What is Splunk?
Splunk is an observability platform that gives enterprise IT and operations teams real-time visibility across their entire technology stack. It collects machine data at petabyte scale and uses AI to help teams detect issues, find root causes, and prevent outages before they hit users.
The platform combines full-stack observability with security monitoring in one data foundation. Teams get the business context they need to know which problems actually matter, not just which systems are throwing alerts. Whether the issue lives in cloud infrastructure, a microservice, a third-party network, or an AI workload, this observability platform surfaces it and helps engineers act fast.
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Features & Benefits
- AI SRE Agents: deploy agentic AI that correlates signals across domains, assembles traces, logs, network paths, and business KPIs into ready-made context, and proposes specific remediation actions like rollbacks, feature flag changes, or capacity adjustments
- Application Performance Monitoring: troubleshoot performance problems down to the code level, covering third-party APIs and network paths, with AI assistants to cut mean time to resolution
- Infrastructure Monitoring: watch clouds, containers, and on-prem systems in a single live view with real-time streaming architecture that spots anomalies in seconds
- Alert Noise Reduction: correlate alert storms into one actionable view so the observability platform surfaces what needs attention rather than burying teams in noise
- Digital Experience Analytics: track web and mobile user experiences to detect and prevent issues that affect end users before they escalate
- Agent Observability: monitor AI infrastructure end-to-end, including GPUs, models, vector databases, and agent frameworks, while tracking hallucinations, PII leakage, token consumption, and model ROI
- AIOps / IT Service Intelligence: use AI and machine learning to identify anomalies across multiple monitoring sources, reduce alert noise, and prevent service outages
- Business Context Mapping: tie services to SLOs, KPIs, customer segments, and geos so impact is measured in revenue and user experience, not just system health
- Federated Search: query data across different sources without moving it, giving teams a unified view of distributed environments
- Telemetry Pipeline Management: control data routing, filtering, and costs with built-in pipeline tools and native OpenTelemetry support
- Integrations: connect to 2,000+ sources across cloud providers, SaaS tools, IT systems, and OT and IoT machine data
What can Splunk do?
- Monitor cloud, container, and on-prem infrastructure in real time
- Detect performance anomalies across the full application stack
- Correlate alerts into a single root cause view
- Troubleshoot microservices and distributed systems
- Track AI model performance, cost, and safety signals
- Monitor GPUs and AI agent frameworks end-to-end
- Reduce mean time to resolution with AI-assisted investigation
- Map service issues to business KPIs and revenue impact
- Analyze web and mobile user experience data
- Prevent service outages with AIOps-driven anomaly detection
- Search telemetry data across federated environments
- Control observability data pipeline costs
Real-World Applications
SRE and platform engineering teams at large enterprises may use the observability platform to get ahead of outages instead of reacting to them. When an alert storm hits, Splunk’s AI SRE agents can correlate signals across infrastructure, services, and network layers, then surface a single actionable view with a proposed fix. For a team managing hundreds of microservices, that can mean resolving incidents that would otherwise take hours.
Retail and e-commerce companies can use Splunk to tie service health directly to checkout performance and revenue. If latency spikes in a payment service, the platform can identify which customer segments are affected, how severely, and what the downstream revenue risk looks like. That kind of business context helps engineering and product teams prioritize the right work.
Organizations running AI workloads have a specific need the observability platform addresses directly. Agent Observability monitors the entire AI stack, including models, vector databases, and orchestration layers. Teams can track token costs, spot silent degradations that standard monitoring misses, and flag safety issues like hallucinations or PII leakage before they reach users.
Airlines, insurers, and other high-availability operations can use Splunk’s Digital Experience Analytics to monitor what real users are seeing on web and mobile. Issues that degrade the customer experience can be caught and escalated before they turn into support volume or brand damage. The platform surfaces both technical signals and user journey data in the same view.
