As observability becomes a cornerstone of modern infrastructure, organizations are turning to platforms like Grafana Cloud and Datadog to monitor logs, metrics, and traces. However, these tools often come with hidden complexities, not just in their functionality but also in their pricing models. At Gigapipe, we’ve built an alternative that prioritizes simplicity and affordability, ensuring that observability is accessible to all teams without breaking the bank.
Vantage recently released a detailed article comparing the complex costing models of both Datadog and Grafana cloud: https://www.vantage.sh/blog/datadog-vs-grafana-cost
It highlights the pitfalls many companies fall into with the ‘cheap entry’ or ‘free credits’ offerings which can end up vendor locking you with spiralling costs.
The Challenges of Cloud Observability
Cloud observability platforms promise seamless insights into your systems, but the reality is often more complicated. Here are the three primary challenges we see in the industry:
1. Overwhelming Complexity
Many observability tools are packed with features, but this often leads to steep learning curves or more often than not, a system you end up using only a fraction of, but paying for all of. Configuring alerts, managing dashboards, and integrating with existing tools can become a daunting task, especially for smaller teams.
2. Performance Trade-offs
Running observability platforms in the cloud means relying on their infrastructure. This can lead to performance bottlenecks, especially during high-traffic periods or when handling large datasets. For example, in Grafana Cloud, users often report delays in rendering dashboards or querying data during peak usage as you cannot control the power of the infrastructure you’re using.
3. Opaque Pricing Models
The most significant pain point is pricing. Platforms like Datadog and Grafana Cloud often employ complex, usage-based pricing models that make it hard to predict costs. The Vantage blog post highlights how these models can spiral out of control, especially for growing businesses. From per-user fees to charges based on data ingestion, storage, and query volume, the pricing structure often feels more like a labyrinth than a transparent system.
The Gigapipe Difference
At Gigapipe, we’ve reimagined cloud observability with a focus on simplicity and fairness. Here’s how we stand out:
1. Simple, Transparent Pricing
Our pricing model is straightforward: one flat rate based on your data volume. No hidden fees, no surprises. Whether you’re a Startup monitoring a few services or an enterprise handling terabytes of data, you’ll know exactly what you’re paying. Check out our pricing page for details: Gigapipe Pricing.
2. Superior Performance
Gigapipe’s architecture leverages its own open-source observability suite (think of it as if Grafana combined all their different tools and correlated it all for you in a single database), ensuring high-speed data processing and real-time insights. By optimizing our platform for performance, we’ve eliminated many of the latency issues users face with other cloud solutions.
3. User-Friendly Design
We’ve built Gigapipe to be intuitive, with streamlined dashboards and easy-to-configure alerts. This means less time spent on setup and troubleshooting and more time focusing on your core business.
Comparing Pricing: Gigapipe vs. the alternatives
Let’s take a closer look at how Gigapipe compares to other platforms:
Grafana Cloud: While Grafana Cloud offers a free tier, its paid plans quickly become expensive as you scale. The pricing is based on ingestion rates, retention periods, and additional features like alerting and user management. Predicting your monthly bill can feel like solving a puzzle.
Datadog: Known for its robust features, Datadog’s pricing model is even more intricate. With separate charges for infrastructure monitoring, log management, APM, and more, businesses often find themselves paying far more than expected.
Gigapipe: In contrast, Gigapipe offers a single, predictable rate. No matter how much you scale, you’ll always know your costs upfront. This makes budgeting easier and removes the stress of surprise bills.
€149/month: 32gb RAM, 8 vCPUs, 1TB data storage
€249/month: 48GB RAM, 10 vCPUs, 2TB data storage
…
€1449/month: 192GB RAM, 48 vCPUs, 10TB data storage
To make the best direct comparison possible, we’ll use Vantage’s example for Logs. Now this example is quite heavily biased towards Grafana over Datadog already, making Grafana look infinitely more appealing by using this specific case where the indexing in Datadog puts its monthly rate over the $65k mark.
Their example also doesn’t account for queries and compute, which would increase the cost further especially if it’s a read-heavy setup. However here are their proposed costings for each (quoted from the article):
Pricing Scenario #3: Logs
25,000 GB of log data is ingested and stored for 1 month.
Grafana Cloud: 25,000 GB x $0.50 per GB = $12,500 total Grafana Cloud
Datadog:
25,000 GB x $0.50 per GB = $12,500 total Grafana Cloud
25,000 GB x $0.10 per GB = $2,500 for ingestion
25,000 GB / 1 KB (assuming average log event size is 1 KB) = 25 billion log events
25 billion log events x ($2.50 / 1 million log events) = $62,500 for indexing
$2,500 for ingestion + $62,500 for indexing = $65,000 total Datadog $2,500 for ingestion + $62,500 for indexing = $65,000 total Datadog
Gigapipe:
However, to put it into perspective for 25 billion logs equalling 25TB for the month, here’s what a sensible breakdown in Gigapipe would look like if we take into account the likely querying requirements of a dataset of this size:
Total monthly cost under Gigapipe: €3984/month or $4101/month
Gigapipe aims to provide the tools and infrastructure growing companies require, in a clear and easily forecastable way. Infinite scalability with a clear cost vs performance structure that will REMAIN cost effective as client’s grow.
Why Simplicity Matters
Complex pricing models don’t just hurt your wallet, they also waste valuable time. Teams end up spending hours trying to optimize their usage to fit within budget constraints. At Gigapipe, we believe that observability should empower teams, not burden them. By keeping our pricing simple and our setup fast, we let you focus on what matters: building and maintaining great systems.
Conclusion
Cloud observability is essential, but it shouldn’t come with unnecessary complexity or unpredictable costs. Gigapipe offers a streamlined alternative that combines powerful features with straightforward pricing. If you’re tired of navigating convoluted pricing models and dealing with performance issues, it’s time to give Gigapipe a try.
Visit Gigapipe today to learn more and see how we can transform your observability experience.
