support
• Exceptional Performance: Built with Rust for reliability, featuring rich indexing options (inverted, fulltext, skipping, and vector) that enable sub-second responses on massive datasets
• Massive Cost Savings: Achieve 50x lower operational and storage costs through compute-storage separation and flexible cloud scaling
• Infinite Scalability: Purpose-built for Kubernetes with industry-leading architecture that handles cardinality explosion at massive scale
• Developer-Friendly: Access through standardized interfaces including web dashboard, REST API, and MySQL/PostgreSQL protocols
• Flexible Deployment: Deploy anywhere from ARM-based edge devices to cloud environments with unified APIs

Trusted by companies like Li Auto (reduced traffic costs by 50%, storage costs by 98%), SGCC (2x write performance, 5x query performance), and others who have migrated from InfluxDB, Loki, and Thanos to achieve superior performance and simplified operations.

Helicone is the open-source platform that helps developers build reliable AI applications through comprehensive observability. Trusted by the world's fastest-growing AI companies, it provides essential tools for routing, debugging, and analyzing LLM applications.

Key Features:

• Universal Integration: Access 100+ models with a single integration (beta)
• Complete Observability: Log, monitor, and debug your AI applications
• Advanced Analytics: Track requests, segments, sessions, and user properties
• Developer Tools: Prompts playground, experiments, evaluators, and datasets
• Enterprise Ready: Scalable solution for growing AI companies

The platform offers a comprehensive dashboard for monitoring AI application performance, with detailed request tracking and user analytics. Developers can experiment with prompts, run evaluations, and manage datasets all within one unified interface.

Getting Started: No credit card required with a 7-day free trial. The platform is designed to help developers quickly identify issues, optimize performance, and ensure their AI applications run reliably at scale.

Apache Pinot is a distributed OLAP database built for real-time analytics where latency and concurrency actually matter. Originally developed at LinkedIn, it's now used by Stripe, Uber, Walmart, and others to serve analytical queries at hundreds of thousands of requests per second, often with P99 latencies under 100ms.

The core use case: you have streaming data and you need to query it interactively, at scale, without pre-aggregating everything in advance. Pinot handles that through columnar storage, a rich set of pluggable indexes, and a distributed architecture that scales horizontally.

Key capabilities:

• Real-time ingestion from Kafka, Kinesis, and Pulsar, plus batch sources like S3, Hadoop, and Spark. Both can feed the same table.
• Upserts built in, so repeated records resolve to their latest value at query time without extra application logic.
• High-concurrency query serving, designed for scenarios where end users or AI agents are hitting the database directly, not just internal dashboards.
• Versatile joins across petabyte datasets, not just simple lookups.
• Multitenancy with logical namespace isolation, useful for SaaS products serving per-customer analytics.
• SQL interface with a built-in query editor and REST API.

Pinot fits two broad patterns. First, user-facing analytics: embedded dashboards, customer-facing data exploration, leaderboards, and usage metrics where your product's users are running queries in real time. Second, AI agent backends: LLM-powered systems that need fresh context from streaming data rather than stale snapshots. Think fraud scoring, real-time RAG retrieval, or agentic observability over live logs.

Compared to tools like ClickHouse, Pinot's design leans heavily toward serving many concurrent external users rather than fewer internal analysts running complex ad-hoc queries. The trade-off is intentional. Pinot's indexing options (inverted, range, text, geospatial, and more) let you tune for specific query patterns without restructuring your data model.

At Stripe, it handles 200K queries per second across 3 petabytes with P99 latency of 70ms. At Uber, a single service runs 500 million Pinot queries daily. These aren't edge cases; the architecture is built around this kind of load from the start.

Logfire brings powerful observability to Python applications with remarkable simplicity. Built by the team behind Pydantic, it offers developers an intuitive way to gain deep insights into their code.

Key features:

• Seamless integration: Easy setup with popular Python libraries and frameworks
• Comprehensive visibility: Monitor logs, traces, and performance metrics in one place
• Structured data: Query-ready logs for easy analysis and visualization
• Manual tracing: Create custom logs and traces with a modern, user-friendly interface
• OpenTelemetry support: Leverage the power of OTel with simplified implementation

Logfire transforms complex observability tasks into actionable insights. Whether you're building AI tools or cloud-based applications, it provides a clear window into your code's behavior. With features like performance profiling and full execution tracing, Logfire helps developers quickly identify and resolve issues.

The platform's intuitive design makes it accessible for teams of all sizes, eliminating the need for dedicated observability experts. By combining ease of use with powerful analytics capabilities, Logfire empowers developers to make data-driven decisions and continuously improve their applications.

Tracecat is an open source alternative to proprietary security orchestration, automation and response (SOAR) platforms like Tines and Splunk SOAR. It empowers security engineers to automate their workflows and playbooks without restrictions.

Key features:

• Unlimited workflows: Build, reuse and scale security playbooks without limits using the visual drag-and-drop builder or YAML configuration.
• Low-code integrations: Use pre-built integrations or easily create custom ones to connect your security tools.
• Self-hostable: Deploy Tracecat in your own environment using Docker, Kubernetes or AWS Fargate for maximum control and data privacy.
• Open source: Fully open source and built on Temporal, the same durable execution engine used by major tech companies.
• Enterprise-ready: Offers mission-critical alerting and 99.99% uptime SLAs for organizations that need guaranteed reliability.

Tracecat allows security teams to automate alert triage, threat enrichment, incident response and more. The platform scales to handle high volumes of workflows in parallel across isolated tenants. With both no-code and code-based options, it provides flexibility for teams of all technical levels.

By offering an open source alternative to proprietary SOAR tools, Tracecat aims to make powerful security automation accessible to more organizations. The self-hosted deployment model ensures sensitive security data and workflows remain under your control.

Uptrace is an open-source observability platform built on OpenTelemetry, designed to help developers and operations teams monitor, understand, and optimize complex distributed systems. It offers a comprehensive solution for application performance monitoring (APM) with integrated tracing, metrics, and logging capabilities.

Key features and benefits:

1. All-in-one solution:

   • Integrates traces, metrics, and logs in a single platform
   • Eliminates the need for multiple monitoring tools
   • Supports data from OpenTelemetry, Prometheus, Vector, FluentBit, and CloudWatch

2. Flexible deployment options:

   • Self-hosted: Free to use without limitations
   • Managed cloud service: For those who prefer a hands-off approach
   • On-premise installation available upon request

3. Cost-effective and predictable pricing:

   • Pay only for ingested gigabytes and active timeseries
   • Set a budget to avoid unexpected costs
   • First month free with 1TB storage and 50,000 timeseries (no credit card required)

4. OpenTelemetry integration:

   • Quick setup with minimal code changes
   • Supports multiple programming languages (Go, Python, Ruby, Node.js, .NET, Java, Erlang, Elixir, Rust, PHP)
   • Vendor-agnostic instrumentation for easy switching between providers

5. Comprehensive monitoring dashboard:

   • Service graph showing relationships between components
   • RED metrics (Rate, Errors, Duration)
   • Latency percentiles (p50/p90/p99/max)
   • Most frequent logs and errors
   • Slowest requests identification

6. Scalability:

   • Designed to work at any scale, from small applications to large distributed systems

7. Incident response:

   • Helps teams identify and resolve issues quickly, often before customers notice

By offering a unified platform for observability, Uptrace simplifies the monitoring process and provides valuable insights into application performance, helping teams optimize their systems and respond to incidents more effectively.

Comprehensive IT monitoring that scales from small teams to enterprise environments with millions of services. Checkmk automatically discovers and monitors your entire infrastructure - from cloud providers to data centers, servers, networks, containers, and applications.

Key advantages include:

• 2,000+ vendor-maintained plugins for out-of-the-box monitoring of virtually any system
• Automated discovery and configuration via REST API reduces manual setup time
• High-performance core designed to handle massive scale while maintaining a small footprint
• Granular alerting system that notifies only relevant teams and integrates with ServiceNow, Jira, Slack, and more

Multiple deployment options cater to different needs:

• Raw Edition: Free open-source version for mid-sized infrastructures
• Enterprise Edition: Advanced automation and visualization features
• Cloud Edition: SaaS solution optimized for hybrid cloud environments
• MSP Edition: Multi-tenant capabilities for service providers

Advanced features include dynamic dashboards, business intelligence mapping, custom self-healing actions, and comprehensive SLA reporting. The platform combines infrastructure monitoring with log analysis, synthetic testing capabilities, and historical performance forecasting to provide complete visibility into your IT operations.

Maple is an observability platform for distributed systems, built on OpenTelemetry and backed by ClickHouse for sub-second queries across billions of rows. It handles traces, logs, and metrics in one place, with correlated data across all three signals tied to a single trace ID. No stitching between tools, no second search in a second product.

The incident workflow is its sharpest edge. An alert arrives carrying the service, the broken threshold, and sample traces. From there you open the failing span tree, jump to correlated logs on the same trace ID, and see exactly what happened. Retry exhaustion, a full connection pool, three Stripe timeouts at 1.75 seconds each – all visible without switching tabs.

Key capabilities:

• Distributed tracing – full span trees with every attribute intact, no sampling gap hiding the outlier
• Structured logs – OTLP logs searchable by severity, service, message, and duration in seconds
• Session replay – browser clicks, routes, console lines, and failed requests, joined to spans by session ID
• Metrics and dashboards – request rate, error rate, latency percentiles, drag-to-build or agent-suggested
• Service maps – live request flow across services, the dependency cascade you'd otherwise reconstruct after the fact
• Error tracking – errors grouped by type, with trends, affected services, and sample traces attached
• Alerting – seven signal types with severity, incident tracking, and auto-resolution; routes to Slack, Discord, PagerDuty, or any webhook
• MCP server – any compatible AI agent (Claude, Cursor, others) can list services, search traces, read source files, and open a PR with a proposed fix
• Kubernetes integration – Helm chart that joins spans to pod, node, and namespace; kube-state metrics included

Compared to tools like HyperDX or Uptrace, Maple's first-class MCP surface is a genuine differentiator. The agent doesn't just read dashboards – it pulls the source file behind a failing span, so the fix it proposes cites your actual code. It can also write back: claim an issue, set severity, attach a fix.

The local mode runs as a single compiled binary with an embedded ClickHouse, OTLP ingest, query API, and dashboard – all on localhost, no account required. For production, you can self-host against your own ClickHouse or use the hosted plan at $39/month for 100 GB per signal, then $0.30/GB flat. No per-host fees. No per-seat fees.

The source is on GitHub under FSL-1.1, which converts to Apache 2.0 two years after each release. OpenTelemetry in means no proprietary agent and no re-instrumentation if you switch.

A powerful observability platform that brings together logs, metrics, traces and profiles in one unified solution. Built on high-performance OLAP engines ClickHouse and DuckDB with NVMe storage, Gigapipe delivers exceptional speed and reliability.

Key advantages:

• Drop-in compatibility with OpenTelemetry, Loki, Prometheus, Tempo, Pyroscope and other popular tools
• Flat-cost pricing model with no usage limits or surprise bills
• True open source solution under AGPLv3 license
• Single platform approach eliminates data silos and reduces complexity
• Native support for thousands of compatible agents
• Query API that emulates familiar tools like Loki and Prometheus

Perfect for engineering teams and DevOps professionals who need comprehensive observability without the complexity of managing multiple tools or worrying about data volume costs. Gigapipe's polyglot approach ensures you can work with your data your way, while the unified platform enables quick correlation between different data types for faster troubleshooting and deeper insights.