Haystack Analytics
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Eventum.run
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Haystack is a real-time delivery analytics platform designed for engineering leaders like CTOs, VPs of Engineering, Directors of Software Engineering, and Engineering Managers. Haystack provides actionable insights that enable data-driven decision-making, aligning engineering performance with business objectives. Haystack platform integrates seamlessly with essential developer tools like GitHub and JIRA, offering a comprehensive view of team productivity and delivery efficiency.
Leading companies like AngelList, Shutterstock, Schneider Electric, and many more trust Haystack to optimize their development processes. By transforming historical Git data into objective insights, we help you identify bottlenecks and visualize trends, ensuring timely project delivery and sustained business growth. Our analytics dashboard allows you to monitor critical metrics such as cycle time, making it easier to spot inefficiencies before they escalate into costly delays.
Haystack helps engineering leaders to mitigate risks and improve workflow efficiency. With a unified view of the entire delivery lifecycle, you can track KPIs, compare performance trends, and make informed decisions that drive measurable outcomes. Our platform goes beyond merely measuring productivity; it equips you with the tools to foster continuous improvement and innovation within your teams.
Designed to scale with your organization, Haystack is the competitive advantage that data-driven engineering teams need to thrive. By leveraging analytics, you can transform your engineering operations, enhance collaboration, and accelerate your path to market success. Join top companies in harnessing the power of Haystack for a more efficient and effective engineering process.
Describe events, schedule them, and stream to ClickHouse, OpenSearch, Kafka, files or any HTTP endpoint. Eventum is used for testing pipelines and detection rules, live demos, seeding databases and load testing.
Highlights: - Pipeline of three swappable stages: when events happen, what they contain, where they go - Scheduling from cron and fixed intervals to statistical time patterns - Jinja templates with an extended API (Faker and Mimesis data generators, weighted random helpers, CSV/JSON samples, and more), or Python scripts when templates aren't enough - Stateful generation: three scopes of state plus a finite state machine mode for multi-step scenarios - Parallel fan-out: stdout, files, ClickHouse, OpenSearch, Kafka, any HTTP endpoint - Live mode (events fire at their timestamps) or sample mode (everything at once) - Eventum Studio web UI, REST API, and an MCP server for AI agents
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Haystack Analytics's answer
Engineering Leaders and Managers
Eventum.run's answer:
Data engineers, SIEM and detection engineers, and developers who need realistic data for testing pipelines, live demos, seeding databases or load testing - teams that would otherwise write throwaway generator scripts.
Eventum.run's answer:
Python (FastAPI, Pydantic, Jinja2) for the engine, CLI and REST API; React + TypeScript for the Eventum Studio web UI. Ships as a pip package and Docker image.
Eventum.run's answer:
Libraries like Faker give you fake values - Eventum gives you the whole pipeline: scheduling, templating, state, and parallel delivery to ClickHouse, OpenSearch, Kafka, files or any HTTP endpoint. And it ships with Eventum Studio, a web UI where you preview and debug events before anything goes live.
Eventum.run's answer:
Most data generators produce random values at a flat rate. Eventum also models behavior: traffic follows cron schedules, intervals or statistical time patterns with peaks, bursts and quiet periods, and templates persist state between events - three scopes of state plus a finite state machine mode for multi-step scenarios like user sessions.
Eventum.run's answer:
The author works on a data analytics platform similar to Splunk, where every customer demo needs a believable case running on data that looks alive. The team generated demo data with Splunk Eventgen, but the workflow never felt convenient, so around 2023 he started building his own generator. It grew into Eventum, now used by his SIEM team and data engineers daily.
Eventum.run's answer:
Internal SIEM and data engineering teams at the author's Cyber Security company
Based on our record, Haystack Analytics seems to be more popular. It has been mentiond 2 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
Heads up: site is not loading. Ios Safari & macOS Chrome. Mixed Content: The page at 'https://usehaystack.io/' was loaded over HTTPS, but requested an insecure favicon 'http://www.usehaystack.io/favicon.ico'. This request has been blocked; the content must be served over HTTPS. - Source: Hacker News / over 5 years ago
Hey HN! I'm Julian, co-founder of Haystack (https://usehaystack.io). Weโre building one-click dashboards and alerts using Github data. While managing teams from startups to more established companies like Cloudflare, my cofounder Kan and I were constantly trying to improve our team and process. But it was pretty tough to tell if our efforts were paying off. Even tougher to tell where we could improve. We tried... - Source: Hacker News / over 5 years ago
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