We keep it simple and useful: who each tool is for, what it does best, how it’s priced, and when it makes most sense.
To get value fast:
- Scan the table to shortlist a potential Splunk replacement
- If you self-manage, pay particular attention to competitors of Splunk that align with your stack, including the Splunk Enterprise alternatives
- Prefer fully managed solutions? Check out the Splunk SaaS competitors
However you search for competitors for Splunk, the goal is the same: pick a few options that seem to meet your needs, run a trial that reproduces your planned use, and then confidently choose an option that has the best chance of working for you.
Acronym key up front, because this space is dense with alphabet soup which can trip up anyone who doesn’t live and breathe monitoring full-time: application performance monitoring (APM), artificial intelligence (AI), artificial intelligence for IT operations (AIOps), Kubernetes (K8s), real user monitoring (RUM), service level objectives (SLOs), Security Information and Event Management (SIEM), software as a service (SaaS), stock keeping unit (SKU), User Experience (UX).
| Product | Best For | G2 Rating | Key Features | Compelling Use Case | Pricing |
|---|---|---|---|---|---|
| SolarWinds Observability | Best for hybrid stacks | 4.3/5 |
Unified Observability Across Metrics, Traces, Logs, Digital Experience and Database Deep Network and Infrastructure Observability across hybrid topologies Guided setup for native cloud integrations (AWS, Azure, GCP) Support for multiple open standards such as OpenTelemetry, Telegraf, Prometheus etc. End-to-end hybrid visibility with built-in AI assist |
Deep Network and Infrastructure Observability across hybrid topologies | From $144 per network device or host annually |
| Datadog | Best for cloud-native | 4.4/5 |
Broad integration catalog Application performance tracing Real user monitoring Cloud security signals |
Consolidated SaaS monitoring at hyperscale | From $180 per host annually (Pro Tier) |
| Dynatrace | Best for auto-discovery | 4.5/5 |
OneAgent auto-discovery Davis AI correlation Kubernetes-native monitoring Topology and root cause |
Autonomous discovery with strong root-cause analysis | From $350 per host annually |
| New Relic | Best for developers | 4.4/5 |
Unified telemetry lake Code-level application tracing Errors inbox workflows Developer-friendly quickstarts |
Single telemetry pipeline with dev-friendly UX | From $120 (1st user only) - $1,188 (additional users) annually plus usage fees |
| Elastic Observability | Best for search-driven troubleshooting | 4.2/5 |
Search-driven investigation Logs, metrics, traces APM agents available Uptime and synthetics |
Search-first troubleshooting across logs and traces | Usage-based pricing |
| Grafana Cloud | Best for open source-first | 4.5/5 |
Grafana dashboards Loki log pipeline Tempo distributed tracing Mimir scalable metrics |
Open source stack without self-hosting pain | From $228 annually (Pro Tier) plus usage fees |
| Sumo Logic | Best for SIEM plus observability | 4.3/5 |
Scalable log analytics Cloud SIEM integration Prebuilt app content Ingest and retention controls |
Security-heavy observability in one UI | Usage based |
| IBM Instana | Best for containers | 4.4/5 |
Automatic instrumentation Real-time service discovery Continuous profiling Smart problem detection |
Real-time service maps with minimal config | $240 annually per Managed Virtual Server (Essentials tier) |
| Cisco AppDynamics | Best for enterprises | 4.3/5 |
Business transaction monitoring Deep code diagnostics Kubernetes visibility Synthetic monitoring |
Business-transaction views for large apps | Custom Quotes |
| Honeycomb | Best for high-cardinality | 4.7/5 |
High-cardinality analysis Proprietary “BubbleUp” outlier detection Trace-centric debugging SLOs and error budgets |
Exploratory debugging with granular data | Free tier and from $1,560 annually for Pro tier |
| ServiceNow Cloud Observability (LightStep) | Best for SLOs | 4.6/5 |
Change Intelligence insights SLO and budget tracking Unified distributed tracing Native ServiceNow workflows |
SLO-driven ops tied to workflows | Custom Quotes |
| LogicMonitor | Best for infra ops | 4.5/5 |
Broad infrastructure coverage AIOps event correlation Hybrid topology views NetFlow and network monitoring |
Hybrid IT monitoring with strong infra depth | Custom Quotes |
| Chronosphere | Best for cost control | 4.5/5 |
Prometheus-native platform Data and drop rules Usage cost profiler Grafana dashboard imports |
Prometheus at scale with spend control | Custom Quotes |
| Observe, Inc. | Best for data lake observability | N/A |
Unified operational data lake Proprietary OPAL query language Relationships data graph Live investigative views |
Unified lake for logs, metrics, traces | Custom Quotes |
| AWS CloudWatch | Best for all-AWS-shops | 4.3/5 |
Native AWS metrics Logs, alarms, dashboards Kubernetes and container services Serverless monitoring |
All-in monitoring for AWS workloads | Usage based |
| Azure Monitor | Best for all-Azure shops | 4.3/5 |
Application Insights APM Alerts and automation Azure Kubernetes Service views Azure telemetry with Kusto Query analytics |
Azure telemetry with Kusto Query analytics | Usage based |
As of September 2025
Top 16 Alternatives to Splunk in 2025
1) SolarWinds Observability
What it is, who it is for:
SolarWinds® Observability is a full-stack platform designed to connect signals across applications, infrastructure, networks, databases, logs, and digital experience. SolarWinds is popular in both the mid-market and enterprise sectors, placing it prominently amongst Splunk Enterprise competitors. If you run hybrid or multi-cloud and want fewer blind spots and faster mean time to resolution, this is built for you.
Core features - why SolarWinds ranks amongst the top competitors to Splunk
Full-stack telemetry
Collect metrics, traces, logs, events, and user experience in one place. Navigate by service, dependency, and topology instead of juggling tabs. Pivot from a symptom to the related components in a click, so teams move from “what broke” to “why it broke” without losing context.
Database depth
See waits, locks, slow queries, and resource hotspots across engines. Use guided diagnostics to locate the statement, plan, and host involved. Trend query performance over time, compare versions, and understand which changes actually improved latency and throughput in production.
Network and infrastructure
Observe hosts, devices, containers, load balancers, cloud services, and more. Topology awareness shows how infrastructure supports services, so you can diagnose packet loss, saturation, or noisy neighbors quickly. Tie infrastructure health directly to the applications and users it serves.
Log intelligence
Ingest by gigabyte with flexible retention. Enrich logs with trace and resource context, then jump from a spike to the exact span or host. Shape noisy streams, keep high-value events, and avoid paying to store lines that will never be queried again.
Advanced capabilities
AI-assisted insights
Use built-in intelligence to baseline golden signals, flag anomalies, and suggest likely root causes. Reduce alert fatigue by correlating events across layers and suppressing duplicates. Focus response where it matters: the change, service, or dependency that actually started the incident.
OpenTelemetry first
Bring standard collectors and instrumentation. Reuse pipelines, avoid vendor lock-in, and keep portability for new services. Map spans to services and owners consistently, so duty engineers know exactly where to start when they get the call.
Data controls
Control ingest, aggregation, sampling, and retention policies per team or service. Spend on signals that produce outcomes, not on telemetry you never read. Report usage clearly, so engineering leaders align budgets with reliability goals.
Service health
Define service level objectives for availability and latency. Alert on error rate and trending risk, not just thresholds. Triage by customer impact to keep focus on incidents users might notice, rather than on distracting internal noise.
Dependency mapping
Visualize how services, hosts, databases, queues, and network paths relate. During incidents, blast radius and upstream dependencies are obvious. When planning changes, you can see what might break and who needs a heads-up.
Anomaly detection
Learn typical patterns for traffic, latency, saturation, and errors. Highlight regressions during releases and seasonal events. Give responders context about when behavior diverged and which dimensions matter most.
Release guardrails
Compare pre- and post-deploy performance automatically. Tie change events to incidents, spikes, and slowdowns. Roll forward with confidence when telemetry looks healthy; roll back quickly when it doesn’t.
Synthetic journeys
Script key transactions like checkout, onboarding, and search. Catch regressions before customers feel them. When a step fails, pivot from synthetic results to relevant traces, logs, and resources instantly.
API and automation
Manage dashboards, alerts, and integrations as code. Bake observability into platform golden paths and templates. Keep environments consistent across teams and regions.
Use cases
Hybrid troubleshooting
Follow symptoms across services, hosts, databases, and networks. Move from a 500 error to the troublesome slow query, overloaded node, or misconfigured policy in minutes, not hours.
Cloud migration
Run legacy and cloud workloads side by side. Baseline and compare performance, and validate improvements with objective telemetry. De-risk cutovers with SLOs and synthetic checks.
E-commerce peaks
Protect critical flows during traffic spikes. SLOs and anomaly detection highlight trouble early. Tie incidents to revenue, so teams prioritize the highest-impact fixes.
Platform engineering
Offer observability as a paved road with sane defaults. Give developers standard dashboards, alerts, and runbooks. Keep freedom where it matters—code—while standardizing the reliability basics.
Site Reliability Engineering analytics
Track incident patterns, toil, and time to restore. Invest where reliability actually improves. Share clear metrics with leadership without spreadsheets.
Performance tuning
Find hot queries, memory leaks, and chatty dependencies and inefficient calls. Validate optimizations with before-and-after comparisons tied to user experience.
Capacity planning
Trend usage, saturation, and headroom. Plan upgrades and autoscaling based on facts, not hunches. Avoid unexpected surprise limits during launches.
Security context
Bring change data and alerts into the same view as operations telemetry. Improve investigations with shared timelines and ownership
Support
SolarWinds offers options designed to help you move quickly from install to insight. The Success Center covers product docs and how-to guides. THWACK®, the SolarWinds user community, shares dashboards, scripts, and lessons learned. SolarWinds Academy offers role-based training and certifications so teams can ramp together. If you want to interact with a human, open a ticket or schedule time with support. For strategic rollouts, success plans can align goals, milestones, and adoption metrics. The aim is simple: keep your deployment healthy and your team productive.
Pricing
Pricing is built to fit how you work. Start with the signals you need, then expand. Network and Infrastructure monitoring starts at $12 per active network device or host per month, ideal for hybrid estates. Application Observability starts at $27.50 per service, so microservices teams can scale predictably. Log Observability is $5 per gigabyte, with controls to manage ingest and retention. Database Observability is $70 per database instance, covering popular engines and deep wait analysis. A 30-day free trial helps you validate value, wire critical integrations, and get buy-in without surprise costs.
Next Steps With SolarWinds
To learn more about SolarWinds Observability, start a free trial today, or if you’d prefer, test drive the interactive demo environment. And when you’re preparing to talk to Finance, check out the prices for SolarWinds Observability.
2) Datadog
Overview
Datadog is a software-as-a-service monitoring and security platform spanning infrastructure, application performance monitoring, logs, user experience, and serverless. Teams like the breadth of integrations and quick setup, then layer anomaly detection, service level objectives, and governance. As estates expand, organizations mix products to consolidate point tools and standardize workflows across squads.
Key features and strengths
- Broad integration library for fast onboarding
- Solid application performance monitoring tracing at scale
- Real user monitoring and session replay options
- Security signals integrated with operations workflows
- Serverless and Kubernetes visibility for modern stacks
Pricing
Usage and host-based; free trial available
3) Dynatrace
Overview
Dynatrace emphasizes automation. OneAgent discovers services, maps dependencies with Smartscape, and feeds Davis artificial intelligence for correlation. The approach reduces manual triage and explains likely causes in complex, regulated environments. Grail unifies analytics for logs and events. Enterprises running large Kubernetes estates appreciate the autonomous discovery and clean problem narratives during incidents.
Key features and strengths
- OneAgent deployment and automatic discovery
- Davis artificial intelligence for causation
- Kubernetes and containers with deep context
- Grail data lakehouse for analytics
- Business events for user impact insight
Pricing
Enterprise and consumption models; free trial available
4) New Relic
Overview
New Relic centers on a developer-friendly telemetry lake with opinionated workflows for application performance, logs, errors, browser, and mobile telemetry. Quickstarts and dashboards help teams get value fast, while a “queryable” layer keeps power users happy. Many teams instrument services quickly, then shift into anomaly detection and error tracking across environments and releases.
Key features and strengths
- Unified telemetry lake for flexible queries
- Friendly quickstarts and curated dashboards
- Error tracking across services and clients
- Browser, mobile, and synthetic monitoring coverage
- Service level objectives and alerting tools
Pricing
Usage-based with free tier
5) Elastic Observability
Overview
Elastic Observability brings logs, metrics, and traces together in a search-first experience. If your teams already know Elasticsearch and Kibana, onboarding is straightforward. Elastic is compelling when you want deep search plus observability, or when security operations also runs on Elastic. Recent features add AI-assisted investigation and guided troubleshooting.
Key features and strengths
- Search-centric workflows favored by analysts
- Logs, metrics, and tracing in one place
- Application performance monitoring agents available
- Uptime and synthetics for critical journeys
- AIOps signals to reduce noise
Pricing
Elastic Cloud usage pricing; free trial available
6) Grafana Cloud
Overview
Grafana Cloud runs the LGTM stack as a managed service: Loki for logs, Grafana for visualization, Tempo for traces, and Mimir for metrics. You keep the open-source feel without self-hosting toil. Teams with Grafana experience like familiar dashboards and alerts, while the free tier makes it easy to start small and scale deliberately.
Key features and strengths
- Grafana visualizations for flexible dashboards
- Loki log pipeline with labels and queries
- Tempo tracing with OpenTelemetry support
- Mimir metrics for large cardinality cases
- Plug-in ecosystem and integrations
Pricing
Free, Pro, and Enterprise; usage-based
7) Sumo Logic
Overview
Sumo Logic blends log analytics, observability, and Cloud Security Information and Event Management in one platform. It appeals when security and operations want shared context with curated content. Credits-based plans help right-size ingest and scanning, while apps accelerate time to dashboards and alerts. Enterprises value its multi-tenant software as a service reliability.
Key features and strengths
- Log analytics at scale with content packs
- Cloud Security Information and Event Management options
- App quickstarts for common platforms
- Credits-based usage and controls
- Ingest governance and retention tools
Pricing
Self-serve tiers; free trial
8) IBM Instana
Overview
Instana focuses on automatic instrumentation and continuous profiling with strong service mapping for microservices. Teams praise quick time to value in containerized environments and prescriptive problem detection. Its real-time discovery and curated insights reduce configuration effort and keep attention on code, not dashboards.
Key features and strengths
- Auto-instrumentation across popular languages
- Real-time discovery and dependency mapping
- Continuous profiling for cost and performance
- Kubernetes visibility with context
- Smart alerting tuned for services
Pricing
Quote based; trial typically available
9) Cisco AppDynamics
Overview
AppDynamics centers on business transactions and correlates application, infrastructure, and user experience telemetry. It is common in enterprises that need governance, change windows, and deep coverage for legacy platforms. Business-level analytics help tie technical health to outcomes, which supports prioritization during incidents.
Key features and strengths
- Business transaction tracing and analytics
- Deep application flow and code insights
- Kubernetes views and topology maps
- Synthetic monitoring for key journeys
- Dashboards aligned to stakeholders
Pricing
Quote-based
10) Honeycomb
Overview
Honeycomb popularized observability for high-cardinality systems. Queries feel exploratory, with BubbleUp and trace-centric workflows to pinpoint outliers. Teams use it to ask new questions of production without reworking dashboards. It rewards curiosity and helps engineers understand why a small slice of traffic behaves differently.
Key features and strengths
- BubbleUp to surface unusual subsets
- High-cardinality analysis at interactive speeds
- Trace-first debugging and correlations
- Service level objectives and budgets
- Developer-friendly query experience
Pricing
Free, Pro, and Enterprise
11) ServiceNow Cloud Observability
Overview
ServiceNow Cloud Observability, formerly Lightstep, emphasizes service level objectives, change intelligence, and tracing with tight links to the ServiceNow platform. Teams running incidents through ServiceNow value native handoffs, clean dashboards, and service catalogs that reflect ownership. It supports progressive delivery with change-aware analysis.
Key features and strengths
- Change Intelligence linked to deploys
- SLOs and error budgets for reliability
- Trace correlations for root cause
- Clean dashboards and service maps
- OpenTelemetry friendly ingestion
Pricing
Community free; otherwise quote-based
12) LogicMonitor
Overview
LogicMonitor is infrastructure-first monitoring with coverage for networks, servers, storage, and cloud. AIOps-style event correlation reduces noise, and built-in dashboards make it practical for hybrid environments. Many organizations use it to modernize legacy infrastructure monitoring while adding cloud awareness without rewriting everything.
Key features and strengths
- Broad device coverage and templates
- Event correlation to focus response
- Cloud and on-premises parity
- Topology and dependency context
- NetFlow and network performance monitoring
Pricing
Quote based; free trial typically available
13) Chronosphere
Overview
Chronosphere is Prometheus-native observability with strong data controls to rein in cardinality and cost. Engineering-driven organizations use it to scale metrics reliably and keep spend predictable. The platform encourages thoughtful aggregation, retention, and query patterns that protect performance.
Key features and strengths
- Prometheus compatibility and migration paths
- Aggregation and drop rules for control
- Usage profiler to visualize costs
- Grafana imports and dashboards
- Fast queries with guardrails
Pricing
Quote-based
14) Observe, Inc.
Overview
Observe treats observability as a data problem. It stores logs, metrics, and traces in a single lake, models relationships, and lets you query with OPAL. Teams that want fewer silos and flexible analysis across operational data find the approach compelling, especially during complex investigations.
Key features and strengths
- Unified data lake for operations
- OPAL query language and modeling
- Relationships graph across entities
- Live mode for iterative exploration
- Cost-aware design and governance
Pricing
Usage-based
15) AWS CloudWatch
Overview
CloudWatch is native monitoring and logging for Amazon Web Services. If you are all-in on Amazon Web Services, it is a logical starting point: metrics, logs, alarms, dashboards, and tight service integrations. It keeps wiring simple and centralizes telemetry for managed services.
Key features and strengths
- Native Amazon Web Services metrics and logs
- Alarms and dashboards for quick visibility
- Elastic Kubernetes Service and Elastic Container Service coverage
- Lambda and serverless context
- EventBridge and automation hooks
Pricing
Amazon Web Services pay-as-you-go; free tier exists
16) Azure Monitor
Overview
Azure Monitor centralizes telemetry for Microsoft Azure resources. Application Insights brings application performance monitoring, traces, and error detection, while Kusto Query Language powers deep analysis. If you are Azure-first, it provides coherent operations with native role-based access control and workbooks.
Key features and strengths
- Application Insights for application performance monitoring
- Kusto Query Language analytics and workbooks
- Alerts, actions, and automation options
- Virtual machines and Azure Kubernetes Service views
- Native identity and access alignment
Pricing
Azure consumption pricing; free tier exists
What is observability software and what are its common uses?
Observability software helps you understand complex systems by collecting, correlating, and analyzing telemetry—metrics, logs, traces, and user experience—so you can detect issues, find root causes, and improve reliability.
Standard observability
Platforms that centralize telemetry with dashboards, alerting, and incident workflows so operations can run day to day with clarity
Secure observability
Adds security analytics and detections so security and operations share context and accelerate investigations with the same signals
Hybrid observability
Focused on on-premises and cloud together, mapping devices, services, and dependencies across networks, hosts, containers, and managed services
Developer observability
Developer-centric flows like errors inbox, feature-flag correlations, continuous delivery visibility, and fast ad hoc queries for debugging
Benefits of using observability software
Faster root-cause analysis
Correlate symptoms across services and layers to cut triage time and reduce mean time to resolution
Improved system reliability
Service level objectives and early-warning alerts help teams prevent incidents and keep service levels steady
Enhanced performance optimization
Pinpoint slow queries, noisy neighbors, and inefficient code paths before customers feel pain
Proactive incident detection
Baselines and anomaly detection highlight regressions during and after deployments
Scalability and flexibility
Handle growth in services and telemetry without rebuilding your pipeline
AI and automation
Reduce alert fatigue, highlight likely causes, and suggest next steps so engineers move faster
Features to look for in observability software
Must-have features
- Full telemetry: metrics, logs, traces with unified context
- Embedded artificial intelligence assistance for anomaly detection and triage
- Service level objectives and alerting that map to user impact
- Open standards support such as OpenTelemetry
Important considerations
- Integrations with your stack and continuous delivery tools
- Scalability, data controls, and predictable pricing
- Quality of support, documentation, and training resources
Choosing the right Splunk alternative
- Create a list of must-have features
- Form an evaluation team with key stakeholders
- Run and evaluate trials and proofs of concept against pre-agreed success criteria
How to set up your new observability software
- Define clear goals for the software
- Plan the implementation to minimize friction for the team
- Configure settings and integrations
Document your usage and testing your new setup
Documentation: Write a lightweight “how we use it” guide—naming conventions, dashboards, alert thresholds, and on-call rules
Testing: Pilot with a small group and real incidents, gather feedback, and adjust dashboards and alerts
Keep optimizing
Schedule a monthly tune-up to trim noise, watch cost, and refine dashboards so your team stays fast and focused.
Product specifications and other information set forth herein have either been made accessible by suppliers, manufacturers, publications, or gathered from publicly available sources as of the date of this document. Although measures are taken to ensure the accuracy of the information, SolarWinds makes no representations or warranties as to the completeness or accuracy of the information and shall incur no liability for any errors or omissions.
As of September 2025
