2022 Application Performance Management Predictions - Part 2

Industry experts offer thoughtful, insightful, and often controversial predictions on how APM, AIOps, Observability, OpenTelemetry, and related technologies will evolve and impact business in 2022. Part 2 covers AIOps.

Start with: 2022 Application Performance Management Predictions - Part 1

AIOPS: Find, Fail and Fix Faster

Rising inflation, worker shortage, and the uncertainty of COVIDs long-term impact on the Global economy will make visibility to Operations more critical now than ever. There will be renewed focus on solving visibility, scalability and predictability for a large global, mobile workforce. In 2022, Automation at scale and Telemetry pre-release will be key around predictable find, fail and fix faster cycle times.
Jeanne Morain
Founder and Digital Transformation Catalyst, iSpeak Cloud

AIOPS LEADS TO SELF HEALING

2022 is the year where IT hygiene will catch up to the speed and scale of business. Much like the rise of personal wellness, we will start to think in similar terms when it comes to the people and technology that support the digital infrastructure of every organization today. We are headed, eventually, toward a future of the "self-healing enterprise" via technologies like AIOps. But before we get there, we need "self-care in the enterprise" — which involves constantly looking at the health and performance of the infrastructure and proactively addressing its stressors. Just like we go to the dentist whether we "need to" or not in order to prevent cavities, IT teams will focus on keeping employees happy and healthy and the infrastructure resilient and agile with more transparent monitoring and management.
Christina Kosmowski
President, LogicMonitor

FULL STACK AIOPS

Full stack AIOPs will be the key AI theme of 2022 enterprise networking. Fueled by increasingly complex networks and distributed workloads, artificial intelligence for IT operations (AIOps) has throttled its way to the top theme of the coming year. Expect to see enterprises invest in four key areas where AIOps make the biggest impact: user experience, operations experience, DevOps/application experience and location services. Further, organizations will also increasingly turn to AIOps to boost cybersecurity and immediately identify and mitigate potential issues before they occur.
Bob Friday
VP and CTO, Juniper Networks AI-Driven Enterprise

Infrastructure teams were the IT heroes of the pandemic as they moved systems and processes out of the office and into people's homes. This upheaval has highlighted the need for infrastructure teams to be both agile and resilient in the face of unforeseen emergencies. As organizations are able to take stock of post-Covid infrastructure requirements, we predict an increase in investments which improve visibility across the stack and which enable organizations to make large scale infrastructure changes at speed.
Andrew Sweeney
Co-Founder and Co-CEO, ReadyWorks

AIOPS GOES FROM DRAWING BOARD TO SHOP FLOOR

In 2022, enterprises will take big steps forward in their journey to AIOps. The catalyst: Organizations must deliver comprehensive, service-level awareness that measures business outcomes by visualizing connections across the IT estate and existing SLAs. This will force a shift away from device-level performance; ITOps leaders will instead prioritize how they define and determine enterprise service health, availability and risk via automated, real-time dashboards that can gauge business and customer impact. Furthermore, AIOps initiatives will elevate and enrich multi-directional data federation in real time to improve data-driven business decisions. It will be vital to accelerate automations with enterprise endpoints and functional capabilities, such as DevSecOps and financial systems. Watch for 2022 as the year AIOps goes from drawing board to shop floor.
Michael Nappi
CPO, ScienceLogic

AIOPS CLOSES SILOS BETWEEN OPS TEAMS

IT operations teams are finding it more difficult to rely on rule-based approaches alone for preventing and managing outages and alerts. Over the next year, we anticipate seeing a growing demand for AI models to be explainable when it comes to recommendations around diagnostics and solutions. Additionally, we believe AIOps will be a critical component to closing the silos between operations teams and enabling them to grow their skillset by offering better visibility across application, infrastructure and network domains.
Girish Muckai
Chief Sales & Marketing Officer, HEAL Software

DEMOCRATIZATION OF DOMAIN-AGNOSTIC AIOPS

In the 2022 timeframe, we will continue to see the democratization of domain agnostic AIOps, as complex ML tools kits are replaced by cost-effective purpose-built tools that leverage no-code/low-code and bring powerful API's that encourage automation. A more specific area of innovation will be around the application of AI to change management, where ML can be used to perform risk and impact analysis on potential changes.
Richard Whitehead
Evangelist in Chief, CTO, Moogsoft

Closing the AI Talent Gap Will Give Rise to AIOps Adoption

AIOps introduces governance, scaling, and transparency issues. Do you have AI governance in place? How are you scaling? Is it transparent? What do you do when the model is drifting? There's a lot of issues specific to AI that people are uncovering, but don't know how to resolve because of the lack of skilled professionals in the space. This AI talent shortage presents a huge barrier to AIOps adoption. As we continue to train and hire skilled AI professionals, more organizations will have the capabilities to utilize big data, machine learning and other advanced analytics technologies to gather data from their application environment. With these insights, it will soon be possible for organizations to have a bird's eye view of their entire ecosystem, allowing them to proactively spot trends and issues that will enable them to proactively manage their IT operations.
Rachel Roumeliotis
VP of AI and Data Content Strategy, O'Reilly Media

AIOPS SOLVES STAFFING AND SKILLS GAP

As we get into 2022, ITOps leaders will be pressing their software providers to keep pushing the bounds on what AIOps can bring to bear. Faster root-cause isolation and automated remediations must be huge parts of this. Teams are not growing, and tech workers are changing jobs more frequently — especially with the great disruption continuing for the foreseeable future. The only way to fill the staffing and skills gap is by deploying smarter systems. AIOps can fill this gap and leaders who aren't planning a 2022 rollout of an AIOps platform risk hurting the business's bottom line.
Rich Lane
Chief Strategy Officer, Netenrich

AIOPS STRUGGLES IN THE CLOUD

AIOps will continue to struggle with the increasing rate of change in modern cloud environments. High deployment frequencies coupled with cloud-native product velocities makes it increasingly difficult to baseline systems and discover useful patterns.
Tobias KunzeCEO and Co-Founder, Glasnostic

AIOps Will Be Dismantled, Repackaged and Rebranded

AIOps is an amalgamation of capabilities with some being more hype than hope. Considering that 39% of DevOps' SRE said they've never used AIOps and 68% said received AIOps value was only "low" or "moderate", the shift to AIOps in its current form is slow. Capabilities like "self-heal" and "auto remedy" have largely failed to deliver on their promises whereas capabilities such as "correlation" and "root cause analysis" have not. The result: a repackaged set of capabilities (sans "self-heal") that usefully focus on actionability and the addition of active, observational data sources (e.g., business KPI and competitive intelligence benchmarking) will emerge as AIOps NextGen.
Leo Vasiliou
Director of Product Marketing, Catchpoint

Go to: 2022 Application Performance Management Predictions - Part 3, covering Observability predictions.

Related Links

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Agentic Remediation: Capitalizing on the New Era of Database Observability

Developers building AI applications are not just looking for fault patterns after deployment; they must detect issues quickly during development and have the ability to prevent issues after going live. Unfortunately, traditional observability tools can no longer meet the needs of AI-driven enterprise application development. AI-powered detection and auto-remediation tools designed to keep pace with rapid development are now emerging to proactively manage performance and prevent downtime ...

ZTNA 101: Common Misconceptions That Keep Companies From Adopting It

Every few years, the cybersecurity industry adopts a new buzzword. "Zero Trust" has endured longer than most — and for good reason. Its promise is simple: trust nothing by default, verify everything continuously. Yet many organizations still hesitate to implement Zero Trust Network Access (ZTNA). The problem isn't that ZTNA doesn't work. It's that it's often misunderstood ...

When Dashboards Say "Green" But Customers See Red: Why Digital Experience Still Fails at the Last Mile

For many retail brands, peak season is the annual stress test of their digital infrastructure. It's also when often technical dashboards glow green, yet customer feedback, digital experience frustration, and conversion trends tell a different story entirely. Over the past several years, we've seen the same pattern across retail, financial services, travel, and media: internal application performance metrics fail to capture the true experience of users connecting over local broadband, mobile carriers, and congested networks using multiple devices across geographies ...

Don't Fall Into These 5 PostgreSQL Traps

PostgreSQL promises greater flexibility, performance, and cost savings compared to proprietary alternatives. But successfully deploying it isn't always straightforward, and there are some hidden traps along the way that even seasoned IT leaders can stumble into. In this blog, I'll highlight five of the most common pitfalls with PostgreSQL deployment and offer guidance on how to avoid them, along with the best path forward ...

Why AI Is No Longer Optional for IT Operations

The rise of hybrid cloud environments, the explosion of IoT devices, the proliferation of remote work, and advanced cyber threats have created a monitoring challenge that traditional approaches simply cannot meet. IT teams find themselves drowning in a sea of data, struggling to identify critical threats amidst a deluge of alerts, and often reacting to incidents long after they've begun. This is where AI and ML are leveraged ...

Outages Aren't the Enemy, Complacency Is

Three practices, chaos testing, incident retrospectives, and AIOps-driven monitoring, are transforming platform teams from reactive responders into proactive builders of resilient, self-healing systems. The evolution is not just technical; it's cultural. The modern platform engineer isn't just maintaining infrastructure. They're product owners designing for reliability, observability, and continuous improvement ...

The Changing World of Application Delivery (and why it pays to have choices)

Getting applications into the hands of those who need them quickly and securely has long been the goal of a branch of IT often referred to as End User Computing (EUC). Over recent years, the way applications (and data) have been delivered to these "users" has changed noticeably. Organizations have many more choices available to them now, and there will be more to come ... But how did we get here? Where are we going? Is this all too complicated? ...

When a Metadata Change Broke the Internet: What the Cloudflare Outage Really Revealed

On November 18, a single database permission change inside Cloudflare set off a chain of failures that rippled across the Internet. Traffic stalled. Authentication broke. Workers KV returned waves of 5xx errors as systems fell in and out of sync. For nearly three hours, one of the most resilient networks on the planet struggled under the weight of a change no one expected to matter ... Cloudflare recovered quickly, but the deeper lesson reaches far beyond this incident ...

Cybersecurity Awesomeness Podcast: Cloudflare Outage

Chris Steffen and Ken Buckler from EMA discuss the Cloudflare outage and what availability means in the technology space ...

When Milliseconds Matter: What Every Industry Can Learn From the Self-Driving Playbook

Every modern industry is confronting the same challenge: human reaction time is no longer fast enough for real-time decision environments. Across sectors, from financial services to manufacturing to cybersecurity and beyond, the stakes mirror those of autonomous vehicles — systems operating in complex, high-risk environments where milliseconds matter ...

2022 Application Performance Management Predictions - Part 2

Industry experts offer thoughtful, insightful, and often controversial predictions on how APM, AIOps, Observability, OpenTelemetry, and related technologies will evolve and impact business in 2022. Part 2 covers AIOps.

Start with: 2022 Application Performance Management Predictions - Part 1

AIOPS: Find, Fail and Fix Faster

Rising inflation, worker shortage, and the uncertainty of COVIDs long-term impact on the Global economy will make visibility to Operations more critical now than ever. There will be renewed focus on solving visibility, scalability and predictability for a large global, mobile workforce. In 2022, Automation at scale and Telemetry pre-release will be key around predictable find, fail and fix faster cycle times.
Jeanne Morain
Founder and Digital Transformation Catalyst, iSpeak Cloud

AIOPS LEADS TO SELF HEALING

2022 is the year where IT hygiene will catch up to the speed and scale of business. Much like the rise of personal wellness, we will start to think in similar terms when it comes to the people and technology that support the digital infrastructure of every organization today. We are headed, eventually, toward a future of the "self-healing enterprise" via technologies like AIOps. But before we get there, we need "self-care in the enterprise" — which involves constantly looking at the health and performance of the infrastructure and proactively addressing its stressors. Just like we go to the dentist whether we "need to" or not in order to prevent cavities, IT teams will focus on keeping employees happy and healthy and the infrastructure resilient and agile with more transparent monitoring and management.
Christina Kosmowski
President, LogicMonitor

FULL STACK AIOPS

Full stack AIOPs will be the key AI theme of 2022 enterprise networking. Fueled by increasingly complex networks and distributed workloads, artificial intelligence for IT operations (AIOps) has throttled its way to the top theme of the coming year. Expect to see enterprises invest in four key areas where AIOps make the biggest impact: user experience, operations experience, DevOps/application experience and location services. Further, organizations will also increasingly turn to AIOps to boost cybersecurity and immediately identify and mitigate potential issues before they occur.
Bob Friday
VP and CTO, Juniper Networks AI-Driven Enterprise

Infrastructure teams were the IT heroes of the pandemic as they moved systems and processes out of the office and into people's homes. This upheaval has highlighted the need for infrastructure teams to be both agile and resilient in the face of unforeseen emergencies. As organizations are able to take stock of post-Covid infrastructure requirements, we predict an increase in investments which improve visibility across the stack and which enable organizations to make large scale infrastructure changes at speed.
Andrew Sweeney
Co-Founder and Co-CEO, ReadyWorks

AIOPS GOES FROM DRAWING BOARD TO SHOP FLOOR

In 2022, enterprises will take big steps forward in their journey to AIOps. The catalyst: Organizations must deliver comprehensive, service-level awareness that measures business outcomes by visualizing connections across the IT estate and existing SLAs. This will force a shift away from device-level performance; ITOps leaders will instead prioritize how they define and determine enterprise service health, availability and risk via automated, real-time dashboards that can gauge business and customer impact. Furthermore, AIOps initiatives will elevate and enrich multi-directional data federation in real time to improve data-driven business decisions. It will be vital to accelerate automations with enterprise endpoints and functional capabilities, such as DevSecOps and financial systems. Watch for 2022 as the year AIOps goes from drawing board to shop floor.
Michael Nappi
CPO, ScienceLogic

AIOPS CLOSES SILOS BETWEEN OPS TEAMS

IT operations teams are finding it more difficult to rely on rule-based approaches alone for preventing and managing outages and alerts. Over the next year, we anticipate seeing a growing demand for AI models to be explainable when it comes to recommendations around diagnostics and solutions. Additionally, we believe AIOps will be a critical component to closing the silos between operations teams and enabling them to grow their skillset by offering better visibility across application, infrastructure and network domains.
Girish Muckai
Chief Sales & Marketing Officer, HEAL Software

DEMOCRATIZATION OF DOMAIN-AGNOSTIC AIOPS

In the 2022 timeframe, we will continue to see the democratization of domain agnostic AIOps, as complex ML tools kits are replaced by cost-effective purpose-built tools that leverage no-code/low-code and bring powerful API's that encourage automation. A more specific area of innovation will be around the application of AI to change management, where ML can be used to perform risk and impact analysis on potential changes.
Richard Whitehead
Evangelist in Chief, CTO, Moogsoft

Closing the AI Talent Gap Will Give Rise to AIOps Adoption

AIOps introduces governance, scaling, and transparency issues. Do you have AI governance in place? How are you scaling? Is it transparent? What do you do when the model is drifting? There's a lot of issues specific to AI that people are uncovering, but don't know how to resolve because of the lack of skilled professionals in the space. This AI talent shortage presents a huge barrier to AIOps adoption. As we continue to train and hire skilled AI professionals, more organizations will have the capabilities to utilize big data, machine learning and other advanced analytics technologies to gather data from their application environment. With these insights, it will soon be possible for organizations to have a bird's eye view of their entire ecosystem, allowing them to proactively spot trends and issues that will enable them to proactively manage their IT operations.
Rachel Roumeliotis
VP of AI and Data Content Strategy, O'Reilly Media

AIOPS SOLVES STAFFING AND SKILLS GAP

As we get into 2022, ITOps leaders will be pressing their software providers to keep pushing the bounds on what AIOps can bring to bear. Faster root-cause isolation and automated remediations must be huge parts of this. Teams are not growing, and tech workers are changing jobs more frequently — especially with the great disruption continuing for the foreseeable future. The only way to fill the staffing and skills gap is by deploying smarter systems. AIOps can fill this gap and leaders who aren't planning a 2022 rollout of an AIOps platform risk hurting the business's bottom line.
Rich Lane
Chief Strategy Officer, Netenrich

AIOPS STRUGGLES IN THE CLOUD

AIOps will continue to struggle with the increasing rate of change in modern cloud environments. High deployment frequencies coupled with cloud-native product velocities makes it increasingly difficult to baseline systems and discover useful patterns.
Tobias KunzeCEO and Co-Founder, Glasnostic

AIOps Will Be Dismantled, Repackaged and Rebranded

AIOps is an amalgamation of capabilities with some being more hype than hope. Considering that 39% of DevOps' SRE said they've never used AIOps and 68% said received AIOps value was only "low" or "moderate", the shift to AIOps in its current form is slow. Capabilities like "self-heal" and "auto remedy" have largely failed to deliver on their promises whereas capabilities such as "correlation" and "root cause analysis" have not. The result: a repackaged set of capabilities (sans "self-heal") that usefully focus on actionability and the addition of active, observational data sources (e.g., business KPI and competitive intelligence benchmarking) will emerge as AIOps NextGen.
Leo Vasiliou
Director of Product Marketing, Catchpoint

Go to: 2022 Application Performance Management Predictions - Part 3, covering Observability predictions.

Related Links

Hot Topics

The Latest

Agentic Remediation: Capitalizing on the New Era of Database Observability

Developers building AI applications are not just looking for fault patterns after deployment; they must detect issues quickly during development and have the ability to prevent issues after going live. Unfortunately, traditional observability tools can no longer meet the needs of AI-driven enterprise application development. AI-powered detection and auto-remediation tools designed to keep pace with rapid development are now emerging to proactively manage performance and prevent downtime ...

ZTNA 101: Common Misconceptions That Keep Companies From Adopting It

Every few years, the cybersecurity industry adopts a new buzzword. "Zero Trust" has endured longer than most — and for good reason. Its promise is simple: trust nothing by default, verify everything continuously. Yet many organizations still hesitate to implement Zero Trust Network Access (ZTNA). The problem isn't that ZTNA doesn't work. It's that it's often misunderstood ...

When Dashboards Say "Green" But Customers See Red: Why Digital Experience Still Fails at the Last Mile

For many retail brands, peak season is the annual stress test of their digital infrastructure. It's also when often technical dashboards glow green, yet customer feedback, digital experience frustration, and conversion trends tell a different story entirely. Over the past several years, we've seen the same pattern across retail, financial services, travel, and media: internal application performance metrics fail to capture the true experience of users connecting over local broadband, mobile carriers, and congested networks using multiple devices across geographies ...

Don't Fall Into These 5 PostgreSQL Traps

PostgreSQL promises greater flexibility, performance, and cost savings compared to proprietary alternatives. But successfully deploying it isn't always straightforward, and there are some hidden traps along the way that even seasoned IT leaders can stumble into. In this blog, I'll highlight five of the most common pitfalls with PostgreSQL deployment and offer guidance on how to avoid them, along with the best path forward ...

Why AI Is No Longer Optional for IT Operations

The rise of hybrid cloud environments, the explosion of IoT devices, the proliferation of remote work, and advanced cyber threats have created a monitoring challenge that traditional approaches simply cannot meet. IT teams find themselves drowning in a sea of data, struggling to identify critical threats amidst a deluge of alerts, and often reacting to incidents long after they've begun. This is where AI and ML are leveraged ...

Outages Aren't the Enemy, Complacency Is

Three practices, chaos testing, incident retrospectives, and AIOps-driven monitoring, are transforming platform teams from reactive responders into proactive builders of resilient, self-healing systems. The evolution is not just technical; it's cultural. The modern platform engineer isn't just maintaining infrastructure. They're product owners designing for reliability, observability, and continuous improvement ...

The Changing World of Application Delivery (and why it pays to have choices)

Getting applications into the hands of those who need them quickly and securely has long been the goal of a branch of IT often referred to as End User Computing (EUC). Over recent years, the way applications (and data) have been delivered to these "users" has changed noticeably. Organizations have many more choices available to them now, and there will be more to come ... But how did we get here? Where are we going? Is this all too complicated? ...

When a Metadata Change Broke the Internet: What the Cloudflare Outage Really Revealed

On November 18, a single database permission change inside Cloudflare set off a chain of failures that rippled across the Internet. Traffic stalled. Authentication broke. Workers KV returned waves of 5xx errors as systems fell in and out of sync. For nearly three hours, one of the most resilient networks on the planet struggled under the weight of a change no one expected to matter ... Cloudflare recovered quickly, but the deeper lesson reaches far beyond this incident ...

Cybersecurity Awesomeness Podcast: Cloudflare Outage

Chris Steffen and Ken Buckler from EMA discuss the Cloudflare outage and what availability means in the technology space ...

When Milliseconds Matter: What Every Industry Can Learn From the Self-Driving Playbook

Every modern industry is confronting the same challenge: human reaction time is no longer fast enough for real-time decision environments. Across sectors, from financial services to manufacturing to cybersecurity and beyond, the stakes mirror those of autonomous vehicles — systems operating in complex, high-risk environments where milliseconds matter ...