Applying security at the end of the development cycle is like checking a car’s brakes after it’s already on the track. It works—sometimes. But it fails when it matters most.
With increasingly automated pipelines, ephemeral infrastructure, and distributed systems running across multiple clouds, relying on manual audits or occasional analyses no longer makes sense. DevSecOps emerges as a pragmatic approach: integrating security as a natural part of development and operations. No drama, no extra steps, no halting delivery.
2025: the context has changed — and continues to evolve
In 2025, attack vectors are numerous. Third-party libraries, containers, open-source code, vulnerable pipelines, misconfigured APIs—everything can be exploited. The time between a CVE disclosure and its actual exploitation by automated bots is now measured in hours.
In this environment, DevSecOps doesn’t rely on good intentions. It depends on real automation that detects risks during development. These include scanners embedded in the CI/CD pipeline, validations that block the merging of vulnerable code, and policies that precisely control access to environments. The response is no longer reactive—it’s proactive.
Security as Code: executable, versioned, and auditable policy
DevSecOps doesn’t require every developer to become a security expert. But it does require the process to be secure by default.
This means versioning security policies alongside the source code. It means a malicious commit doesn’t go unnoticed because static and dynamic tests (SAST and DAST) are embedded in the pipeline. It means access permissions to the database or storage aren’t managed through spreadsheets, but through auditable code.
Tools like Snyk, Aqua, Checkmarx, and Trivy already enable this type of integration without causing friction with the Dev team.
Realistic integration: what works in practice for DevSecOps.
Implementing DevSecOps with realism means accepting that not everything will be secure from day one. But it also means you don’t have to wait months to get started.
It works better this way:
- Start with a lightweight static analysis tool in the repository (e.g., Snyk or SonarQube).
- Configure silent alerts to avoid blocking delivery at the beginning. Monitor.
- Track the main failure patterns and gradually introduce blocking rules.
- Automate the fixing of known vulnerabilities in dependencies (with automatic PRs).
- Train the team based on real examples that occurred in the company’s own code.
DevSecOps is a short marathon: you start slow, but you need to gain momentum quickly.
Metrics that matter — and that don’t deceive.
Instead of chasing reports with “100% security coverage” (which often hide gaps), prioritize metrics that indicate practical responses:
- MTTR (Mean Time to Remediate): how long does it really take you to fix a flaw?
- Block rate vs. false positives: does your pipeline block when it should — or when it shouldn’t?
- Exception flow: how do you handle code that fails the checks but still needs to go to production?
These are the questions that reveal maturity. And they can be answered with data, not with promises.
Adoption without dogma
The goal is not to follow a DevSecOps playbook. It’s to reduce operational risks without slowing down deliveries.
If your stack is based on sensitive data, exposed via API, running in the cloud, with multiple teams deploying every day, then some form of DevSecOps is already happening — even if informally. What this article proposes is to make it visible, traceable, and, most importantly, sustainable.
At dbsnoop, we talk a lot about observability, automation, and security in data environments. If you’re looking to implement consistent DevSecOps practices in your infrastructure, follow our articles and see how to connect security to the real lifecycle of your applications.
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