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What Is Full Stack Observability? Best Observability Solutions

Full stack observability (FSO) includes the ability to measure and monitor all layers of business infrastructure, security, and applications, from the underlying hardware and network performance to the user-facing software. As businesses shift from traditional, monolithic systems to more complex environments involving on-premises (on-prem) and cloud infrastructure, there comes a critical need for holistic observability. Full stack observability offers a unified view across these multi-cloud environments, enabling businesses to monitor their entire technology stack in real time.

Best Observability Solution

Importance of Full Stack Observability

Full Stack Observability vs. Traditional Monitoring

Benefits of Observability Solutions in IT and DevOps Teams

5 Best Full Stack Observability Tools

1. SolarWinds Observability (Free Trial)

2. Dynatrace

3. Datadog

4. LogicMonitor

5. New Relic

These days, applications are built on microservices and serverless architectures that coexist with legacy systems. This creates a distributed and fragmented environment where parts of the infrastructure reside on-prem, others in the cloud, and others increasingly at the edge. The traditional observability tools are designed for specific domains such as logging, metric, or tracing, and are insufficient for this modern setup. Full stack observability, therefore, addresses these challenges by providing a complete, unified picture of the entire infrastructure, thereby allowing businesses to correlate data across all layers, from application performance to business outcome.

The value of FSO lies in its ability to provide insights not only into technical performance but also into how systems support business goals. It allows companies to move beyond siloed monitoring tools and gain visibility into how every layer of their infrastructure contributes to overall business objectives. This level of observability is very important for decision-making, as businesses need to understand the impact of their technology on their strategic goals.

Best Observability Solution

A full-stack observability platform should offer AI/ML capabilities that accelerate performance, optimize costs, and enhance the customer experience by detecting anomalies and expediting troubleshooting and remediation. With the IT team’s ability to observe everything from anywhere, the FSO solution provides businesses with AI-powered insights to help them filter out noise and focus on actionable intelligence. This comprehensive monitoring makes lifecycle management simple, thereby allowing businesses to visualize and analyze data in a unified platform without dealing with multiple proprietary systems.

Importance of Full Stack Observability

As businesses embrace digitization, their applications and infrastructure become increasingly complex. Gone are the days when a traditional on-prem data center met all operational needs. Modern applications stretch across on-prem, cloud, and even edge environments. This is where a full-stack observability tool comes into play. Here, we will look at some of the importance of FSO.

1. Digitization Across Industries

We can all agree that in various sectors, from manufacturing to finance, businesses are adopting cloud technologies at unprecedented rates. Cloud providers like AWS, GCP, and Azure are continuously growing as they support this digital transformation. However, this adoption of multiple cloud environments introduces several complexities; these companies face an increasing number of endpoints to monitor. One major pain point for many of these businesses is the use of multiple monitoring tools across different environments, such as logging for one system, metrics for another, and tracing for yet another. But these full stack monitoring tools rarely offer an integrated view of the entire application stack, as they were designed for specific domains or expertise. This siloed approach is no longer sustainable in a multi-cloud world. FSO solves this problem by providing a unified full stack visibility of all components within an application, regardless of their location or technology stack.

2. Consolidation of Observability Data Into a Single Platform

At the heart of full-stack observability is the concept of consolidating observability data into a single platform. This does not just simplify lifecycle management but also reduces the need for multiple agents or data formats that businesses previously struggled with. Take SolarWinds, for example. As a leading player in the observability space, SolarWinds helps organizations collect and process observability data such as metrics, events, logs, and traces into a unified format, making it easier for a business to monitor its entire stack. SolarWinds provides a centralized collector that can retrieve data from different sources and output it into a format understandable by its various tools, whether it’s for visualization, performance analytics, or root cause identification.

3. Eliminating Duplicate Data

Another advantage of full stack observability lies in its ability to do away with the need for storing duplicate data. Traditional systems usually collect the same data for multiple use cases, which leads to an increased storage requirement. However, with FSO, businesses are able to collect data once and then proceed to use this collected data for various applications, including troubleshooting, monitoring, and performance analysis. The business saves storage costs and has faster access to important data across various departments.

4. Exposing Shadow IT

Shadow IT is a term used when a department within an organization uses a technology, application, or information technology system without the consent or approval of the IT department. FSO is key for businesses to detect and manage shadow IT, protecting against security risks and compliance issues. By providing real-time full-stack visibility into all technology components, organizations can identify unauthorized systems and applications, regain control, and optimize resources. This comprehensive monitoring approach gives proactive IT management and reduces the likelihood of data breaches, downtime, and reputational damage. FSO can ultimately ensure governance, improve system reliability, and drive IT efficiency for a business.

5. Monitoring From a Business Perspective

A major benefit of full stack observability is the ability to monitor infrastructure and applications from the business perspective rather than just focusing on individual components. Now, businesses can know if an application is performing in the context of a specific business transaction and customer need and not only if the application is just running. For instance, if there are complaints about the slow performance of a website, with FSO the business IT team can determine if the issue is due to the application code, network latency, or issues within a Kubernetes environment. FSO enables a company to track the problem down to its root cause and resolve it quickly in order to foster customer satisfaction.

Full Stack Observability vs. Traditional Monitoring

With traditional monitoring tools, monitoring can become fragmented. Since each tool generates its own data in isolation, it can be difficult to get a holistic view of system performance or troubleshoot complex issues that span across different environments.

Full stack observability provides a comprehensive, end-to-end view of your entire tech stack, covering everything from application code to infrastructure, from user interactions to network traffic. The idea is not just to monitor each layer individually but to observe the system as a whole. This includes the correlation of metrics, logs, traces, and events across multiple domains.

Some key differences between full-stack observability and traditional monitoring are highlighted below:

1. Scope and Coverage

Traditional monitoring tools focus on specific, isolated components, while FSO seamlessly provides a comprehensive view of your entire environment—on-premise, cloud, and edge.

2. Contextual Insights

When making use of a traditional setup, resolving an issue requires looking through logs, checking metrics, and tracing each component separately. This can really be tedious. FSO, on the other hand, brings context to the data and makes the work a lot easier by connecting the dots across systems, applications, and networks, thereby providing real-time insights into how the different components affect each other.

3. Flexibility

Traditional monitoring will always require the installation of different agents for different tools being used. FSO platforms like SolarWinds minimize the need for multiple agents by offering a unified data pipeline, simplifying the process, and enhancing visibility.

4. Real-Time Business Impact

While traditional monitoring focuses on infrastructure health, such as when a server is down, or an application is lagging, FSO will tie system performance directly to business outcomes. It will further answer key business questions like, “How is this application issue affecting customer experience?” or “Is a slowdown in this service impacting revenue?”

5. Multi-Cloud and Hybrid Cloud Support

Traditional monitoring tools are designed to handle the intricacies of modern multi-cloud environments. FSO solutions like SolarWinds, on the other hand, thrive in these distributed architectures, offering seamless integration across cloud platforms like AWS, Azure, or Google Cloud, in addition to on-prem infrastructure.

Benefits of Observability Solutions in IT and DevOps Teams

Observability solutions have become essential for maintaining performance, resolving issues quickly, and enabling continuous improvement. But what exactly makes FSO beneficial to IT and DevOps teams?

Proactive Issue Detection

One of FSO’s outstanding benefits is its ability to detect issues before they affect end users. This is because constant collection and analysis of metrics, logs, and traces enables an FSO solution to provide a real-time view of system health, allowing teams to quickly identify anomalies before they escalate into larger problems. For example, a sudden spike in CPU usage can alert the team to a potential issue so they can address it proactively.

Faster Root Cause Analysis

The faster you can identify the root cause of something that went wrong, the faster you are able to resolve the issue. Full stack observability platforms enable DevOps teams to correlate data across the stack, thereby making it a lot easier to pinpoint the source of the problem. Full stack observability solutions provide context and connect the dots, reducing the time it takes to troubleshoot complex issues.

Reduced Downtime and Improved Reliability

It comes with a costly price when a business experiences downtime, not just in revenue but also in damaged customer trust. FSO helps reduce downtime by providing real-time insights into system performance and health. IT and DevOps teams can take immediate corrective actions when they spot potential problems even before they occur.

Enhanced Collaboration Between Teams

Having a unified observability platform allows different teams to view the same set of data, breaking down barriers and ensuring everyone is on the same page. When an issue arises, both developers and operations teams can see how changes in application code impact system performance, making it easier to work together to resolve the problem.

Optimized Performance and Cost Efficiency

When the IT team has that visibility into how applications and infrastructure are being utilized, teams can make data-driven decisions to improve performance, scale resources more efficiently, and ultimately reduce unnecessary costs. For example, an FSO platform could reveal that certain cloud resources are underutilized, so the team can make targeted improvements.

5 Best Full Stack Observability Tools

Here is a list of the best full-stack observability tools:

1.    SolarWinds Observability (Free Trial)

©2024 SolarWinds Worldwide, LLC. All rights reserved.

SolarWinds Observability is a versatile solution that offers comprehensive monitoring and observability for both on-premises and cloud environments. As the first modern observability solution for hybrid ecosystems, the platform delivers flexibility, scalability, and value, allowing businesses to monitor their infrastructure no matter where they are located. SolarWinds offers AI/ML capabilities that accelerate performance, optimize costs, and enhance customer experience by detecting anomalies and expediting troubleshooting and remediation. It simplifies troubleshooting and cross-team collaboration with a unified view across on-prem and cloud servers, network devices, VMs, hosts, containers, and infrastructure. Furthermore, it provides deep visibility into your databases to increase performance by correlating database metrics with application performance, traces, and log monitoring to identify contributing factors. With a dedicated security dashboard, this platform helps you focus on critical issues across complex distributed environments.

2.    Dynatrace

© 2024 Dynatrace LLC. All rights reserved.

Dynatrace simplifies cloud complexity by offering unified observability and security through its AI-powered analytics and automation platform. Key features include end-to-end infrastructure observability, application performance monitoring (APM), real-time vulnerability protection, and advanced security analytics. Dynatrace enables organizations to deliver flawless digital experiences, automate operations, and gain actionable insights across all layers of their tech stack, making it a comprehensive solution for modern IT environments.

3.    Datadog

© Datadog 2024

Datadog provides modern monitoring and security solutions for any tech stack, application, or scale. It offers comprehensive features like infrastructure monitoring, APM (application performance monitoring), log management, security monitoring, and synthetic and real-user monitoring. Trusted by thousands of global brands, Datadog enables businesses to gain detailed insights across all layers of their cloud environments and ensures smooth operations with fast, in-depth visibility.

4.    LogicMonitor

© Copyright 2024 LogicMonitor Inc.

LogicMonitor offers AI-powered hybrid observability to monitor infrastructure, applications, and business services through a unified SaaS-based platform. Its advanced features include anomaly detection, dynamic thresholds, root cause analysis, and forecasting, helping IT teams reduce alert noise by 90% and improve mean time to resolution (MTTR) by 46%. With more than 3,000 integrations, LogicMonitor simplifies deployment and enables instant monitoring of a wide range of technologies and services, delivering real-time insights and proactive issue prevention across hybrid environments. Additionally, it has automatic support, discovery, and dashboards for over 2,000 types of infrastructure and applications.

5.    New Relic

©2008-24 New Relic, Inc. All rights reserved

New Relic is a unified observability platform designed to give full-stack visibility across all aspects of your infrastructure, applications, and digital experiences. It supports over 750 integrations. It offers essential features like application performance monitoring (APM), error tracking, logs, Kubernetes, and cloud monitoring, empowering teams to detect and resolve issues faster. New Relic is secured and trusted with enterprise-level security to protect your data.

Conclusion

Full stack observability provides a unified approach to monitoring and troubleshooting across all IT layers, from infrastructure to applications, offering better insights than traditional monitoring. Its importance lies in helping IT and DevOps teams proactively detect issues, improve performance, and optimize workflows. Leading tools like SolarWinds Observability, Dynatrace, Datadog, LogicMonitor, and New Relic provide robust observability solutions, driving efficiency and innovation across cloud and on-prem environments.

This post was written by Theophilus Onyejiaku. Theophilus has over five years of experience as a data scientist and a machine learning engineer. He has garnered expertise in the field of Data Science, Machine Learning, Computer Vision, Deep Learning, Object Detection, Model Development and Deployment. He has written over 660 articles in the aforementioned fields, python programming, data analytics, and much more.