Panther
Cloud security monitoring and analytics software
Security information and event management (SIEM) software
Log analysis software
Cloud security software
System security software
DevSecOps software
- Features
- Ease of use
- Ease of management
- Quality of support
- Affordability
- Market presence
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What is Panther
Panther is a cloud-native SIEM and security analytics platform that centralizes security logs and cloud telemetry for detection, investigation, and alerting. It is used by security operations and cloud security teams to build and run detections across AWS, GCP, Azure, and common SaaS and endpoint data sources. Panther emphasizes detection-as-code workflows (using Python/SQL) and integrates with data lakes and modern cloud storage to support scalable log retention and search. It is typically deployed by organizations that want engineering-friendly customization and cloud-first operations rather than appliance-style SIEM management.
Detection-as-code workflows
Panther supports writing and managing detections as code, commonly using Python and SQL, which aligns with DevSecOps practices. This approach enables version control, code review, CI/CD, and repeatable deployment of detection logic. It can reduce reliance on point-and-click rule building for teams that already operate with software engineering processes.
Cloud-first data collection
Panther is designed to ingest and analyze cloud logs and events from major cloud providers and common SaaS sources. It fits environments where security telemetry is primarily cloud-native (for example, cloud audit logs, identity events, and SaaS activity). This focus can simplify onboarding for cloud-centric organizations compared with SIEMs optimized around on-prem infrastructure.
Integrations for alerting and response
Panther integrates with common incident management, messaging, and ticketing tools to route alerts and support investigation workflows. It also supports enrichment and context through integrations, helping analysts triage events with additional metadata. These capabilities support operationalizing detections into SOC processes without requiring a separate orchestration layer for basic workflows.
Engineering skills often required
The detection-as-code model can be a barrier for teams that lack Python/SQL skills or do not have mature code management practices. Organizations that prefer GUI-driven rule creation may face a longer time-to-value. Ongoing tuning and maintenance may also require developer time rather than purely analyst-driven administration.
Not a full CNAPP suite
Panther primarily addresses log-based detection, investigation, and alerting rather than providing a complete cloud security posture and workload protection suite in one product. Teams may still need separate tools for CSPM, vulnerability management, container/Kubernetes runtime protection, or asset inventory depending on requirements. This can increase toolchain complexity for buyers seeking a single consolidated cloud security platform.
Cost and scale depend on logs
As with many SIEM and log analytics products, total cost and performance are sensitive to ingestion volume, retention requirements, and query patterns. High-cardinality logs and long retention can increase storage and processing needs. Buyers typically need careful data source selection, filtering, and retention policies to manage spend and operational overhead.
Seller details
Panther Labs, Inc.
San Francisco, CA, USA
2018
Private
https://panther.com/
https://x.com/pantherlabs
https://www.linkedin.com/company/panther-labs/
