Demystifying Full Stack Observability For Better Performance & Reliability

More than a year ago, Sayers posed the question: Is a full-stack observability solution in your future?

Since then, observability has become a hot topic everywhere from team conference rooms to industry summits. Observability platforms can consolidate monitoring tools, proactively identify issues in your environment, improve uptime, lower the total cost of ownership, and increase visibility for your on-premise infrastructure as well as cloud-native applications and containers.

Today’s observability platforms combine the best attributes of multiple tools to monitor your application, database, infrastructure, and network layers. This full-stack approach also adds AI and machine learning elements to be more intelligent and proactive.

What Does Observability Do?

Modern observability platforms, exemplified by market leaders such as Dynatrace, New Relic, and LogicMonitor, offer several big advantages over legacy monitoring tools. Those advantages include:

1. Full-Stack Visibility Into Applications And Infrastructure

With the next generation of network monitoring and alerting tools, observability takes a full-stack approach to gain visibility into your infrastructure and applications. Observability platforms pull and analyze data not just from servers and other infrastructure elements, but also monitor applications and database performance.

Mark McCully, Director of Modern Data Center Engineering at Sayers, says:

“If you have a Tier 1 application that’s running slow, observability allows you to quickly see where the issue is, drill down into it, and find the root cause a lot more quickly than when you had your networking and infrastructure teams using disparate monitoring tools.”

An observability platform’s tool consolidation leads to cost savings, and benefits go beyond TCO. Full-stack visibility enables teams to recover more quickly after an incident, as well as identify and address potential issues before things can go wrong.

2. Single-Pane-Of-Glass Approach

Picture a company with more than 60 different monitoring tools in their environment – a combination of home-grown and third-party tools. 

An observability platform solution would enable the company to consolidate those tools using a single-pane-of-glass approach. Such a solution offers faster root-cause analysis plus customizable dashboards that multiple teams can use including network, infrastructure, DevOps, development, and cloud teams.

With all those teams working from the same tool, which collects logs and metrics from numerous sources, the company can address issues sooner before they affect the company’s operations and customer experience.

3. Proactive Vs. Reactive Teams Thanks To AI And Automation

Newer observability platforms use artificial intelligence and machine learning for predictive analytics and performance baselining. After the tool runs in your environment for a specified period, it can baseline typical performance and create alerts when it detects deviations from that baseline. 

Intelligent alerts – with the context of predictive analytics and performance baselining – can alleviate staff fatigue by producing alerts that are fewer in number, more meaningful, and more actionable. 

4. Greater Visibility Into Cloud-Native Services

As enterprises put more of their workloads into the cloud, they need end-to-end visibility into cloud-native applications. Native tools from cloud providers for monitoring, logging, and analytics don’t achieve all the visibility needed for containers and applications such as platform-as-a-service web apps. McCully says:

“Having an observability tool such as Dynatrace or New Relic that you can inject into that application can give you much better insights because they are more fully featured than cloud-native monitoring tools.”

Why Do Enterprises Need Observability?

In many organizations, monitoring is present but fragmented. Teams work in silos with different point products. Insights are delayed or drown in the noisy, overwhelming number of alerts. 

Today’s infrastructure and operations teams in particular are trying to keep up with complex environments, the ever-increasing volume and velocity of data, and more services moving to the cloud and container environments. 

Amid all this, customers expect a frictionless user experience with reliable uptime and speed for your customer-facing applications.

According to a New Relic survey:

Only 27% of respondents had achieved full-stack observability, but 78% saw observability as a key enabler for achieving core business goals. A third still detected outages manually or from complaints.

Adopting modern observability is about up-leveling traditional monitoring tools to a platform that pulls in data from multiple sources and platforms. This gives you a full, actionable picture of what’s happening in your environment on a day-to-day basis.

Observability is a main tenant of infrastructure platform engineering, which focuses on ways to deliver applications more quickly and reliably. Observability platforms can monitor everything from infrastructure, applications, and network performance, to cloud, and DevOps environments, applications security, and end-user experience. 

Modern observability platforms also provide business analytics and dependency mapping. Such mapping identifies the operational dependencies among applications, servers, databases, and other components of your environment to better understand the business impact of potential risks.

Customer Use Case: Observability Platform Brings Predictive Intelligence And Lowers TCO

A fintech solutions company was frustrated with their existing network performance monitoring platform. The platform had too much administrative overhead and lacked predictive analytics, automation, and proactive notifications when circuits, ports, or equipment were down. 

The company’s network team felt they were in continual reactive mode. They also had forecasting issues resulting in some sites running out of port capacity. The organization wanted an observability platform with intelligence and machine learning built in, one that they wouldn’t have to run on premise and would lower their total cost of ownership.

Sayers recommended LogicMonitor, a SaaS-based observability platform. The platform collects data on prem but all logs run in the cloud, lowering the customer’s TCO. The observability platform uses predictive analytics and machine learning for proactive monitoring, load forecasting, and capacity planning for the network team.

Pleased with the results, the fintech company’s network team recommended the observability platform to the company’s infrastructure team for better and more cost-effective infrastructure monitoring.

Next Steps For Improved Observability

Wondering if your company needs a modern observability platform? Consider these aspects of your organization:

• What and how many monitoring and observability tools are you using in your environment? 
• Do you have monitoring and alerting coverage gaps? 
• How well are you monitoring your cloud-native applications and containers? 
• Are your current monitoring tools using AI and machine learning for predictive analytics, automation, and remediation? 
• Are you looking for better visibility and correlation with other applications in your full tech stack? 
• Do you need to improve your mean time to recovery and service-level objectives?
• Do you want to consolidate performance monitoring for network, applications, and cloud onto one platform? 

Questions? Contact us at Sayers today. We offer extensive solutions and expertise to cover all areas of your business.