Why public sector organisations are shifting from monitoring to observability

public sector organisations
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Head Geekat SolarWinds, Sascha Giese, explores how public sector organisations are implementing observability over their previous method of network monitoring

Advances in technology have been accelerated by the pandemic and with many tech improvements becoming integral to daily life, we wouldn’t dream of going back to the way things were before

Network monitoring vs. observability is a case in point. Monitoring meets public sector organisations’ needs by telling IT pros which components are up, which ones are down, and which ones may have changed. But monitoring alone doesn’t have powers beyond this point. It’s limited to focusing on each element in isolation—a specific network, cloud, or infrastructure, tracking discrete application and infrastructure elements.

Many government and public sector organisations still monitor their networks in this way, not questioning how it captures and processes vast amounts of infrastructure and application telemetry data and notifications. Instead of watching the trees but missing the forest, there must be a better way to manage the tech ecosystem in 2022.

Challenges of monitoring in public sector IT environments

One of the most common challenges public sector organisations face within their IT environments is the significant multitasking required to manage an ever-increasing number of individually dedicated tools. Talented and already time-pressurised tech experts face burnout due to under-resourcing and physical stress. At the same time, the ripple effects of this lack of productivity can cause much broader business inefficiencies.

New capabilities with observability

Enter observability, which is the evolution of traditional monitoring to handle the modern digital-first tech stack. Smart public sector organisations have discovered new efficiencies by prioritising observability over monitoring. Why would they go back to the way things were before?

Observability surpasses traditional monitoring by minimising the operational administration weighing down IT operations (ITOps), software development and IT operations (DevOps), and security teams. By continually assessing applications and systems, including end-user experience and server-side metrics and logs, it examines the output information to measure the internal state of systems. A robust observability system should use artificial intelligence/machine learning (AI/ML) technologies to make quick corrections or empower an IT pro with insights to fix the issue rapidly.

In this way, tech pros are provided with an ongoing end-to-end service delivery analysis where they can quickly identify and act upon issues and anomalies to optimise their tech performance and compliance. This enables them to re-allocate time for higher priority business initiatives.

Get the bigger picture

Amidst the demands of a new multi- or hybrid-cloud environment, it’s less a conscious choice not to revert to traditional monitoring as these methods are no longer fit for purpose. There’s a new driving need to be connected across computer, application, and database domains. With an overwhelming amount of telemetry data, the monitoring tool’s support easily falls short in delivering cross-domain service delivery insight, operational dependencies, or predictability. Its disjointed approach can’t support the needs of a dynamic digital organisation.

The benefits of embracing observability

Observability can boost operational efficiencies in various ways. Public sector IT teams can continuously enhance their performance, availability, and digital experience across complex hybrid- and multi-cloud environments. The critical areas of success benefiting most from observability include:

  • Minimised downtime: Observability enables predictable service, which significantly reduces downtime. IT teams’ increased proactivity in issue and anomaly detection can optimise IT performance, compliance, and resilience. Organisations can obtain comprehensive, integrated, and cost-effective functionality through cloud-connected on-premises or Software as a Service (SaaS).
  • Certainty from data: The ‘guesswork’ approach has evolved into actionable intelligence. With end-to-end observability now including ML and artificial intelligence for IT Operations (AIOps), it leverages a considerable amount of data to provide intelligent insights and automated analytics. With a more holistic view of the entire tech ecosystem, teams can rapidly identify system issues.
  • Rapid problem resolution: In supplying insights, automated analytics, and actionable intelligence, observability can rapidly resolve problems while covering extensive real-time and historical metrics, logs, and trace data.

Potential for zero percent downtime

Government and public sector workers and customers benefit equally from observability as systems operate more effectively. Meanwhile, IT professionals are now reflecting less on system problems, as they have more time to dedicate to improving their processes and focusing on new priorities.

While it might be unthinkable at this point to compare monitoring with observability, there’s still the bonus potential for zero percent downtime. An observability system can automate rapid responses when it’s powered by AI/ML models explicitly tuned to handle IT operations (AIOps). Public sector organisations jumping on the observability train in 2022 won’t be looking back.


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