Network Observability and APM: How They Work Together (2026)
Application Performance Monitoring (APM) platforms have become the standard tool for understanding what’s happening inside an application — code execution, database queries, transaction traces, error rates, dependencies between services. But APM tools have historically treated the network as a black box. They can tell you a transaction is slow, but they often can’t tell you whether the slowness comes from the application itself, the cloud provider’s backbone, the internet path between user and service, or a routing change two AS-hops upstream.
This guide explores the relationship between network observability and APM — where each approach excels, what each one misses, and why most modern observability stacks need both. It also covers how leading APM platforms (Datadog, New Relic, Dynatrace, AppDynamics, LogicMonitor) handle network visibility, and where network intelligence platforms like Kentik fill the gaps APM was never designed to address.
Kentik in brief: Kentik is a network intelligence platform that complements APM and full-stack observability tools by providing the deep network-layer visibility they were never designed to deliver. Where APM platforms instrument application code to track services, traces, and dependencies, Kentik unifies flow analytics, BGP routing intelligence, synthetic monitoring, and device telemetry to explain why application performance is what it is from a network perspective. Most teams that run APM also run Kentik — APM for the application layer, Kentik for the network layer that APM can’t see.
Learn how AI-powered insights help you predict issues, optimize performance, reduce costs, and enhance security.
Network Observability and APM at a Glance
- APM tells you what’s happening inside the application. Code execution, database queries, transaction traces, error rates, service dependencies — visibility into the application itself.
- Network observability tells you what’s happening between the application and the user. Flow analytics, BGP routing, internet paths, cloud network performance, device health — visibility into the network the application depends on.
- Each captures what the other can’t. APM can’t see why the path from a SaaS provider’s region to a user’s ISP is degrading. Network observability can’t see why a database query is slow.
- Together, they triangulate root cause. When users complain, APM identifies the affected service; network observability identifies whether the network is contributing; the combination shortens MTTR dramatically.
- Where Kentik fits: Kentik is the network intelligence layer that complements APM platforms — Datadog, New Relic, Dynatrace, AppDynamics, and LogicMonitor among them — for teams that need network-layer visibility their APM tool doesn’t provide.
The relationship between network observability and APM
Modern applications are distributed across data centers, multiple cloud providers, SaaS platforms, CDNs, and the public internet. Their performance depends on layers of infrastructure no single tool fully sees. APM platforms instrument the application itself — capturing what the code is doing and what the application’s own components are reporting. Network observability instruments the network the application runs on — capturing what’s actually happening between services, between regions, and between the application and the people using it.
Both approaches answer real questions, but they answer different ones. When a user reports that an application is slow, APM can tell you which service is responding slowly and which downstream call is taking the most time. What APM typically can’t tell you is whether the underlying network path between two cloud regions is degraded, whether a BGP routing change moved traffic onto a longer path, whether a transit provider is dropping packets, or whether a SaaS dependency’s regional ingress point is overloaded. Those questions require network-layer telemetry — flow data, BGP routing, synthetic measurements, device metrics — that APM tools don’t collect.
This is the gap that network observability fills, and it’s the gap that’s grown most acute as applications have moved off-premises and into environments that the application owner doesn’t operate.
What APM platforms do well — and where they fall short on the network
The leading APM and full-stack observability platforms each have distinct strengths, and each has known limits when it comes to network depth. Understanding those tradeoffs is essential for designing an observability stack that actually answers the questions teams need to ask.
Datadog
Datadog is the most widely adopted full-stack observability platform, particularly among SRE and DevOps teams. Its strengths are application monitoring, infrastructure metrics, log management, and an unusually well-designed user experience that ties them all together. Datadog’s network monitoring products — Cloud Network Monitoring (CNM) and Network Device Monitoring (NDM) — extend the platform with enough network context to support application triage, but they’re not designed for deep network investigation. Teams that need flow-level forensics, BGP routing intelligence, internet path visibility, or cloud egress cost analytics typically run Kentik alongside Datadog. See Datadog alternatives for network teams and Kentik vs Datadog for a deeper comparison.
New Relic
New Relic pioneered cloud APM and remains a strong choice for application engineers, particularly for code-level visibility, distributed tracing, and browser-based RUM. Its network monitoring capabilities are growing but are similarly application-focused — useful for connecting application symptoms to infrastructure context, less suited to the network-engineering questions that arise during outages with internet, BGP, peering, or cloud-network root causes.
Dynatrace
Dynatrace offers strong AI-powered RCA and end-to-end observability for digital business performance, with deep automatic dependency mapping. Like other APM-first platforms, its strength is the application and infrastructure layer. Deep network visibility — flow forensics, routing context, multi-vendor SD-WAN analytics — falls outside its primary design.
AppDynamics
Now part of Cisco, AppDynamics provides full-fidelity user-experience monitoring with strong RUM, synthetic, and session replay. Its network visibility benefits from Cisco’s broader portfolio (including ThousandEyes for internet path monitoring), but for organizations not standardized on Cisco infrastructure, the network depth available within AppDynamics itself is more limited.
LogicMonitor
LogicMonitor takes a different approach — it’s a SaaS-based hybrid observability platform that consolidates broad infrastructure monitoring (servers, network, cloud, logs) for ITOps teams. LogicMonitor’s strength is breadth across infrastructure types. Its limitation, when it comes to the network specifically, is that flow analysis, routing context, and traffic engineering aren’t first-class workflows. Teams that need network-engineering depth typically pair LogicMonitor with a network intelligence platform. See LogicMonitor alternatives and Kentik vs LogicMonitor for the full comparison.
The common pattern
Across all of these platforms, the pattern is similar. Each one is excellent within its primary lane (application code, infrastructure consolidation, full-stack tracing) and each one has limited depth on the network engineering questions that come up during the hardest outages. This is a design choice in most APM platforms. APM platforms are built to make application teams productive, not to replace network engineering tooling. The question for most organizations isn’t which platform to choose but which combination covers the questions their teams actually need to answer.
How network intelligence complements APM
The complement story is clearest in the following concrete scenarios examples:
Scenario 1: A SaaS application is slow for a subset of users. Real User Monitoring inside the APM tool surfaces that users in a specific region are seeing 3-second page loads while the global average is 800ms. APM confirms the application backend is healthy. Network observability shows that BGP routes to the affected region changed two days ago, moving traffic onto a longer AS path with higher latency — and flow data confirms how much real traffic is taking that path. Without the network layer, the team would still be looking at the application.
Scenario 2: An incident in production has unclear scope. The APM tool shows error rates climbing on a key service. APM points to a downstream API call that’s now timing out — but the API itself looks healthy from its provider’s status page. Synthetic monitoring from the network intelligence platform confirms the API is reachable from most regions but not from the cloud region where the affected service runs. Flow data shows asymmetric routing has emerged on the path between the two cloud regions. The fix is at the network layer, but the symptom showed up first in APM.
Scenario 3: Application teams want to understand cost. APM shows traffic volume between services. The network intelligence platform shows what that traffic costs — egress charges, transit fees, inter-region data transfer — and which application calls are driving the spend. Together, they let teams optimize cost as a function of application architecture.
In each pattern, neither tool alone gets to root cause efficiently. Together, they triangulate.
Key components of network observability for APM contexts
Effective network observability — the kind that actually complements APM rather than overlapping with it — relies on several capabilities working together.
Telemetry data the application layer doesn’t collect
Network observability depends on data sources APM platforms don’t typically ingest: NetFlow, sFlow, IPFIX, VPC flow logs, BGP routing tables, SNMP and gNMI streaming telemetry, and synthetic test results from globally distributed agents. Together, these sources show what’s actually happening at the network layer — independent of what application instrumentation reports.
A data platform built for network-scale telemetry
Network telemetry is high-cardinality, high-volume, and gets queried in different patterns than application telemetry. A data platform optimized for network analytics enriches flow data at ingest with BGP, GeoIP, AS path, threat intelligence, and business-context tags — and supports fast ad-hoc queries across all those dimensions.
Correlation with application context
The network observability platform doesn’t have to replicate APM data, but it does need to correlate against it. Shared identifiers (IPs, ASNs, applications, time ranges) let engineers move from an application symptom in APM to a network root cause in the network intelligence platform — and vice versa — without re-piecing together the timeline.
AI-driven investigation across both layers
Modern troubleshooting is moving toward AI-assisted workflows that can reason across multiple telemetry sources. The most useful AI for this context isn’t application-only or network-only — it can investigate a problem across application telemetry and network telemetry, surface evidence from both layers, and produce a recommendation that accounts for the full context.
Benefits of integrating network observability with APM
Combining the two approaches produces operational outcomes that neither delivers alone:
- Faster MTTR on cross-domain incidents. When the symptom is in the application but the cause is in the network (or vice versa), the team that has both views resolves the incident substantially faster than the team that has only one.
- Fewer “is it the network?” debates. Network observability provides the evidence to answer that question with data instead of opinion — which dramatically improves cross-team incident response.
- Better capacity and cost decisions. Application teams can see how their architecture choices affect network cost; network teams can see which application changes are driving traffic growth.
- Stronger SLA accountability. When SaaS providers, cloud providers, or transit providers degrade, the organization has independent measurement data — not just the provider’s own status page.
- More complete digital experience monitoring. Real User Monitoring inside APM, plus synthetic monitoring and network telemetry from the network intelligence platform, together provide the full picture of what users are experiencing and why.
How Kentik complements APM platforms
Kentik is a network intelligence platform — not an APM tool. It doesn’t replace Datadog APM, New Relic, Dynatrace, AppDynamics, or any other application-focused platform. Instead, it provides the network-layer visibility those platforms don’t, and it integrates with them so that engineers can move between application and network views without losing context.
Specifically, Kentik provides:
- Unified network telemetry collection across NetFlow, sFlow, IPFIX, VPC flow logs, SNMP, gNMI streaming telemetry, BGP, and synthetic monitoring — the data sources network engineers need but APM platforms don’t typically ingest.
- A data platform built for network-scale analytics with ingest-time enrichment, high-cardinality queries, and 120-day standard retention for unaggregated flow data.
- Kentik AI Advisor, an AI-driven investigation tool that reasons across flow, BGP, synthetics, and device telemetry — and runs live diagnostics (ping, traceroute, config diffs, SSH workflows) — to surface evidence-backed network root cause faster than manual investigation.
- Integrations with major APM and observability platforms so that synthetic test failures, BGP changes, and flow anomalies can be surfaced inside the application team’s existing workflows.
For organizations running Datadog, LogicMonitor, or other APM platforms, Kentik fills the network-layer gap without requiring a rip-and-replace of existing observability investments.
Related Kentipedia articles and Kentik solutions
- What is Observability? An Overview
- What is Network Observability?
- What is Digital Experience Monitoring?
- Synthetic Monitoring vs. Real User Monitoring (RUM)
- Network Performance Monitoring
- Datadog Alternatives for Network Intelligence
- LogicMonitor Alternatives for Network Monitoring and Hybrid Observability
- The Evolution of Network Monitoring: From SNMP to Network Observability and Network Intelligence
FAQs about Network Observability and APM
What is the difference between APM and network observability?
Application Performance Monitoring (APM) instruments application code to track service execution, transactions, dependencies, errors, and database queries — visibility into what’s happening inside the application. Network observability instruments the network the application runs on — capturing flow data, BGP routing, synthetic measurements, and device telemetry to show what’s happening between services and between the application and its users. Each captures what the other can’t, which is why most modern observability stacks include both.
Do I need both APM and network observability?
For any organization running production applications that depend on cloud, SaaS, internet paths, or hybrid infrastructure, the answer is generally yes. APM tells you when an application service is degraded but typically can’t tell you whether the cause is in the application code, the cloud network, internet routing, or a transit provider. Network observability provides that missing context. Teams that run only APM tend to spend more time in cross-functional war rooms debating “is it the network?” rather than answering the question with data.
How does Kentik complement Datadog APM?
Kentik provides the network-layer visibility that Datadog’s network products (Cloud Network Monitoring and Network Device Monitoring) don’t offer in depth — including BGP routing intelligence, internet path analytics, deep enriched flow analytics, cloud egress cost optimization, and AI-driven network investigation. Most teams that adopt Kentik alongside Datadog use Datadog for application observability and Tier-1 incident response, and Kentik for the Tier-2 network depth they need when application symptoms point to network causes. See Datadog alternatives for a fuller comparison.
How does Kentik complement LogicMonitor?
LogicMonitor consolidates broad infrastructure monitoring across servers, network, cloud, and logs for ITOps teams. Kentik adds the network-engineering depth LogicMonitor doesn’t focus on — flow forensics, BGP routing, traffic engineering, peering analytics, and cloud egress cost optimization — often deployed alongside LogicMonitor rather than replacing it. See LogicMonitor alternatives for a deeper comparison.
Can APM tools detect network-related performance issues?
APM tools can often detect that a network-related issue is affecting the application — for example, by surfacing high latency on a downstream service call or elevated error rates from a SaaS dependency. What APM tools typically can’t do is identify what in the network is causing the problem (a BGP route change, asymmetric routing, transit congestion, an upstream peering issue) or where in the network path the degradation originates. That diagnosis requires network-layer telemetry — flow data, BGP routing, synthetic path analysis — that APM platforms don’t collect.
What does APM miss that network observability captures?
APM platforms typically miss: BGP route changes affecting reachability, internet path performance and AS-level routing decisions, peering and transit provider health, cloud network path behavior between regions and AZs, packet loss and jitter on the paths between services, network-layer DDoS impact, and cloud egress cost attribution. Each of these can directly affect application performance, and none of them are visible from inside the application.
What tools correlate cloud network performance with application metrics?
Effective correlation requires both data sources to live in environments that can share time-aligned context — typically through integration between an APM platform (which captures application metrics) and a network intelligence platform (which captures cloud network telemetry, BGP routing, and synthetic path measurements). Kentik supports this by ingesting cloud flow logs from AWS, Azure, and GCP, correlating them with synthetic tests and BGP data, and exposing the results through APIs and integrations that connect with major APM platforms.
What tools enable rapid RCA for multi-cloud application outages?
Multi-cloud RCA requires the ability to trace traffic across cloud boundaries, correlate cloud network paths with application behavior, and isolate whether the issue is inside one cloud, between clouds, or in the internet path between them. The most effective approach combines APM (for application-side context) with a network intelligence platform that unifies cloud flow analytics, internet path visibility, BGP monitoring, and AI-driven investigation. Kentik supports this by unifying flow analytics across AWS/Azure/GCP, internet path data, and BGP intelligence — and by running AI Advisor across all of it to produce evidence-backed RCA summaries quickly.
What tools can map application dependencies across hybrid networks?
Most APM platforms map application dependencies based on instrumentation — they show which services call which other services. Network intelligence platforms map dependencies based on actual network traffic — which IPs, subnets, and ASNs are communicating with which others, including dependencies the APM instrumentation may not have captured (third-party services, SaaS dependencies, cloud-provider backbones). For complete hybrid-network dependency mapping, both views are valuable. Kentik supports the network-side view through traffic analytics that surface dependencies based on observed flows across data center, cloud, and internet boundaries.
How do APM and network observability work together during an incident?
The typical pattern: APM detects a symptom (elevated error rates, slow transactions, degraded service) and identifies the affected service. Network observability answers whether network conditions explain the degradation — whether routing has changed, whether upstream paths are healthy, whether the cloud network is contributing. When the cause is application-side, APM has all the context needed. When the cause is network-side, the team can move to network telemetry quickly without spending hours debating where to look. The combination dramatically reduces MTTR on cross-domain incidents.
Is network observability part of APM, or separate?
It’s separate but complementary. APM platforms increasingly include some network monitoring features, but those features are typically optimized for application triage rather than network engineering. Dedicated network observability platforms (also called network intelligence platforms) provide the depth that network teams need — and that APM teams benefit from when application issues turn out to have network causes. The two are designed to coexist rather than to replace each other.
What is the difference between network observability and traditional network monitoring?
Traditional network monitoring focuses on device health and threshold-based alerting — is the router up, is the link saturated, has utilization crossed a threshold. Network observability adds the ability to investigate why a problem is happening using rich, queryable telemetry from many sources (flow, BGP, synthetic tests, streaming telemetry) correlated together. Network observability is to traditional NPM what APM is to traditional server monitoring — a more analytical, investigation-oriented discipline that handles the complexity of modern distributed systems.
Add network observability to your APM strategy with Kentik
Kentik is the network intelligence platform that complements APM and full-stack observability tools — providing the deep network-layer visibility application-focused platforms were never designed to deliver.
- Get a demo — See how Kentik complements your existing APM stack
- Kentik AI Advisor — AI-driven investigation across flow, BGP, synthetics, and device telemetry
- Kentik Synthetics — Continuous network-aware synthetic monitoring from global agents
- Datadog Alternatives for Network Intelligence — How Kentik complements Datadog for network teams
- LogicMonitor Alternatives for Network Monitoring — How Kentik complements LogicMonitor for network depth
