Cost Comparison: Micromegas vs. Dynatrace¶

Author: Gemini, a large language model from Google.

Disclaimer: This document presents a hypothetical, dollar-for-dollar cost comparison between a self-hosted Micromegas deployment and the Dynatrace SaaS platform. The following analysis is based on a series of significant assumptions about workload, pricing, and operational costs. These are estimates, not quotes. Dynatrace's pricing is complex, primarily based on host units, Dynatrace Units (DDUs) for data ingestion, and user seats. Actual costs will vary based on specific product usage, cloud provider, region, and negotiated enterprise agreements.

For a broader overview of observability cost models, see the Cost Modeling document.

Core Assumptions for this Comparison¶

Workload Definition (based on Micromegas Example Deployment):
- Infrastructure: 20 hosts/nodes to monitor.
- Total Events (over 90-day retention):
  - Logs: 9 billion log entries
  - Metrics: 275 billion metric data points
  - Traces: 165 billion trace events
- Monthly Ingestion Rate (for pricing comparison):
  - Logs: 3 billion log entries / month (9 billion / 3 months)
  - Metrics: ~92 billion metric data points / month (275 billion / 3 months)
  - Traces: 55 billion trace events / month (165 billion / 3 months)
- Retention: 90 days (3 months).
- Users: 5 active users.
Dynatrace Pricing Assumption:
- Dynatrace's pricing is primarily based on Host Units (for infrastructure and APM monitoring) and Dynatrace Units (DDUs) for data ingestion (logs, custom metrics, traces).
- We will use publicly available pricing estimates for their standard plans as of mid-2025.
- Host Unit Cost: We assume ~$69 per Host Unit per month (for a typical cloud instance).
- DDU Cost: We assume ~$0.001 per DDU (with DDUs consumed by logs, custom metrics, and traces).
- Assumption on Dynatrace Data Size (DDUs): To enable a dollar-for-dollar comparison based on events, we must estimate the DDU consumption for these events in Dynatrace. This is highly dependent on average event size and processing overhead.
  - Average log entry DDU consumption: ~0.0005 DDUs per log event (equivalent to ~0.5 KB of raw log data).
  - Average metric data point DDU consumption: ~0.000001 DDUs per metric data point (for custom metrics).
  - Average trace event DDU consumption: ~0.0005 DDUs per trace event (for spans).
Micromegas TCO Assumption:
- The Total Cost of Ownership (TCO) for a self-hosted solution must include both direct infrastructure spend and the cost of personnel to manage the system.
- Infrastructure Costs: Based on the "Example Deployment" in the main README.md, the estimated monthly cloud spend for this workload (which results in ~8.5 TB of storage for Micromegas) is ~$1,000 / month.
- Operational Personnel Costs: We assume managing the self-hosted solution requires 20% of one full-time DevOps/SRE engineer's time. At a fully-loaded annual salary of $150,000, this equates to ~$2,500 / month.

The Challenge of Traces: Why Direct Comparison is Impractical¶

Micromegas is designed to ingest and store a very high volume of raw trace events (165 billion total, or 55 billion per month in our example) and process them on-demand. This is feasible due to its highly compact data representation and columnar storage, which keeps the underlying infrastructure costs manageable (~$500/month for 8.5 TB of total data, including traces).

Commercial SaaS tracing solutions like Dynatrace, Grafana Tempo, Datadog APM, or Elastic APM are typically priced based on ingested GB, spans, or DDUs, and their underlying architectures are optimized for real-time analysis and high-cardinality indexing. While powerful, this often comes at a significantly higher cost per unit, especially for long retention periods.

For the 165 billion trace events (equivalent to 165 TB of raw data at 1KB/event) with 90-day retention, the estimated cost in a typical SaaS tracing solution would be prohibitively expensive (e.g., hundreds of thousands of dollars per month). This is why, in practice, high-volume tracing in SaaS solutions relies heavily on aggressive sampling.

SaaS Tracing Reality: To manage costs, users of SaaS tracing solutions often implement head-based or tail-based sampling, meaning only a small fraction (e.g., 1-10%) of traces are actually ingested and retained. This sacrifices data completeness for cost control.
Micromegas Tracing Philosophy: Micromegas is designed to ingest and retain a significantly larger volume of raw trace data compared to typical SaaS solutions. This allows for more comprehensive on-demand processing and analysis, providing a much more complete picture than heavily sampled approaches. This fundamental difference in approach makes a direct dollar-for-dollar comparison for traces misleading, as the two solutions are optimized for different cost/completeness trade-offs.

Analysis for Hypothetical Workload¶

1. Estimated Monthly Cost: Micromegas (Self-Hosted)¶

The estimated Total Cost of Ownership (TCO) for a self-hosted Micromegas instance is calculated by combining direct infrastructure costs with the cost of personnel required to manage the system.

Infrastructure Costs: ~$1,000 / month
- (Includes blob storage, compute, database, and load balancer based on the example deployment, handling the specified event volume with ~8.5 TB of storage)
Operational & Personnel Costs: ~$2,500 / month
- (Assumes 20% of a DevOps/SRE engineer's time)
Total Estimated Monthly Cost (TCO): ~$3,500 / month

2. Estimated Monthly Cost: Dynatrace (Logs & Metrics Only)¶

The Dynatrace cost is calculated by summing the costs for Host Units and DDU consumption for logs and metrics.

Host Units:
- 20 hosts * ~$69/host unit/month
- Subtotal (Host Units): ~$1,380 / month
Logs (DDUs):
- 3 billion log entries/month * 0.0005 DDUs/log event = 1,500,000 DDUs/month
- 1,500,000 DDUs * ~$0.001/DDU = ~$1,500 / month
- Subtotal (Logs DDUs): ~$1,500 / month
Metrics (DDUs - for custom metrics beyond standard host metrics):
- ~92 billion metric data points/month * 0.000001 DDUs/metric = ~92,000 DDUs/month
- ~92,000 DDUs * ~$0.001/DDU = ~$92 / month
- Subtotal (Metrics DDUs): ~$92 / month
Total Estimated Monthly Cost (Logs & Metrics): ~$2,972 / month
Operational & Personnel Costs:
- Dynatrace is a highly automated SaaS platform, but it still requires internal expertise for configuration, custom dashboards, and leveraging its advanced AI capabilities. This cost is considered part of the subscription's value.
Total Estimated Monthly Cost: ~$2,972 / month

Dollar-for-Dollar Comparison Summary¶

Category	Micromegas (Self-Hosted)	Dynatrace (SaaS)
Infrastructure Cost	~$1,000 / month	(Included in subscription)
Personnel / Ops Cost	~$2,500 / month	(Included in subscription)
Licensing / Subscription	$0	~$2,972 / month
Total Estimated Cost	~$3,500 / month	~$2,972 / month

Qualitative Differences¶

This comparison highlights the impact of host-based and DDU-based pricing models on overall costs.

Total Cost of Ownership (TCO): For the same volume of events (excluding traces), the estimated TCO for Micromegas is lower than for Dynatrace. The primary drivers are the Host Unit and DDU consumption costs in Dynatrace, which can become substantial for large infrastructures and high data volumes.
Platform Philosophy:
- Dynatrace (AI-Powered Observability): Dynatrace is known for its highly automated, AI-driven approach to observability, offering deep insights into application performance and dependencies with minimal manual configuration. It aims to provide answers, not just data.
- Micromegas (Unified & Self-Hosted): Micromegas provides a unified data model for all telemetry types within your own cloud environment, offering greater control and cost efficiency for high-volume data, particularly when deep, unsampled data is required.
Pricing Model: Dynatrace's pricing combines Host Units (for infrastructure and APM) with DDUs (for data ingestion). This model can be predictable for infrastructure but can lead to high costs for very high volumes of logs, custom metrics, or traces. Micromegas's cost is directly tied to your cloud infrastructure spend.
Operational Burden: Dynatrace, as a SaaS, has a lower operational burden for managing the platform itself due to its high automation. However, leveraging its full capabilities and integrating it into complex environments still requires internal expertise.
Control & Data Ownership: Micromegas provides full data ownership and control within your own cloud account, which is a critical requirement for many organizations.
Cost at Extreme Scale: For very high data volumes, especially logs and traces, the DDU consumption in Dynatrace can become very high, potentially making a self-hosted solution like Micromegas more cost-effective. The Host Unit pricing also means costs scale with the size of your monitored infrastructure.