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Exploring the Convergence of Observability and Security - Part 4: Dashboards

Pete Goldin
APMdigest

With input from industry experts — both analysts and vendors — this 8-part blog series will explore what is driving the convergence of observability and security, the challenges and advantages, and how it may transform the IT landscape.

Start with: Exploring the Convergence of Observability and Security - Part 1

Start with: Exploring the Convergence of Observability and Security - Part 2: Logs, Metrics and Traces

Start with: Exploring the Convergence of Observability and Security - Part 3: Tools

In Part 3 of this blog series, most experts concurred that observability and security tools should be combined, or at least integrated. Interestingly, some experts say that — although convergence is happening, and sharing the data has great value — the security dashboards should not necessarily be combined with observability dashboards for ITOps, NetOps or DevOps.

"I think security and ops will need different dashboards — security staff and operations staff are asking different questions about similar data," Mike Loukides, VP of Emerging Tech Content at O'Reilly Media predicts.

"Are there intruders on the site?" isn't the same as "Is the load too high on server 7 in the Amsterdam colo?" At a minimum, they will remain distinct specialties, with their own tools and dashboards, Loukides says.

Roger Floren, Principal Product Manager at Red Hat suggests that there may be challenges with combining security and observability dashboards. "Using a single platform will ensure the data to be consistent and up-to-date. This will lead to more actionable insights for security and observability. On the other hand the integration challenges to bring this together can be complex and time consuming, leading to compatibility issues and vendor lock-in. You would also risk some feature trade-offs."

Ajit Sancheti, GM, Falcon LogScale at CrowdStrike explains that DevOps, ITOps and SecOps teams will likely want their own dashboards and views of data. Each team will care about different priorities, such as threats, resource utilization or VM health monitoring, and their individual dashboards will reflect their areas of interest.

Dashboards Converging Over Time

Over time, we will see combined dashboards for security, ITOps, NetOps and DevOps, according to other experts.

"As NetOps, SecOps, and DevOps come together, having tools that can integrate both log data and network-derived intelligence into a single interface or dashboard will provide the deep observability they require to enhance business agility, ensure cloud security, and contain hybrid cloud cost and complexity," says Chaim Mazal, Chief Security Officer at Gigamon.

Colin Fallwell, Field CTO of Sumo Logic agrees, "I do see more convergence happening here. DevOps and SRE teams are interested in overlaying security data, intel threat feeds and such, and security teams are seeing the value in operational metrics and top-level application health."

Ideally, merging security and observability should include the dashboards, given they provide a clear visual of application health and availability, and provide flexibility to enable security information from the application to also be integrated to broader reaching SEIM tools as well, Gregg Ostrowski, CTO Adviser at Cisco AppDynamics concludes. "To take full advantage of application monitoring with observability and security insights, customizable dashboards are a great way to extend visibility and support cross-team collaboration, showcasing all the performance data in one place."

Different Organizations Have Different Needs

Prashant Prahlad, VP of Cloud Security Products at Datadog believes the level of dashboard convergence depends on the organization. "Dashboards may converge, but it depends on the size and maturity levels of the teams involved. At startups and smaller organizations where there is no centralized security function, you will likely see the same dashboards used for security and operations. But as organizations mature and security becomes a central function, dashboards may separate."

"In even more advanced organizations, however, the reverse may start happening where centralized security dashboards exist but security starts becoming part of the operations dashboards to provide more context to DevOps or SecOps teams for remediation efforts."

Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at Enterprise Management Associates (EMA) says, "Some dashboards will be converged, usually the ones used for tier 1 response and event management. But tier 2 and tier 3 support will involve specialists with siloed dashboards and specialized tools."

McGillicuddy suggests that convergence of tools will depend on the individual organization. "Users/owners of security tools and users/owners of observability tools have very different skillsets, processes, and cultures. These differences will present barriers to converging on shared tools. However, some organizations will welcome this, especially smaller ones that have fewer silos and more IT generalists than specialists. NetOps teams have told me that they want more security insights in their network observability solutions, but not necessarily because they're sharing those tools with the cybersecurity team. They simply want more context."

Use the player or download the MP3 below to listen to EMA-APMdigest Podcast Episode 2 — Shamus McGillicuddy talks about Network Observability, the convergence of observability and security, and more.

Click here for a direct MP3 download of Episode 2 - Part 1

Similarly, Asaf Yigal, CTO of Logz.io feels that different teams, or even unique use cases, will probably always demand unique dashboards for specific workflows that drive a related response, such as monitoring app performance, threat detection, and prioritization of alerts. Even within a shared observability and security platform, there will be unique UIs for monitoring uptime of applications services versus monitoring and alerting of threats, such as with a SIEM.

Yet, driven by the convergence of data as well as security and performance issues, the overlap of something like a threat that causes an outage somewhere in the apps or infrastructure clearly illustrates increasing value in some shared dashboards, such as top-level overviews or home pages where there is some percolating up of all of this data.

"For the immediate future, we think that there is a need for dashboarding to support every variant of this work," Yigal says. "This is where customization also plays a key role to support the unique makeup of every team and organization. In the long term, there will be more and more crossover."

"Dashboards have not yet converged, however, when they begin to, they should be more elastic to the needs of the business and not determined by third parties," Jam Leomi, Lead Security Engineer at Honeycomb advises. "Each business should determine what its specific needs are to create custom and flexible dashboards for effective observability. To emphasize, observability is all about the efficiency of the business doing it and should be specific to engineering and business priorities."

Go to: Exploring the Convergence of Observability and Security - Part 5: Teams

Pete Goldin is Editor and Publisher of APMdigest

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 ...

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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 ...

Exploring the Convergence of Observability and Security - Part 4: Dashboards

Pete Goldin
APMdigest

With input from industry experts — both analysts and vendors — this 8-part blog series will explore what is driving the convergence of observability and security, the challenges and advantages, and how it may transform the IT landscape.

Start with: Exploring the Convergence of Observability and Security - Part 1

Start with: Exploring the Convergence of Observability and Security - Part 2: Logs, Metrics and Traces

Start with: Exploring the Convergence of Observability and Security - Part 3: Tools

In Part 3 of this blog series, most experts concurred that observability and security tools should be combined, or at least integrated. Interestingly, some experts say that — although convergence is happening, and sharing the data has great value — the security dashboards should not necessarily be combined with observability dashboards for ITOps, NetOps or DevOps.

"I think security and ops will need different dashboards — security staff and operations staff are asking different questions about similar data," Mike Loukides, VP of Emerging Tech Content at O'Reilly Media predicts.

"Are there intruders on the site?" isn't the same as "Is the load too high on server 7 in the Amsterdam colo?" At a minimum, they will remain distinct specialties, with their own tools and dashboards, Loukides says.

Roger Floren, Principal Product Manager at Red Hat suggests that there may be challenges with combining security and observability dashboards. "Using a single platform will ensure the data to be consistent and up-to-date. This will lead to more actionable insights for security and observability. On the other hand the integration challenges to bring this together can be complex and time consuming, leading to compatibility issues and vendor lock-in. You would also risk some feature trade-offs."

Ajit Sancheti, GM, Falcon LogScale at CrowdStrike explains that DevOps, ITOps and SecOps teams will likely want their own dashboards and views of data. Each team will care about different priorities, such as threats, resource utilization or VM health monitoring, and their individual dashboards will reflect their areas of interest.

Dashboards Converging Over Time

Over time, we will see combined dashboards for security, ITOps, NetOps and DevOps, according to other experts.

"As NetOps, SecOps, and DevOps come together, having tools that can integrate both log data and network-derived intelligence into a single interface or dashboard will provide the deep observability they require to enhance business agility, ensure cloud security, and contain hybrid cloud cost and complexity," says Chaim Mazal, Chief Security Officer at Gigamon.

Colin Fallwell, Field CTO of Sumo Logic agrees, "I do see more convergence happening here. DevOps and SRE teams are interested in overlaying security data, intel threat feeds and such, and security teams are seeing the value in operational metrics and top-level application health."

Ideally, merging security and observability should include the dashboards, given they provide a clear visual of application health and availability, and provide flexibility to enable security information from the application to also be integrated to broader reaching SEIM tools as well, Gregg Ostrowski, CTO Adviser at Cisco AppDynamics concludes. "To take full advantage of application monitoring with observability and security insights, customizable dashboards are a great way to extend visibility and support cross-team collaboration, showcasing all the performance data in one place."

Different Organizations Have Different Needs

Prashant Prahlad, VP of Cloud Security Products at Datadog believes the level of dashboard convergence depends on the organization. "Dashboards may converge, but it depends on the size and maturity levels of the teams involved. At startups and smaller organizations where there is no centralized security function, you will likely see the same dashboards used for security and operations. But as organizations mature and security becomes a central function, dashboards may separate."

"In even more advanced organizations, however, the reverse may start happening where centralized security dashboards exist but security starts becoming part of the operations dashboards to provide more context to DevOps or SecOps teams for remediation efforts."

Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at Enterprise Management Associates (EMA) says, "Some dashboards will be converged, usually the ones used for tier 1 response and event management. But tier 2 and tier 3 support will involve specialists with siloed dashboards and specialized tools."

McGillicuddy suggests that convergence of tools will depend on the individual organization. "Users/owners of security tools and users/owners of observability tools have very different skillsets, processes, and cultures. These differences will present barriers to converging on shared tools. However, some organizations will welcome this, especially smaller ones that have fewer silos and more IT generalists than specialists. NetOps teams have told me that they want more security insights in their network observability solutions, but not necessarily because they're sharing those tools with the cybersecurity team. They simply want more context."

Use the player or download the MP3 below to listen to EMA-APMdigest Podcast Episode 2 — Shamus McGillicuddy talks about Network Observability, the convergence of observability and security, and more.

Click here for a direct MP3 download of Episode 2 - Part 1

Similarly, Asaf Yigal, CTO of Logz.io feels that different teams, or even unique use cases, will probably always demand unique dashboards for specific workflows that drive a related response, such as monitoring app performance, threat detection, and prioritization of alerts. Even within a shared observability and security platform, there will be unique UIs for monitoring uptime of applications services versus monitoring and alerting of threats, such as with a SIEM.

Yet, driven by the convergence of data as well as security and performance issues, the overlap of something like a threat that causes an outage somewhere in the apps or infrastructure clearly illustrates increasing value in some shared dashboards, such as top-level overviews or home pages where there is some percolating up of all of this data.

"For the immediate future, we think that there is a need for dashboarding to support every variant of this work," Yigal says. "This is where customization also plays a key role to support the unique makeup of every team and organization. In the long term, there will be more and more crossover."

"Dashboards have not yet converged, however, when they begin to, they should be more elastic to the needs of the business and not determined by third parties," Jam Leomi, Lead Security Engineer at Honeycomb advises. "Each business should determine what its specific needs are to create custom and flexible dashboards for effective observability. To emphasize, observability is all about the efficiency of the business doing it and should be specific to engineering and business priorities."

Go to: Exploring the Convergence of Observability and Security - Part 5: Teams

Pete Goldin is Editor and Publisher of APMdigest

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 ...