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What is Lacework?

Lacework is a cloud security platform that uses artificial intelligence to monitor and protect cloud infrastructure by detecting unusual behaviour patterns. It works across major cloud providers like AWS, Azure, and Google Cloud, watching for suspicious activity that might indicate a security breach or misconfiguration. Rather than relying solely on predefined rules, Lacework learns what normal activity looks like in your environment and alerts you when something deviates from that baseline. This approach helps catch threats that traditional security tools might miss. The platform is designed for organisations running containerised and cloud-native applications, where traditional security tools often struggle to keep pace with the speed and scale of modern infrastructure.

Key Features

Behavioural anomaly detection

identifies unusual patterns in cloud activity by learning baseline behaviour

Multi-cloud support

works across AWS, Azure, Google Cloud, and other cloud platforms from a single console

Container and Kubernetes monitoring

provides visibility into containerised workloads and orchestration platforms

Compliance reporting

generates reports for standards like CIS, PCI-DSS, SOC 2, and HIPAA

Threat investigation tools

helps teams analyse and respond to detected security events

API integrations

connects with incident response and ticketing systems for automated workflows

Pros & Cons

Advantages

  • Free tier available with meaningful functionality for small teams and organisations evaluating the platform
  • Behaviour-based detection catches novel threats that signature-based tools might miss
  • Works across multiple cloud providers, useful for organisations with hybrid or multi-cloud setups
  • Reduces false positives through machine learning rather than generating excessive alerts

Limitations

  • Requires integration with cloud providers and may take time to establish accurate baseline behaviour before full effectiveness
  • Can be complex to configure and tune properly, particularly for teams without dedicated cloud security expertise
  • Pricing for larger deployments and advanced features may become significant as your cloud footprint grows

Use Cases

Monitoring containerised applications in Kubernetes clusters for suspicious behaviour

Detecting compromised cloud accounts or credentials being misused

Identifying misconfigurations in cloud infrastructure before they become security risks

Continuous compliance monitoring and evidence gathering for regulatory audits

Threat investigation and incident response within cloud environments