By Krishna Sai, Senior Vice President of Engineering, SolarWinds
In the ever-evolving landscape of public sector IT, complexity has emerged as a formidable challenge.
Well-intentioned technology investments like cloud services, meant to modernize government operations, are inadvertently creating labyrinthine IT ecosystems that are difficult to manage and secure. This complicated environment isn’t just an operational headache — it can become a roadblock against further innovation.
This trend was addressed in a National Audit Office study entitled “The challenges in implementing digital change.” The watchdog report stated: “Failure to understand the complexity and dependencies associated with replacing legacy IT has undermined government’s attempts to move away from legacy systems. Making the transition from legacy systems to modern replacements is complex and difficult, especially if the legacy system has many dependencies.”
The report urged enterprises to “avoid the operational complexity and decline in performance that can occur when too much change happens too quickly and incoherently.”
Government IT leaders face a paradox. How can they accelerate digital transformation without causing extra complexity for their tech teams? Perhaps counterintuitively, the answer might be more technology.
The potential of self-driving operations
Imagine an IT environment where artificial intelligence (AI) and machine learning (ML) step in to assist IT professionals in analyzing, predicting, and decision-making. This would free IT teams from the minutiae of day-to-day operations, enabling a shift from reactive to proactive IT management. This promising solution is called self-driving operations, and rapid advancements in AI are bringing it closer to reality. Ultimately, self-driving operations will help ensure that the IT environment — from legacy infrastructure to cloud services to databases — won’t crash.
Observability is the foundation of self-driving ops
For self-driving operations to become a reality, government organizations must first prioritize observability. Observability technology goes beyond traditional monitoring tools to provide a holistic view of an organization’s entire digital ecosystem across on-premises, hybrid, and multi-cloud environments.
According to Gartner, the average organization uses 15 monitoring tools. This contributes to alert fatigue and tool sprawl. With a unified observability tool, teams can consolidate the number of monitoring solutions in place and receive more intelligent, actionable alerts.
Through a single pane of glass, teams can receive health scores and insights across networks, applications, databases, and systems. Observability enables IT professionals to understand dependencies across complex IT systems so that they can identify and resolve problems faster.
Preparing for a future with autonomous operations
Gaining visibility of the IT environment enables organizations to move a step closer to fully autonomous IT operations.
Think of driving a car. In this case, an observability solution acts like lane assist. It uses intelligence to make certain decisions independently, but still requires human oversight and control. On the other hand, self-driving operations are more akin to Tesla’s autopilot, which uses artificial intelligence and machine learning to navigate the roads autonomously.
In an IT environment, self-driving operations would enable the automation of routine maintenance tasks and problem resolution, addressing issues before they impact operations. If a database shows signs of strain, the system can automatically allocate additional resources or reroute traffic to maintain performance.
Although self-driving operations are not a reality yet — and some overworked IT pros might label it a fantasy — glimpses of an autonomous future are starting to appear. In this future, tech teams will spend significantly less time identifying and remediating problems, and more time focused on strategy and innovation.
In the meantime, an AI-powered observability solution can correlate metrics and events, identify anomalies, and intelligently reduce alerts. This helps teams understand what issues are actually important so that they can be addressed promptly. IT professionals are empowered to concentrate on developing new products and executing critical business initiatives while minimizing the need to constantly hop between monitoring tools.
An exciting new frontier
As the next chapter in IT management, self-driving ops is set to revolutionize government IT. By embracing AI-powered observability now, organizations can get a handle on complex IT environments, enhance resiliency, and continue to drive digital transformation. These forward-thinking administrations will position themselves to reap the benefits of self-driving operations, ensuring they can deliver mission-critical government services for decades to come.
Krishna Sai leads the engineering, technology, and architecture teams at SolarWinds. He is a seasoned leader and entrepreneur with over two decades of experience scaling global engineering teams and building winning products across multiple industries. Sai has held leadership roles at Atlassian, Groupon, and Polycom, co-founded two technology companies, and holds several patents.
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