Staying competitive in the managed services business means keeping pace with how DevOps practices, tools, and philosophies are evolving. While containers and continuous delivery pipelines have become table stakes, the ecosystem continues to push further. Below are five DevOps trends that managed service providers (MSPs) should have on their radar.
1. Serverless Computing
Serverless computing is not a new concept — the underlying ideas have existed since the mid-2000s. What changed is accessibility. Modern serverless platforms such as AWS Lambda and Apache OpenWhisk dramatically lowered the barrier to entry, letting developers deploy event-driven functions without managing the underlying infrastructure. For MSPs, this means clients can reduce operational overhead and infrastructure costs. Expect serverless to become an increasingly common architecture choice for applications that demand elastic scaling and consumption-based pricing.
2. Self-Healing Infrastructure and the Push Toward NoOps
Automation has always been a foundational principle of DevOps, but maturing tooling is pushing it much further. The term NoOps describes an environment where infrastructure provisioning, scaling, and application management are so thoroughly automated that routine human intervention is no longer required. Self-healing systems can detect failures and remediate them automatically — restarting crashed containers, rerouting traffic away from unhealthy nodes, or rolling back a bad deployment without a pager alert firing at 2 a.m.
For MSPs, NoOps principles create an opportunity to deliver higher service quality at lower operational cost. The practical reality is that full NoOps remains aspirational for most organizations, but directional movement toward greater automation is well underway.
3. Shift-Left: Moving Quality, Security, and Compliance Earlier in the Pipeline
Shift-left refers to moving software delivery practices — particularly quality assurance, security reviews, and compliance checks — earlier in the development lifecycle rather than treating them as gates at the end. The metaphor comes from reading a pipeline diagram left to right: shifting activities to the left means performing them sooner.
The benefits are concrete: defects found during development cost far less to fix than those discovered after deployment. Shift-left practices include test-driven development (TDD), static code analysis integrated into CI pipelines, automated compliance policy checks, and pre-commit security scanning. For MSPs managing multiple client pipelines, embedding these checks into a shared CI/CD platform is an efficient way to deliver consistent quality across accounts.
4. DevSecOps: Integrating Security into the DevOps Workflow
In many organizations, security teams historically operated in isolation — reviewing code and infrastructure only after development work was complete. This created friction, slowed delivery, and left vulnerabilities undetected until late in the cycle. DevSecOps aims to break down that silo by treating security as a shared responsibility integrated throughout the software delivery process rather than a separate phase at the end.
Practical DevSecOps implementations include automated vulnerability scanning in CI pipelines, infrastructure-as-code security linting, secrets management tooling, and ongoing runtime threat detection. For MSPs, offering DevSecOps capabilities — or helping clients adopt them — is a meaningful differentiator as security requirements grow more stringent across regulated industries.
5. DataOps: Applying DevOps Principles to Data Pipelines
Just as security teams were initially left out of the DevOps movement, data engineering and analytics teams have often operated separately from software delivery workflows. DataOps extends DevOps principles — automation, collaboration, version control, and continuous delivery — to the data pipeline lifecycle. This means treating data ingestion, transformation, and delivery with the same rigor applied to application code: automated testing of data quality, version-controlled pipeline definitions, and monitoring of data freshness and accuracy.
Organizations that adopt DataOps can expect faster iteration on analytics products, fewer data quality incidents reaching production, and tighter alignment between data teams and the rest of engineering. MSPs with data engineering practices should evaluate how DataOps tooling and culture can be wrapped into their service offerings.
What This Means for MSPs
Each of these trends represents both a challenge and an opportunity for managed service providers. Clients will increasingly expect their MSP to have working knowledge of serverless architectures, automated remediation, shift-left pipelines, integrated security practices, and data operations. MSPs that build internal expertise in these areas — and translate that expertise into repeatable service offerings — will be better positioned to retain existing accounts and win new ones.
The common thread across all five trends is the same principle that has driven DevOps from the beginning: break down silos, automate repetitive work, and deliver faster with greater confidence. The scope of that mission is simply expanding.