APM BOTTOM-LINE BENEFIT: Increased Revenue

Sridhar Iyengar
Learn more about ManageEngine

Today's Business is heavily dependent on IT systems to perform at the best.

For example, an IT component failing in an eCommerce business could result in a shopping cart order failure that in turn results in loss of revenue for that business. If IT is able to proactively detect performance degradation and rectify it before it severely impacts the business, that could not only save loss of revenue and also credibility for the business with its customers.

On the other hand, if IT can ensure the highest level of service, that could result in higher levels of satisfaction for the customer who execute transactions on the IT system and eventually profitability for the business.

The question arises: "How can the business ensure that the applications perform at the optimal level?" This can be done by using 2 key concepts: Application Performance Monitoring (APM) and Service Level Management (SLM).

Application Performance Monitoring deals with the capability to proactively monitor IT application components that determine quality of application services.

SLM deals with the ability to monitor Service Level Agreements (based on KPI such as availability, health) and ensure that the IT team delivers the application service at the quality that has been agreed upon. This allows the business to measure IT service delivery and ensure optimal levels of services that is required to sustain the business.

It is imperative for IT to understand the relationship between business services and the underlying IT components/applications so that the impact of a IT failure/degradation on the business service can be well understood.

Additionally, there has to be SLAs associated with the Business Service. The higher the business service impact, typically higher should be the SLA (and the priority). That will be the expected quality of service from IT. If the business service impacts are not understood, then IT will be unable to deliver IT Services within agreed upon SLA times.

The business service impact for any IT incident helps establish KPIs (such as resolution priority, MTTR, SLA levels, etc.).

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APM BOTTOM-LINE BENEFIT: Increased Revenue

Sridhar Iyengar
Learn more about ManageEngine

Today's Business is heavily dependent on IT systems to perform at the best.

For example, an IT component failing in an eCommerce business could result in a shopping cart order failure that in turn results in loss of revenue for that business. If IT is able to proactively detect performance degradation and rectify it before it severely impacts the business, that could not only save loss of revenue and also credibility for the business with its customers.

On the other hand, if IT can ensure the highest level of service, that could result in higher levels of satisfaction for the customer who execute transactions on the IT system and eventually profitability for the business.

The question arises: "How can the business ensure that the applications perform at the optimal level?" This can be done by using 2 key concepts: Application Performance Monitoring (APM) and Service Level Management (SLM).

Application Performance Monitoring deals with the capability to proactively monitor IT application components that determine quality of application services.

SLM deals with the ability to monitor Service Level Agreements (based on KPI such as availability, health) and ensure that the IT team delivers the application service at the quality that has been agreed upon. This allows the business to measure IT service delivery and ensure optimal levels of services that is required to sustain the business.

It is imperative for IT to understand the relationship between business services and the underlying IT components/applications so that the impact of a IT failure/degradation on the business service can be well understood.

Additionally, there has to be SLAs associated with the Business Service. The higher the business service impact, typically higher should be the SLA (and the priority). That will be the expected quality of service from IT. If the business service impacts are not understood, then IT will be unable to deliver IT Services within agreed upon SLA times.

The business service impact for any IT incident helps establish KPIs (such as resolution priority, MTTR, SLA levels, etc.).

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Exploring AI Observability – Part 4: Challenges

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 ...

Exploring AI Observability – Part 3: The Current State of AI Observability

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 ...

Exploring AI Observability – Part 2: Traditional vs. AI Observability

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 ...

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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 ...

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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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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 ...

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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 ...

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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 ...

Visibility Is Not a Strategy - What Matters Is What Happens Next

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 ...

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Government agencies are largely misjudging their level of AI governance as the technology permeates their organization, according to Racing to Deploy: How Public Sector AI Adoption is Moving Faster Than the Foundations Needed to Support It, a new report from SolarWinds ...