On-prem application performance monitoring is still relevant, here’s why

Application users want seamless digital experiences — and they want them now. This common thread has organizations grappling with how to meet user expectations in increasingly complex application environments. Despite the cost and scalability benefits of cloud native applications, research shows more than half of organizations (54%) are moving workloads and data away from public clouds. Why? Reasons are unique, but many agree that the cloud can’t compete with an in-house solution when it comes to keeping data private, secure and compliant.

With a recent survey showing 94% of organizations still using on-prem servers in some way, it’s easy to see that hosting applications onsite remains relevant for delivering the high-performing digital experiences users want while sustaining a focus on security. While many organizations prefer the ease and efficiency of cloud-based applications — delivering optimal performance doesn’t require public cloud infrastructure. With the right application performance monitoring solution, technologists can optimize fluctuating workloads and support the dynamic scale-out/back strategy they need — regardless of infrastructure type.

Optimizing on-premises applications

For many organizations, the most difficult part of on-prem optimization is maintaining a clear picture of user behavior during peak demand and keeping up with the planning and support required to meet such demand. However, the ability to do so is critical in today’s digital environment, where user experience and user trust are key drivers of application KPIs. Planning, supporting and managing demand requires technology and business leaders to stay apprised of the data center inventory, resource usage and peak times to ensure quick responses to rapid fluctuation. Common techniques include load balancing, managing bandwidth, compression, caching and deduplication — plus monitoring network and storage performance and utilization. Doing so enables teams to adjust settings and allocate accordingly to distribute workloads, reduce latency, save space and optimize availability.

Support an Agile and DevOps Culture

Collaboration is at the root of Agile and DevOps methodologies, and both can help optimize in-house application environments by enabling proactive, faster, more frequent and more collaborative development, iterations and delivery. Therefore, adopting a common tooling framework includes support for version control and CI/CD, plus continuous testing, monitoring and improvement that helps align digital experiences with business goals.

Leverage the right application monitoring tool for on-premises environments

Application performance monitoring (APM) is a methodology that allows technologists to see application health status in a shared view and detect the source of issues. It that way, it can eliminate roadblocks between siloed teams and support fast and proactive remediation of user experience problems. Leveraging APM best practices in a shared view can also ensure a strong portfolio, which is key to preventing risk associated with outdated technology, poor documentation and/or lack of ownership that may plague legacy, on-prem environments. And not to be overlooked — cultivating an APM practice provides a platform from which IT and business stakeholders can quickly and easily understand exactly how app performance impacts revenue-generating transactions.

User journeys: Monitoring on-premises user journeys with business context

When a business-critical transaction, such as shopping cart checkout or loan application submission suffers, IT and business leaders need to prioritize and fix issues — fast. Having an always-on, proactive view of application health across on-prem hosted user transactions is key. With journey mapping, an organization can measure how business components and customer experience come together to drive top-level KPIs. For example, optimizing new bank account setup or loan submission processes or online retailers getting a complete view of how customers shop online. With it, technologists and business stakeholders can see issues across all the different parts of user journeys that impact application health and business outcomes.

Business journeys: Monitoring on-premises performance across multiple events

Business Journey Mapping gives modern businesses insights to improve the building and running of mission-critical and strategic services. It works with application performance monitoring and enables app teams to author, join, analyze and monitor multiple distributed business events as a single process. With it, teams can identify patterns and discover performance latency, risk and opportunity for an entire line of business.

Let’s take the loan application workflow as an example. Application submission information may come from business transaction events, but document verification and loan application status might come from logs. And credit approval and underwriting are often tied to third-party service provider actions while final approval could be updated in transaction events. Mapping the entire journey to ensure a smooth transaction for the borrower and the loan officer supports a high-performing user experience for both — and enables IT to validate investments and prioritize coding fixes and feature releases based on what matters most.

For more information about how Cisco AppDynamics can help your organization optimize on-premises application performance, read what Ronak Desai, Cisco SVP & GM AppDynamics and full-stack observability has to say about On-premises to cloud: Observability for customers where they are and where they’re going.

Related Articles

Coding Conundrums and the Rabbit Invasion: How to Avoid Disaster in Your Production Environment
Observability
4 Minute Read

Coding Conundrums and the Rabbit Invasion: How to Avoid Disaster in Your Production Environment

Splunker Gabriela Parker explains how Splunk Observability Cloud makes the process of testing and review of new code easy for developers.
How Splunk Observability Cloud Helps To Alleviate Developer Burnout
Observability
1 Minute Read

How Splunk Observability Cloud Helps To Alleviate Developer Burnout

Splunk Observability Cloud has built-in capabilities to help improve developer experience and productivity.
How to Simplify Your Incident Response Workflow with Splunk On-Call
Observability
5 Minute Read

How to Simplify Your Incident Response Workflow with Splunk On-Call

Splunker Jennifer Elkhouri explains how Splunk On-Call relieves on-call stress: clear alerting practices and defined workflows mitigate developer team burdens.
Data Storage Costs Keeping You Up at Night? Meet Archived Metrics
Observability
3 Minute Read

Data Storage Costs Keeping You Up at Night? Meet Archived Metrics

Splunkers Joanna Zouhour and Navtej Singh introduce Splunk's Archived Metrics, storing data affordably, enhancing accessibility, and reducing costs in Metrics Pipeline Management.
Begin Your Trip to Observability by Packing Your Baggage With Context
Observability
6 Minute Read

Begin Your Trip to Observability by Packing Your Baggage With Context

OpenTelemetry context with baggage can help you quickly find value, errors and maybe your luggage.
Why Lingusitic and non-Linguistic AI are Complementary
Observability
9 Minute Read

Why Lingusitic and non-Linguistic AI are Complementary

Splunk’s observability strategy has always put AI functionality at the centre. We have always recognised that, in order to make actionable sense of full fidelity data metric, event, log, and trace data streams, human cognition requires an automated assist which is precisely what AI brings to the table. As a result, throughout our observability portfolio, customers will find a variety of machine learning and pattern discovery algorithms being put to work, separating signals from noise, surfacing patterns of correlation, diagnosing root causes, and enabling remedial responses to incidents. AI, itself, is, of course, evolving at a rapid clip and with AI Assist, Splunk adds Generative or linguistic AI functionality to the mix. But what is linguistic AI and how does it relate to the non-linguistic or Foundational AI that Splunk has deployed in its products to date?
Don’t Live in the Past - APM 3.0 and Why You Need It
Observability
11 Minute Read

Don’t Live in the Past - APM 3.0 and Why You Need It

Application Performance Monitoring (APM) as a discipline and as a collection of supporting technologies has evolved rapidly since a distinct recognisable market for APM products first emerged in the 2007 - 2008 time frame. While there are many who would argue that APM has mutated into or been replaced by Observability, it makes more sense to see APM as one of many possible use cases now able to exploit the functionalities that Observability brings to the table - particularly when combined with AI.
Unlock the Power of Observability with OpenTelemetry Logs Data Model
Observability
3 Minute Read

Unlock the Power of Observability with OpenTelemetry Logs Data Model

If you're building a new application or enhancing an existing one, consider adopting the OpenTelemetry Logs Data Model's Log and Event Record Definition.
Generate Dashboards for OpenTelemetry Receivers in Splunk Observability
Observability
2 Minute Read

Generate Dashboards for OpenTelemetry Receivers in Splunk Observability

Need a dashboard for that new OpenTelemetry receiver you’re using? Generate a Terraform configuration in Splunk Observability.