Full Stack Observability

Everything you need to know about full stack observability

End-to-end visibility across your technology stack is invaluable for troubleshooting issues and optimizing performance. Our guide to full-stack observability explains all you need to know, including opportunities and challenges, how to achieve it, and how the Vertice platform can enable real-time insights into your IT ecosystem.

What is

Full Stack Observability

?

What is full-stack observability?

Full-stack observability involves gaining comprehensive visibility into the health and performance of your entire IT environment, from the end-user experience down to the underlying infrastructure.

While traditional monitoring is a reactive approach typically focused on individual aspects of an ecosystem, full-stack observability is more proactive in nature and lets you understand the status of any endpoint within your stack in real-time. This insight is invaluable, with today’s IT environments featuring complex dependencies across on-premise solutions, cloud-hosted services, Kubernetes containers, open-source technologies, microservices, and much more.

Achieving full-stack visibility typically involves collecting and analyzing telemetry data — metrics, events, logs, and traces (sometimes referred to as MELT) — from various sources across your stack. Consequently, DevOps and IT teams can understand how every component interacts to optimize performance and identify potential issues earlier.

Here’s what full-stack observability might look like in action:

  • Imagine an e-commerce website where a sudden surge in traffic causes the website to slow down. Through full-stack observability, the IT department can see if the performance issues are due to overloaded servers, inefficient database queries, or issues with the user interface. This holistic view helps pinpoint and fix the root cause faster, ensuring minimal impact on the customer experience.
  • Following new code deployment, yclouou might notice a slowdown in your application’s response times. A full-stack observability solution can display code-level profiling data, information about resource utilization on your servers, and performance metrics like page load times. From there, you can identify the cause. These could include inefficient code changes, increased server load from new features, or unintended impacts on the user interface.
  • A crash report in your mobile app mentions the app freezing during checkout. Observability tools let you analyze logs from the user’s device and the app server alongside network traffic data, helping you identify the issue: the device, a bug within the app itself, or network communication problems.

The opportunities of full-stack observability

A unified view across your entire technology stack offers a proliferation of opportunities. Here’s where full-stack observability can help your organization:

  • Quicker identification and resolution of problems – By correlating data from various sources, it’s easier to determine the issue’s root cause, minimizing downtime, ensuring a smoother user experience, and enhancing an organization’s digital transformation.
  • Improved application performance – Insights into bottlenecks and resource utilization within your application enable proactive optimization and performance enhancements, a practice known as APM (application performance management).
  • Enhanced DEM – Full-stack observability can improve your digital experience monitoring, letting you quickly identify and remedy issues throughout the development lifecycle to create a more reliable and enjoyable user experience.
  • Incident response – Empowering your staff with a comprehensive data set can result in more effective incident response, reducing mean time to recovery (MTTR) during outages.  
  • Informed decision-making – Data-driven, actionable insights from observability tools enable more strategic infrastructure scaling, resource allocation, and future development decisions to improve business outcomes.
  • Reduced operational costs – Faster issue resolution, proactive maintenance, and optimized resource allocation can all improve operational costs.
  • Improved security posture – A clear view of system behavior across your tech stack makes detecting suspicious activity and potential security vulnerabilities easier. This leads to enhanced application security and organization-wide cloud and SaaS security posture.

Barriers to full-stack observability

Numerous roadblocks stand in the way of achieving full-stack observability within your organization. Here’s what you should watch out for:

  • Cost and resource constraints – Implementing and maintaining observability tools can be expensive, with skilled personnel required to manage and analyze the generated data.
  • Data overload and siloed information – Observability of your entire tech stack inherently generates a lot of data, which can become overwhelming. It may also be siloed in different tools, hindering a unified view and leading to more complex latency issues. Without proper management of this data, valuable insights can get lost.
  • Stack complexity – Modern tech stacks may incorporate hybrid cloud or multi-cloud environments alongside a plethora of software solutions, with the resulting complexity making comprehensive visibility more challenging.
  • Tool sprawl – Organizations may rely on a patchwork of different monitoring tools for various aspects of their IT stack, which can lead to difficulties managing and integrating data across different platforms.
  • Shadow IT – Using unauthorized or unsanctioned technology, known as shadow IT, can create blind spots. As these resources may not be integrated with your FSO systems, tracking their performance and potential impact across your stack is difficult.
  • Legacy systems – Older technology within your IT ecosystem may not be equipped to collect observability data, creating visibility gaps.

How to achieve full-stack observability

Implementing true full-stack observability within your organization requires careful consideration and a well-defined strategy. Here’s a breakdown of key steps and best practices to remember on your FSO journey.

1. Define your goals

Before diving in, clearly define your objectives. What do you want to achieve through full-stack observability? Collaborate with stakeholders to identify the key metrics and data points most critical to your applications and infrastructure, as this will guide your tool selection and the data you collect.

2. Assess your stack

Develop a clear picture of your existing applications and infrastructure. You might need to implement new code or instrumentation so your apps can emit relevant telemetry data, or leverage existing monitoring tools built into your solutions. Additionally, consider how your cloud provider (i.e. AWS, Microsoft Azure or Google Cloud) will affect full-stack observability efforts.

3. Select your tools

Various cloud-native and on-prem observability tools exist, each catering to specific data types and needs. You should choose scalable tools that integrate well with your existing infrastructure. Popular providers include AppDynamics, Cisco, New Relic, and Datadog. For a more cost-effective approach, you might want to consider open-source options alongside commercial solutions.

4. Prioritize security

Security should be a top priority when collecting and storing observability data, which is often sensitive in nature. Be sure to implement proper access controls and encryption measures.

5. Centralize your data

Implement a central platform or logging system to collect data from across your stack. FSO tools commonly include this functionality. You should also establish consistent practices for data collection, logging, and tagging across your environment to simplify data management — you’ll be dealing with a lot of it!

6. Analyze and visualize

It’s worth investing in analysis and visualization tools for transforming your raw data into actionable insights. Many cloud visibility solutions offer dashboarding and reporting features to help you identify trends that might indicate underlying issues.

7. Implement automatic alerts

To maximize observability data, consider setting up intelligent alerts to notify your teams about potential issues before they impact users or system performance.

8. Embrace AIOps

Artificial Intelligence for IT Operations, commonly known as AIOps, can dramatically reduce the burden of managing your stack. AIOps tools can ingest and analyze your observability data to identify patterns and anomalies, automating tasks like incident correlation and root cause analysis and subsequently taking action to quickly remediate issues.

9. Foster observability culture

Full-stack observability isn’t just about technology — it requires a shift in mindset across development, operations, and business teams. Within your organization, foster a culture of data-driven decision-making and encourage collaboration around observability practices through well-defined policies and procedures. This can tie into wider Cloud FinOps best practices.

10. Continuously improve

Once it’s in place, you should regularly evaluate your approach to full-stack observability, ensuring your chosen tools and analysis practices remain effective and aligned with your evolving needs.

Gain control of every facet of your tech stack with Vertice

Effective full-stack observability remains a challenge for many organizations, but Vertice can help. Our SaaS Purchasing Platform provides granular, real-time insights into the utilization of solutions within your ecosystem, helping you optimize your resources, eliminate blind spots by uncovering shadow IT, and ultimately reduce cost.

We can also help you save money at acquisition or renewal. By letting us handle SaaS contract negotiation on your behalf, you’ll get access to the best discounts and prices thanks to our market intel on what other businesses are paying. To get started, simply get in touch below.

Full Stack Observability

FAQs

How do you get cloud visibility?

Organizations leverage several strategies to achieve greater cloud visibility and eliminate blind spots across cloud environments. In essence, the main objective is gathering a centralized view of your cloud infrastructure. Most cloud providers provide basic cloud-native logging and monitoring tools – a good place to start, but not sustainable in the long run. Gaining a holistic account of an enterprise with shared dashboards and real-time data gathering is only possible with a third-party cloud visibility solution like Vertice. Our platform ensures total network visibility with detailed insights, consistent monitoring, and integrated dashboards, helping you visualize your cloud infrastructure with complete clarity.

How can I improve cloud visibility for multi-cloud management?

Achieving strong multi-cloud visibility poses additional challenges compared to managing a single cloud platform. Multi-cloud organizations must collect and unify data simultaneously from AWS, Azure, Google Cloud, IBM Cloud, and any other services they’re using, requiring more advanced log management and standardization across code languages. Leverage Infrastructure as Code (IaC) tools like Terraform and Ansible alongside orchestration software to get a clearer and more homogeneous idea of your network. Autoscaling is also highly effective for enhancing multi-cloud visibility and protecting resources, especially with organizations prone to fluctuations in workload and revenue.

What is limited cloud usage visibility?

Limited cloud usage visibility is a fundamental characteristic to avoid if you want a healthy, robust, and cost-effective cloud network. It’s akin to navigating a map with numerous blind spots and missing locations. Effective cloud management with tools like the Vertice platform helps to avoid this, unifying your cloud data to achieve more consistent visibility across a network.

What is multi-cloud visibility?

While standard cloud visibility refers to the management of a single cloud, multi-cloud visibility is for organizations simultaneously leveraging several networks like Azure, AWS, and Google. The cloud landscape immediately becomes less homogenous, so standardization, containerization, and extensive monitoring is crucial. Larger enterprises must pay particular attention to multi-cloud visibility, as their infrastructure is often built with multi-cloud or even hybrid-cloud approaches.

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