To overcome the resulting complexity, companies often equip themselves with a large number of monitoring and management devices. Their goal is to simplify system monitoring, but the opposite is happening: they see silos developing as teams use many different tools to manage their networks or infrastructure.
This fragmented approach accentuates operational blind spots and slows problem solving. It also further threatens the security of the company. Soon, overworked IT professionals can no longer keep up with the evolution of ever-modernizing applications, or the dynamics of infrastructures, as they become overwhelmed with complexity. However, while this scenario is common, it is not inevitable. IT teams can simplify their digital transformation process by implementing a cost-effective, integrated, full-stack, end-to-end monitoring service that can overcome complexity and break down silos. Thus, companies demand full stack observability.
Difference Between Observability and Traditional Monitoring
Observability goes far beyond traditional monitoring. Traditional monitoring allows IT teams to understand the current state of their infrastructure and applications. It captures and processes large volumes of infrastructure and application telemetry data, as well as notifications, and displays active, inactive and changed components. Usually, this type of monitoring targets a specific network, cloud, or infrastructure. It tracks application and infrastructure elements to enable IT professionals to identify anomalies and investigate issues as they arise.
Monitoring uses indicator-focused dashboards to assess telemetry data against manual or elementary thresholds that are statistically relevant. Monitoring tools are a must, but they don’t offer cross-domain correlation, insight into service delivery and operational dependencies, or predictability. Modern systems have complex multi-cloud environments and a wealth of telemetry data, which limits them.
Observability goes further. It measures the internal state of systems by observing the outputs produced and examining applications and systems in their entirety, from the end-user experience to server-related metrics and logs.
Yet monitoring is a critical element of observability. Observability requires the prior collection of information through monitoring operations. Observability uses the information and indicators generated through monitoring to understand the origin of the problem to be solved.
Monitoring helps aggregate and display data to determine if systems are operating as expected. The analysis of this information is compared to the targeted results and objectives. This allows IT professionals to understand the state of their infrastructure and applications. They then avoid silos by being able to visualize complex environments in their entirety.
Observability in action
Once installed, observability software enables IT teams to continuously improve performance, availability, and digital experience within a variety of complex cloud, hybrid, and distributed environments.
With observability features, organizations can quickly detect and remediate anomalies. However, full-stack observability is not just about monitoring and accelerating problem resolution: it provides insights, automated analytics, and actionable intelligence through cross-domain data correlation, maching learning, and intelligence. artificial intelligence for IT operations (AIOps). It processes massive volumes of historical and real-time data from indicators, logs, and tracking.
Observability goes beyond the silos and fragmented approach of traditional monitoring. So, since observability has no limits, when it integrates ML and AIOps, it leverages the large volume of collected data and provides insights, automated analytics, and actionable intelligence to help IT staff to solve problems faster. It also enables ITOps, DevOps, and security teams to ensure the consistent, optimized, and predictable delivery of business services by continuously optimizing the digital experience and IT productivity.
Customers and employees then have the advantage of using better managed systems. The technology provides companies of all sizes, and specializing in various sectors, complete, integrated and cost-effective functionalities thanks to the flexibility of cloud, on-premises or SaaS (Software as a Service) deployments.
When embarking on their digital transformation, companies want to avoid additional complexity, especially when updating legacy applications and adding a host of modern services and capabilities to their stack. Only observability reduces complexity because it simplifies the transformation process. It limits the amount of unnecessary operations information to make it easier for ITOps, DevOps, and security teams. This is when organizations can more proactively detect issues and anomalies to optimize IT performance, compliance, and resiliency. With full-stack observability, all businesses, regardless of size and industry, can reduce IT complexity while preparing for digital transformation.
By Thomas LaRock, Head Geek™, SolarWinds
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Overcome IT Complexity with Full Stack Observability
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