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Maximizing Impact Amid Constraints: The Role of Automation and Orchestration in Federal IT Modernization

Travis Galloway
SolarWinds

Technology leaders across the federal landscape are facing, and will continue to face, an uphill battle when it comes to fortifying their digital environments against hostile and persistent threat actors.

On one hand, they are being asked to push digital transformation, namely the implementation of new AI technology to streamline critical workflows and fill workforce gaps, while navigating FISMA, NIST frameworks, and agency-specific requirements.

On the other hand, they are facing the fiscal uncertainty of continuing resolutions (CR) and government shutdowns looming near and far.

In the face of these challenges, CIOs, CTOs, and CISOs must figure out how to modernize legacy systems and infrastructure while doing more with less and still defending against external and internal threats. To accomplish these requirements simultaneously, technology leaders must identify current IT gaps and surfaces, determine where automation and orchestration could reduce operational noise, and strategically plan for the next phase of their digital transformation.

Lagging Behind in Digital Transformation

According to the Next-Gen Government IT: AI and Observability Insights report, only six percent of public sector organizations have fully completed their digital transformation journeys. While this pace of digital transformation can be linked to the aforementioned budget constraints, this is not the only cause. Complex system integration and ongoing concerns around data privacy and security also continue to slow progress.

As federal organizations continue to operate complex multi-vendor systems across complex hybrid environments, operational challenges persist, and they may remain vulnerable to potential disruptions. For example, observability and monitoring are important functions of any digital environment. However, per the report, 63% of federal IT leaders face challenges monitoring their IT tools across multiple environments. In addition, 73% encounter challenges in managing these environments.

Both of these findings are indicators that legacy, multi-vendor tooling coupled with distributed architecture across hybrid environments are likely perpetuating both the challenges to manage and monitor their environments yet alone leverage the capabilities of observability. Legacy tooling creates integration gaps that force IT leaders to deploy multiple monitoring tools across their stack, with each tool overing different pieces of technology. This not only exacerbates monitoring issues, but it also resource-intensive in terms of manpower and tool costs. Digital transformation is expanding the attack surface federal organizations must defend. Attacks from nation-state actors are becoming more prevalent. In fact, according to data from the report, more than half (59%) of federal IT leaders fear the "general hacking community." When monitoring and observability are not automated and are disparate in nature, it becomes much more difficult to spot potential vulnerabilities in a tech stack and proactively secure every part of an IT environment.

These potential gaps present the risks federal organizations must mitigate in their IT modernization journey. In addition, these weaknesses show why digital transformation must continue, but occur strategically, even in a resource-constrained environment.

Automation and Orchestration in a Federal IT Environment

Automation and orchestration are not only essential capabilities in a zero-trust architecture, but they are essential tools for federal IT teams to defend across expanding attack surfaces in today's threat environment. The exponential growth in monitoring data and telemetry in modern IT environments requires integrated AI technologies that provide context-aware intelligence to optimize resources and enable IT teams to focus on mission critical requirements.

To maximize the impact of limited IT modernization budgets, agencies must have a clear picture of their current technology stack. Existing tools may already leverage AI or automation to streamline workflows and reduce manual intervention for routine operations. Understanding these capabilities helps teams avoid unnecessary spending on redundant point solutions or prematurely replacing functional technology simply because it's the newest offering on the market.

Next, tapping into proactive observability and security technologies that build on that automation and easily integrate with dated and current technology will allow IT teams to transition from a less reactive posture to a more proactive response. This doesn't mean introducing AI or automation on a large scale. When it comes to automation, AI tooling could begin on a smaller scale with alert analysis or anomaly detection. With the right orchestration tooling, teams can tap into a single-pane-of-glass solution, providing centralized monitoring capabilities and reducing monitoring complexities of large, diverse digital ecosystems.

Combined, these solutions can limit the time wasted for federal employees. It would also give employees time to focus on strategic initiatives that could improve IT workflow or further secure systems against potential threats.

As this methodical and strategic approach to IT modernization progresses, teams should begin seeing measurable benefits from incremental observability improvements. Metrics such as mean time to detection (MTTD) and mean time to resolution (MTTR) provide concrete indicators of IT environment efficiency gains. When these numbers improve, they provide the evidence federal IT leaders need to justify scaling their modernization — turning an initial pilot success into budget advocacy for broader implementation.

Moving Modernization Forward Amidst Present Constraints

The US federal government operates one of the world's most complex and dynamic digital infrastructure, and its dependence on a modern, resilient IT infrastructure will only intensify as technology evolves and mission requirements expand. Federal IT leaders cannot wait for budget certainty before advancing their modernization efforts. Instead, agencies must embrace a strategic, incremental approach that maximizes existing investments. By taking a calculated approach to implementing automation and orchestration capabilities, teams can optimize talent, streamline workflows, and extend the value of current technology — ensuring every budget dollar delivers maximum impact. A disciplined approach enables federal agencies to maintain mission readiness and operational resilience, regardless of the fiscal constraints ahead.

Travis Galloway is Director of Government Affairs at SolarWinds

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Maximizing Impact Amid Constraints: The Role of Automation and Orchestration in Federal IT Modernization

Travis Galloway
SolarWinds

Technology leaders across the federal landscape are facing, and will continue to face, an uphill battle when it comes to fortifying their digital environments against hostile and persistent threat actors.

On one hand, they are being asked to push digital transformation, namely the implementation of new AI technology to streamline critical workflows and fill workforce gaps, while navigating FISMA, NIST frameworks, and agency-specific requirements.

On the other hand, they are facing the fiscal uncertainty of continuing resolutions (CR) and government shutdowns looming near and far.

In the face of these challenges, CIOs, CTOs, and CISOs must figure out how to modernize legacy systems and infrastructure while doing more with less and still defending against external and internal threats. To accomplish these requirements simultaneously, technology leaders must identify current IT gaps and surfaces, determine where automation and orchestration could reduce operational noise, and strategically plan for the next phase of their digital transformation.

Lagging Behind in Digital Transformation

According to the Next-Gen Government IT: AI and Observability Insights report, only six percent of public sector organizations have fully completed their digital transformation journeys. While this pace of digital transformation can be linked to the aforementioned budget constraints, this is not the only cause. Complex system integration and ongoing concerns around data privacy and security also continue to slow progress.

As federal organizations continue to operate complex multi-vendor systems across complex hybrid environments, operational challenges persist, and they may remain vulnerable to potential disruptions. For example, observability and monitoring are important functions of any digital environment. However, per the report, 63% of federal IT leaders face challenges monitoring their IT tools across multiple environments. In addition, 73% encounter challenges in managing these environments.

Both of these findings are indicators that legacy, multi-vendor tooling coupled with distributed architecture across hybrid environments are likely perpetuating both the challenges to manage and monitor their environments yet alone leverage the capabilities of observability. Legacy tooling creates integration gaps that force IT leaders to deploy multiple monitoring tools across their stack, with each tool overing different pieces of technology. This not only exacerbates monitoring issues, but it also resource-intensive in terms of manpower and tool costs. Digital transformation is expanding the attack surface federal organizations must defend. Attacks from nation-state actors are becoming more prevalent. In fact, according to data from the report, more than half (59%) of federal IT leaders fear the "general hacking community." When monitoring and observability are not automated and are disparate in nature, it becomes much more difficult to spot potential vulnerabilities in a tech stack and proactively secure every part of an IT environment.

These potential gaps present the risks federal organizations must mitigate in their IT modernization journey. In addition, these weaknesses show why digital transformation must continue, but occur strategically, even in a resource-constrained environment.

Automation and Orchestration in a Federal IT Environment

Automation and orchestration are not only essential capabilities in a zero-trust architecture, but they are essential tools for federal IT teams to defend across expanding attack surfaces in today's threat environment. The exponential growth in monitoring data and telemetry in modern IT environments requires integrated AI technologies that provide context-aware intelligence to optimize resources and enable IT teams to focus on mission critical requirements.

To maximize the impact of limited IT modernization budgets, agencies must have a clear picture of their current technology stack. Existing tools may already leverage AI or automation to streamline workflows and reduce manual intervention for routine operations. Understanding these capabilities helps teams avoid unnecessary spending on redundant point solutions or prematurely replacing functional technology simply because it's the newest offering on the market.

Next, tapping into proactive observability and security technologies that build on that automation and easily integrate with dated and current technology will allow IT teams to transition from a less reactive posture to a more proactive response. This doesn't mean introducing AI or automation on a large scale. When it comes to automation, AI tooling could begin on a smaller scale with alert analysis or anomaly detection. With the right orchestration tooling, teams can tap into a single-pane-of-glass solution, providing centralized monitoring capabilities and reducing monitoring complexities of large, diverse digital ecosystems.

Combined, these solutions can limit the time wasted for federal employees. It would also give employees time to focus on strategic initiatives that could improve IT workflow or further secure systems against potential threats.

As this methodical and strategic approach to IT modernization progresses, teams should begin seeing measurable benefits from incremental observability improvements. Metrics such as mean time to detection (MTTD) and mean time to resolution (MTTR) provide concrete indicators of IT environment efficiency gains. When these numbers improve, they provide the evidence federal IT leaders need to justify scaling their modernization — turning an initial pilot success into budget advocacy for broader implementation.

Moving Modernization Forward Amidst Present Constraints

The US federal government operates one of the world's most complex and dynamic digital infrastructure, and its dependence on a modern, resilient IT infrastructure will only intensify as technology evolves and mission requirements expand. Federal IT leaders cannot wait for budget certainty before advancing their modernization efforts. Instead, agencies must embrace a strategic, incremental approach that maximizes existing investments. By taking a calculated approach to implementing automation and orchestration capabilities, teams can optimize talent, streamline workflows, and extend the value of current technology — ensuring every budget dollar delivers maximum impact. A disciplined approach enables federal agencies to maintain mission readiness and operational resilience, regardless of the fiscal constraints ahead.

Travis Galloway is Director of Government Affairs at SolarWinds

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Production incidents rarely announce themselves as database problems. They appear as slow transactions, timeouts, rising response times, or an application struggling under a workload it previously handled. APM provides an essential starting point. It can identify a slow transaction path, highlight an affected service, and show that a database dependency is consuming more time than expected. But identifying the database as part of the problem is not the same as explaining what is happening inside it ...

Cloud teams are under constant pressure to reduce spend without slowing development or increasing operational risk. They are deploying autoscalers, rightsizing workloads, enforcing resource requests, reviewing utilization dashboards, and building FinOps processes around cloud-native environments. Yet the results often disappoint ...

Ask most IT leaders about their biggest concern with AI and you'll hear the same answer: hallucinations ... Today, however, the conversation has shifted ... As organizations move beyond chatbots and experiments, they are increasingly deploying AI agents that perform multi-step tasks. These systems retrieve documents, query databases, call APIs, generate reports, write code, and make recommendations. The issue is not whether the model can reason. The issue is whether the organization can see, verify, and govern the decisions being made along the way ...

While organizations want to take control of their telemetry, building telemetry pipelines from scratch can be a very daunting, complicated task, even when leveraging open-source standards like OpenTelemetry. It requires specialized knowledge across distributed systems, data engineering, and security. This fragmented approach across systems causes higher operational costs; it puts a strain on resources and reduces efficiency as teams have to work with different interfaces and processes ...

For decades, enterprise networks were designed around a simple assumption: work happened inside the office. Applications lived in centralized data centers, employees connected through internal infrastructure, and security focused on protecting the perimeter that surrounded everything ... But the way organizations operate today bears little resemblance to that environment. Cloud platforms host critical applications, employees connect from homes and airports as often as they do from offices, and partners collaborate through shared systems that exist far beyond corporate walls. In short, the corporate network no longer resembles the environment it was designed to protect ...

As an analyst who researches how IT organizations design, build, and operate their networks, I find that network data is a constant source of pain. Network teams struggle with data quality, fragmentation, authority, access, and trust. And these issues undermine everything they try to do. Here are the numbers: Only 45% of network teams are completely confident in the accuracy of their network source of truth, which documents the intent of their network ...

The 2026 Global Data Center Survey from Uptime Institute reveals an industry navigating workforce constraints, escalating outage expenses, even as rising costs remain the top concern for management teams ...

The next observability gap may not be in the code. It may be under the rack. That sounds strange until you think about how AI incidents actually feel in the middle of an investigation ... The application dashboard may be accurate. It may also be stopping at the wrong boundary. AI systems depend on software, but they also depend on a dense physical stack: racks, power paths, thermal margin, maintenance activity and, in many environments, liquid cooling. Those physical dependencies can change slowly before they look like a software incident ...

Certificate expiration is the rare outage you can see coming. Every TLS certificate carries the date it stops working, so the moment it will begin breaking connections is knowable in advance. That's what makes an expired certificate such a frustrating way to lose a service. What's changing now is how often that date comes around ...

Enterprises operate different combinations of workloads across cloud, hybrid and multicloud environments. For business-critical workloads, teams need to consider monitoring and observability early so they can detect health issues, investigate failures, and understand operational impact. Organizations place workloads on cloud platforms based on a combination of technical requirements, economics, existing dependencies, organizational standards, and business priorities. Their monitoring priorities therefore depend on what they operate and where those systems run. Those priorities will not look the same for every organization ...