Security with Datadog (DevSecOps)
Security with Datadog (DevSecOps)
For years, security and IT operations worked in silos: separate tools, separate data, separate teams. The result is a gap between the speed of software delivery and the ability to detect and respond to threats. By the time the security team analyzes an incident, the operations team has often already been responding for hours with incomplete information.
Datadog unifies security and observability in a single platform. Apiwan implements Datadog’s security capabilities so that DevOps, SRE, and Security teams work with the same data, the same context, and a coordinated response — from runtime threat detection to cloud security posture assessment and application protection in production.
Who is this service for?
Ideal for organizations that:
- Want to adopt DevSecOps and need to integrate security into their existing observability workflows without adding yet another tool to the stack.
- Have compliance requirements (PCI-DSS, SOC 2, ISO 27001, HIPAA, GDPR) and need continuous, automated evidence of compliance.
- Are looking to replace or complement traditional SIEM tools (Splunk, IBM QRadar) with a more integrated solution built for cloud-native environments.
- Are in the cloud (AWS, Azure, GCP) and lack clear visibility into their security posture: which resources are exposed? Which configurations are wrong?
- Develop applications and want to detect vulnerabilities in dependencies and protect APIs in production.
What does the service include?
Cloud SIEM — Real-time threat detection
Datadog Cloud SIEM detects threats in real time across the logs, metrics, and traces already flowing through the platform. No need to move data to a separate SIEM: security lives where observability lives.
What we implement:
- Cloud SIEM configuration and activation of out-of-the-box detection rules (700+ rules maintained by Datadog for AWS, Azure, GCP, Kubernetes, Active Directory, and more)
- Design of custom detection rules tailored to the client’s risk model and the expected behavior of their environment
- Security signal configuration: severity classification, event correlation, and grouping of related signals
- Integration with incident response workflows: PagerDuty, Jira, ServiceNow, Slack
- False-positive reduction through continuous rule tuning and suppression of expected noise
- Log Management for security sources: CloudTrail, VPC Flow Logs, WAF, DNS, authentication, privileged access
Cloud Security Posture Management (CSPM)
CSPM continuously evaluates cloud infrastructure configuration to detect deviations from security best practices before they can be exploited.
What we implement:
- CSPM activation across AWS, Azure, and Google Cloud accounts
- Continuous evaluation against compliance frameworks: CIS Benchmarks, PCI-DSS, SOC 2, HIPAA, NIST, ISO 27001
- Detection of misconfigurations: public S3 buckets, overexposed security groups, unrotated access keys, unencrypted services, roles with excessive permissions
- Drift Detection in Infrastructure as Code: detection of manual changes to resources that should be managed by Terraform or CloudFormation
- Security posture dashboards and audit-ready compliance reports
- Prioritization of findings by severity and real exposure, so the team addresses what matters most first
Application Security Management (ASM) & Code Security
Application security is addressed on two fronts: in the code during development, and at runtime once the application is in production.
At runtime — Application Security Management (ASM):
- Protection of APIs and web applications against the most common attacks: SQL injection, XSS, SSRF, LDAP injection, and more (based on OWASP Top 10 rules)
- Real-time detection of exploitation attempts, with automatic correlation to APM traces — the same observability stack protects and monitors
- Vulnerability management: identification of exposed services with known vulnerable dependencies (CVEs)
In the code — Code Security:
- Software Composition Analysis (SCA): analysis of open-source dependencies for known vulnerabilities (CVEs), integrated into the CI/CD pipeline
- Static Analysis (SAST): static source-code analysis to detect insecure patterns before they reach production
- Secret Scanning: detection of credentials, API tokens, and secrets accidentally exposed in source code or logs
Workload Protection (CWS):
- Runtime detection of anomalous behavior at the process, file, and container level
- Alerts when a process runs unexpected commands, accesses sensitive files, or escalates privileges
- Coverage of hosts, Docker containers, and Kubernetes pods
Security tool consolidation
If the organization already operates separate security tools — SIEMs like Splunk or IBM QRadar, workload protection solutions like CrowdStrike or Prisma Cloud, or vulnerability management platforms — Apiwan evaluates possible consolidation scenarios within Datadog.
Consolidation reduces the operational cost of maintaining multiple platforms, eliminates data silos between security and operations, and simplifies incident response by keeping everything in the same context.
The value of native integration
Unlike a traditional SIEM that receives data as static logs, Datadog Security has native access to the full observability context: it knows which service generated the alert, which host it’s running on, its dependency topology, whether it had a recent deployment, and its current SLO. This turns every security signal into an alert with complete operational context — and dramatically cuts investigation time.
