Tuesday, April 7, 2015

Towards Compliance as Code

Infrastructure as Code is fundamental to DevOps. Automating the work of setting up and maintaining systems infrastructure. Making it defined, efficient, testable, auditable and standardized.

For the many of us who work in regulated environments, we need more. We need Compliance as Code.

Take regulatory constraints and policies and compliance procedures and the processes and constraints that they drive, and wire as much of this as possible into automated workflows and tests. Making it defined, efficient, testable, auditable and standardized.

DevOps Audit Defense Toolkit

Some big steps towards Compliance as Code are laid out in the Devops Audit Defense Toolkit, a freely-available document which explains how compliance requirements such as separation of duties between developers and operations, and detecting/preventing unauthorized changes, can be met in a DevOps environment, using some common, basic controls:

  1. Code Reviews. All code changes must be peer reviewed before check-in. Any changes to high-risk code must be reviewed a second time by an expert. Reviewers check code and tests for functional and operational correctness and consistency. They look for coding and design mistakes and gaps, operational dependencies, for back doors and for security vulnerabilities. Which means that developers must be trained and guided in how to do reviews properly. Peer reviews also ensure that changes can’t be pushed without at least one other person on the team understanding what is going on.
  2. Static analysis. Static analysis is run on all changes to catch security bugs and other problems. Any violations of coding rules will break the build.
  3. Automated testing is done in Continuous Integration/Continuous Delivery – unit and integration testing, and security testing. The Audit Toolkit assumes that developers follow TDD to ensure a high level of test coverage. All tests must pass.
  4. Traceability of all changes back to the original request, using a ticketing system like Jira (you can’t just use index cards on a wall to describe stories and throw them out when you are done).
  5. Operations checks/asserts after deployment and startup, and feedback from operations monitoring and especially from production failures. Metrics and post mortem review findings are used to drive improvements to testing and instrumentation, as well as deeper changes to policy definition, training and hiring – see John Allspaw’s presentation Ops Meta-Metrics: The Currency you use to pay for Change, from Velocity 2010, on how this can be done.
  6. All changes to code and infrastructure definitions, including bug fixes and patches, are deployed through the same automated, auditable Continuous Delivery pipeline.

A starting point

The DevOps Audit Defense Toolkit provides a starting point, an example to build on. You can add your own rules, checks, reviews, tests, and feedback loops.

It is also a work in progress. There are a few important problems still to be worked out:

Major Changes

The Audit Toolkit describes how standard changes can be handled in Continuous Delivery: small, well-defined, low-impact changes that are effectively pre-approved. Operations and management are notified as these changes are deployed (the changes are logged, information is displayed on screens and included in reports), but there is no upfront communication or coordination of these changes, because it shouldn’t be necessary. Developers can push changes out as soon as they are ready, and they get deployed immediately after all reviews and tests and other checks pass.

But the Audit Toolkit is silent on how to manage larger scale changes, including changes to data and databases, changes to interfaces with other systems, changes required to comply with new laws and regulations, major new customer features and technical upgrades. Changes that are harder to rollout, that have wider impact and higher risk, and require much more coordination. Which is, of course, the stuff that matters most.

You need clear and explicit hand-offs to operations and customer service for larger changes, so that all stakeholders understand the dependencies and risks and impact on how they work so that they can plan ahead. This can still be done in a DevOps way, but it does require meetings and planning, and some project management and paperwork. As an example, see how Etsy manages feature launches.

You also need to ensure that the policies for defining which changes are small enough and simple enough to be pre-approved, and for deciding which code changes are high risk and need additional review, are reasonable and unambiguous and consistent. You need to do frequent reviews to ensure that these policies are rigorously followed and that people don’t misunderstand or try to get away with pushing higher-risk, non-standard changes through without management/CAB oversight and explicit change approval.

Done properly, this means that the full weight of change control is only brought to bear when it is needed – for changes that have real operational or business risk. Then you want to find ways to minimize these risks, to break changes down into smaller pieces, to simplify, streamline and automate as much of the work required as possible, leveraging the same testing and delivery infrastructure.

Security testing

There is a lot of attention to responsible security testing in the Audit Toolkit. Because changes are made incrementally and iteratively, and pushed out automatically, you’ll need tools and tests that work automatically, incrementally and iteratively. Which is unfortunately not how most security tools work, and not how most security testing is done today.

There aren’t that many organizations using tools like Gauntlt or BDD-Security to write higher-level automated security tests and checks as part of Continuous Integration or Continuous Delivery. Most of us depend on dynamic and static scanners and fuzzers that can take hours to run and require manual review and attention, or expensive, time-consuming manual pen tests. This clearly can’t be done on every check-in.

But as more teams adopt Agile and now DevOps practices, the way that security testing is done is also changing, in order to keep up. Static analysis tools are getting speedier, and many tools can provide feedback directly to developers in their IDEs, or work against incremental change sets. Dynamic testing tools and services are becoming more scriptable and more scalable and simpler to use, with open APIs.

Interactive security testing tools like Contrast or Quotium Seeker can catch security errors at run-time as the system is being tested in Continuous Integration/Delivery. And companies like Signal Sciences are working on new ways to do agile security for online systems. But this is new ground: there’s still lots of digging and hoeing that needs to be done.

Do developers need access to production?

The Audit Toolkit assumes that developers will have read access to production logs, and that they may also need direct access to production in order to help with troubleshooting and support. Even if you restrict developers to read only access, this raises concerns around data privacy and confidentiality.

And what if read access is not enough? What if developers need to make a hot fix to code or configuration that can’t be done through the automated pipeline, or repair production data? Now you have problems with separation of duties and data integrity.

What should developers be able to do, what should they be able to see? And how can this be controlled and tracked? If you are allowing developers in production, you need to have solid answers for these questions.

Continuous Deployment or Continuous Delivery?

The Audit Toolkit makes the argument that with proper controls in place, developers should be able to push changes directly out to production when they are ready – provided that these changes are low-risk and only if the changes pass through all of the reviews and tests in the automated deployment pipeline.

But this is not something that you have to do or even can do – not because of compliance constraints necessarily, but because your business environment or your architecture won’t support making changes on the fly. Continuous Delivery does not have to mean Continuous Deployment. You can still follow disciplined Continuous Delivery through to pre-production, with all of the reviews and checks in place, and then bundle changes together and release them when it makes sense.

Selling to regulators and auditors

You will need to explain and sell this approach to regulators and auditors – to lawyers or wanna-be lawyers. Convincing them – and helping them – to look at code and logs instead of legal policies and checklists. Convincing them that it’s ok for developers to push low-risk, pre-approved changes to production, if you want to go this far.

Just as beauty is in the eye of the beholder, compliance is in the opinion of the auditor. They may not agree with or understand what you are doing. And even if one auditor does, the next one may not. Be prepared for a hard sell, and for set backs.

Disciplined, Agile and Lean

The DevOps Audit Defense Toolkit describes a disciplined, but Agile/Lean approach to managing software and system changes in a highly regulated environment.

This is definitely not easy. It’s not lightweight. It takes a lot of engineering discipline. And a lot of investment in automation and in management oversight to make it work.

But it’s still Agile. It supports the rapid pace and iterative, incremental way that development teams want to work today. And Lean. Because all of the work is clearly laid out and automated wherever possible. You can map the value chains and workflows, measure delays and optimize, review and improve.

Instead of detailed policies and procedures and checklists that nobody can be sure are actually being followed, you have automated delivery and deployment processes that you exercise all of the time, so you know they work. Policies and guidelines are used to drive decisions, which means that they can be simpler and clearer and more practical. Procedures and checklists are burned into automated steps and controls.

This could work. It should work. And it’s worth trying to make work. Instead of compliance theater and tedious and expensive overhead, it promises that changes to systems can be made simpler, more predictable, more efficient and safer. That’s something that’s worth doing.

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