The autonomous cloud FinOps middleware for high-throughput Nextflow and WDL workflows. Powered by low-overhead Rust eBPF kernel profiling, dynamic container right-sizing, and autonomous AWS Spot & GCP Preemptible recovery with zero task evictions.
Compute Waste Reclaimed
Linux eBPF Kernel Overhead
Workflow Code Changes
Concurrent Container Scale
Traditional cloud tools only observe billing after instances terminate. BaseScale operates directly in the Linux kernel, optimizing workloads in real-time before, during, and after execution.
Statically parses standard Nextflow DSL2 and WDL 1.0 workflow files. Constructs topological DAG execution waves and executes predictive Spot pre-warming T-120 seconds in advance to eliminate cold-start queue bottlenecks.
Pure-Rust basescale-ebpf-agent attaching to kernel tracepoints (sched_switch, page faults, block I/O). Captures true physical RSS high-water marks without user-space overhead.
Bioinformatics tasks routinely request 64GB+ for worst-case peaks. BaseScale dynamically recommends P95 consumption + 25% safety headroom, slashing overprovisioned memory spend by up to 85.6%.
Intercepts AWS EC2 IMDSv2 preemption warnings, checkpoints active container memory states to S3 in under 12 seconds, and re-dispatches tasks on stable capacity pools with zero failed jobs.
Probes strictly profile task hashes, PIDs, and memory limits. Raw biological files (.fastq, .bam, .vcf) are architecturally prevented from socket egress.
Every provisioning recommendation, spot auction bid, and container resize is cryptographically recorded using SHA-256 block hashing, ready for continuous enterprise compliance audits.
A zero-touch, dual-layer architecture spanning Linux kernel probes on worker nodes and a centralized FinOps intelligence engine.
Parses Nextflow .nf or WDL .wdl graphs. Computes execution wave dependencies and dispatches predictive Spot warming T-120s early.
Aya-compiled daemon attaching to tracepoints inside compute nodes. Observes container high-water marks and ring-buffer events with <1% CPU footprint.
Hardware-accelerated transport with custom binary framing codec (GENX). Strictly verifies zero biological string patterns before transmission.
Evaluates spot market volatility across AWS Batch and GCP Batch. Resizes container allocations dynamically and handles automated S3 preemption snapshot recovery.
# 1. Zero-Rewrite Nextflow awsbatch.config integration
process {
executor = 'awsbatch'
queue = 'genix-basescale-spot-queue-prod'
// BaseScale automatically intercepts and optimizes without code alterations:
withName: 'ALIGN_STAR' {
cpus = { check_max( 12 * task.attempt, 'cpus' ) }
memory = { check_max( 64.GB * task.attempt, 'memory' ) }
}
}
# Command to execute (transparently rightsized on Spot):
$ nextflow run nf-core/rnaseq -profile basescale_spot --input samplesheet.csv
Calculated from empirical eBPF kernel memory RSS distributions and historical AWS EC2 Spot market rates.
Based on empirical P95 right-sizing & Spot pre-warming
Generated directly by our programmatic benchmark simulator across industry-standard genomics pipelines.
| Pipeline Profile | Orchestrator | Baseline (On-Demand) | BaseScale (Spot + Right-Sizing) | Dollar Savings | Savings % | Memory Reclaimed |
|---|---|---|---|---|---|---|
| nf-core/rnaseq (Transcriptomics) | Nextflow DSL2 | $990.96 | $244.24 | -$746.72 | 75.4% | 50,600 GB-hrs |
| nf-core/sarek (30x WGS Germline) | WDL 1.0 / Nextflow | $3,408.00 | $790.18 | -$2,617.82 | 76.8% | 208,600 GB-hrs |
| Combined Multi-Cohort Impact | Hybrid Nextflow + WDL | $4,398.96 | $1,034.42 | -$3,364.54 | 76.5% | 259,200 GB-hrs |
Biopharma organizations cannot compromise on patient data sovereignty. BaseScale is architected from the ground up with zero payload exposure, certified for clinical diagnostic and commercial drug discovery operations.
Localized low-latency orchestration for key research clusters:
Deploy BaseScale in non-intrusive Read-Only Audit Mode. Profile 10,000+ biological tasks to see exactly how much cloud compute spend you will reclaim before turning on active optimization.