You Have 40 Monitoring Tools, Make the Next One Count

Richard Whitehead
Moogsoft

In our growing digital economy, end users have no tolerance for downtime. Consequently, IT leaders invest heavily in availability: DevOps and SRE (site reliability engineering) teams to ensure digital apps and services are continuously available and digital tools built to influence uptime.

As recent research uncovered, IT leaders invest in a lot of single-domain monitoring tools. In fact, teams rely on an average of 16 monitoring tools — and up to 40 — according to the Moogsoft State of Availability Report.

Despite this heavy investment, teams are not achieving positive availability outcomes. Perhaps most telling, monitoring tools only catch performance issues or outages about half of the time. Customers flag the rest.

In other words, monitoring tool investments are not paying dividends. They are not helping teams quickly catch data anomalies and expediently fix incidents, and they certainly are not creating a positive customer experience. Yet, DevOps and SREs need monitoring solutions as manually monitoring ever-complex IT ecosystems with ever more data would be impossible.

So what's the secret to modern availability? How can teams better leverage their tools?

The Point Solution Problem: Partial Information

Part of the proliferation of monitoring tools in the IT stack is due to a proliferation of tools in the incident management space in general. Over the past few years, software vendors have introduced a slew of specific point solutions that solve specific problems.

On the positive side, point solutions specialize in monitoring certain aspects of an organization's IT ecosystem: the network, application, IT infrastructure or digital experience. But, problematically, point solutions do not integrate and cannot enable continuous insights across an IT stack. This siloed approach to monitoring:

■ Costs time and resources

Licensing copious amounts of monitoring tools is expensive. Perhaps even more expensive, human teams need to spend time managing and maintaining these monitoring solutions. And that is likely why research finds engineers spend more time monitoring over any other activity, innovation and value creation included.

■ Expands operational risk

Siloed approaches to anything — monitoring included — increase operational efficiencies and slow progress. When knowledge sits in one tool, the information tends to get orphaned and this lengthens communication lines and delays incident triage and resolution.

■ Increases downtime

Issues within the IT ecosystem are typically connected. But, because point solutions lack insight across the entire system, alerts tend to show up in multiple tools, creating a lot of unnecessary noise and further compounding and slowing incident remediation.

The Availability Answer: Use AIOps to Connect Monitoring Tools

To extract value out of monitoring tools and ensure more uptime, engineering teams need to connect their point solutions, creating a single line of sight across the entire incident lifecycle. Domain-agnostic artificial intelligence for IT operations (AIOps) can be this connective tissue. By converging data from all aspects of the incident lifecycle, AIOps connects otherwise siloed point solutions. This integrated approach to monitoring:

■ Provides a unified dashboard

Point solutions require engineers to hop from tool and tool, monitoring and maintaining various dashboards and charts. AIOps, on the other hand, integrates and aggregates data from across an organization's entire tool stack. As a result, engineering teams can look at one single dashboard that summarizes the health of all of their systems.

■ Streamlines the incident lifecycle

In addition to providing a summary of system health, AIOps solutions provide one single system of incident engagement. In this incident home base, engineering teams can track the incident lifecycle: detection, notification and resolution. Seeing the full picture of the incident lifecycle in one platform simplifies and speeds the response, and in the meantime, helps engineers understand — and then reduce — the amount of time each phase takes.

■ Optimizes overall systems

Because AIOps tools take a holistic approach to monitoring, they act as the connective tissue between an organization's monitoring data and help fill data gaps. These solutions make sense of data pulled from multiple point solutions, deduplicating and correlating alerts, enriching data and adding context across systems. This helps teams eliminate noise and identify root causes faster.

Instead of adding another point solution to a growing monitoring toolbox, IT leaders should make their next investment count. And AIOps could be the key. By adopting an AIOps tool, teams understand the whole picture of system health and can sidestep unnecessary noise and alerts to expediently respond to service-disrupting incidents. DevOps and SREs, facing less unplanned work, can invest in the future, paying down technical debt and further increasing system stability.

Richard Whitehead is Chief Evangelist at Moogsoft

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You Have 40 Monitoring Tools, Make the Next One Count

Richard Whitehead
Moogsoft

In our growing digital economy, end users have no tolerance for downtime. Consequently, IT leaders invest heavily in availability: DevOps and SRE (site reliability engineering) teams to ensure digital apps and services are continuously available and digital tools built to influence uptime.

As recent research uncovered, IT leaders invest in a lot of single-domain monitoring tools. In fact, teams rely on an average of 16 monitoring tools — and up to 40 — according to the Moogsoft State of Availability Report.

Despite this heavy investment, teams are not achieving positive availability outcomes. Perhaps most telling, monitoring tools only catch performance issues or outages about half of the time. Customers flag the rest.

In other words, monitoring tool investments are not paying dividends. They are not helping teams quickly catch data anomalies and expediently fix incidents, and they certainly are not creating a positive customer experience. Yet, DevOps and SREs need monitoring solutions as manually monitoring ever-complex IT ecosystems with ever more data would be impossible.

So what's the secret to modern availability? How can teams better leverage their tools?

The Point Solution Problem: Partial Information

Part of the proliferation of monitoring tools in the IT stack is due to a proliferation of tools in the incident management space in general. Over the past few years, software vendors have introduced a slew of specific point solutions that solve specific problems.

On the positive side, point solutions specialize in monitoring certain aspects of an organization's IT ecosystem: the network, application, IT infrastructure or digital experience. But, problematically, point solutions do not integrate and cannot enable continuous insights across an IT stack. This siloed approach to monitoring:

■ Costs time and resources

Licensing copious amounts of monitoring tools is expensive. Perhaps even more expensive, human teams need to spend time managing and maintaining these monitoring solutions. And that is likely why research finds engineers spend more time monitoring over any other activity, innovation and value creation included.

■ Expands operational risk

Siloed approaches to anything — monitoring included — increase operational efficiencies and slow progress. When knowledge sits in one tool, the information tends to get orphaned and this lengthens communication lines and delays incident triage and resolution.

■ Increases downtime

Issues within the IT ecosystem are typically connected. But, because point solutions lack insight across the entire system, alerts tend to show up in multiple tools, creating a lot of unnecessary noise and further compounding and slowing incident remediation.

The Availability Answer: Use AIOps to Connect Monitoring Tools

To extract value out of monitoring tools and ensure more uptime, engineering teams need to connect their point solutions, creating a single line of sight across the entire incident lifecycle. Domain-agnostic artificial intelligence for IT operations (AIOps) can be this connective tissue. By converging data from all aspects of the incident lifecycle, AIOps connects otherwise siloed point solutions. This integrated approach to monitoring:

■ Provides a unified dashboard

Point solutions require engineers to hop from tool and tool, monitoring and maintaining various dashboards and charts. AIOps, on the other hand, integrates and aggregates data from across an organization's entire tool stack. As a result, engineering teams can look at one single dashboard that summarizes the health of all of their systems.

■ Streamlines the incident lifecycle

In addition to providing a summary of system health, AIOps solutions provide one single system of incident engagement. In this incident home base, engineering teams can track the incident lifecycle: detection, notification and resolution. Seeing the full picture of the incident lifecycle in one platform simplifies and speeds the response, and in the meantime, helps engineers understand — and then reduce — the amount of time each phase takes.

■ Optimizes overall systems

Because AIOps tools take a holistic approach to monitoring, they act as the connective tissue between an organization's monitoring data and help fill data gaps. These solutions make sense of data pulled from multiple point solutions, deduplicating and correlating alerts, enriching data and adding context across systems. This helps teams eliminate noise and identify root causes faster.

Instead of adding another point solution to a growing monitoring toolbox, IT leaders should make their next investment count. And AIOps could be the key. By adopting an AIOps tool, teams understand the whole picture of system health and can sidestep unnecessary noise and alerts to expediently respond to service-disrupting incidents. DevOps and SREs, facing less unplanned work, can invest in the future, paying down technical debt and further increasing system stability.

Richard Whitehead is Chief Evangelist at Moogsoft

Related Links

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While organizations want to take control of their telemetry, building telemetry pipelines from scratch can be a very daunting, complicated task, even when leveraging open-source standards like OpenTelemetry. It requires specialized knowledge across distributed systems, data engineering, and security. This fragmented approach across systems causes higher operational costs; it puts a strain on resources and reduces efficiency as teams have to work with different interfaces and processes ...

The Corporate Network Is Fading - Here's What Replaces It

For decades, enterprise networks were designed around a simple assumption: work happened inside the office. Applications lived in centralized data centers, employees connected through internal infrastructure, and security focused on protecting the perimeter that surrounded everything ... But the way organizations operate today bears little resemblance to that environment. Cloud platforms host critical applications, employees connect from homes and airports as often as they do from offices, and partners collaborate through shared systems that exist far beyond corporate walls. In short, the corporate network no longer resembles the environment it was designed to protect ...

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Certificate expiration is the rare outage you can see coming. Every TLS certificate carries the date it stops working, so the moment it will begin breaking connections is knowable in advance. That's what makes an expired certificate such a frustrating way to lose a service. What's changing now is how often that date comes around ...

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Enterprises operate different combinations of workloads across cloud, hybrid and multicloud environments. For business-critical workloads, teams need to consider monitoring and observability early so they can detect health issues, investigate failures, and understand operational impact. Organizations place workloads on cloud platforms based on a combination of technical requirements, economics, existing dependencies, organizational standards, and business priorities. Their monitoring priorities therefore depend on what they operate and where those systems run. Those priorities will not look the same for every organization ...

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