Welcome to The Long View—where we peruse the news of the week and strip it to the essentials. Let’s work out what really matters.
This week: People won’t shut up about Rustlang, and Musk mandates Twitter teams return to the office. (more…)

Welcome to The Long View—where we peruse the news of the week and strip it to the essentials. Let’s work out what really matters.
This week: People won’t shut up about Rustlang, and Musk mandates Twitter teams return to the office. (more…)

The most successful software companies rely on repeatability, auditability and simplicity when building solutions. The emergence of infrastructure-as-code (IaC) has empowered developers to apply these practices to infrastructure allocation. What are the best practices for storing IaC? Should IaC code be stored with the application and feature code? Should it be stored separately in its own application-specific repo? Or should all IaC code for all applications in an organization reside in the same repo?
Let’s explore these questions, determine the tradeoffs between each solution and create guidelines that consider your organization’s needs.
The naive option for storing IaC is to keep all IaC code within the application repository that consumes this IaC code as part of its CI/CD pipeline. It’s easy to set up, doesn’t require complex permission allocation and will be fully visible to developers who work on this codebase, thus making it easy to retrieve context. This ease is why 20% of polled developers state they always store feature code and IaC in the same repo. However, there are a number of problems with holding IaC code with feature code.
Software development best practices include minimizing redundancy. Storing all IaC code within the dependent application’s codebase violates best practices by requiring the infrastructure-as-code to contain not just application-specific allocation information but also all foundational infrastructure. Organizations may classify common infrastructure shared across multiple applications and ecosystems as foundational infrastructure. Examples of such base, foundational infrastructure include Kubernetes clusters and log storage accounts.
In addition, storing IaC code with feature code introduces risk. Allowing developers admin-level access to all deployment scripts needed to bring code to production violates the principle of least privilege and makes lateral movement easier for attackers who manage to hijack a developer account.
Organizations benefit from a degree of secrecy regarding their deployment processes; the deployment pipeline and its configurations are bespoke and attackers who have a mapping of the services an organization uses can more easily architect supply chain attacks. Storing IaC with feature code makes it so that a code leak reveals all CI/CD configurations for not just the application, but the whole organization. The last thing an organization should do is perform an attacker’s reconnaissance for them, but that’s exactly what happens in the above situation.
Storing infrastructure-as-code alongside product code may be easier to set up initially, but violates the principle of least privilege and zero-trust principles. This method of storing code introduces unnecessary risk–there must be a better solution.
Since storing IaC with feature code in a common repo isn’t the optimal solution, what about storing all IaC in a dedicated IaC repo? This would allow DevOps and security teams to implement granular access controls and make code redundancy easily identifiable and preventable. However, this organizational structure introduces its own problems.
When all IaC is stored in a separate, shared repository, it becomes difficult to match feature changes to IaC changes. This scenario introduces friction to the development processes, puts a damper on developer velocity and increases tension between development teams, DevOps teams and security teams.
Storing all IaC in a common repository gives developers virtually no control over security decisions affecting their workflows. Between the lack of ownership and the additional steps needed to modify any code-specific deployment scripts, storing all IaC together prevents developers from quickly changing IaC and it unnecessarily hurts the organization.
IaC and other CI/CD scripts ultimately fall into two categories: base and feature.

Base deployment scripts may be described as code used broadly by an organization for, among other things, routine deployment actions or to interface with shared resources. Separating this code empowers organizations to allocate base IaC ownership and maintenance responsibilities to their DevOps team, which is well suited to maintain shared infrastructure.
Feature IaC scripts are the bits of code used to provision and manage resources associated with specific software. Developers frequently interact with the deployment scripts tied to their deliverables; changing release steps, modifying gateways, updating server configurations and many other needs necessitate different handling protocols for feature IaC versus base IaC.
Now that we understand the difference between the feature and base IaC, we can define proper management strategies for each.
Best practices call for categorizing feature IaC and base IaC differently and allocating the responsibilities to separate teams to maximize security while not adding unnecessary friction to the development and release process. Base IaC should be managed by DevOps teams, while feature-specific IaC should be handled by the code owners of the managed software.
For your organization, this starts with inventorying the organization’s systems and services. Gaining visibility into how these resources are shared helps inform business decisions regarding IaC code storage, helping minimize redundancies within deployment protocols. Visibility is integral to defining which IaC is foundational to software deployed by the organization versus IaC which is specific to certain applications, libraries and other software deliverables.
Best practices don’t mean much if organizations can’t enforce them. Some concluding tips:
These integrations allow complex insights to be derived that are simply not possible with other security tools. In addition, these integrations allow for constant monitoring for security updates, thus reducing the time between a zero-day being discovered and patching the vulnerability.

Developers spend much of their day digging into their systems’ guts, allocating storage to an application, connecting the security system to the user interface and tracking which version of the application is where in the development cycle, among other tasks.
That’s why a new category of software has emerged, infrastructure-as-code (IaC), that promises to automate system infrastructure provisioning and integration. It frees up time so developers can focus more on frontend solutions rather than backend configuration management. First, though, let’s find out what IaC is and how it helps your organization.
IaC reduces system infrastructure creation and configuration time through the use of sets of tools, protocols, languages and processes. In conventional data center system management, each configuration entry and change has historically required manual action. Now, technology teams can manage everything in an intelligent, automated manner.
With IaC, infrastructure configuration management data is stored within standardized files. The tools monitor and maintain the state of the infrastructure and ensure that the right resources are available whenever an application runs. This saves DevOps teams from excessive manual effort. In essence, large-scale configuration and management become dramatically simplified.
Currently, development is a cumbersome process because friction arises in many places. A great deal of progress has been made in speeding up the front end of application development—building the feature set. Still, the process slows down on the back end when the software components are tied to the computer infrastructure.
Historically, software was deployed as one large, monolithic block of code. Updates were tedious to make because all of the application’s code had to run, even if it wasn’t involved in the update or bug fix. The advent of containers and microservices enabled developers to design applications that are modular in nature and therefore easier to update, add to or debug.
However, the application still has to be tied into the existing compute infrastructure. Cloud solutions—like AWS, Google Cloud Platform or Microsoft Azure, for instance—provide companies with quick access to large volumes of computing processing power. But that application software must be told how to access the network, present security information, allocate storage and run code on central servers.
Because of this, developers spend a lot of time building and maintaining infrastructure-as-code. To do so, they use languages like Python and solutions such as Chef and GitHub. They want to use automation to simplify and accelerate the process, but here, again, they encounter some roadblocks.
As applications become larger and components become smaller, developers find themselves mixing and matching software from a wide variety of places. Tracking what’s where in the process is a frequent challenge. Current workflows are often non-intuitive and rely heavily on pull requests. Some solutions try to address the problem with multiple workspaces, but the end result is fragile and nondeterministic code.
Without mapping of projects to branches or tags, someone who comments on an approved pull request can push unapproved code to production. In today’s fast-paced DevOps work environment, an approval meant for a short-lived test run becomes the current release, creating a ripple effect of unintended consequences that create confusion and defective code, slowing development—often substantially.
Most tools do not offer access control models. Developers can track a single repository and a single Terraform project, for example, but as the number of repositories and projects grows, ensuring that proper access control features are in place becomes more daunting.
Legacy waterfall and static development projects allowed IT teams to set their system infrastructure up once and forget about it. But in a dynamic environment, microservices come and go in the blink of an eye. New environments proliferate and product teams must continually configure their own workspaces, which eats up time and resources.
Generic IaC platforms don’t provide mechanisms to detect if the infrastructure is drifting. Because so much configuration is done at runtime, differences arise between the desired and the actual state of the infrastructure.
Drift has many causes, such as developer or machine script contingencies or the lack of system resources. Too much drift results in unstable applications. Catching such problems early in the development cycle is more efficient than trying to fix a production system. But needed visibility is often lacking, and shortcomings become clear only when the system is fully in use.
Given today’s dynamic environment, developers need clear visibility. They must be able to closely examine what happens as their job runs. Though they offer many advantages, CI/CD platforms deliver little insight into resource usage from a real-time or historical perspective.
So, whenever performance problems arise, these platforms offer little insight into what the source of the problem is or how to fix it. Consequently, developers’ attention shifts from application enhancements to troubleshooting.
Legacy infrastructure failed to let teams reuse tried-and-true system images across multiple environments. To address this problem, teams often create a new image for each version of each application, slowing development time.
Setting up each IT environment manually requires time and manpower, which raises costs. Companies must have dedicated teams of engineers responsible for creating the infrastructure. But they also need supervisors and data center resources, which ultimately boost technology expenses. IaC tools centrally manage the process and create the right environment. That way, organizations pay only for system resources that they truly need.
Legacy IT practices are expensive, slow and inconsistent because they rely heavily on manual input. Infrastructure-as-code automates much of the infrastructure management process, which delivers a range of benefits.
With IaC, provisioning and management are lightyears faster and more efficient than with a manual system. The environment’s infrastructure is defined in code. That code-based infrastructure significantly accelerates each phase of the software development and delivery cycle. Consequently, DevOps teams deliver applications faster and at scale while improving software quality.
IaC deploys consistent configurations constantly and with no discrepancies. Because of this, it enables fast delivery of consistent infrastructure and environments. This reduces errors and overhead while boosting productivity.
Infrastructure automation helps to reduce the number of people with hands on the routing parts of the software development process. That’s because human resources aren’t needed in the management of networking and storage. Companies free up personnel to work on more strategic initiatives.
IaC helps to reduce risks and avoid human errors. It also protects against runtime issues and security weaknesses caused by missing dependencies or configuration drift.
Developers version IaC configuration files the same way they do any other source code file. This gives them complete traceability of any changes. In this way, IaC ensures efficient, exceptionally transparent workflows and speeds up the development process.
Maintaining legacy infrastructure was a time-consuming, complex process. IaC is emerging as a solution that alleviates much of the stress and pain that developer teams feel daily. Now, they can speed up the deployment and connection of system resources to applications. Developers can become more efficient and enable the company to respond to business demands in a faster, more reliable and more cost-effective manner. The development process no longer slows down the business.

Over the past few years, I have been watching the shift to infrastructure as code (IaC) frameworks closely. With the shift from monolithic to microservices, and with the shift from mostly virtual machines (VMs) to cloud-native architecture, applications are much more complicated, making it much more important to automate infrastructure to respond with speed.

In that sense, I refer to IaC as “The third cloud revolution.” Looking at the history of cloud transformation, the shift from physical servers to virtual machines (led by VMware about 20 years ago) would be the first cloud revolution. The move from virtualized data centers to the public cloud (led by AWS about 10 years ago) would be the second cloud revolution. With the shift to public clouds, people were suddenly able to click buttons to provision new resources, including “hardware.”
In the last few years however, we see fewer clicks and more code. Engineers write and maintain that IaC, and something executes that code. Engineers influence the infrastructure much more than they used to – that is the third cloud revolution. We mainly see four IaC frameworks that drove this revolution – Terraform and Pulumi (both multi-cloud), CloudFormation and ARM (vendor specific).
I recently talked with Joe Duffy, CEO, Pulumi, Mark Russinovich, CTO, Azure and Anton Babenko, AWS community hero and Hashicorp ambassador, the head of Terraform at Microsoft, the head of Terraform at IBM Cloud and one of the founders at Gruntwork. After our brainstorming session, it’s clear we all agree that IaC will have a huge effect on cloud operations. In this blog, I’ll share my point of view regarding multi-vendor IaC versus single-vendor IaC frameworks; discuss how they compare to the differences between iOS and Android and which direction I believe will win the day.
The big cloud vendors seem to go “all-in” and create full ecosystem, iOS-style, and they have everything working nicely with the relevant services and tools. AWS just released AWS Proton, which works with CloudFormation. They say that Terraform is on their roadmap, but time will tell. Microsoft seems to offer more solutions that are ARM-based, like Bicep. When I talk with executives at those companies, they strongly believe in the great value of this vendor lock-in/closed approach. They truly believe that this will help their customers in the best way possible. Perhaps they are right.
On the other hand, when I talk with the community, I hear different opinions. DevOps engineers at Azure customers do not debate whether to choose Terraform or ARM. DevOps engineers at AWS customers do not debate whether to choose Cloudformation or Terraform. While this was the case three years ago, it is not, anymore. Now, the real debate is whether to choose Terraform or Pulumi. Engineers prefer a language that is multi-vendor, open-source, no vendor lock-in and that is compatible with other open source solutions built on top, like Open Policy Agent and Terragrunt, to help Terraform users. This is the Android-style approach – open platform.
Moreover, I hear new phrases from the community that make me think the future is going in this direction. Erik Osterman at Cloud Posse started using the acronym TACOS – Terraform Automation and Collaboration Software (see the video here). It takes time, but, going forward, developers and the community will hold the key to the future of IaC, not executives and large vendors.
You can, of course, challenge this by replying that, “iOS is a great OS.” This is obviously true, but I think there is one big difference here as to why the Android approach is winning the IaC market. The answer lies with the end user; the Apple ecosystem is a solution for the end user and consumer, and IaC is about larger-scale infrastructure decisions. Like the shift from monolith to microservices, developers prefer small and isolated parts, not one big system. With Terraform and Pulumi, developers get more freedom. Maybe the company will move from AWS to GCP or Azure or vice versa. Maybe IT will need an Auth0 provider, as well, and will want to manage it the same way. Maybe the use of Open Policy Agent to govern deployments becomes the status quo. Developers need freedom, whereas consumers just need a great product.

But the question has still not been answered: Terraform or Pulumi? It is still too early to tell, and, frankly, there is more than enough room in the IaC space for both. Maybe more open-source and multi-vendor frameworks will emerge and one that’s yet unknown will rule the day. Terraform provides a great ecosystem of providers, support and maintainers. Pulumi has started to provide all of those, together with its imperative approach, which seems to be a bit more appealing to developers.