This article is based on a piece originally published on bdaily.co.uk.
Why Cloud and DevOps Go Hand in Hand
Cloud computing and DevOps are two sides of the same coin. DevOps aims to reduce friction between development and operations so that software changes reach production faster and more reliably. Cloud platforms amplify this by providing on-demand infrastructure provisioning, elastic scaling, and managed services that would otherwise require significant manual work.
Despite the natural synergy, many teams still struggle when combining the two. The most common obstacles are not purely technical—they stem from cultural misalignment, unclear ownership, and poorly defined processes. The five practices below address both dimensions.
1. Train Staff on Both DevOps and Cloud Computing
Most DevOps adoption failures have a people problem at their root, not a tools problem. When engineers and managers do not share a common understanding of DevOps principles—continuous integration, continuous delivery, shared responsibility for reliability—the process breaks down regardless of which cloud platform you use.
Invest in structured training that covers both DevOps methodologies and the specific cloud services your teams use. Training alone is rarely sufficient; pair it with mentoring, hands-on projects, and clear explanations of why specific practices matter. When engineers understand the business rationale behind a practice, adoption follows more naturally than when it is imposed as a mandate.
- Schedule recurring knowledge-sharing sessions (brown bags, internal wikis, post-mortems).
- Identify internal champions who can mentor peers and model good practices.
- Use cloud provider training programs (most major providers offer free foundational courses) to accelerate cloud-specific literacy.
2. Integrate Security from the Start (Shift Left)
Security is one of the most commonly neglected aspects of cloud DevOps, and it is also one of the most consequential. Cloud environments introduce security models that differ significantly from traditional on-premises setups. Identity and access management, secrets handling, network policies, and shared-responsibility boundaries all require deliberate design choices.
Rather than treating security as an audit gate at the end of a release cycle, embed it throughout the pipeline:
- Static analysis and dependency scanning in every pull request.
- Secrets management using dedicated vaults (such as HashiCorp Vault or your cloud provider’s native secrets service) rather than environment variables or config files checked into source control.
- Infrastructure-as-code security scanning to catch misconfigured storage buckets, overly permissive IAM roles, or open security groups before they reach production.
- Automated compliance checks integrated into your CI/CD pipeline.
If your organization’s cloud footprint is significant, consider designating a cloud security engineer or establishing a dedicated security-as-code practice to own these controls across all applications.
3. Choose Flexible, Cloud-Agnostic DevOps Tooling Where Practical
It is tempting to rely exclusively on the native DevOps tooling bundled with a single cloud provider. This approach can accelerate early adoption, but it can also create tight coupling that makes migrations, multi-cloud strategies, or negotiating contract renewals significantly harder.
Where feasible, prefer tools that are portable across environments. CI/CD platforms, container orchestration, monitoring solutions, and infrastructure-as-code frameworks that work across providers give you flexibility without sacrificing capability. Evaluate your toolchain against these questions:
- Can this tool deploy to a second cloud or on-premises environment if needed?
- Does the tool’s configuration live in source control as code, or is it locked inside a proprietary console?
- Is there a viable migration path if the vendor changes pricing or deprecates the service?
Cloud-agnosticism is a spectrum, not a binary choice. Even teams committed to a single provider benefit from keeping deployment manifests and pipeline definitions in a portable format.
4. Establish Governance and Resource Management Early
Cloud platforms make it easy to spin up new services—so easy that organizations frequently accumulate sprawling collections of resources with no clear owner, undocumented dependencies, and runaway costs. This problem tends to emerge during the first year of serious cloud DevOps adoption, when the pace of provisioning outpaces the maturity of governance processes.
Avoid this by establishing governance policies before the sprawl starts:
- Tagging conventions: enforce resource tags (owner, environment, cost center, application) through policy-as-code so every resource is attributable.
- Cost visibility: set up budget alerts and review cloud spend in your regular engineering review cadence, not just in finance.
- Service catalog: define approved infrastructure patterns teams can self-serve, reducing the likelihood of insecure or non-standard resources being created ad hoc.
- Deprecation workflows: build a process for decommissioning unused resources. What gets provisioned easily should be cleaned up easily.
5. Automate Performance Testing in the Pipeline
Performance issues are notorious for remaining hidden until an application reaches production under real load. By that point, users have already experienced the problem, and the reputational and operational cost is high. Automated performance testing, run as part of your CI/CD pipeline, moves performance regressions into the development phase where they are far cheaper to fix.
Practical approaches include:
- Load testing on every release candidate using tools that simulate realistic traffic patterns against a staging environment that mirrors production in configuration.
- Performance budgets: define acceptable latency and throughput thresholds and fail the pipeline automatically if they are breached.
- Continuous profiling in production to capture baselines and detect gradual degradation between releases.
- Chaos engineering experiments to validate that the system behaves gracefully under failure conditions—not just under normal load.
Putting It All Together
No single practice here is sufficient on its own. The organizations that get the most value from cloud DevOps treat it as an ongoing discipline rather than a one-time migration project. Staff capability, security posture, toolchain flexibility, governance, and quality assurance all need to mature in parallel.
Start by auditing where your team currently stands against each of these five areas, identify the highest-risk gaps, and address them incrementally. Continuous improvement—the same principle that underpins DevOps itself—applies equally to the way you practice DevOps in the cloud.