allOps is now an AWS DevOps Services Competency Partner. This Competency covers planning, requirements and architecture alongside build, test, deploy and operate, while asking specifically how partners use generative AI to improve those processes.

To get this one, we had to go through technical validation against AWS best practices and then provide live customer engagements. We supplied named clients, real architectures, and documented outcomes.

AWS has validated our DevOps practice across the full software development lifecycle, including how we apply generative AI to it.

“The DevOps competency validates eight years of practice, not a capability assembled for an audit. We are more than proud of our team for achieving this.

Dzenan Dzevlan, CEO and Co-founder of allOps”

You can see the validated partner list on the AWS DevOps Competency page.

Why AWS raised the bar for the DevOps Competency

AI adoption in engineering teams is now effectively universal. DORA’s 2025 State of AI-assisted Software Development, built on responses from nearly 5,000 technology professionals, found 90% of them using AI at work, up 14 points in a single year.

But it also found that AI lifts throughput and instability together. It amplifies the system it lands in. Strong platforms get faster. Weak ones get faster at failing.

The security data follows. Veracode has run the same benchmark against 100+ models since 2023. Syntax correctness climbed past 95% while the security pass rate never moved, and its Spring 2026 update still finds a known flaw in 45% of generated code.

Java fails 72% of the time, and generated code defends against cross-site scripting in only 14% of relevant samples.

Cloud Security Alliance research shows what that does at scale. AI-assisted developers commit three to four times more often and generate security findings ten times faster.

Debt piles up faster than anyone can clear it, and the bill for clearing it late is well established. ITIC puts hourly downtime above $300,000 for 91% of mid-size and large enterprises, and between $1M and $5M for 41% of them.

That’s why the DevOps Competency exists in its current form.

Generation speed without delivery discipline is a liability. Customers need a way to mitigate the risks and actually build proper processes and guardrails.

AWS is committed to customer success and always looks for ways to provide their best practices from frontlines to their partners. Being part of an ecosystem and as a successful DevOps service provider for years, allOps has cleared all the bars.

The technical bar for the DevOps Competency

The technical bar lists six requirements, but it all comes to two key questions. Can the pipeline be trusted to run without someone watching it? This is what we showed to them:

Pipelines where security, compliance and quality checks are steps that code has to pass through, not reports generated alongside it.
IaC that ships with security controls and compliance validation embedded
Drift detection running against live accounts, so the template is the control instead of a suggestion the environment quietly drifts away from.
Event-driven architectures where anomaly detection triggers remediation on its own, observability that goes past dashboards into distributed tracing, log correlation and predictive analytics, and multi-environment deployments running canary tests, progressive delivery and automated rollback.

The AI requirements are where the benchmark numbers land directly on the architecture. A model that generates syntactically perfect doesn’t mean secure code and lean operations.

Our AI-assisted code review was validated against customizable rule engines carrying client-specific policy, as well as entire architectures.

Business value is at the core of the DevOps Competency

The business requirements are the ones you cannot argue in the abstract. Every claim has to trace back to a client.

We had quantifiable ROI through:

Faster time to market and lower operating cost
Developer productivity gains expressed in profit gains
Enhanced understanding between business and engineering
Automated governance and audit-ready reporting that takes compliance work off engineering calendars
Feedback loops short enough for customer input to reach developers while it still matters
Resilient systems that keep downtime off the P&L.

It is the same case we make to every client. Fragmented vendors leave gaps between architecture, cost and operations, and those gaps are where outages and overspend live.

We make sure we close those gaps, while providing extensive business value. You can read more about the results in our case study about TrueStay. We helped them migrate to AWS Bedrock and cut their AI spend by 90 percent, while contributing to a 4x user growth.

What this means for you if you are on AWS

The DevOps Competency does not change how we work. It changes how much you have to take on trust.

If your team needs to make both pre-development planning and delivery almost seamless, you can rely on a verified partner who has been doing this as a core service.

If you are shipping AI-assisted code through a delivery pipeline designed for the volume and risk profile of a few years ago, the gap between what your developers can generate and what your system can safely absorb is the thing worth fixing this quarter.

Schedule a session with an AWS Hero and improve your development processes, while driving down the overall costs of development.