6 Best Inspektor Gadget Alternatives for Kubernetes Debugging

Inspektor Gadget gives you eBPF-powered tracing as Kubernetes-native gadgets that run directly through kubectl. Its automatic context enrichment adds pod names, namespaces, and labels to your trace results, so you do not have to manually correlate process IDs with Kubernetes resources when debugging network, filesystem, or process activity inside your clusters.

While it works well for hands-on, on-demand troubleshooting, you may consider alternatives if you need continuous monitoring instead of manual invocation, a web-based interface beyond CLI tools, historical data storage and analysis, tighter integration with a broader observability platform, or deeper application-level context. In production environments that require always-on telemetry or different debugging workflows, complementary or different tools may better fit your needs.

Why Look for Inspektor Gadget Alternatives?

Inspektor Gadget delivers powerful Kubernetes-native debugging, but specific requirements reveal gaps:

On-demand invocation limits continuous monitoring. Gadgets run when you execute them, making Inspektor Gadget excellent for active debugging but less suitable for continuous observability. Teams needing always-on monitoring, historical trend analysis, or proactive alerting require tools that collect data continuously.

CLI-focused interface lacks visualization capabilities. While gadgets output results to your terminal, there's no built-in dashboard, service map, or graphical visualization. Teams wanting visual exploration, interactive debugging, or management-friendly views need tools with web interfaces.

No built-in data retention or historical analysis. Gadgets stream results during execution but don't store data for later analysis. Investigating patterns over time, correlating multiple debug sessions, or analyzing trends requires external storage and processing.

Limited application-level context. Inspektor Gadget captures system-level events—network connections, file operations, system calls—but doesn't provide application traces, business metrics, or custom instrumentation. Deep application debugging needs richer context than system events alone.

Gadget collection focuses on specific use cases. While the gadget library covers many debugging scenarios, it's optimized for troubleshooting rather than comprehensive observability. Teams needing distributed tracing, log aggregation, or metrics collection alongside debugging require broader platforms.

Requires kubectl access and familiarity. Using Inspektor Gadget assumes comfort with kubectl commands and understanding of which gadgets to run for specific problems. Teams wanting more accessible debugging tools or guided troubleshooting may prefer alternatives with different interfaces.

The Best Inspektor Gadget Alternatives in 2026

1. kubectl-trace

kubectl-trace brings bpftrace to Kubernetes through kubectl, letting you run custom eBPF scripts on specific nodes or pods. Where Inspektor Gadget provides pre-built gadgets, kubectl-trace offers flexibility to write exactly the tracing logic you need.

kubectl-trace eliminates SSH access requirements by packaging bpftrace as Kubernetes Jobs. Provide your bpftrace script, target a pod or node, and kubectl-trace handles deployment and cleanup automatically. This makes custom eBPF tracing accessible to anyone with kubectl permissions.

The bpftrace language provides concise syntax for complex tracing scenarios. Write one-liners or short scripts to trace kernel functions, capture stack traces, build histograms, or aggregate custom metrics. When pre-built tools don't match your exact debugging needs, custom scripts provide precise instrumentation.

Main Benefits:

Run custom bpftrace programs through kubectl
No SSH access to nodes required
Flexible tracing for unique debugging scenarios
Target specific pods, nodes, or namespaces
Automatic deployment and cleanup
Integrates with Kubernetes RBAC
Open-source from iovisor community

2. BCC (BPF Compiler Collection)

BCC offers over 100 production-ready eBPF tracing tools for Linux systems. Where Inspektor Gadget focuses on Kubernetes integration, BCC provides comprehensive system tracing tools that work on any Linux host, including cluster nodes accessed directly.

BCC's tool collection covers virtually every system debugging scenario. Track filesystem operations with opensnoop, analyze network retransmits with tcpretrans, profile CPU usage with profile, or investigate disk I/O with biolatency. Each tool targets specific performance questions with detailed man pages.

For custom instrumentation, BCC provides Python and C APIs. Write sophisticated tracing programs that filter events, aggregate data, or integrate with external systems. This programming approach enables complex analysis beyond what command-line tools provide.

Main Benefits:

100+ ready-to-use tracing tools
Works on any Linux system, not just Kubernetes
Python and C APIs for custom development
Detailed man pages and examples
Battle-tested at major tech companies
Extensive documentation and community
CO-RE support for portable binaries

3. k9s

k9s provides a terminal-based UI for Kubernetes with real-time monitoring and debugging capabilities. Where Inspektor Gadget requires running specific commands, k9s offers continuous visibility with interactive navigation through cluster resources.

k9s continuously refreshes resource views showing live cluster state. Navigate pods, deployments, services, and any Kubernetes resource with fast keyboard shortcuts. The UI updates in real-time, showing resource changes, events, and metrics without manual commands.

Built-in features handle common debugging tasks directly. View logs, describe resources, edit YAML, exec into containers, or port-forward—all from the k9s interface. The tool provides context-aware actions based on selected resources, making operations instant.

Main Benefits:

Terminal-based UI with minimal resource usage
Real-time cluster monitoring and navigation
Fast keyboard-driven workflow
Built-in log viewing and container exec
Works over SSH and low-bandwidth connections
Plugin support for custom commands
Active open-source development
Lower learning curve than CLI tools

4. Cilium Hubble

Cilium Hubble specializes in network observability using eBPF with continuous monitoring and visualization. Where Inspektor Gadget requires manual gadget invocation, Hubble runs continuously, capturing network flows and building service maps automatically.

Hubble monitors all network traffic at both packet and application protocol level. See HTTP requests, gRPC calls, Kafka messages, and DNS queries with response codes and latency. The continuous collection enables historical analysis and trend identification that on-demand tools can't provide.

The Hubble UI visualizes service dependencies and network flows automatically. Service maps show actual communication patterns discovered from traffic rather than requiring manual inspection. When debugging connectivity issues, Hubble's flow logs show exactly why connections fail—network policy drops, DNS issues, or routing problems.

Main Benefits:

Continuous network flow monitoring with eBPF
Layer 7 protocol visibility (HTTP, gRPC, Kafka, DNS)
Web UI with automatic service maps
Network policy debugging with detailed logs
Historical data for trend analysis
CNCF graduated project (part of Cilium)
Works standalone or with Cilium CNI

5. Pixie

Pixie provides automatic Kubernetes observability using eBPF with built-in storage and query interface. Where Inspektor Gadget offers on-demand debugging, Pixie continuously captures application behavior, storing data locally for historical queries.

Pixie's eBPF programs automatically capture comprehensive telemetry without any configuration. Monitor HTTP requests, database queries, gRPC calls, and DNS lookups across your entire cluster. The automatic approach eliminates the need to know which tool to run for specific debugging scenarios.

Data stays on cluster nodes for fast queries using PxL (Pixie Language). Query recent telemetry in milliseconds without centralized data movement. The edge storage architecture keeps sensitive data in your cluster while enabling powerful analysis.

Main Benefits:

Automatic continuous telemetry collection
Protocol visibility (HTTP, gRPC, PostgreSQL, MySQL, Redis, Kafka)
Built-in query language and web UI
Edge storage for fast queries
Historical data retention for trend analysis
Open-source with community edition
Acquired by New Relic with continued development

6. Lens

Lens offers a desktop IDE for Kubernetes with comprehensive cluster management and debugging. Where Inspektor Gadget focuses on eBPF-based system tracing, Lens provides a complete development environment with built-in debugging tools and visual exploration.

Lens automatically discovers all your Kubernetes contexts with unified multi-cluster management. Switch between clusters, namespaces, and resources from a single interface. The real-time dashboard shows cluster health, resource utilization, and event streams continuously.

Built-in terminal access, log streaming, and resource editing eliminate context switching. Click any pod to view logs, open a shell, or edit manifests directly. Debugging workflows stay within the Lens interface, reducing friction compared to CLI-based tools.

Main Benefits:

Desktop application with rich visual interface
Multi-cluster management from single window
Built-in terminal and log streaming
Resource editing with validation
Prometheus metrics integration
Commercial support available with Lens Pro
Active development and regular updates

Commercial Kubernetes Observability Platforms

While open-source debugging tools handle specific troubleshooting scenarios, production environments often need platforms that combine debugging with continuous monitoring, alerting, and team collaboration features.

Better Stack

Better Stack provides unified Kubernetes observability with eBPF-based automatic instrumentation and fully managed infrastructure. While tools like Inspektor Gadget excel at on-demand debugging, Better Stack is designed for continuous monitoring, persistent storage, alerting, and AI-driven analysis.

Deploy Better Stack’s collector once, and your entire cluster is instrumented automatically. No code changes, no manual gadget runs, and no SDK installation are required. The eBPF collector continuously gathers distributed traces, logs, and metrics, giving you always-on visibility that complements manual debugging workflows.

With continuous, network-level instrumentation, application behavior is revealed automatically. HTTP requests, database queries, gRPC calls, message queues, and cache interactions are all captured with latency, status, and parameter details. This persistent telemetry enables historical analysis and trend detection, providing insights that ad hoc debugging alone cannot offer.

Service dependency maps update in real time based on actual traffic. These visualizations highlight request volumes, latency percentiles, and error rates, helping you proactively identify bottlenecks or misconfigurations instead of waiting for incidents to occur.

Live Tail streams logs continuously with powerful filtering and search. You can follow patterns, isolate severity levels, or trace user sessions across distributed requests. This complements manual debugging with always-on log visibility.

Querying telemetry is simple with SQL or PromQL syntax and sub-second response times. You can explore logs, metrics, and traces freely to investigate issues, analyze trends, or validate hypotheses, giving more flexibility than predefined debugging commands.

Long-term data retention with ClickHouse enables deep historical analysis. By storing traces, logs, and metrics for weeks or months, you can correlate recurring incidents, identify patterns, and understand seasonal or long-term trends.

OpenTelemetry-native architecture ensures flexibility and prevents vendor lock-in. It combines automatic eBPF instrumentation with SDK-based context collection, allowing you to export data to multiple backends or observability platforms.

Automated anomaly detection notifies you when behavior deviates from the norm. Unlimited phone and SMS alerts cover system errors, performance issues, resource exhaustion, and security events, helping detect problems before they escalate.

AI-powered root cause analysis accelerates incident resolution. By correlating network traces, service dependencies, error patterns, and performance metrics, the AI SRE suggests probable causes, helping you quickly narrow the scope of investigation and reduce downtime.

Main Benefits:

Continuous eBPF auto-instrumentation for Kubernetes and Docker
Long-term retention with ClickHouse storage
SQL and PromQL queries with sub-second response times
Unified platform for logs, metrics, and traces
30x cheaper than Datadog with predictable pricing
OpenTelemetry-native for vendor flexibility
Automatic database monitoring without agents
Service maps from eBPF network traces
AI-powered root cause analysis
Integration with Better Stack Uptime
Available in 4 regions with custom deployments
SOC 2 Type 2, GDPR, and ISO 27001 compliant
60-day money-back guarantee

Final thoughts

Inspektor Gadget is an excellent tool when you need fast, on-demand debugging in Kubernetes. It automatically adds pod names, namespaces, and labels to your trace results, so you can investigate network, filesystem, and process issues without manually correlating process IDs or accessing nodes via SSH.

Depending on how you work, you may need additional tools. If you want continuous visibility and historical data, platforms like Cilium Hubble or Better Stack provide always-on monitoring and retention. If you prefer interactive exploration of your cluster, Lens or k9s offer rich visual interfaces. If you need deep system-level tracing, BCC or kubectl-trace give you flexible, low-level tools.

Start by thinking about your typical debugging patterns. If you primarily respond to issues as they arise, Inspektor Gadget is a strong fit for your workflow. If you need proactive monitoring, automated alerts, or historical trend analysis, continuous observability tools will complement your manual debugging.

In many cases, combining tools gives you the best results. You can use Inspektor Gadget for targeted troubleshooting, k9s for everyday cluster navigation, and Better Stack or Hubble for production monitoring and retention. This layered approach lets you leverage the strengths of each tool while covering the full range of debugging and observability needs in Kubernetes.

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