Trusted Open Source Code Contributors
We Don't Just Use Open Source.We Contribute to it
Every fix our team ships to Apache NiFi, Kafka, Cassandra, Airflow, and StarRocks
goes straight upstream, so your stack gets better whether you work with us or not.
Contribution Status Breakdown
A live snapshot across all phases and all technologies in our open source programme.
Total Contributions
102
+24 last quarter
Merged / Resolved
70
68.6% merge rate
In Review · Active
27
PR raised & awaiting
Tech Stack where Ksolves has left a measurable footprint in the last Quarter.
Spanning query engine performance, pipeline reliability, commit log integrity, processor-level fixes, and more. Our open-source contributions this quarter ran deep across distributed data and real-time streaming infrastructure for many repositories, some of which are:
StarRocks
Apache Cassandra
Apache Kafka
Apache NiFi
Apache Airflow
Apache HBase
Apache Atlas
Apache Ambari
Apache Flink
Apache Iceberg
Apache Spark
Apache ClickHouse
And Many More
Why We Contribute
We use this infrastructure every day. Contributing back is the obvious next step. Here’s why
Better Code for Clients
Every fix we ship upstream runs inside your production stack. When we improve NiFi's processor reliability, every client on NiFi benefits, including ours.
Stronger Engineers
Contributing to Apache-level codebases demands deep system knowledge. It's the kind of work that makes engineers sharper, and that shows up in client engagements.
Community First
We've built our business on open source tools. Contributing back is the only intellectually honest position for a team that depends on this infrastructure every day.
From Upstream Fixes to Client Results
Engineers who contribute to the stack think differently when they build on it.
We'd worked with implementation partners before, but Ksolves was the first team that could actually read the codebase when something broke. When we hit a NiFi processor issue in production, they had a fix in hours, not a workaround, an actual fix. That's a different category of partner.
We were three major versions behind on Cassandra and had no realistic upgrade window. Ksolves came in, assessed our exposure, and kept us patched and stable without touching our production topology. We bought ourselves eighteen months to plan the upgrade properly.
A zero-day hit one of our Kafka deployments on a Friday evening. Ksolves had assessed the impact and sent us a clear brief by Saturday morning. By Monday, we had a targeted patch applied. I've never seen a vendor move that fast on something that wasn't in the original scope.
What stood out wasn't just the implementation quality; it was that their engineers understood why certain design decisions exist in these tools, not just how to configure them. That depth showed up every time we hit an edge case.
Built on Open Source. Contributing Back to It.
Work with a team that doesn't just implement big data solutions. They improve the tools that power them.
Frequently Asked Questions
The community eventually patches it, but between disclosure and a stable release, your deployment is exposed. Teams with engineers inside the codebase can assess impact and apply fixes immediately. Everyone else waits.
Our engineers have merged contributions across Apache Kafka, Apache Cassandra, Apache NiFi, Apache Airflow, Apache HBase, Apache Atlas, Apache Ambari, and StarRocks, covering SSL hardening, commit log fixes, API cleanup, processor-level bug corrections, and query engine performance patches.
Older versions stop receiving community patches, so known vulnerabilities accumulate over time. Safety on an older version requires someone actively monitoring the vulnerability landscape and applying targeted fixes; it is not a set-and-forget position.
When your implementation partner has already debugged NiFi processors, patched Cassandra commit log behaviour, and cleaned up Kafka’s API surface, that context shows up in your engagement. It does not come from reading documentation.
Upgrades are disruptive. For teams running critical pipelines, the risk of upgrading often feels higher than the risk of staying put, until a vulnerability or hard deprecation forces the issue.
We track the vulnerability landscape across the Apache ecosystem, assess client exposure when something surfaces, and work at the code level where a community patch is not yet available. This is possible because our engineers already operate inside these codebases.
A contribution needs to solve a real problem, meet the project’s coding standards, and survive review by committers who know the codebase deeply. Superficial or poorly scoped patches get rejected, which is why the merge rate is a meaningful signal.
Every contribution is publicly verifiable on GitHub. Our merged pull requests across Apache Kafka, Apache NiFi, Apache Cassandra, and StarRocks are on permanent public record. A 68.6% merge rate across 102 contributions reflects code that met Apache maintainer standards.
