Top Open Source Alternatives to Datadog for Log, Metrics and Traces

Rethinking Observability for Growing Teams

Monitoring solutions are essential for maintaining IT infrastructure performance, but teams often struggle with the high costs and complexity of enterprise tools like Datadog. As applications scale, monitoring expenses can grow to the point where companies are forced to choose between visibility and budget constraints.

For teams in search of open source alternatives, there are powerful options that provide real-time insights, root cause analysis, and infrastructure monitoring without the hefty price tag. Identifying the right open source tools can help you optimize performance and streamline monitoring while keeping within budget.

In this guide, we'll explore the best open source alternatives to Datadog, comparing features, scalability, and ease of use to help you identify the right monitoring solution for your needs.

Are Open Source Alternatives Really Better?

Choosing the right monitoring solution isn't just about keeping systems online—it's about ensuring teams can respond quickly and make decisions with the right data. As infrastructure grows more complex, teams need tools that offer clarity, speed, and flexibility without getting lost in endless dashboards. Unfortunately, many teams struggle to achieve that in bloated platforms like Datadog.

While powerful, Datadog is complex and has a pricing model that's not designed for smaller teams or growing companies. Notably, it's the bloat, the configuration burden, and the feeling that you're overpaying for features you don't need while still juggling separate tools for logs, metrics, and traces.

Meanwhile, open source monitoring solutions offer several key benefits:

• Cost-effective: Face no usage-based pricing surprises
• Flexible: Customize to fit your exact infrastructure and workflows
• Real-time insights: Spot issues as they happen
• Data control: Keep logs and metrics within your environment
• Scalability: Easily extend monitoring as your infrastructure grows
• Compliance-friendly: Meet internal and external requirements easily

Open source monitoring tools aren't just a budget-friendly alternative, they're often better aligned with how modern teams work. They offer the ability to adapt quickly to unique infrastructure needs and provide a solid foundation to build scalable systems without getting locked into a rigid ecosystem.

Key Features in Alternatives to Datadog

Optimizing for cost is not always the best approach when looking to replace a larger enterprise monitoring solution. Teams should look to find a solution that provides the visibility and control that is best suited for maintaining their specific application.

A strong monitoring solution should offer clear and immediate value. That starts with real-time insights. Teams need to see what's happening across their systems as it happens. Delays in data can mean delays in response, and live feedback is essential for catching issues early.

Root cause analysis is another top priority. It should be simple to trace an issue from a user-facing symptom back to the backend component causing it. That includes seeing the logs, the metrics, and the request traces all in one place. When teams can move from symptom to cause in seconds, downtime shrinks.

Additionally, the ability to track custom metrics is also key. Not all systems are the same and as such, teams often need to track things specific to their business or infrastructure. A good tool makes it easy to define and monitor the exact data that matters to your environment.

With this all in mind, look for tools that support:

• Real-time log and metric monitoring with low latency
• End-to-end visibility from frontend to backend
• Integrated traces, logs, and metrics in one interface
• Custom metrics that reflect what matters in your stack
• Clear dashboards that don't overwhelm
• Alerting that notifies you when something's off—not after

Open source tools often shine here. They tend to be more flexible and allow deeper access to configuration and integration. They also avoid the clutter of enterprise platforms. What you get is lean, useful observability that works with your stack, not against it.

Finally, any monitoring solution ultimately must be cost-effective. The value it brings should scale with your business. Whether you're monitoring a few services or a large cloud deployment, the tool should support your team without forcing tradeoffs between coverage and cost.

The Best Open Source Log & Metric Monitoring Tools

There are several open source monitoring tools that deliver reliable log and metric monitoring without the high cost of enterprise platforms like Datadog or New Relic. These tools give teams the ability to track and troubleshoot performance issues across their IT infrastructure while staying flexible, cost effective, and in control of their data.

Below are some of the best alternatives available today.

HyperDX – Unified, Real-Time Observability

HyperDX offers an all-in-one platform that brings together logs, metrics, traces, and session replays for full visibility into your stack. It's built for speed and clarity, helping teams resolve issues before they impact end users.

Key features:

• Combines real-time monitoring and root cause analysis in one view
• Supports containerized applications, virtual machines, and cloud services
• Enables custom metrics and alerting without complex setup
• Optimized for debugging and incident resolution
• Provides a comprehensive view of your systems and detailed insights for teams

HyperDX is especially useful for teams who need to optimize infrastructure's performance and scale confidently without sacrificing clarity or cost.

Who uses HyperDX? HyperDX has been adopted by startups and enterprises, including Sunsama, Zenhub, Nutrient, Leya, and Howl.

Prometheus – Time-Series Metrics Monitoring

Prometheus is a leading open-source system for collecting and querying metrics from your services. It's built for infrastructure monitoring and excels at tracking resource utilization, memory usage, and uptime.

Key features:

• Great for cloud environments and container-based systems like Kubernetes
• Highly customizable with alerting and data visualization via Grafana
• Designed for high availability and continuous monitoring
• Ideal for monitoring network devices, system health, and service endpoints

Prometheus is known for its reliability at scale and is used by companies like SoundCloud (who originally created it), Red Hat, and DigitalOcean. Its simplicity and pull-based model make it especially attractive for environments with frequent changes or dynamic infrastructure.

If you're running microservices, Prometheus can serve as the backbone of your observability stack, especially when paired with tools like Grafana and Alertmanager.

Grafana Loki – Scalable Log Aggregation

Loki is an open-source log aggregation tool that integrates directly with Grafana. It's designed to work alongside Prometheus, providing a seamless way to correlate logs and metrics in one dashboard.

Key features:

• Lightweight log collection built for scale
• Tight integration with existing data visualization workflows
• Fast access to logs for root cause analysis
• Helpful for teams managing cloud deployments and it infrastructure

Loki is used by teams at Grafana Labs, Piedmont Healthcare, and Autodesk to bring clarity to large-scale logging environments without the indexing complexity of tools like Elasticsearch. It's a good fit for teams already invested in the Grafana ecosystem and looking for a unified approach to metrics and logs.

By pairing Loki with Prometheus, you gain context-rich observability without relying on multiple disconnected platforms

Jaeger – Distributed Tracing

Jaeger helps teams understand how requests flow through their systems, making it an excellent tool for tracing, debugging, and performance optimization.

Key features:

• Tracks request latency across microservices
• Useful for root causes and complex application performance issues
• Can integrate with other tools to support incident resolution workflows
• Supports deployment in cloud-native and hybrid environments

Originally built by Uber, Jaeger has become the go-to tracing tool for many engineering teams. It's now used by companies like Basecamp, Cisco, and NetApp to improve service reliability and speed up root cause identification.

Jaeger is especially powerful when used in environments with high service-to-service communication, where understanding trace paths is key to diagnosing latency and bottlenecks.

OpenTelemetry – Unified Telemetry Collection**

OpenTelemetry is not a full monitoring tool, but it plays a critical role in observability by collecting and forwarding logs, metrics, and traces from your systems.

Key features:

• Supports compliance, configuration, and deployment flexibility
• Helps you collect the right data for multiple tools
• Works well with platforms like HyperDX, Prometheus, and Loki
• Ensures consistent telemetry across your stack

OpenTelemetry is supported by the Cloud Native Computing Foundation (CNCF) and has contributors from companies like Microsoft, Google, and Splunk. It's become the emerging standard for telemetry instrumentation across cloud environments.

If your team wants flexibility in where observability data goes—without vendor lock-in—OpenTelemetry provides a stable, extensible foundation.

These tools are all powerful in their own right, but the best results come from choosing a stack that fits your team's priorities. No matter your focus area, open source monitoring solutions provide the flexibility and insight to support your team's long-term success

Getting Started with an Open Source Monitoring Solution

Reading through this list of modern monitoring solutions may feel overwhelming. Chances are your team already has some tools in place—maybe a mix of logs in one platform, metrics in another, and traces somewhere else. But stitching them together and keeping them working as your infrastructure grows can feel like a second job. The good news is, moving to an open source monitoring stack doesn't have to be all-or-nothing. With the approach outlined below, your team can build a setup that gives you the visibility you need without adding unnecessary overhead or complexity.

Define What You Need to Monitor

Before choosing tools or writing any configs, step one is to understand what needs monitoring in your environment. This includes your core infrastructure, applications, and all supporting services.

Start by mapping out your ecosystem:

• Cloud services like AWS, GCP, or Azure
• Virtual machines or bare metal servers
• Containerized applications running in Kubernetes or Docker
• Databases, network devices, and external APIs

Most teams prioritize application performance tracking and uptime monitoring for end-user systems. It's also important to have continuous visibility into how much memory your systems are using, how efficiently you're using resources, and how well your infrastructure is holding up under load. Detecting issues early prevents escalation to major incidents.

Choose the Right Stack

Open source monitoring gives you flexibility, but it also means selecting and stitching together different tools that specialize in different areas.

A common stack looks like this:

• Prometheus for collecting and querying time-series metrics
• Grafana for data visualization
• Loki for aggregating logs
• Jaeger for distributed tracing
• Synthetic monitoring tools for simulating user behavior

This modular setup offers deep visibility but often comes with tradeoffs. Each tool requires its own configuration and maintenance. Teams also need to handle integration between tools and ensure data formats remain compatible as the stack grows.

An alternative is to use a comprehensive platform like HyperDX, which brings all of these layers—logs, metrics, traces, dashboards, and session replays—into a single, open-source system. Rather than managing five separate tools, HyperDX offers out-of-the-box observability that supports containerized applications, cloud services, and traditional infrastructure. For teams that prefer less setup and more immediate insights, it's a powerful way to reduce overhead without losing depth.

The right stack depends on your team's goals and capacity. If you need flexibility and don't mind ongoing upkeep, building your own open source stack may be the right path. But if you're looking for simplicity, speed, and scale, a unified platform like HyperDX can save time and reduce complexity.

Plan for Integration and Ongoing Management

Integrating multiple monitoring tools is a commitment to ongoing upkeep. You'll need to connect components and make sure everything stays in sync as your system evolves.

That includes:

• Setting up alerting logic across tools
• Maintaining data pipelines between services
• Creating workflows for incident resolution and reporting
• Supporting security, compliance, and access control policies

For many teams, this adds hours of configuration and deployment time—and introduces a new layer of complexity that must be documented and managed over time.

Factor in Human Touch

Your tools are only as effective as the people using them. Open source monitoring requires that teams have a strong awareness of how all the pieces come together. Specifically, team members should:

• Understand how the stack works
• Know who's responsible for maintenance and troubleshooting
• Share workflows for tracking root causes and responding to alerts

Successful observability is about building a culture of visibility and process ownership.

Get Up and Running Fast

Every element in this comprehensive approach can be stitched together manually so your team get up and running with the optimal solution. For a faster path forward, it's worth exploring the benefits of a platform like HyperDX.

HyperDX provides a unified monitoring solution that brings together:

• Real-time log and metric monitoring
• Distributed tracing and session replays
• Built-in alerting, custom metrics, and detailed dashboards
• Support for cloud environments, containerized applications
• Flexibility to monitor legacy systems and hybrid environments through one unified view

All of it works out of the box. No complex integrations. No syncing logs between services. Just the right data when you need it.

It's built for teams that want to move fast and scale without managing a full observability stack. This solution is especially powerful for teams that are not looking to have a dedicated person on staff to maintain infrastructure monitoring.

Final Thoughts on Choosing the Right Monitoring Solution

Investing in observability marks a technical milestone that shows your team is ready for a more thoughtful approach to systems management. When implementing a new monitoring solution, remember that effective monitoring empowers teams to work faster with fewer errors.

For organizations where performance directly impacts patients, clinicians, or customers, monitoring safeguards critical outcomes. Whether supporting care workflows or maintaining digital products, your team needs tools that expose root causes and make insights actionable. Ultimately, whether you build an open source stack or adopt a platform like HyperDX, your monitoring tool should simplify configuration, enhance management, and drive team success.