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Sift Tech Stack
Machine data platform for complex systems monitoring and analysis
Sift ingests and analyzes machine telemetry at scale using a polyglot stack (Go, Java, Rust, Python) backed by streaming (Kafka, Redpanda, Flink) and time-series databases (Druid, Pinot, Timescale). The engineering-heavy org (20 engineers across 35 total hires) is actively building monitoring/alerting, secure CI/CD, and zero-trust infrastructure—suggesting both product maturation and internal security hardening. Pain points center on scaling telemetry ingest and bottleneck elimination, core challenges for real-time data platforms serving high-frequency sensor workloads.
Tech Stack 69 technologies
Core StackAWS Docker Kubernetes Terraform Go Java React TypeScript Kafka Apache Flink Python Next.js Rust PostgreSQL gRPC Redux Azure GCP AWS CDK Redpanda Druid Apache Pinot Timescale ECharts WebGL D3.js WebAssembly Protocol Buffers Arrow DataFusion+35 more
What Sift Is Building
◆Challenges
- Scaling telemetry
- Eliminating bottlenecks
- High-frequency telemetry bottlenecks
- Adoption of technical products
- Improving infrastructure reliability, performance, and cost efficiency
- Faster, more reliable development
- Scaling early-stage platform
- Ensuring mission reliability
- Improving infrastructure reliability
- Ensuring resilience against modern threats
▲Active Projects
- Monitoring and alerting systems
- Build secure ci/cd pipelines
- Scalable infrastructure solutions
- High-performance scalable systems for data processing and visualization
- Lead soc 2 compliance
- Implement zero-trust networking
- Reusable component libraries for complex telemetry data
- Deployment automation
- Pilot design and execution
- Implementation roadmap development
Hiring Activity
45 roles · 10 in 30d
Department
Seniority
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