IT Trends 2018: The Intersection of Hype and Performance - Part 2

Leon Adato
Learn more about SolarWinds

If IT professionals want to be instrumental to their organization's successful digital transformation journey, they should continue prioritizing a hybrid IT environment while simultaneously developing new skillsets and leveraging emerging technologies.

To help IT professionals arm themselves with a new set of skills, technologies, and resources to bridge the leadership gap and manage the intersection of hype and performance, consider the following recommendations.

Start with: IT Trends 2018: The Intersection of Hype and Performance - Part 1

1. Concentrate on Containers

Because delivering organizational value is a constant goal, IT professionals should continue to prioritize container deployment, both from an investment and skills-development perspective.

For IT professionals seeking to concentrate on containers, they should first find out if the IT organization is already working with the technology. If it is, get to know the people involved and engage with them. If the IT organization is not working with containers, IT professionals can simply find resources or platforms online. There are also communities like GitHub that allow container experts to freely share their knowledge. Once IT professionals learn how containers work, they should start learning about container automation and orchestration to enable a bridge into scaling the integration and delivery of distributed apps and cloud deployments, all while opening a path to greater understanding of how those workloads are managed.

2. Cloud Power-Up

IT professionals are beginning to consume different service delivery models, like moving from Microsoft Exchange Servers to Office 365, and migrate more of their mission-critical applications to the cloud.

In parallel with these changes, there must be increased observability — leveraging combined metrics, logs, and application traces for controllability — built into an organization's cloud monitoring strategy. This degree of monitoring with discipline must carry forward the same level of granularity and source of truth that has existed in on-premises environments for decades. The key part of this process is establishing a baseline of observability within their hybrid IT environments across the entirety of their cloud-based applications.

3. Bridge the Leadership Gap

There will continue to be a great deal of excitement around ML and AI in the foreseeable future. As we saw with cloud, executives are eager to implement the technology, which promises the hyped benefits of disruptive innovation, and want to activate a new technology quickly without the experience to understand current capabilities, technical complexities, or deployment challenges. The best course of action for IT professionals is to become educators: identify ways to discuss the basics, the specific cost-benefit analysis of how the technology will benefit the business, and what it means for service integration and service delivery.

4. Embrace Resiliency and Reliability as Performance Metrics

To achieve digital transformation success, it's imperative that IT professionals begin to embrace resiliency and reliability of their environments as critical performance metrics.

Resiliency and reliability underscore the business value that IT professionals can bring to fruition for their organizations. They also represent measures of how well a distributed application was integrated and delivered; and because they also represent overall performance, these metrics translate into dollar values. With the stakes so high, the ability to ensure the end-user's digital experience is essential. IT should look to leverage tools that deliver full-stack observability into the logs, metrics, and tracing data that underpin reliability and resiliency metrics to ultimately optimize environments.

IT professionals must keep business leaders realistic about what technology implementations make the most sense for their organization. According to a recent report from Forrester, 55 percent of companies have not yet achieved tangible business outcomes from AI, and 43 percent say it's too soon to tell. AI and ML might not be a top priority today, but by focusing on optimizing cloud and hybrid IT environments right now, IT professionals can build the foundation for AI and ML while meeting the current needs of the business.

In 2018, IT professionals should balance optimizing the digital experience for end-users in hybrid IT environments with strategic decisions around which technologies their organization should invest in for business value beyond IT.

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IT Trends 2018: The Intersection of Hype and Performance - Part 2

Leon Adato
Learn more about SolarWinds

If IT professionals want to be instrumental to their organization's successful digital transformation journey, they should continue prioritizing a hybrid IT environment while simultaneously developing new skillsets and leveraging emerging technologies.

To help IT professionals arm themselves with a new set of skills, technologies, and resources to bridge the leadership gap and manage the intersection of hype and performance, consider the following recommendations.

Start with: IT Trends 2018: The Intersection of Hype and Performance - Part 1

1. Concentrate on Containers

Because delivering organizational value is a constant goal, IT professionals should continue to prioritize container deployment, both from an investment and skills-development perspective.

For IT professionals seeking to concentrate on containers, they should first find out if the IT organization is already working with the technology. If it is, get to know the people involved and engage with them. If the IT organization is not working with containers, IT professionals can simply find resources or platforms online. There are also communities like GitHub that allow container experts to freely share their knowledge. Once IT professionals learn how containers work, they should start learning about container automation and orchestration to enable a bridge into scaling the integration and delivery of distributed apps and cloud deployments, all while opening a path to greater understanding of how those workloads are managed.

2. Cloud Power-Up

IT professionals are beginning to consume different service delivery models, like moving from Microsoft Exchange Servers to Office 365, and migrate more of their mission-critical applications to the cloud.

In parallel with these changes, there must be increased observability — leveraging combined metrics, logs, and application traces for controllability — built into an organization's cloud monitoring strategy. This degree of monitoring with discipline must carry forward the same level of granularity and source of truth that has existed in on-premises environments for decades. The key part of this process is establishing a baseline of observability within their hybrid IT environments across the entirety of their cloud-based applications.

3. Bridge the Leadership Gap

There will continue to be a great deal of excitement around ML and AI in the foreseeable future. As we saw with cloud, executives are eager to implement the technology, which promises the hyped benefits of disruptive innovation, and want to activate a new technology quickly without the experience to understand current capabilities, technical complexities, or deployment challenges. The best course of action for IT professionals is to become educators: identify ways to discuss the basics, the specific cost-benefit analysis of how the technology will benefit the business, and what it means for service integration and service delivery.

4. Embrace Resiliency and Reliability as Performance Metrics

To achieve digital transformation success, it's imperative that IT professionals begin to embrace resiliency and reliability of their environments as critical performance metrics.

Resiliency and reliability underscore the business value that IT professionals can bring to fruition for their organizations. They also represent measures of how well a distributed application was integrated and delivered; and because they also represent overall performance, these metrics translate into dollar values. With the stakes so high, the ability to ensure the end-user's digital experience is essential. IT should look to leverage tools that deliver full-stack observability into the logs, metrics, and tracing data that underpin reliability and resiliency metrics to ultimately optimize environments.

IT professionals must keep business leaders realistic about what technology implementations make the most sense for their organization. According to a recent report from Forrester, 55 percent of companies have not yet achieved tangible business outcomes from AI, and 43 percent say it's too soon to tell. AI and ML might not be a top priority today, but by focusing on optimizing cloud and hybrid IT environments right now, IT professionals can build the foundation for AI and ML while meeting the current needs of the business.

In 2018, IT professionals should balance optimizing the digital experience for end-users in hybrid IT environments with strategic decisions around which technologies their organization should invest in for business value beyond IT.

Related Links

Hot Topics

Related Vendors

The Latest

How AI Agents Are Reshaping DataOps for the Always-On Enterprise

Enterprises today operate in a real-time environment where uninterrupted access to trusted data has become a baseline expectation for users, applications and automated systems. Traditional DataOps models, built on manual effort and human triage, cannot keep pace with this always active demand. AI agents are emerging as the operational backbone, ensuring consistent data availability, reinforcing trustworthiness and enabling a level of scale that manual processes cannot achieve ...

AI Deepfakes: Rethinking Trust in the Workplace

For decades, trust in the digital workplace rested on familiar signals. We trusted faces on video calls, voices on the phone, and emails that appeared to come from people we knew. These cues felt human and intuitive. They anchored how decisions were made, approvals were granted, and access was authorized. AI-powered deepfakes have quietly broken that model ...

Nine in Ten Enterprises Plan Cloud Data Repatriation amid Rising Cloud Costs and Data Sovereignty Mandates

Cloud migration was supposed to be a one-way door. For most enterprises, it turns out it isn't. Cloud data repatriation is a real and growing trend. A new survey ... finds that 89% of organizations plan to expand their on-premises infrastructure footprint over the next two years — and 75% have already moved at least some workloads back from public cloud in the past 24 months. The findings point to a broad rethinking of where data belongs ...

Why ITOps Need Right-Sized AI, Not Bigger Models

Over the past few years, large language models (LLMs) have revolutionized the software industry. Given their ability to excel at multi-step reasoning, LLMs have helped enterprises streamline workflows and adapt to the unknown. However, employing such models comes with sky-high costs, latency issues, and limited flexibility. In the realm of IT operations, it is generally wiser to employ smaller, domain-specific models instead ...

The End of Reactive DevOps: AI-Driven Observability for Zero-Defect Digital Systems

For years, DevOps teams operated under a simple assumption: collect enough telemetry, and you can find and fix any problem. That assumption is breaking down. Modern enterprises now operate across microservices, hybrid cloud environments, APIs, Kubernetes, and highly automated delivery pipelines. Releases happen continuously, dependencies shift constantly, and failures spread faster than teams can diagnose them ...

5 Takeaways from the Observability Forecast for Media and Entertainment

New Relic surveyed IT and engineering leaders from the media and entertainment (M&E) sector to understand what's working — and where challenges persist with their observability practices. The findings reveal how M&E organizations are navigating rising platform complexity, audience expectations, and AI-driven change. Below are five takeaways that stand out ...

Why Moving Off the Cloud Is the Easy Part and What Comes Next Is Where Things Get Hard

Let me start with something I've seen play out more times than I can count. A team hits a wall with the cloud. Costs creep up, then spike. Performance starts to feel inconsistent. Someone in finance asks a simple question like "why did this double?" and nobody has a clean answer ... Maybe this isn't the right place for everything. That realization feels like a breakthrough, like you've identified the problem. In reality, you've just identified the starting line ...

MEAN TIME TO INSIGHT Podcast - Episode 24: Network Observability Tool Sprawl

In MEAN TIME TO INSIGHT Episode 24, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses network observability tool sprawl ... 

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In cloud-native systems, scaling is often as simple as moving a slider. For on-premise databases, the stakes are different. Over-provisioning hardware is expensive. Under-provisioning leads to performance bottlenecks that are difficult to fix once the equipment is in the rack ...

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