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AI agents & downloadable tools

Open-source agents built for real storage and infrastructure workloads. Free to download, run, and extend.

Storage & performance

Storage benchmark agent

Describe a storage workload in plain English. The agent generates configs for fio, vdbench, iozone, and iometer, runs all four in parallel, parses IOPS / throughput / latency / CPU, and produces a full side-by-side comparison report saved to disk.

  • Natural language → fio + vdbench + iozone + iometer configs automatically
  • All 4 tools run concurrently via ThreadPoolExecutor — no waiting
  • Parses IOPS, throughput, P99 latency, and CPU from each tool
  • Full comparison report saved as JSON + text on every run
  • Dry-run mode — full simulation with no tools or API key needed
  • GitHub Actions CI included — green badge on every push
  • Rate-limit safe — 5s throttle keeps under Gemini free tier (15 RPM)
LangGraph Gemini 1.5 Flash fio vdbench iozone iometer ThreadPoolExecutor Python 3.9+
Docs
Agent flow
Natural language prompt
"70/30 R/W, 128K, 32 threads, 60s"
↓
Planner (Gemini)
generates 4 configs
↓ parallel
fio
vdbench
iozone
iometer
↓ parse all
Comparator (Gemini)
full report + recommendation
~68K
IOPS (sim)
4355
MB/s (sim)
650µs
read lat
<3%
tool variance
Quick start
$ pip install -r requirements.txt
$ export DRY_RUN=true
$ python storage_benchmark_agent.py
API & automation

REST API agent (LangGraph + CrewAI)

Two complete agent implementations — LangGraph and CrewAI — both targeting REST APIs from natural language prompts. Includes retry logic, exponential back-off on 5xx, Gemini free-tier throttling, and a side-by-side comparison runner.

  • LangGraph agent: stateful graph with conditional retry edges and MemorySaver checkpointing
  • CrewAI agent: 4-role crew — researcher, API caller, parser, writer
  • 5s throttle between LLM calls — stays under Gemini's 15 RPM free tier
  • Exponential back-off with jitter on 429 rate limit errors
  • Side-by-side runner compares both frameworks on the same query
  • Demo target: JSONPlaceholder — no auth, runs immediately
LangGraph CrewAI Gemini 1.5 Flash REST API Python 3.9+
LangGraph vs CrewAI
LangGraph — graph-based
Planner node
LLM decides endpoint
↓ tool call
REST executor
HTTP request + retry
↓ 200 OK
Formatter node
plain English answer
CrewAI — role-based
Researcher
API caller
Parser
Writer
Quick start
$ pip install langgraph crewai
$ export GOOGLE_API_KEY="AIza..."
$ python rest_api_agents_starter.py
Kubernetes & cloud

PrestoDB EKS scaling agent

Replaced a fragile Selenium-based browser automation workflow with an AI agent that autonomously scales a PrestoDB cluster on AWS EKS from 0 → 80 Kubernetes pods — supporting large-scale financial data query workloads at a financial institution.

  • Replaces Selenium browser automation with goal-driven agent execution
  • Scales PrestoDB from 0 → 80 EKS pods based on query load signals
  • Monitors pod readiness and coordinator registration before declaring scale complete
  • Fault-tolerant — retries failed pod schedules and handles node pressure
  • Built for a financial institution handling large distributed SQL queries
AWS EKS Kubernetes PrestoDB Python kubectl agentic AI
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Scaling flow
Query load signal
CPU / queue depth threshold
↓
Scale decision agent
LLM decides target replica count
↓ kubectl scale
pods 1–20
pods 21–40
pods 41–60
pods 61–80
↓ readiness check
80 pods ready
coordinator registered
0→80
pod scale
0
Selenium deps