How Observability Helps Organizations Shift Left Effectively

Observability

Solutions Review’s Expert Insights Series is a collection of contributed articles written by industry experts in enterprise software categories. Adam Hert of Riverbed observes the benefits of automation and unified observability in helping organizations shift left.

Expert Insights badgeInvestment in much of the technology market has cooled recently over concerns about high-interest rates and a possible recession. But at least one area appears to be poised for growth: observability, where half of the respondents to a recent IDC survey expect budgets to grow over the next few years. Why? Because unified observability can help enterprises achieve their goals of shift-left in NetOps as well as in DevOps to improve performance, increase productivity and boost customer satisfaction. It can help companies thrive in challenging times.

A lot of the focus on shift-left has often been, for obvious reasons, to make better software– more reliable, high-performing, scalable, and secure. But with NetOps, it also can deliver other benefits, making for more productive employees at every level and feeding a better company culture. It helps organizations manage an increasingly complex infrastructure where the amount of data they’re processing is growing exponentially. Shifting left with Unified Observability aligns with companies’ desires to redirect IT staff from routine, tactical duties to more strategic projects, such as predictive modeling or infrastructure optimization. Shift-left improves network performance, certainly, but it also supports business objectives by enabling senior IT leaders to focus on problems that affect a company’s bottom line.

In today’s increasingly complex IT environment, where the economic climate can be uncertain, companies need those benefits more than ever.

Runbooks Become Indispensable

Enterprises typically rely on highly skilled IT pros to troubleshoot and fix problems, but on-staff experts are often in short supply, particularly in a field where boomers are retiring, and the shortage of skilled young workers is essentially endemic. Meanwhile, the job keeps getting bigger as the infrastructure grows. When the experts — who ideally would spend their time on strategic initiatives for the company — aren’t available, resolving incidents or system faults not only takes longer, but the impact spreads to other parts of the enterprise as other team members are pulled away from their own strategic projects to try their hand at troubleshooting.

The kind of left shift an observability platform provides can help solve that dilemma by codifying resident experts’ experience and domain knowledge into automated runbooks. Companies can ask senior leaders how they would address a certain problem and put their answers into a guide, which can then be customized into workflows that meet the organization’s requirements. Those runbooks help resolve problems faster while easing the burden on highly valued experts and giving junior IT staff the chance to learn quickly and take on more responsibility. It gives organizations the opportunity to retain knowledge that isn’t easily reproduced.

The Tools to Reduce Alert Fatigue

IT staffs are frequently overwhelmed by monitoring alerts, most of which provide scant context about an incident and little guidance to the troubleshooting process. Identifying critical events from the noise becomes impossible without manually investigating every alert, which often proves too much for the staff members on hand. Some will just turn off alerts and wait for the phone to ring.

An observability platform can take over the most time-consuming parts of that job. It can make use of artificial intelligence (AI) and machine learning (ML) to find correlations in issues that impact business. Pre-built runbooks perform automated, low-code investigations that gather evidence, put events into context, and set priorities for response. Meanwhile, IT staff, including senior and junior levels, can focus on tasks that create value for the business. Identifying the issues that represent the biggest risks to the business enables first-level responders to resolve the most important problems in a timely manner.

How Observability Works in Practice

Observability is a significant step forward from monitoring, which while valuable to enterprises, is limited. Monitoring is built on pre-set metrics, which are in turn based on pre-conceived ideas of what a team is looking for. Observability, however, opens the door to investigating unknown or previously unseen events. It can also support correlating information from disparate tools and performing advanced analysis with AI and ML, adding extra context. Combining monitoring, visibility, and automation, observability determines the state of a system by examining its outputs, leading to the discovery of actionable insights that couldn’t otherwise be found without a lot of manual input.

A unified observability platform can provide full-fidelity data from across the enterprise — including all transactions, packets, and workflows — and accelerate the resolution of problems ranging from workflow bottlenecks to cyber-attacks, while enabling organizations to improve service delivery. It allows organizations to apply the advantages of a shift-left philosophy throughout the enterprise, whether in the DevOps team or at the help desk.

Observability delivers tangible benefits in other ways. For example, it delivers faster mean time to resolution (MTTR) and higher first-level resolution rates by isolating the source of a delay or problem to a client device, network, or backend component, and drilling down via one click to investigate. It also can analyze the common characteristics among users experiencing the same problem to identify the likely cause. As a result, an observability platform can quickly diagnose and resolve issues that are impacting users. Organizations making use of observability have reduced service desk ticket volume by 15 percent and MTTR by 24 percent.

Automation is a Must

IT teams are small. They haven’t grown in years and, realistically, are getting smaller in proportion to the growing size and complexity of the IT environments they work with, including on-premises data centers, multiple clouds (public, private and hybrid), mobile and remote devices, and expanding numbers of edge locations and Internet of Things (IoT) devices. Managing and securing those environments effectively just isn’t possible with the human resources organizations have. The job can only be addressed through automation.

More than simply automating rote tasks, however, organizations need the advanced automation that an observability platform provides through the use of AI and ML. Sorting through the noise of endless monitoring alerts — and handing off only critical challenges to human IT problem-solvers — requires collecting information from disparate sources across the enterprise, correlating common issues and determining a likely cause. Automated no-code runbooks drawn from senior IT leaders’ experience significantly shorten the time it takes to identify and resolve a problem.

Reaping the Real Benefits of Shift-Left

Shift-left has demonstrated that it can improve software quality, security, and business performance by moving critical processes into the early stages of development. But the scope and complexity of today’s environments requires comprehensive visibility into the infrastructure, along with advanced analytics tools. Unified observability makes a shift left more effective, by optimizing the collection and analysis of an organization’s data, reducing MTTR, and allowing IT experts to focus on forward-looking initiatives that advance the organization’s digital transformation—and improve its bottom line.

Adam Hert
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