Do the words, “It’s audit time!” make your stomach sink? If so, you’re not alone. Assisting with evidence collection for compliance audits around PCI DSS, SOC-2, ISO 27001, NIST and HITRUST is a drain on DevOps teams’ time and resources at companies of all types and sizes – time and resources that could be better spent driving innovation.
The good news is, vendors have taken notice, and are delivering new tools and platforms that use automation to eliminate repetitive manual tasks and dramatically speed the audit process. This is entirely in line with the DevOps philosophy of tackling various IT tasks and requirements “as code” to remove tedium and improve efficiency and orchestration. In fact, as this movement to improve the compliance process picks up steam, I believe it’s entirely likely the next evolution is the use of open APIs and online communities where engineers can build and share software to automate a wide variety of evidence collection for compliance.
But before we can get there, let’s understand where we are today and assess new opportunities going forward.
Audit Support: DevOps’ Favorite Task
As keepers of cloud environments, DevOps teams typically spend hundreds or thousands of hours each year gathering evidence for compliance audits. This tedious, manual labor takes significant time away from their primary job responsibilities. Large enterprises often have multiple, overlapping audits each year, with little break from the grind of evidence collection. Companies that make heavy use of the public cloud face additional challenges; the increased complexity means that evidence collection is more difficult, and the fast pace of software development and change management in the cloud (compared to more traditional monolithic application updates) makes it difficult for compliance to keep up. This contributes to an overall lack of clarity and confidence in the compliance process at the leadership level.
Audit Prep as Code
When I ran a cloud engineering team at a previous job, we realized the vast majority of repetitive, manual labor involved in evidence collection could be automated to save time and free up resources for other business needs. This automation also improved the completeness and accuracy of the evidence gathered, ensured that important areas weren’t overlooked and allowed for more regular assessment to prevent “drifting” out of compliance in the fast-paced cloud world. While automation helps with multiple aspects of compliance audits (such as evidence-to-control mapping and cross-walking evidence across common control frameworks), it’s the automation of evidence collection that primarily impacts DevOps.
In this scenario, automated collectors crawl your public cloud environments and connected SaaS systems to rapidly gather technical evidence such as specifics on user access, encryption of data at rest, key management, network segmentation, firewalls, vulnerability scan reports and more. The results are transformed into formatted reports ready for internal review, analysis and auditor review/approval. This, alone, can save thousands of hours annually for typical enterprises facing multiple audits. Even better, the data is considered more complete and accurate from a compliance perspective, because it includes time stamps and other metadata to ensure capture and processing integrity.
As mentioned, this is well aligned with the broader “X as code” mantra that underlies many DevOps automation initiatives – and why not? What could possibly be a more repetitive, manual task than capturing, renaming, organizing and describing screenshots?
The Scripting Curse
When confronted with evidence collection, an engineer’s first thought is usually, “I can write a script for that!” Scripting is a form of automation, but it has some limits in this scenario. First, scripting and doing the necessary QA shouldn’t be your day job; there are better things to spend time on. Second, given the explosion of cloud infrastructure and SaaS apps, there can be a lot of scripts to create. In fact, it’s arguably a never-ending task. Finally, while you understand your scripts, who’s doing the next audit? If it’s not you, are you going to explain and train someone else on all the work you’ve done? Scripting elements of evidence collection is an improvement over doing it manually, but is still only one piece of the larger puzzle.
Compliance is a Community, not an Island
So what’s the best way to automate evidence collection? Multiple vendors are tackling the challenge, from cloud platform providers to established GRC vendors and cloud compliance startups – and new tools have already begun to hit the market over the last few months.
But as discussed, a primary challenge is that there is a lot of complexity in most cloud environments, and tools that approach the puzzle from only one direction – say, a particular cloud platform – still leave a lot of potentially relevant systems untouched. In fact, when you take all of the variations possible with cloud infrastructure into account, this might, ultimately, be a challenge that is best tackled at the DevOps community level.
Consider this: adherence to industry standards for data handling, privacy and protection is not a competitive issue. We are all better off if everyone shares a basic commitment to complying with these IT security and compliance standards. Viewed from that perspective, the more we can lower the barriers to achieving this compliance, the broader the adoption will be.
What I hope to see is a DevOps community that coalesces around automating audit readiness. At the engineering level, this could entail sharing of custom collectors. For platform and SaaS vendors, it means ensuring open APIs that allow capture and extraction of relevant data. And the compliance tool vendors must design their collection engines, evidence libraries and usage policies such that customization and sharing is possible. Similarly, automation tools must not only pull data from standard systems, but support pushing data from custom systems or legacy infrastructure. In my view, this bottoms-up approach is the best way to stop wasting DevOps’ time on audit prep, while still allowing enough autonomy to do what works best for their specific environment.
In this future, then, perhaps an upcoming compliance audit won’t produce a collective groan from the DevOps team – or at least, generate a quieter one.
