Application Monitoring Tools: What They Do, What to Track and How to Pick One

Every B2B SaaS product depends on a chain of services: a front end, APIs, databases, queues, identity providers and third-party integrations. Application monitoring watches that chain end to end, so one failing link shows up as a clear signal instead of a vague customer complaint. A popular open-source standard in this space is OpenTelemetry.

This guide explains the core concepts, the metrics worth tracking and how to shortlist a platform, with links to the products published on SaaSPodium.

Application Monitoring vs Network and Infrastructure Monitoring

Network and infrastructure monitoring show whether systems are reachable and have capacity, while application monitoring shows whether the software behaves correctly for users. An app can sit on healthy servers and a clean network and still return errors or slow responses.

That gap is why mature teams run all three and correlate them. When a ticket says "the app is slow," you need to rule out the network, the host and the code in minutes, not hours.

How Application Monitoring Works

Application monitoring collects telemetry from running software through agents, instrumentation libraries, log shipping or agentless polling, then stores it for dashboards, alerting and analysis. Modern tools combine metrics, traces and logs, increasingly through the OpenTelemetry standard.

• Agent-based: a small process or library inside the application or host reports deep data such as code-level timings.
• Agentless: the tool polls services using protocols and APIs, which is lighter to deploy but shallower.
• Tracing: follows one request across services so you can see which call added the delay.
• Logs and events: capture errors and business events that numbers alone do not explain.

What to Monitor in Every Application

Track the four golden signals: latency, traffic, errors and saturation. They cover how fast requests complete, how many arrive, how many fail and how close resources are to their limits. Add business metrics, such as sign-ups or orders, so alerts reflect real impact.

A simple formula many teams use to set reliability targets is the error budget:

SLO is the service level objective you commit to. When the budget is spent, teams pause risky releases and focus on stability, which turns monitoring data into a decision rule.

Synthetic Monitoring, Real User Monitoring and Code-Level Monitoring

Synthetic monitoring runs scripted tests on a schedule, real user monitoring records actual visits, and code-level monitoring profiles functions inside the application. Together they catch outages before customers do, show true experience, and pinpoint the slow method.

• Synthetic: best for uptime and key journeys, such as login and checkout, from several regions.
• RUM: best for understanding browser, device and geography differences in speed.
• Code-level: best for finding the database call or loop behind a slow endpoint.

Which Application Monitoring Platforms to Evaluate

SaaSPodium lists nine platforms in its application performance management category. Start your shortlist from three profiles: full-stack enterprise suites, free-tier-friendly platforms for smaller teams, and tools that fit an existing logging stack.

• Enterprise suites: Dynatrace, Cisco AppDynamics and IBM Instana emphasize automatic discovery and business-level views.
• Cloud-native SaaS: Datadog APM and Splunk Observability combine metrics, traces and logs, with Splunk highlighting no-sample tracing.
• Entry points: New Relic, Elastic APM and Honeycomb offer freemium plans.
• IT operations suite: ManageEngine Applications Manager monitors applications, middleware and servers in one on-premises console.

How to Choose and Roll Out Application Monitoring

Pick a tool by testing three things in a trial: how fast it discovers your services, whether traces connect across them, and how pricing scales with hosts and data. Then roll out in stages, starting with the most business-critical application.

1. List your critical applications and the user journeys that matter.
2. Define SLOs for each journey, starting with availability and latency.
3. Install agents on a staging copy first, then production.
4. Create a short set of alerts tied to user impact and route them to on-call tools.
5. Review alerts monthly and remove those nobody acts on.

Align the program with the continuous monitoring approach in NIST SP 800-137 and the logging and monitoring failures described in the OWASP Top Ten. For deeper dives, read our guides to database monitoring tools, IIS monitoring tools and AIOps platforms, or browse the full APM category.

Frequently Asked Questions

How much does application monitoring software cost?
Pricing ranges from free tiers to enterprise contracts. New Relic, Elastic APM and Honeycomb offer freemium plans, while Datadog APM, Dynatrace, Instana, AppDynamics and Splunk are paid. SaaSPodium lists starting prices of $31 for Datadog APM and $75 for Instana, so confirm current rates with vendors.

How long does it take to implement application monitoring?
Installing agents takes hours for a single service. A meaningful rollout, including tracing across services, dashboards and tuned alerts, usually takes two to six weeks depending on the number of applications, how consistent your deployment pipelines are and how much instrumentation each team must add.

Do I need both APM and infrastructure monitoring?
Most production teams do. Infrastructure monitoring shows capacity and host health, while APM shows request behavior, errors and code-level delays. Many platforms in this category include both, which lets you move from a slow endpoint to the overloaded host or container behind it in one view.