The transition from physical servers to Infrastructure as Code fundamentally transformed operations in the 2010s—bringing massive scalability alongside new management complexities. We’re witnessing history repeat itself with software supply chain security. The same pattern that made manual server provisioning obsolete is now playing out with Software Bill of Materials (SBOM) management. This pattern is creating an entirely new category of operational debt for organizations that refuse to adapt.
The shift from ad-hoc security scans to continuous, automated supply chain management is not just a technical upgrade. At enterprise scale, you simply cannot secure what you cannot see. You cannot trust what you cannot verify. Automation is the only mechanism that delivers consistent visibility and confidence in the system.
“Establishing trust starts with verifying the provenance of OSS code and validating supplier SBOMs. As well as, storing the SBOMs to track your ingredients over time.”
The Scale Problem: When “Good Enough” Isn’t
Manual processes work fine until they don’t. When you are managing a single application with a handful of dependencies you can get away with lots of unscalable solutions. But modern enterprise environments are fundamentally different. A single monolithic application might have had stable, well-understood libraries but modern cloud-native architectures rely on thousands of ephemeral components that change daily.
This fundamental difference creates a visibility crisis that traditional spreadsheets and manual scans cannot solve. Organizations attempting to manage this complexity with “Phase 1” tactics like manual scans or simple CI scripts typically find themselves buried under a mountain of data.
Supply Chain Security Evolution
- Phase 1: The Ad-Hoc Era (Pre-2010s) was characterized by manual generation and point-in-time scanning. Developers would run a tool on their local machine before a release. This was feasible because release cycles were measured in weeks or months, and dependency trees were relatively shallow.
- Phase 2: The Scripted Integration (2020s) brought entry-level automation. Teams wired open source tools like Syft and Grype into CI pipelines. This exploded the volume of security data without a solution for scaling data management. “Automate or not?” became the debate, but it missed the point. As Sean Fazenbaker, Solution Architect at Anchore, notes: “‘Automate or not?’ is the wrong question. ‘How can we make our pipeline set and forget?’ is the better question.”
- Phase 3: The Enterprise Platform (Present) emerged as organizations realized that generating an SBOM is only the starting line. True security requires managing that data over time. Platforms like Anchore Enterprise transformed SBOMs from static compliance artifacts into dynamic operational intelligence, making continuous monitoring a standard part of the workflow.
The Operational Reality of “Set and Forget”
The goal of Phase 3 is to move beyond the reactive “firefighting” mode of security. In this model, a vulnerability disclosure like Log4j triggers a panic: teams scramble to re-scan every artifact in every registry to see if they are affected.
In an automated, platform-centric model, the data already exists. You don’t need to re-scan the images; you simply query the data you’ve already stored. This is fundamentally different from traditional vulnerability management.
Anchore scans SBOMs built whenever: five months from now, six months ago, 30 years in the future. If a new vulnerability is detected, you’ll know when, where and for how long.
Continuous assessment of historical artifacts is what separates compliance theater from true resilience. It allows organizations to answer the critical question (“Are we affected?”) in minutes rather than months.
The Implementation of Shift Left
Automation also fundamentally changes the developer experience. In traditional models, security is a gatekeeper that fails builds at the last minute, forcing context-switching and delays. In an automated, policy-driven environment, security feedback is immediate.
When automation is integrated correctly into the pull request workflow, developers can resolve issues before code ever merges. “I’ve identified issues. Fixed them. Rebuilt and pushed. I didn’t rely on another team to catch my mistakes. I shifted left instead.”
This is the promise of DevSecOps: security becomes a quality metric of the code, handled with the same speed and autonomy as a syntax error or a failed unit test.
Where Do We Go From Here?
We are still in the early stages of this evolution, which creates both risk and opportunity. First-movers can establish a trust foundation before the next major supply chain incident. Those who wait will face the crushing weight of manual management.
Crawl: The Open Source Foundation
Start with industry standards. Tools like Syft (SBOM generation) and Grype (vulnerability scanning) provide the baseline capabilities needed to understand your software.
- Generate SBOMs for your critical applications using Syft.
- Scan for vulnerabilities using Grype to understand your current risk posture.
- Archive these artifacts to begin building a history, even if it is just in a local filesystem or S3 bucket.
Walk: Integrated Automation
Early adopters can take concrete steps to wire these tools into their daily flow:
- Integrate scans into GitHub Actions (or your CI of choice) to catch issues on every commit.
- Define basic policies (e.g., “fail on critical severity”) to prevent new risks from entering production.
- Separate generation from scanning. It is often more efficient to generate the SBOM once and scan the JSON artifact repeatedly, rather than re-analyzing the heavy container image every time.
Want to bring these steps to life? Watch the full Automate, Generate, and Manage SBOMs webinar to see exactly how to wire this up in your own pipeline.
