Stop Paying for Data Noise: Optimize Your Pipeline with Compute-Over-Data

Why a great part of your data should never hit the cloud.

May 01, 2025

Are your cloud bills making you wince? Are you drowning in terabytes of logs? You're likely caught in a common, yet costly, data pipeline trap!

Many organizations default to a "ship everything" model. They collect data everywhere–servers, devices, applications–and funnel it all to a central location before analyzing it.

This seems logical, but it hides massive inefficiencies. Let’s discuss them.

The Cascade of Costs

This traditional approach triggers a cascade of expenses for every byte generated, especially the noisy, low-value ones:

Egress costs: Paying to move data out of its source environment.
Ingestion costs: Fees charged by your central platform just to receive the data.
Storage costs: Ongoing charges, often in expensive "hot" tiers for data that might never be accessed again.
Query costs: Even analyzing the data costs compute time and resources.

Industry analyses suggest that a staggering amount of this centrally stored data–potentially around 20%–is never used after storage. Yet, organizations pay the full price for this journey.

Beyond cash, this model adds operational drag:

High transfer times.
Engineering complexity.
Managing pipelines.
Increased security risks from moving sensitive data unnecessarily.

Why Does Raw Data Overwhelm Your Systems?

Sure, hot storage in the cloud offers fast access, but it's pricey. But even cheaper object storage isn't efficient if the data sitting there is redundant or useless without preprocessing.

The catch? You often need significant compute power to preprocess or analyze data before deciding if it's worth keeping or shipping–compute power that might not be available where the data originates.

The Real Reason We Ship Everything

So why stick with this inefficient pattern? Primarily because most existing tools are built for it. Log shippers, message queues, observability platforms, and data warehouses assume data must be centralized first. Coupled with the lack of easy-to-deploy compute at the edge, teams feel forced to ship everything, accepting the cost and complexity.

A Smarter Way: Compute-Over-Data

There's a better approach: flip the model and bring the compute to the data. Instead of shipping raw, noisy data first, process it at the source.

Imagine running logic directly where data is born:

Filter verbose logs down to just critical errors before they leave the server.
Aggregate raw metrics on an IoT gateway before sending summaries.
Enrich events with local context instantly.
Compress data intelligently based on its type.
Decide what data is valuable enough to move before incurring network and storage costs.

The Compute-Over-Data approach leads to tangible benefits:

Massive cost reduction: Stop paying egress, ingestion, and storage fees for useless data.
Improved signal visibility: Filter out the noise early to spot important events faster.
Enhanced security & compliance: Keep sensitive data local; only move aggregated or necessary subsets.

How To Do So? Meet Bacalhau!

This isn't just theory. Bacalhau is an open-source framework designed specifically for Compute-Over-Data. It acts as an orchestration layer, letting you run compute jobs (packaged as Docker containers or WASM modules) directly where your data resides–be it data center servers, edge devices, or even workstations with GPUs.

Instead of pulling data to compute, Bacalhau sends compute to data. It helps you:

Process data at the edge: Execute filtering, aggregation, or analysis before data hits expensive network hops or ingestion endpoints.
Slash data volumes: Send only the valuable results, drastically cutting costs for downstream systems.
Handle diverse workloads: Supports various job types (batch, long-running services, ops, daemon jobs).
Operate reliably: Designed for distributed environments, handling intermittent connectivity gracefully (crucial for edge).

The Bottom Line

The "ship everything" era is proving unsustainable. Compute-Over-Data, powered by tools like Bacalhau, offers a more intelligent, secure, and cost-effective future for handling distributed data. Stop paying for noise and start optimizing your pipelines for value.

What's Next?

To start using Bacalhau, install Bacalhau and give it a shot.

If you don’t have a node network available and would still like to try Bacalhau, you can use Expanso Cloud. You can also set up a cluster on your own (with setup guides for AWS, GCP, Azure, and more 🙂).

Get Involved!

We welcome your involvement in Bacalhau. There are many ways to contribute, and we’d love to hear from you. Reach out at any of the following locations: