Certified: The GIAC GPCS Audio Course

In this episode, we compare the major public cloud providers by recurring security patterns rather than brand loyalty, tribal preference, or marketing claims that sound comforting but do not hold up in real incidents. Amazon Web Services (A W S), Microsoft Azure (A Z U R E), and Google Cloud Platform (G C P) each have strong security capabilities, and each also has defaults and human workflows that can produce the same kinds of exposures you see everywhere else. The trick is learning how to recognize the underlying control goals so you can evaluate a new environment quickly, even if the labels and consoles look unfamiliar. When you use patterns instead of provider narratives, you become harder to mislead and easier to keep calm, because your analysis does not depend on remembering a vendor’s terminology. That is the mindset that lets you compare strengths honestly while still spotting the weak defaults that show up in fresh deployments.

Before we continue, a quick note: this audio course is a companion to our course companion books. The first book is about the exam and provides detailed information on how to pass it best. The second book is a Kindle-only eBook that contains 1,000 flashcards that can be used on your mobile device or Kindle. Check them both out at Cyber Author dot me, in the Bare Metal Study Guides Series.

A phrase you will hear constantly is secure by default, and it is worth defining carefully because it misleads more often than it helps. Secure by default can mean that a platform ships with reasonable baseline protections, such as encryption available, strong separation at the infrastructure layer, and sensible access boundaries for management operations. The misleading part is that people interpret it as secure in your deployment by default, which is a different claim entirely. Most real-world risk comes from the choices customers make when they connect services, set permissions, expose endpoints, and move data, and those are almost never fully locked down out of the box. Even when a default is conservative, teams frequently change it quickly to get a workload working, and the change becomes the real default in practice. A provider can be secure in how it builds the platform while still leaving customers plenty of room to create dangerous exposure with ordinary configuration work.

A useful way to compare providers is to start with shared building blocks that exist across all three and then examine how each provider expresses them. Identity and Access Management (I A M) is always present in some form, because every action in cloud is ultimately an identity exercising permissions. Networking controls exist everywhere, whether you call them security groups, network security groups, firewall rules, or something else, because reachability still matters even in identity-first designs. Logging and monitoring capabilities exist across all three, but the consistency of defaults, the ease of centralization, and the friction of enabling high-value signals varies a great deal. Encryption and key management exist everywhere too, but the division between provider-managed keys and customer-controlled keys changes the operational burden and the failure modes. Storage services are universally powerful and universally dangerous when access boundaries are unclear, because storage is where sensitive data tends to accumulate quietly over time.

Once you accept that the building blocks are shared, the next step is to recognize that different names often hide very similar control concepts. A W S, A Z U R E, and G C P each present their services as unique, but many controls are variations on the same underlying idea: identity policies define who can do what, network rules define who can reach what, and logging defines what you can prove after something goes wrong. This matters because vendor-specific thinking is a common failure pattern, where a practitioner assumes a control does not exist because it is not named the way they expect. Another common pattern is assuming a control behaves differently because it has a different user interface or different terminology, when the actual enforcement model is similar. You do not want to memorize three clouds as three separate worlds; you want to internalize the control goals and then learn the translation layer. That translation layer is what prevents blind spots when you move between environments.

A translation example makes this more concrete, because it shows how to carry control intent across providers without losing meaning. Consider a simple goal: restrict administrative change so only a small set of identities can modify network exposure for production workloads. In A W S, that goal might be expressed through I A M policies and roles with tightly scoped permissions, along with governance around who can change security groups and routing. In A Z U R E, the same goal can be expressed through role-based access control boundaries that limit who can modify network security groups and public endpoints, combined with management group or subscription-level governance. In G C P, the same intent can be expressed by controlling who can modify firewall rules, load balancer exposure, and service networking, typically through I A M roles and organizational policies. The control is not the label; the control is the ability to constrain who can change exposure, and that concept travels well once you stop anchoring on a single provider’s naming.

Weak defaults are where real environments get hurt, and they commonly appear in new deployments because speed and convenience tend to win early. One weak default pattern is permissive access to make a service work quickly, which later becomes permanent because nobody wants to be the person who breaks production. Another is logging left incomplete or fragmented, where services run without central visibility because enabling logs costs time, money, or attention, and those tradeoffs are postponed. Storage exposure is also a classic, where access boundaries are assumed rather than verified, or where data is shared broadly to support collaboration and later forgotten. Identity defaults can be weak when initial administrative identities are too powerful, when service accounts are created without tight scope, or when key rotation and credential hygiene is postponed. Networking defaults can be weak when public access is easy to enable and the boundary between private and public services is not enforced as a standard. These patterns show up across A W S, A Z U R E, and G C P because they are human patterns more than vendor patterns.

A quick win that works across providers is to standardize baseline expectations before you evaluate any environment, so your assessment is not improvised. Baseline expectations are not a specific product configuration; they are a set of control outcomes you expect to see, such as centralized logging for critical actions, clear identity boundaries for administrative change, and explicit decisions about what is internet-facing. When teams standardize outcomes, they reduce variance, and variance is what creates hidden exposures. This also creates a shared language across engineering and security, because you are not arguing about whose cloud is better; you are checking whether the baseline outcomes are met. Standardization helps you scale governance across multi-cloud environments, where each provider’s UI could otherwise pull teams into inconsistent habits. When your baseline is outcome-driven, you can spot drift faster, and you can defend decisions more clearly because you are comparing reality against a declared standard rather than against memory.

From there, a practical mental checklist for assessing any new cloud service keeps you from being distracted by shiny managed features. The first question is what identities can administer it and what permissions are required, because the ability to change a service is often more dangerous than the ability to use it. The second question is what data the service stores or processes and how access to that data is constrained, because data risk is often the business risk. The third question is how the service is exposed, including whether it is reachable from the internet, reachable from partner networks, or only reachable inside a private boundary. The fourth question is what logging exists for access and changes, and whether those logs flow to a central place you actually monitor. A final question is what default settings you are inheriting, and whether any convenience features quietly weaken the control posture. This checklist is simple, but it catches a large percentage of real-world failures across providers.

Provider-managed security versus customer-managed configuration choices is one of the most important distinctions in cloud, and it is where many misunderstandings begin. Providers manage the security of the underlying infrastructure, including physical facilities, hardware, and core platform services, and that layer is typically very strong. Customers manage how they configure services, how they grant permissions, how they expose endpoints, and how they protect data, and that layer is where most incidents occur. The boundary between those layers differs by service type, and managed services often shift more responsibility to the provider, but they never remove it entirely. A strong provider reduces certain classes of risk, such as hardware compromise or low-level platform tampering, but it does not prevent misconfiguration and over-permissioning. You want to use managed features to reduce operational burden while still owning the configuration decisions that determine exposure. When you keep the boundary clear, you stop blaming the cloud for customer errors and stop trusting the cloud to fix what only you can configure.

Managed services can reduce risk significantly when configured correctly, and that is a real strength across A W S, A Z U R E, and G C P. When a provider operates a service, patching and infrastructure hardening are often handled more consistently than in customer-managed environments, and that can eliminate an entire category of operational failure. Managed services can also offer built-in encryption options, integrated identity controls, and standardized logging hooks that are harder to implement consistently when you build everything yourself. The catch is that the risk shifts from server maintenance to configuration correctness, meaning the failure modes become less visible and more policy-driven. Misconfigured access to a managed database is still a data breach, even if the database software is perfectly patched. Overly broad permissions to a managed storage service are still exposure, even if the platform is engineered well. Managed services reduce some risks, but they can amplify the impact of misconfiguration because they make powerful capabilities easy to deploy.

This is where a memory anchor helps you stay objective when comparing providers, especially when teams argue from preference rather than evidence. The anchor for this episode is same control goals, different knobs and labels, and the point is to keep your focus on outcomes. If you can describe what the control is trying to achieve, you can find it in any provider, even if the UI and terminology are unfamiliar. If you cannot describe the control goal, you are more likely to be manipulated by branding or by superficial differences in service names. The anchor also reminds you that strong security programs are portable, because they are built on principles, not on product-specific rituals. When you walk into a multi-cloud environment, the anchor keeps you from treating each cloud like a separate discipline. It becomes one discipline expressed through different interfaces and naming conventions.

A mini-review of shared control categories is useful here because it reinforces what you must always evaluate, regardless of provider. Identity remains the core because identity is how actions happen and how attackers move when they gain credentials. Networking still matters because reachability defines which attack paths are even possible and which segments can contain damage. Logging and monitoring are essential because you cannot manage what you cannot observe, and investigations become guesswork without reliable records. Encryption and key management are critical because they shape how data is protected at rest and in transit, and they determine how much damage a storage exposure can cause. Storage access controls deserve special attention because storage tends to accumulate sensitive content and because access mistakes are common. These categories are not optional checkboxes; they are the recurring pillars of cloud security, and every provider provides mechanisms in each area even if the default posture differs.

To compare controls without vendor-specific bias, commit to language that stays anchored in control intent rather than brand identity. Instead of saying one provider is more secure, describe which control outcomes are easier to achieve and which weak defaults are more likely to appear in a typical deployment. Instead of praising a service’s features, describe the risks the feature mitigates and the new risks it introduces if configured poorly. Instead of using a provider’s marketing phrase, translate it into an operational claim you can verify, such as whether logging is enabled by default, whether access boundaries are explicit, and whether identity permissions are easy to scope tightly. Bias often sneaks in when people confuse familiarity with safety, because the cloud they know feels less risky than the cloud they do not. Professional comparison language breaks that illusion by applying the same evaluation lens everywhere. When your language is outcome-based, you can collaborate across teams and clouds without triggering defensive reactions.

That commitment also helps in conversations with stakeholders who want a simple winner and loser narrative. A practical educator’s stance is that each provider has security strengths, but security posture in practice is dominated by configuration discipline, identity governance, visibility, and operational habits. Some providers make certain secure choices easier by reducing friction, while others make some risky choices easier by reducing friction, and friction is often the deciding factor in real outcomes. If you keep your evaluation grounded in how teams actually behave under deadlines, you will produce more accurate risk assessments. You will also avoid the trap of assuming that adopting a new provider fixes old problems, because the same human patterns will recreate the same exposures in a new interface. The goal is not to pick a favorite; the goal is to recognize patterns that create risk and to build standards that prevent them across any platform. That is how you lead multi-cloud security without getting stuck in brand narratives.

To conclude, choose one control category and describe it across A W S, A Z U R E, and G C P in a way that highlights shared goals and typical weak defaults, and logging is an excellent example because it affects everything else. In A W S, you look at whether management actions and service access events are captured, whether they are centralized, and whether alerts focus on identity misuse and exposure changes. In A Z U R E, you examine whether administrative operations and resource access are consistently logged across subscriptions, whether central collection is in place, and whether detection focuses on unusual identity behavior and configuration drift. In G C P, you assess whether audit logs cover key actions, whether they are retained and exported to a central monitoring point, and whether signals are tuned to highlight risky changes and suspicious access patterns. Across all three, the risk is the same when logging is fragmented or incomplete: you cannot see misuse early, and you cannot reconstruct what happened later. Pick one real environment you know, narrate how logging is implemented, and you will immediately see where strength exists and where weak defaults have quietly become normal.