With every minute you can shave off root cause analysis, you get a minute closer to restoring the performance or availability of a process that's important to your business. But the plethora of monitoring tools used throughout your organization, each with its own root cause perspective about the IT environment, can lead to confusion, dysfunction and drawn-out debate when things go wrong. To get the most business value from these diverse views, you need to understand how they can work together.
Think of root cause analysis as a software stack, and the higher the layer is in the stack, the more meaningful it is from a business perspective. For example, in the Open Systems Interconnect (OSI) stack, understanding layer 1, the physical layer, is vital, but layer 7, the application, is more meaningful to the business.
Each layer in the root cause analysis stack is provided by unique monitoring functions, analytics and visualization. Here they are, top down:
- Business Service Root Cause Analysis
- Application-Driven Root Cause Analysis
- Network Fault Root Cause Analysis
- Device Root Cause Analysis
Think of adding each layer in terms of a geometrical analogy of human awareness cleverly explained by the Russian philosopher P.D. Ouspenski in his book Tertium Organum. As he explained, if you were one-dimensional, a point, you couldn't think of a line. If you were a line, you couldn't perceive two-dimensions: a square. If you were a square you couldn't understand a cube. If you were a cube, couldn't understand motion.
Let's see how each layer has legitimate root cause analysis and how each successive layer up the stack adds awareness and greater business value.
1. Device Root Cause Analysis
The device layer is the foundation, letting you know if a server, storage device or switch, router, load balancer, etc. simply is up or down, fast or slow. If it's pingable, you know it has a power source, and diagnostics can tell you which subcomponent has the fault causing the outage. For root cause of performance issues, you'll be relying on your monitoring tools' visual correlation of time series data and threshold alerts to see if the CPU, memory, disk, ports etc. are degraded and why.
But if servers or network devices aren't reachable, how do you know for sure if they are down or if there's an upstream network root cause? To see this, you need to add a higher layer of monitoring and analytics.
2. Network Fault Root Cause Analysis
The next layer is Network Root Cause Analysis. This is partly based on a mechanism called inductive modeling, which discovers relationships between networked devices by discovering port connections and routing and configuration tables in each device.
When an outage occurs, inference, a related Network Root Cause Analysis mechanism, uses known network relationships to determine which devices are downstream from the one that is down. So instead of drowning in a sea of red alerts for all the unreachable devices, you get one upstream network root cause alert. This can also be applied to virtual servers and their underlying physical hosts, as well as network configuration issues.
3. Application-Driven Root Cause Analysis
Next up is Application-Driven Network Performance Management, which includes two monitoring technologies: network flow analysis and end-to-end application delivery analysis.
The first mechanism lets you see which applications are running on your network segments and how much bandwidth each is using. When users are complaining that an application service is slow, this can let you know when a bandwidth-monopolizing application is the root cause. Visualization includes stacked protocol charts, top hosts, top talkers, etc.
The second mechanism in this layer shows you end-to-end application response timing: network round trip, retransmission, data transfer and server response. Together in a stacked graph, this reveals if the network, the server or the application itself is impacting response. To see the detailed root cause in the offending domain, you drill down into a lower layer (e.g., into a network flow analysis, device monitoring or an application forensic tool).
4. Business Service Root Cause Analysis
The best practice is to unify the three layers into a single infrastructure management dashboard, so you can visually correlate all three levels of analytics in an efficient workflow. This is ideal for technical Level 2 Operations specialists and administrators.
But there's one more level at the top of the stack: Business Service Root Cause Analysis. This gives IT Operations Level 1 staff the greatest insight into how infrastructure is impacting business processes.
Examples of business processes include: Concept To Product, Product To Launch, Opportunity To Order, Order To Cash, Request To Service, Design To Build, Manufacturing To Distribution, Build To Order, Build To Stock, Requisition To Payables and so on.
At this layer of the stack, you monitor application and infrastructure components in groups that support each business process. This allows you to monitor each business process as you would an IT infrastructure service, and a mechanism called service impact analysis rates the relative impact each component has on the service performance. From there you can drill down into a lower layer in the stack to see the technical root cause details of the service impact (network outage, not enough bandwidth, server memory degradation, packet loss, not enough host resources for a virtual server, application logic error, etc.).
Once you have a clear understanding of this architecture, and a way to unify the information into a smooth workflow for triage, you can put the human processes in place to realize its business value.
ABOUT David Hayward
David Hayward is Senior Principal Manager, Solutions Marketing at CA Technologies. Hayward specializes in integrated network, systems and application performance management – and his research, writing and speaking engagements focus on IT operations maturity challenges, best-practices and IT management software return on investment. He began his career in 1979 as an editor at the groundbreaking BYTE computer magazine and has since held senior marketing positions in tier one and startup computer system, networking, data warehousing, VoIP and security solution vendors.
The Latest
Incident management processes are not keeping pace with the demands of modern operations teams, failing to meet the needs of SREs as well as platform and ops teams. Results from the State of DevOps Automation and AI Survey, commissioned by Transposit, point to an incident management paradox. Despite nearly 60% of ITOps and DevOps professionals reporting they have a defined incident management process that's fully documented in one place and over 70% saying they have a level of automation that meets their needs, teams are unable to quickly resolve incidents ...
Today, in the world of enterprise technology, the challenges posed by legacy Virtual Desktop Infrastructure (VDI) systems have long been a source of concern for IT departments. In many instances, this promising solution has become an organizational burden, hindering progress, depleting resources, and taking a psychological and operational toll on employees ...
Within retail organizations across the world, IT teams will be bracing themselves for a hectic holiday season ... While this is an exciting opportunity for retailers to boost sales, it also intensifies severe risk. Any application performance slipup will cause consumers to turn their back on brands, possibly forever. Online shoppers will be completely unforgiving to any retailer who doesn't deliver a seamless digital experience ...
Black Friday is a time when consumers can cash in on some of the biggest deals retailers offer all year long ... Nearly two-thirds of consumers utilize a retailer's web and mobile app for holiday shopping, raising the stakes for competitors to provide the best online experience to retain customer loyalty. Perforce's 2023 Black Friday survey sheds light on consumers' expectations this time of year and how developers can properly prepare their applications for increased online traffic ...
This holiday shopping season, the stakes for online retailers couldn't be higher ... Even an hour or two of downtime for a digital storefront during this critical period can cost millions in lost revenue and has the potential to damage brand credibility. Savvy retailers are increasingly investing in observability to help ensure a seamless, omnichannel customer experience. Just ahead of the holiday season, New Relic released its State of Observability for Retail report, which offers insight and analysis on the adoption and business value of observability for the global retail/consumer industry ...
As organizations struggle to find and retain the talent they need to manage complex cloud implementations, many are leaning toward hybrid cloud as a solution ... While it's true that using the cloud is not a "one size fits all" proposition, it is clear that both large and small companies prefer a hybrid cloud model ...
In the same way a city is a sum of its districts and neighborhoods, complex IT systems are made of many components that continually interact. Observability requires a comprehensive and connected view of all aspects of the system, including even some that don't directly relate to its technological innards ...
Multicasting in this context refers to the process of directing data streams to two or more destinations. This might look like sending the same telemetry data to both an on-premises storage system and a cloud-based observability platform concurrently. The two principal benefits of this strategy are cost savings and service redundancy ...
In today's rapidly evolving business environment, Chief Information Officers (CIOs) and Chief Technology Officers (CTOs) are grappling with the challenge of regaining control over their IT roadmap. The constant evolution and introduction of new technology releases, combined with the pressure to deliver innovation on shrinking budgets, has added layers of complexity for executives who must transform the perception of the role of the IT leader from cost managers and maintainers to strategic enablers of growth and profitability ...
Artificial intelligence (AI) has saturated the conversation around technology as compelling new tools like ChatGPT produce headlines every day. Enterprise leaders have correctly identified the potential of AI — and its many tributary technologies — to generate new efficiencies at scale, particularly in the cloud era. But as we now know, these technologies are rarely plug-and-play, for reasons both technical and human ...