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Fault Domain Isolation Key to Avoiding Network Blame Game - Part 2

Jeff Brown

Start with Part 1 of this Blog

What’s the Hold Up?

It always reduces costs and decreases time-to-resolution when root cause analysis is being done in earnest, with confidence (and perhaps a bit of guilt) that the problem simply cannot lay elsewhere. RCA works best when the people working on the problem have the expertise to properly evaluate the cause and resolve the problem.

In Part 1 of this Blog, I explained how a packet-driven FDI process is an effective way to accelerate incident investigations and reduce the number of people involved. Further, to achieve its primary goal of getting only the right people involved in the incident investigation, we know it doesn’t take a lot of taps and equipment to isolate the major technology tiers. So why do team-of-expert meetings still persist in so many major incident investigations?

The problem might be that some simply do not believe that complex incidents can be fully resolved with just a few taps and some network recorders. And you know what, they’re right! But that isn’t the goal of the FDI stage of the incident investigation process. The goal is fault isolation, and that can be done simply and reliably. All you need is the underlying packets and a process to analyze them.

Divide and Conquer

The primary or first-layer FDI process isolates the incident to a single technology tier as defined by the organization’s internal structure and outsourcing arrangement.

Primary FDI is best achieved by:

1. Using network recording tools to monitor and store the network traffic occurring between technology tiers

2. Applying application transaction analysis to perform fault isolation.

Packet storage (rather than just averages or summaries) is key to enabling the back-in-time analysis upon which efficient FDI depends.

As you’ve probably guessed, FDI is a divide and conquer process that can be deployed in layers. FDI can also be used within each tier to further isolate the problem until highly efficient RCA can be done. This can be called intra-tier FDI, or perhaps secondary FDI.

Not surprisingly, network incident investigations are particularly amenable to a secondary FDI workflow, and once again, this is best achieved by monitoring and storing the actual packet flows between key network components for efficient back-in-time analysis.

It is valid to ask where the network tap points and network recording tools should be deployed when intra-network FDI is the goal. The main difference between primary FDI and intra-network FDI is that the location of the observation points is less an organizational issue, and more about physical location, technology, staff expertise, and of course, level of outsourcing and external suppliers. But the FDI process is similar: use packet-based analysis to provide irrefutable evidence as to which technology or service provider is at fault, and which are not.

Always-On or Always-Available?

You do not want to wait for a major incident to occur before you start deploying the tap points and monitoring tools needed for performing FDI -- that would defeat its purpose. So it seems pretty clear that the tap points and network recording tools needed for primary or first-level FDI should be deployed and running all the time. Those are your always-on appliances.

But what about secondary or intra-technology FDI? What about remote sites, regional data centers, and non-critical applications? You can’t tap everywhere, nor can you store everything.

Fortunately many network recording tools have been built to satisfy the needs of the always-on recording required between primary technology tiers, and the “always-available” recording connected via Network Packet Brokers to a plethora of secondary tap points. Always-available appliances do not necessarily give you long-term back-in-time visibility, but they can be quickly configured to begin monitoring where needed, on demand, tuned to the specific visibility needs of the incident investigation underway.

How Simple Is It?

So, is FDI truly as simple as we’ve described? Well, yes and no. Obviously there are plenty of unusual, complex, and just plain bizarre problems that can appear in a system as complex and dynamic as a modern organization’s networked business application infrastructure. And these types of problems will always require deep investigation, and the skills and knowledge of specialists and experts to resolve. But that doesn’t render FDI irrelevant or ineffective for these complex issues. Indeed it makes the need for a rigorous, repeatable, data-driven FDI process all the more important. Put another way, for complex problems why wouldn’t you use a proven divide and conquer approach like FDI?

Jeff Brown is Global Director of Training, NVP at Emulex.

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Fault Domain Isolation Key to Avoiding Network Blame Game - Part 2

Jeff Brown

Start with Part 1 of this Blog

What’s the Hold Up?

It always reduces costs and decreases time-to-resolution when root cause analysis is being done in earnest, with confidence (and perhaps a bit of guilt) that the problem simply cannot lay elsewhere. RCA works best when the people working on the problem have the expertise to properly evaluate the cause and resolve the problem.

In Part 1 of this Blog, I explained how a packet-driven FDI process is an effective way to accelerate incident investigations and reduce the number of people involved. Further, to achieve its primary goal of getting only the right people involved in the incident investigation, we know it doesn’t take a lot of taps and equipment to isolate the major technology tiers. So why do team-of-expert meetings still persist in so many major incident investigations?

The problem might be that some simply do not believe that complex incidents can be fully resolved with just a few taps and some network recorders. And you know what, they’re right! But that isn’t the goal of the FDI stage of the incident investigation process. The goal is fault isolation, and that can be done simply and reliably. All you need is the underlying packets and a process to analyze them.

Divide and Conquer

The primary or first-layer FDI process isolates the incident to a single technology tier as defined by the organization’s internal structure and outsourcing arrangement.

Primary FDI is best achieved by:

1. Using network recording tools to monitor and store the network traffic occurring between technology tiers

2. Applying application transaction analysis to perform fault isolation.

Packet storage (rather than just averages or summaries) is key to enabling the back-in-time analysis upon which efficient FDI depends.

As you’ve probably guessed, FDI is a divide and conquer process that can be deployed in layers. FDI can also be used within each tier to further isolate the problem until highly efficient RCA can be done. This can be called intra-tier FDI, or perhaps secondary FDI.

Not surprisingly, network incident investigations are particularly amenable to a secondary FDI workflow, and once again, this is best achieved by monitoring and storing the actual packet flows between key network components for efficient back-in-time analysis.

It is valid to ask where the network tap points and network recording tools should be deployed when intra-network FDI is the goal. The main difference between primary FDI and intra-network FDI is that the location of the observation points is less an organizational issue, and more about physical location, technology, staff expertise, and of course, level of outsourcing and external suppliers. But the FDI process is similar: use packet-based analysis to provide irrefutable evidence as to which technology or service provider is at fault, and which are not.

Always-On or Always-Available?

You do not want to wait for a major incident to occur before you start deploying the tap points and monitoring tools needed for performing FDI -- that would defeat its purpose. So it seems pretty clear that the tap points and network recording tools needed for primary or first-level FDI should be deployed and running all the time. Those are your always-on appliances.

But what about secondary or intra-technology FDI? What about remote sites, regional data centers, and non-critical applications? You can’t tap everywhere, nor can you store everything.

Fortunately many network recording tools have been built to satisfy the needs of the always-on recording required between primary technology tiers, and the “always-available” recording connected via Network Packet Brokers to a plethora of secondary tap points. Always-available appliances do not necessarily give you long-term back-in-time visibility, but they can be quickly configured to begin monitoring where needed, on demand, tuned to the specific visibility needs of the incident investigation underway.

How Simple Is It?

So, is FDI truly as simple as we’ve described? Well, yes and no. Obviously there are plenty of unusual, complex, and just plain bizarre problems that can appear in a system as complex and dynamic as a modern organization’s networked business application infrastructure. And these types of problems will always require deep investigation, and the skills and knowledge of specialists and experts to resolve. But that doesn’t render FDI irrelevant or ineffective for these complex issues. Indeed it makes the need for a rigorous, repeatable, data-driven FDI process all the more important. Put another way, for complex problems why wouldn’t you use a proven divide and conquer approach like FDI?

Jeff Brown is Global Director of Training, NVP at Emulex.

Hot Topics

The Latest

AI is becoming the operating system of the enterprise. It acts as an invisible coordination layer that understands intent, connects systems, and executes work across complex SaaS environments. Previously, employees had to click through multiple systems — CRM, ERP, support tools, collaboration platforms — to complete a single task. Now, instead of navigating each application manually, they can simply state what they need to accomplish ...

In 2026, the cost of downtime or an outage is no longer just a technical inconvenience; it's a $600 billion wake up call for global businesses. As our digital ecosystems become  more interconnected, each touchpoint introduces new risks and multiplies the consequences when things go wrong. And the data is clear: aggregate downtime costs  for Global 2,000 companies have surged 50% since 2024, reaching a staggering $600 billion ...

Deloitte found that 74% of enterprises expect to deploy agentic AI solutions in the next 24 months. However, the rush to deployment is outpacing foundational work, though. Only 21% of enterprises have fully formed agent governance models in place. The result? AI agents deployed without guidance or governance begin to function as fragmented islands of complexity ...

Cloud spending is no longer viewed as a passthrough IT expense, but as a strategic financial lever that directly impacts innovation capacity, profitability and enterprise resilience, according to the CFO Cloud Cost Optimization Report from Azul ...

As AI moves from generating responses to performing actions, the need for trust increases exponentially. And as organizations enlist AI agents for increasingly sophisticated business processes, trust is going to be the single most important theme for spurring adoption. What can organizations do to build trustworthy AI agents? ...

I've spent a lot of time in the channel, and one thing I keep coming back to is this: a partner program is only as good as what it looks like in the field. Many programs look great on paper, but when a partner is in front of a customer navigating a complex hybrid environment or trying to make the case for AI-powered observability, the gap between what a vendor promises and what it actually delivers becomes very clear, very fast ...

Enterprises today operate in a real-time environment where uninterrupted access to trusted data has become a baseline expectation for users, applications and automated systems. Traditional DataOps models, built on manual effort and human triage, cannot keep pace with this always active demand. AI agents are emerging as the operational backbone, ensuring consistent data availability, reinforcing trustworthiness and enabling a level of scale that manual processes cannot achieve ...

For decades, trust in the digital workplace rested on familiar signals. We trusted faces on video calls, voices on the phone, and emails that appeared to come from people we knew. These cues felt human and intuitive. They anchored how decisions were made, approvals were granted, and access was authorized. AI-powered deepfakes have quietly broken that model ...

Cloud migration was supposed to be a one-way door. For most enterprises, it turns out it isn't. Cloud data repatriation is a real and growing trend. A new survey ... finds that 89% of organizations plan to expand their on-premises infrastructure footprint over the next two years — and 75% have already moved at least some workloads back from public cloud in the past 24 months. The findings point to a broad rethinking of where data belongs ...

Over the past few years, large language models (LLMs) have revolutionized the software industry. Given their ability to excel at multi-step reasoning, LLMs have helped enterprises streamline workflows and adapt to the unknown. However, employing such models comes with sky-high costs, latency issues, and limited flexibility. In the realm of IT operations, it is generally wiser to employ smaller, domain-specific models instead ...