Cisco DEVOPS 300-910 Practice Test Questions, Cisco DEVOPS 300-910 Exam Practice Test Questions

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Cisco 300-910 DEVOPS: Legacy DevOps Skills and the Move to CCNP Automation

Cisco 300-910 DEVOPS, Implementing DevOps Solutions and Practices Using Cisco Platforms, is a retired exam. Cisco lists February 2, 2026 as the last day to test and does not identify a direct replacement. The exam belonged to the former DevNet Professional program, which was substantially redesigned when Cisco launched its new Automation certification track on February 3, 2026.

The historical exam validated DevOps practices around deployment automation, configuration, management, scalability, cloud microservices, and infrastructure processes. Those skills remain current even though the credential is not. Candidates planning a certification today should look to the new 350-901 AUTOCOR core and the CCNP Automation structure instead of treating 300-910 as an active concentration.

This transition is more than a rename. Cisco described the new CCNP Automation program as a reimagining of DevNet Professional, with stronger alignment to network automation, infrastructure as code, operations, security, and AI-enabled automation. The old DevNet Professional page is therefore useful as historical context, not as a current certification roadmap.

DEVOPS remains a useful legacy blueprint because it organized several durable engineering practices into one coherent workflow: source control, CI/CD, automated testing, infrastructure automation, containers, observability, security, and application deployment. These are still the practices that turn ad-hoc scripts into reliable operational systems.

CI/CD pipelines make change repeatable, reviewable, and measurable

A continuous integration and delivery pipeline connects source control to automated build, test, validation, and deployment stages. The value is not simply speed. A pipeline creates a consistent path that every change must follow, making it easier to detect errors early and prove which revision reached an environment.

The legacy DEVOPS blueprint expected candidates to recognize tools and pipeline components, but preparation is stronger when candidates build a small workflow. CI/CD pipelines organize stages, triggers, artifacts, and gates into a repeatable delivery path. A practical lab can lint code, run tests, build an image, scan it, and deploy it to a controlled environment.

Good pipelines also separate evidence from approval. Automated checks should produce clear results, while high-risk production actions can still require human authorization. The goal is not to remove judgment but to ensure judgment is applied to a well-tested change.

Release strategy is another part of delivery engineering. Blue/green, canary, rolling, and feature-flag approaches reduce risk in different ways by limiting how much traffic or how many users see a new version at once. The best method depends on application state, infrastructure cost, rollback requirements, and the ability to compare health between old and new versions. A pipeline should make the chosen strategy explicit rather than treating deployment as a single opaque command.

Infrastructure as code turns configuration into a versioned engineering artifact

Manual infrastructure changes are hard to reproduce and easy to forget. Infrastructure as code represents intended state in files that can be versioned, reviewed, tested, and applied repeatedly. That makes environments easier to rebuild and differences easier to explain.

Candidates should understand the distinction between declaring desired state and writing imperative scripts. Both approaches can be useful, but declarative tools are especially strong when the objective is convergence: define what should exist and let the tool determine the changes required. The relationship between automation, orchestration, and infrastructure as code is important because each operates at a different level of the delivery workflow.

State management, secrets, dependencies, and rollback planning deserve as much attention as syntax. An infrastructure repository is production code because it can create networks, permissions, compute resources, and policies at scale.

Containers and Kubernetes create operational consistency but introduce new failure domains

Containers package applications with their runtime dependencies, reducing environmental differences between development and deployment. Kubernetes adds scheduling, service discovery, scaling, health management, and declarative orchestration. Those capabilities support modern microservices, but they also create layers that operators must understand.

A failed application can originate in the image, container configuration, pod scheduling, service routing, storage, secrets, network policy, or the application itself. Kubernetes and Docker solve different parts of that lifecycle: container packaging creates a portable runtime unit, while orchestration coordinates how those units are deployed and operated.

Legacy DEVOPS labs that use Kubernetes remain relevant. Candidates should be able to deploy an application, inspect workload status, read logs, understand service exposure, and identify why a desired replica is not becoming healthy.

Testing should validate behavior before automation is allowed to scale a mistake

DevOps pipelines need more than unit tests. Infrastructure and network automation benefit from syntax checks, policy validation, schema validation, integration tests, and post-deployment verification. The exact tests vary by system, but the principle is stable: prove as much as possible before making a high-impact change.

Network automation may validate a generated configuration against a model, test reachability in a lab, or compare intended state with known policy. Application pipelines may run unit, API, security, and integration tests. A failed check should stop the pipeline before deployment rather than merely produce a warning that operators learn to ignore.

Test data also matters. A workflow that passes only on a perfect sample can still fail on real inventory containing missing fields, duplicate objects, or unusual naming. Robust automation expects imperfect input and handles it explicitly.

Observability closes the loop between deployment and real service health

Deployment is not the end of a DevOps workflow. Teams need evidence about application health, infrastructure state, latency, errors, saturation, and user impact after a change. Logs, metrics, traces, and events provide different views of the same system, and effective troubleshooting correlates them.

A pipeline can use observability as a release signal. If error rates or latency rise after deployment, an automated or operator-driven rollback may be justified. This is more reliable than assuming success because a deployment command returned without an error.

Operational dashboards should therefore answer questions, not merely display data. Which revision is running? Which service is failing? Did the failure begin after a deployment? Is the problem isolated to one dependency or widespread? These questions turn telemetry into action.

DevSecOps makes security part of the delivery path rather than a late review

Security can be integrated into source control, dependency management, image scanning, infrastructure policy, secret handling, and deployment approval. This is the core DevSecOps idea: security controls become routine engineering checks rather than a separate gate that appears only near release.

Container environments illustrate the need clearly. Images can contain vulnerable packages, manifests can request excessive privileges, and secrets can be exposed through configuration. Early security integration in Kubernetes shifts checks for vulnerable images, unsafe manifests, excessive privilege, and exposed secrets toward the development and deployment stages where they can be corrected sooner.

Security automation should still be explainable. A blocked pipeline must tell the engineer which policy failed and what evidence triggered the decision. Otherwise teams are tempted to bypass controls instead of fixing the underlying issue.

Network automation and software delivery increasingly share the same engineering methods

DEVOPS was particularly relevant to Cisco because programmable infrastructure blurs the line between application delivery and network operations. Network configuration can be generated, tested, reviewed, and deployed through pipelines just like software. APIs expose controllers and devices as programmable systems, while source control becomes the record of intended change.

GitHub in network automation connects repositories, pull requests, automated workflows, and team review practices to infrastructure change control. Current CCNP Automation concentrations such as 300-435 ENAUTO continue that direction, but within the redesigned certification structure.

The strongest practitioners understand both domains. They know enough networking to recognize the operational effect of a change and enough software engineering to make that change repeatable and testable.

The current Automation track is the right certification destination for former DEVOPS candidates

On February 3, 2026 Cisco replaced the DevNet branding with an Automation track and reworked the professional-level path. The current core is 350-901 AUTOCOR, which focuses on designing, deploying, and managing network automation systems, including infrastructure as code, operations, and AI in automation.

That means 300-910 should no longer appear in an active study schedule. An older course can still teach excellent CI/CD, container, testing, and observability skills, but exam-specific preparation must follow the live Automation objectives. The Cisco portfolio now separates current automation credentials from the retired DevNet exam structure.

A practical migration plan is to keep the DEVOPS labs that develop engineering habits, then map them to current AUTOCOR topics. Reuse the knowledge, not the outdated exam status.

A durable DEVOPS lab should prove the entire delivery cycle

Build a small repository containing an application or automation tool, tests, an infrastructure definition, and a pipeline. Make the pipeline validate code, run tests, build an artifact or container, perform a security check, deploy to a controlled target, and collect health evidence. Then deliberately introduce a failure at each stage and observe how the workflow responds.

That exercise is valuable even though the exam is retired because it teaches the connections that separate mature DevOps from a collection of tools. Source control feeds automation; testing protects deployment; infrastructure as code makes the environment reproducible; observability verifies the result; security constrains risk.

Cisco’s retirement table should remain the final authority for status: 300-910 DEVOPS ended on February 2, 2026 and has no direct replacement exam. The skills remain relevant, while the current credential path has moved to CCNP Automation.

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