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Cloud and DevOps

A working reference for engineering leaders planning a cloud migration, adopting cloud native architecture, or hardening DevOps practice across their stack.

Latest in Cloud and DevOps

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Hand-picked by our editors and refreshed quarterly.

About this category

This hub collects practical writing on cloud infrastructure, migration planning, and the DevOps practices that keep systems running once they’re in production. It’s written for engineering leaders who need to make a decision this quarter, not survey the entire field. If you’re comparing providers before a cloud migration, our executive comparison of AWS, Azure, and GCP lays out the tradeoffs without vendor spin, and the piece on building cloud applications from first principles walks through the sequencing most teams get wrong on their first attempt.

Other articles here deal with the operational layer: what breaks after migration, how to keep pipelines fast without losing control, and where cloud native architecture actually pays off versus where it adds overhead you didn’t need. The guide on monitoring and observability practices is a good starting point if incidents are taking too long to diagnose. Teams that have worked with us on a cloud migration usually start with an infrastructure audit, and we’ve supported engagements ranging from lift-and-shift moves to full re-architecture using cloud migration services. Where the gap is people rather than platform, clients bring in dedicated DevOps engineers to close out a backlog of pipeline and provisioning work.

For deeper dives, two subcategories sit underneath this hub. Cloud Platforms and Migration covers provider selection, workload assessment, and migration sequencing in more detail. DevOps Containers and CI/CD focuses on pipeline design, container orchestration, and release engineering. Some engagements start as a migration project and end up needing ongoing platform support, which is where cloud and DevOps consulting tends to get involved beyond the initial move.

If you’re deciding whether to migrate at all versus optimize what you already run, start with the AWS, Azure, and GCP comparison, then read the first-principles architecture piece before scoping any project. Together they help you weigh provider lock-in against rebuild effort. Once that decision is settled, the observability guide helps you judge whether your current operations setup can support the move, or whether that gap needs closing first.

Frequently asked questions

  • What does a cloud migration actually involve?

    It’s an assessment phase, a sequencing decision, and then execution. You audit current workloads and dependencies, decide what moves as-is versus what gets refactored, and pick a provider and target architecture. Most delays come from underestimating data migration and dependency mapping, not the compute move itself. Budget real time for the assessment before committing to a timeline.

  • Should we rearchitect for cloud native or lift and shift first?

    Lift and shift gets you off legacy infrastructure fast but often carries inefficiencies into the new environment. Cloud native architecture pays off when you need elastic scaling, want to reduce operational overhead over time, or are already planning a rewrite. If neither applies yet, migrate first and rearchitect the highest-value services once you have production data to justify it.

  • How do we choose between AWS, Azure, and GCP?

    Existing tooling and team familiarity usually matter more than raw feature comparisons between the three. Enterprise shops already on Microsoft tooling tend to fit Azure more easily. Teams doing heavy data or ML work often lean GCP. AWS has the broadest ecosystem and hiring pool. Run a small proof of concept on your actual workload before committing.

  • What's the difference between scalability and elasticity in cloud infrastructure?

    Scalability is the capacity to handle growth, usually by adding resources deliberately. Elasticity is automatic, near-real-time adjustment of resources based on current load. You need scalability planning regardless of provider; elasticity is a feature you configure once workloads are variable enough to justify the automation and its added complexity.

  • How much DevOps tooling do we actually need before shipping?

    Less than most vendors suggest. A working CI/CD pipeline, basic observability, and a repeatable deployment process cover most early-stage needs. Add container orchestration and advanced pipeline tooling once release frequency or team size makes manual processes a bottleneck, not before. Overbuilding tooling early usually costs more time than it saves.

  • Where do adjacent topics like security or app development fit?

    This hub stays focused on infrastructure, migration, and operations. For deployment pipelines and containers specifically, see DevOps Containers and CI/CD. For provider selection and migration planning in more depth, see Cloud Platforms and Migration. Security hardening of cloud environments is covered in Cybersecurity, and application-layer architecture decisions live in Software Development.