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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

AI observability serves several roles across an organization. AI engineers use it to build, evaluate, and improve AI systems. SREs use it to operate those systems reliably and efficiently in production, including managing their cost. Leaders need it to connect AI behavior and operational performance to business outcomes. The common need is a clear understanding of whether AI systems are delivering the intended result ...

Part 4 outlines the challenges enterprise face when adopting AI observability. The main challenge is that AI complexity compounds at every stage of maturity. LLM-based applications introduce new behavior, dependencies, and quality considerations, while Agentic AI adds further failure modes as systems make decisions and take actions ...

Part 3 reports on the current state of AI observability. Most experts agree: enterprises are moving faster with AI than they are with the operational discipline needed to run it safely ...

When discussing AI Observability, one of the first questions that arises: Is this just an extension of traditional observability or is this a whole new type of tool? Part 2 compares traditional observability with AI observability ...

In this extensive 14-part series that will post over the next three weeks, experts across observability and AI will provide insight and opinions on the need for AI Observability, the challenges, the benefits, the current state, and predictions for the future ...

Amid rising complexity, organizations are moving quickly toward agent-driven operations: AgenticOps, according to The Impact of Agentic AI on Network Operations, a new report from Cisco ...

AI, automation, and enterprise software give organizations an extraordinary amount of leverage. Work that once required hours can happen in minutes. Information buried across systems can be analyzed almost instantly. Complex workflows can be coordinated across teams with far less manual intervention. That leverage creates a temptation to start with the technology ...

Everyone wants to talk about models. Compute clusters. Benchmark scores that climb a fraction of a point and make headlines anyway. It's an easy conversation to have because it's measurable. But it's also increasingly beside the point ...

For more than a decade, the default infrastructure play has been simple. Move more workloads to the cloud, retire on-premises gear and treat the data center as a cost to shrink. That logic held while public cloud offered near-limitless capacity at predictable prices, and AI demand is now testing both halves of that assumption ...

Most enterprise IT leaders can tell you exactly how many applications are running across their organization. They can surface a dashboard showing telecom spend by region, pull a report on SaaS license utilization, or call up a real-time view of mobile device inventory. The data is there, and IT leaders have largely delivered on the promise of visibility. Yet, in most organizations, that visibility has not translated into business value ...

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

AI observability serves several roles across an organization. AI engineers use it to build, evaluate, and improve AI systems. SREs use it to operate those systems reliably and efficiently in production, including managing their cost. Leaders need it to connect AI behavior and operational performance to business outcomes. The common need is a clear understanding of whether AI systems are delivering the intended result ...

Part 4 outlines the challenges enterprise face when adopting AI observability. The main challenge is that AI complexity compounds at every stage of maturity. LLM-based applications introduce new behavior, dependencies, and quality considerations, while Agentic AI adds further failure modes as systems make decisions and take actions ...

Part 3 reports on the current state of AI observability. Most experts agree: enterprises are moving faster with AI than they are with the operational discipline needed to run it safely ...

When discussing AI Observability, one of the first questions that arises: Is this just an extension of traditional observability or is this a whole new type of tool? Part 2 compares traditional observability with AI observability ...

In this extensive 14-part series that will post over the next three weeks, experts across observability and AI will provide insight and opinions on the need for AI Observability, the challenges, the benefits, the current state, and predictions for the future ...

Amid rising complexity, organizations are moving quickly toward agent-driven operations: AgenticOps, according to The Impact of Agentic AI on Network Operations, a new report from Cisco ...

AI, automation, and enterprise software give organizations an extraordinary amount of leverage. Work that once required hours can happen in minutes. Information buried across systems can be analyzed almost instantly. Complex workflows can be coordinated across teams with far less manual intervention. That leverage creates a temptation to start with the technology ...

Everyone wants to talk about models. Compute clusters. Benchmark scores that climb a fraction of a point and make headlines anyway. It's an easy conversation to have because it's measurable. But it's also increasingly beside the point ...

For more than a decade, the default infrastructure play has been simple. Move more workloads to the cloud, retire on-premises gear and treat the data center as a cost to shrink. That logic held while public cloud offered near-limitless capacity at predictable prices, and AI demand is now testing both halves of that assumption ...

Most enterprise IT leaders can tell you exactly how many applications are running across their organization. They can surface a dashboard showing telecom spend by region, pull a report on SaaS license utilization, or call up a real-time view of mobile device inventory. The data is there, and IT leaders have largely delivered on the promise of visibility. Yet, in most organizations, that visibility has not translated into business value ...