Automation can be an unwieldy topic for network operations and DevOps teams who have enough challenges working together cohesively. Networks have been traditionally viewed as the long pole in the tent for emerging DevOps practices.
But for DevOps practitioners and business leaders alike, there’s good news: NetOps are more prepared than ever to embrace automation and programmability—increasing the likelihood of on-time service delivery, with far less friction between IT teams.
According to Enterprise Management Associates (EMA), a strong majority (77%) of organizations deem network automation a high priority, and 58% have already implemented or are planning to implement, approved solutions. This is an important and promising shift.
Traditionally, network leaders have favored an operating model that emphasizes stability and resiliency over agility. Understandably so, as any network interruption can have a cascading impact on the business’ operations and profitability.
While ensuring five 9s of availability remains a top priority for NetOps, the growing need to support DevOps, containerized infrastructure for applications and cutting-edge digital services—among other initiatives—continues to highlight some of the glaring inefficiencies of traditional network management tools that are too error-prone and bound by scalability issues.
With the right automation framework, NetOps can play an equal part in enabling DevOps practices by becoming more adaptable to evolving business and application requirements in the cloud and locally.
Centralizing Management With Cloud-Based Service Delivery
For decades, improving agility has been a dyed-in-the-wool practice for network teams. Organizations worldwide have now realized enormous benefits by implementing new software-defined management tactics that allow the network to become more centralized, programmatic and dynamic in nature. By disaggregating software from hardware, networking teams now can manage many more services and devices with less effort and resources.
Among NetOps’ new arsenal of tools and best practices, centralized management has become one of the key ingredients driving toward greater efficiencies. Utilizing a cloud-based approach for provisioning, deploying and managing network services closely mirrors the way IT has spun up cloud storage and compute over the last decade. Now, DevOps teams no longer have to wait days or weeks for the NetOps team to provision the right networking resources so that they can begin designing, testing and deploying new applications.
Along with the added efficiencies, NetOps teams have greater and more uniform control over device configurations and policies, where security vulnerabilities lie in wait if these do not establish a zero-trust environment. Orchestrating these elements centrally, rather than device by device, places far less burden on individual network operators for protecting high-value corporate assets. Rock-solid network access control also reduces the risk of security or performance degradation that commonly arise from using an ad hoc patchwork of scripts, templates and CLI commands.
Advancing Network Automation Frameworks
Because creating a cloud-native network infrastructure does not all happen with the press of a button, network operations won’t become fully automated overnight. Other factors come into play that inhibit broader adoption of automation frameworks, including budget constraints, difficult technology implementations that lack integration with legacy systems and skill gaps for existing staff.
It’s essential that NetOps teams embrace a network automation framework that aligns to current and future operating models. Through proactive collaboration, NetOps folks can extend the value of automation platforms already used by their DevOps or application counterparts.
Fortunately for NetOps teams, myriad networking vendors today readily offer pre-built, certified solutions for DevOps platforms, making it easier to get started on a cloud-native journey by automating activities such as device onboarding and configuration changes. This way, network administrators can leverage existing vendor partnerships, in-house knowledge and technology that is already proven within the larger IT environment.
Additionally, network engineers shouldn’t need—and won’t have the extra time—to become top-notch developers to take advantage of programmability during their cloud-native journey. Developing basic programming skills is advantageous, but network management systems that offer Python scripting, a consistent set of APIs and webhooks can perform the “heavy lifting” when it comes to enabling extensibility with third-party IT platforms.
Today, this level of extensibility includes being able to integrate with third-party IT service management tools. A common use case that can realize significant time savings and greater network and application availability is to auto-trigger and assign an incident ticket when a performance SLA is breached. It’s very easy to collect and use machine learning-based tools to correlate all of the relevant diagnostics data in order for a network operator to immediately begin a root cause analysis and quickly resolve the issue.
On the Horizon: AI-Driven Operations
Another core aspect of DevOps is continuous improvement—both in terms of elevating service levels, as well as enhancing user experiences. But faster rates of change resulting from continuous improvement processes can negatively impact application performance, and the network is often the first to be blamed.
But there is a huge silver lining within this cloud created by faster rates of change, which also highlights another growth area for NetOps teams to learn and master. That is, the use of AIOps.
Today’s networks are bound by human scale. When things break, it takes a human to realize it broke, research the issue and then apply the fix. While traditional management and monitoring tools can alleviate some of the burden, alert fatigue often becomes a huge problem—in other words, too many false alarms, false positives or, worse yet, drawing attention away from more critical issues.
AIOps tools and technologies mitigate these issues and limitations by combining artificial intelligence, machine learning, and advanced network analytics to automate many aspects of traditional monitoring and troubleshooting. Once deployed, IT organizations have the ability to predict and preempt failures,\ or quickly recover from issues when they do occur. This includes being able to:
Leverage ML-trained data sets to continuously monitor network performance and detect anomalies.
Eliminate guesswork by prioritizing fixes or improvement efforts and validating that those efforts have the desired business impact.
Continuously optimize network performance based on benchmarks.
Put another way, AIOps systems are worth their weight in gold by helping networks move toward a self-healing, self-securing and self-optimizing model. Even in the interim, during the early phases of deployment, such AI-assisted operations can help IT identify and resolve network- or user-impacting issues faster and easier. The results are that dramatic.
Next Steps: Bring a DevOps Mentality to NetOps
Contrary to popular belief, the goals of NetOps are not diametrically opposed to DevOps. Both groups want to deliver more value and help the business innovate.
Equipping NetOps teams to build on existing DevOps-based automation frameworks, paired with AI-driven insights and modern management tools, will go a long way in ensuring frictionless delivery of new services.
Now is the time for network operations teams to get to know your DevOps team, learn how they operate and come together to create new methods for advancing the organization’s IT mission. The investment in time and effort should be a creative win-win for both groups and produce a big payoff in IT’s strategic position and importance to the organization.
