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How ITOps Can Adapt to the New Normal - Part 5

APMdigest posed the following question to the IT Operations community: How should ITOps adapt to the new normal? In response, industry experts offered their best recommendations for how ITOps can adapt to this new remote work environment. Part 5, the final installment in the series, covers open source and emerging technologies.

Start with: How ITOps Can Adapt to the New Normal - Part 1

Start with: How ITOps Can Adapt to the New Normal - Part 2

Start with: How ITOps Can Adapt to the New Normal - Part 3

Start with: How ITOps Can Adapt to the New Normal - Part 4

OPEN SOURCE

Although 2020 has been a year of change, ITOps teams have been building for scale for quite some time, and our teams have become more distributed than ever. By utilizing new capabilities in cloud native architectures, where observability is embedded in our open source stacks teams have more options than ever. Open source is the new normal.
Jonah Kowall
CTO, Logz.io

EMERGING TECHNOLOGIES

We should ensure the teams are up to date with new emerging technologies. While the new norm influences our physical presence, technology continues to progress and we want our team to have the ability to learn, develop and find ways to advance the organization (and themselves) by leveraging new technologies and solutions. The organization should assist the Ops engineers in being up to date from this perspective as well.
Ziv Oren
Chief Delivery Officer, Aqua Security

SAAS

The new normal already has large parts of the workforce WFH and away from the office. ITOps teams will continue to focus on organizational solutions that provide stability and easy integration into pre-existing environments. This gives an advantage to SaaS solutions, which can be updated remotely, typically with high uptimes.
Russell Rothstein
Founder and CEO, IT Central Station

PUBLIC CLOUD IAAS

COVID-19 has dramatically amplified several existing trends and needs across teams. For ITOps, I think it has shown the importance of the move to Public Cloud IaaS — which means a reduction in their role, but it's the only route to scale/reliability. Where ITOps do still run systems, the mass migration to remote working has forever changed the infrastructure needs and cadence of evolution. Although most of what the team does can be done remotely, as everyone has moved to WFH, there is a considerable impact on the SREs and ITOps teams that manage the infrastructure data centers. They need to work in capsules to not to infect each other and maintain a working force that physically administers the data center. All clouds are basically physical servers that need maintenance at the end of the day.
Avishai Sharlin
Division President, Amdocs Technology

SDWAN

One key to navigating these challenging times is for ITOps to look at underlying network infrastructure to make sure it can handle the evolving demands of the business, and then plan a network upgrade in a way that's not disruptive to the business. Many organizations have turned to SD-WAN as the answer — and rightly so, because it provides a way to control application performance while centralizing and simplifying network and resource management. However, pretty much all SD-WAN vendors require an overhaul of the network infrastructure in order to implement, which is time-consuming, costly, disruptive, and slow to deliver results. Our recommendation is that ITOps consider a solution that doesn't require re-engineering of the network. Take advantage of transparent hybrid technologies in order to gain the application performance and network management benefits of SD-WAN immediately (rather than the typical 6-18+ months you'd be looking at with most solutions), without having to re-architect the network. The ideal SD-WAN solution enables a « hands-free » migration, which involves placing a device that is essentially invisible to the network and delivers instant end-to-end application visibility and control. Meanwhile, the business can migrate to a complete SD-WAN at their own pace, avoiding the risk, disruption, and delayed ROI associated with a complex network project. Additionally, the enterprise should consider whether an SD-WAN solution offers multi-cloud capabilities and supports work from home scenarios, because in the long term ,the network edge is expanding beyond the physical boundaries of the corporate perimeter. Lastly, cost flexibility is essential; the enterprise should insist on consumption-based pricing models in order to control costs and maintain flexibility as they grow or shift workloads and sites up or down. Ultimately, ITOps needs a network that can grow and scale with the business, as they adapt to unpredictable circumstances facing their business today and beyond.
Zabrina Doerck
Director of Product Marketing, Infovista

FULL-STACK SCALABILITY

The move to 100% remote ITOps underscores the importance of reliable, scalable, automatable infrastructure up and down the stack. Every part of your application stack, particularly the oft-overlooked foundational parts (think: servers, load balancers, VPNs, DNS), need to be just as agile and easy to deploy, update, and scale as your core application. This will enable you to react to changing business needs rapidly. The ability to scale your internal back-office application by 10x in 10 minutes is fantastic, but if none of your employees can access the system because your VPNs are overloaded, you've got a problem. Take the opportunity to look at every piece of software and hardware that powers your business and ask: "How agile and fragile is this?" "How does it scale?" "How can it be automated?" Because when it comes time to deliver on new goals and KPIs in the future, companies that have invested in making their entire stack more reliable and scalable will have a massive advantage.
Jonathan Sullivan
CTO, NS1

The Latest

In live financial environments, capital markets software cannot pause for rebuilds. New capabilities are introduced as stacked technology layers to meet evolving demands while systems remain active, data keeps moving, and controls stay intact. AI is no exception, and its opportunities are significant: accelerated decision cycles, compressed manual workflows, and more effective operations across complex environments. The constraint isn't the models themselves, but the architectural environments they enter ...

Like most digital transformation shifts, organizations often prioritize productivity and leave security and observability to keep pace. This usually translates to both the mass implementation of new technology and fragmented monitoring and observability (M&O) tooling. In the era of AI and varied cloud architecture, a disparate observability function can be dangerous. IT teams will lack a complete picture of their IT environment, making it harder to diagnose issues while slowing down mean time to resolve (MTTR). In fact, according to recent data from the SolarWinds State of Monitoring & Observability Report, 77% of IT personnel said the lack of visibility across their on-prem and cloud architecture was an issue ...

In MEAN TIME TO INSIGHT Episode 23, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses the NetOps labor shortage ... 

Technology management is evolving, and in turn, so is the scope of FinOps. The FinOps Foundation recently updated their mission statement from "advancing the people who manage the value of cloud" to "advancing the people who manage the value of technology." This seemingly small change solidifies a larger evolution: FinOps practitioners have organically expanded to be focused on more than just cloud cost optimization. Today, FinOps teams are largely — and quickly — expanding their job descriptions, evolving into a critical function for managing the full value of technology ...

Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...

Nearly every conversation about AI eventually circles back to compute. GPUs dominate the headlines while cloud platforms compete for workloads and model benchmarks drive investment decisions. But underneath that noise, a quieter infrastructure challenge is taking shape. The real bottleneck in enterprise AI is not processing power, it is the ability to store, manage and retrieve the relentless volumes of data that AI systems generate, consume and multiply ...

The 2026 Observability Survey from Grafana Labs paints a vivid picture of an industry maturing fast, where AI is welcomed with careful conditions, SaaS economics are reshaping spending decisions, complexity remains a defining challenge, and open standards continue to underpin it all ...

The observability industry has an evolving relationship with AI. We're not skeptics, but it's clear that trust in AI must be earned ... In Grafana Labs' annual Observability Survey, 92% said they see real value in AI surfacing anomalies before they cause downtime. Another 91% endorsed AI for forecasting and root cause analysis. So while the demand is there, customers need it to be trustworthy, as the survey also found that the practitioners most enthusiastic about AI are also the most insistent on explainability ...

In the modern enterprise, the conversation around AI has moved past skepticism toward a stage of active adoption. According to our 2026 State of IT Trends Report: The Human Side of Autonomous AI, nearly 90% of IT professionals view AI as a net positive, and this optimism is well-founded. We are seeing agentic AI move beyond simple automation to actively streamlining complex data insights and eliminating the manual toil that has long hindered innovation. However, as we integrate these autonomous agents into our ecosystems, the fundamental DNA of the IT role is evolving ...

AI workloads require an enormous amount of computing power ... What's also becoming abundantly clear is just how quickly AI's computing needs are leading to enterprise systems failure. According to Cockroach Labs' State of AI Infrastructure 2026 report, enterprise systems are much closer to failure than their organizations realize. The report ... suggests AI scale could cause widespread failures in as little as one year — making it a clear risk for business performance and reliability.

How ITOps Can Adapt to the New Normal - Part 5

APMdigest posed the following question to the IT Operations community: How should ITOps adapt to the new normal? In response, industry experts offered their best recommendations for how ITOps can adapt to this new remote work environment. Part 5, the final installment in the series, covers open source and emerging technologies.

Start with: How ITOps Can Adapt to the New Normal - Part 1

Start with: How ITOps Can Adapt to the New Normal - Part 2

Start with: How ITOps Can Adapt to the New Normal - Part 3

Start with: How ITOps Can Adapt to the New Normal - Part 4

OPEN SOURCE

Although 2020 has been a year of change, ITOps teams have been building for scale for quite some time, and our teams have become more distributed than ever. By utilizing new capabilities in cloud native architectures, where observability is embedded in our open source stacks teams have more options than ever. Open source is the new normal.
Jonah Kowall
CTO, Logz.io

EMERGING TECHNOLOGIES

We should ensure the teams are up to date with new emerging technologies. While the new norm influences our physical presence, technology continues to progress and we want our team to have the ability to learn, develop and find ways to advance the organization (and themselves) by leveraging new technologies and solutions. The organization should assist the Ops engineers in being up to date from this perspective as well.
Ziv Oren
Chief Delivery Officer, Aqua Security

SAAS

The new normal already has large parts of the workforce WFH and away from the office. ITOps teams will continue to focus on organizational solutions that provide stability and easy integration into pre-existing environments. This gives an advantage to SaaS solutions, which can be updated remotely, typically with high uptimes.
Russell Rothstein
Founder and CEO, IT Central Station

PUBLIC CLOUD IAAS

COVID-19 has dramatically amplified several existing trends and needs across teams. For ITOps, I think it has shown the importance of the move to Public Cloud IaaS — which means a reduction in their role, but it's the only route to scale/reliability. Where ITOps do still run systems, the mass migration to remote working has forever changed the infrastructure needs and cadence of evolution. Although most of what the team does can be done remotely, as everyone has moved to WFH, there is a considerable impact on the SREs and ITOps teams that manage the infrastructure data centers. They need to work in capsules to not to infect each other and maintain a working force that physically administers the data center. All clouds are basically physical servers that need maintenance at the end of the day.
Avishai Sharlin
Division President, Amdocs Technology

SDWAN

One key to navigating these challenging times is for ITOps to look at underlying network infrastructure to make sure it can handle the evolving demands of the business, and then plan a network upgrade in a way that's not disruptive to the business. Many organizations have turned to SD-WAN as the answer — and rightly so, because it provides a way to control application performance while centralizing and simplifying network and resource management. However, pretty much all SD-WAN vendors require an overhaul of the network infrastructure in order to implement, which is time-consuming, costly, disruptive, and slow to deliver results. Our recommendation is that ITOps consider a solution that doesn't require re-engineering of the network. Take advantage of transparent hybrid technologies in order to gain the application performance and network management benefits of SD-WAN immediately (rather than the typical 6-18+ months you'd be looking at with most solutions), without having to re-architect the network. The ideal SD-WAN solution enables a « hands-free » migration, which involves placing a device that is essentially invisible to the network and delivers instant end-to-end application visibility and control. Meanwhile, the business can migrate to a complete SD-WAN at their own pace, avoiding the risk, disruption, and delayed ROI associated with a complex network project. Additionally, the enterprise should consider whether an SD-WAN solution offers multi-cloud capabilities and supports work from home scenarios, because in the long term ,the network edge is expanding beyond the physical boundaries of the corporate perimeter. Lastly, cost flexibility is essential; the enterprise should insist on consumption-based pricing models in order to control costs and maintain flexibility as they grow or shift workloads and sites up or down. Ultimately, ITOps needs a network that can grow and scale with the business, as they adapt to unpredictable circumstances facing their business today and beyond.
Zabrina Doerck
Director of Product Marketing, Infovista

FULL-STACK SCALABILITY

The move to 100% remote ITOps underscores the importance of reliable, scalable, automatable infrastructure up and down the stack. Every part of your application stack, particularly the oft-overlooked foundational parts (think: servers, load balancers, VPNs, DNS), need to be just as agile and easy to deploy, update, and scale as your core application. This will enable you to react to changing business needs rapidly. The ability to scale your internal back-office application by 10x in 10 minutes is fantastic, but if none of your employees can access the system because your VPNs are overloaded, you've got a problem. Take the opportunity to look at every piece of software and hardware that powers your business and ask: "How agile and fragile is this?" "How does it scale?" "How can it be automated?" Because when it comes time to deliver on new goals and KPIs in the future, companies that have invested in making their entire stack more reliable and scalable will have a massive advantage.
Jonathan Sullivan
CTO, NS1

The Latest

In live financial environments, capital markets software cannot pause for rebuilds. New capabilities are introduced as stacked technology layers to meet evolving demands while systems remain active, data keeps moving, and controls stay intact. AI is no exception, and its opportunities are significant: accelerated decision cycles, compressed manual workflows, and more effective operations across complex environments. The constraint isn't the models themselves, but the architectural environments they enter ...

Like most digital transformation shifts, organizations often prioritize productivity and leave security and observability to keep pace. This usually translates to both the mass implementation of new technology and fragmented monitoring and observability (M&O) tooling. In the era of AI and varied cloud architecture, a disparate observability function can be dangerous. IT teams will lack a complete picture of their IT environment, making it harder to diagnose issues while slowing down mean time to resolve (MTTR). In fact, according to recent data from the SolarWinds State of Monitoring & Observability Report, 77% of IT personnel said the lack of visibility across their on-prem and cloud architecture was an issue ...

In MEAN TIME TO INSIGHT Episode 23, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses the NetOps labor shortage ... 

Technology management is evolving, and in turn, so is the scope of FinOps. The FinOps Foundation recently updated their mission statement from "advancing the people who manage the value of cloud" to "advancing the people who manage the value of technology." This seemingly small change solidifies a larger evolution: FinOps practitioners have organically expanded to be focused on more than just cloud cost optimization. Today, FinOps teams are largely — and quickly — expanding their job descriptions, evolving into a critical function for managing the full value of technology ...

Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...

Nearly every conversation about AI eventually circles back to compute. GPUs dominate the headlines while cloud platforms compete for workloads and model benchmarks drive investment decisions. But underneath that noise, a quieter infrastructure challenge is taking shape. The real bottleneck in enterprise AI is not processing power, it is the ability to store, manage and retrieve the relentless volumes of data that AI systems generate, consume and multiply ...

The 2026 Observability Survey from Grafana Labs paints a vivid picture of an industry maturing fast, where AI is welcomed with careful conditions, SaaS economics are reshaping spending decisions, complexity remains a defining challenge, and open standards continue to underpin it all ...

The observability industry has an evolving relationship with AI. We're not skeptics, but it's clear that trust in AI must be earned ... In Grafana Labs' annual Observability Survey, 92% said they see real value in AI surfacing anomalies before they cause downtime. Another 91% endorsed AI for forecasting and root cause analysis. So while the demand is there, customers need it to be trustworthy, as the survey also found that the practitioners most enthusiastic about AI are also the most insistent on explainability ...

In the modern enterprise, the conversation around AI has moved past skepticism toward a stage of active adoption. According to our 2026 State of IT Trends Report: The Human Side of Autonomous AI, nearly 90% of IT professionals view AI as a net positive, and this optimism is well-founded. We are seeing agentic AI move beyond simple automation to actively streamlining complex data insights and eliminating the manual toil that has long hindered innovation. However, as we integrate these autonomous agents into our ecosystems, the fundamental DNA of the IT role is evolving ...

AI workloads require an enormous amount of computing power ... What's also becoming abundantly clear is just how quickly AI's computing needs are leading to enterprise systems failure. According to Cockroach Labs' State of AI Infrastructure 2026 report, enterprise systems are much closer to failure than their organizations realize. The report ... suggests AI scale could cause widespread failures in as little as one year — making it a clear risk for business performance and reliability.