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Oves Enterprise
Cloudera & Spark Optimization: Stabilizing a Petabyte-Scale Data Platform
Platform scale
petabytes
Spark job cadence
unreliable
→
daily
Cluster stability
corrupting
→
restored
Oves Enterprise builds analytics and consulting products for enterprises, combining industry expertise with large-scale data processing.
What changed
Before
Cluster
Cloudera
corruption in the distribution
Jobs
Spark
long, failing runs
Availability
Critical services down
After
Cluster
Cloudera
root causes fixed
New nodes
Jobs
Spark
algorithms reworked
Cadence
Daily runs
petabyte scale
A corrupting Cloudera cluster stabilised, then scaled out and tuned until the jobs could run every day.
What we built
We partnered with the client to stabilize and optimize an enterprise navigation application running on Cloudera and Spark, hosted entirely on-premise in a local data center. The platform was handling petabyte-scale workloads and had accumulated a range of systemic issues that were impacting performance, availability, and long-term maintainability.
Challenges Addressed
Corrupt Cloudera installation causing instability and service failures.
Growing data volumes (petabytes) requiring additional nodes for scalability.
Spark jobs running inefficiently, leading to unacceptably long processing times.
Hadoop configuration not fine-tuned for replication and resilience.
Vendor dependency on Cloudera limiting long-term flexibility.
Minimal monitoring and alerting, making it difficult to ensure system availability.
Results
Identified and fixed root causes of corruption in the Cloudera distribution.
Restored stability and availability of critical data services.
Added new nodes to handle petabyte-scale workloads.
Improved Spark job algorithms, significantly reducing execution times and enabling daily job runs.
Fine-tuned resource allocation across YARN for optimized job scheduling.
Tuned replication factors, I/O operations, and failover configurations.
Migrated from Cloudera to a vanilla Hadoop distribution with HA master, eliminating vendor lock-in.
Set up Prometheus and Grafana for real-time monitoring and alerting.
Stack
Engagement: Ongoing · Real-time & Industrial Data Platforms, Product Engineering, Platform & Cloud Engineering