pumpwood-deploy-estimation

Satellite deploy package for the Pumpwood Estimation microservice on Kubernetes. It generates manifests for the API application and estimation secrets — then hands them to pumpwood-deploy for apply.

Developed by Murabei Data Science. BSD-3-Clause.

Pumpwood is a native Brazilian tree with a symbiotic relation to ants (Murabei)

---

What it deploys

Manifest	Kubernetes resources
pumpwood_estimation__secrets	Secret pumpwood-estimation
pumpwood_estimation__deploy	Deployment + Service pumpwood-estimation-app

Estimation defines model parameters and the attributes used as inputs and outputs of mathematical models. The app serves HTTP APIs.

flowchart LR
    subgraph pkg [pumpwood-deploy-estimation]
        A[PumpWoodEstimationMicroservice]
    end
    subgraph core [pumpwood-deploy]
        B[DeployPumpWood]
    end
    subgraph cluster [Cluster]
        ES[pumpwood-estimation Secret]
        APP[pumpwood-estimation-app]
        RMQ[rabbitmq-main]
    end
    A --> B
    B --> ES
    B --> APP
    ES --> APP
    RMQ --> APP

---

Prerequisites

This package does not stand alone. Before estimation pods can start, the cluster must already provide:

Resource	Provided by
storage ConfigMap	StandardMicroservices in pumpwood-deploy
general-secrets	StandardMicroservices
rabbitmq-main-secrets	StandardMicroservices
Storage keys (GCP / Azure / AWS)	DeployPumpWood storage config
Postgres for estimation	PostgresDatabase + PGBouncerDatabase
Auth (typical)	pumpwood-deploy-auth

Storage bucket name and type are read from the cluster storage ConfigMap — they are not passed to PumpWoodEstimationMicroservice.

The application reads DB_PASSWORD and MICROSERVICE_PASSWORD from the pumpwood-estimation secret created by this package.

---

Installation

pip install pumpwood-deploy-estimation

Requires pumpwood-deploy.

---

Quick start

import os
import simplejson as json
from dotenv import load_dotenv
from pumpwood_deploy.deploy import DeployPumpWood
from pumpwood_deploy.microservices.postgres.deploy import (
    PostgresDatabase, PGBouncerDatabase)
from pumpwood_deploy_estimation import PumpWoodEstimationMicroservice

with open("secrets/production.json", "r") as file:
    secrets = json.loads(file.read())
load_dotenv()

deploy = DeployPumpWood(
    model_user_password=secrets["microservices--model"],
    rabbitmq_secret=secrets["rabbitmq_secret"],
    hash_salt=secrets["hash_salt"],
    storage_type="aws_s3",
    storage_deploy_args={
        "storage_bucket_name": "my-pumpwood-bucket",
        "access_key_id": secrets["aws_access_key_id"],
        "secret_access_key": secrets["aws_secret_access_key"],
    },
    k8_provider="aws",
    k8_deploy_args={
        "region": "us-east-1",
        "cluster_name": "my-cluster",
    },
    k8_namespace="pumpwood",
)

deploy.add_microservice(
    PostgresDatabase(
        db_username="pumpwood",
        db_password=secrets["postgres_password"],
        name="postgres-main",
        disk_name="postgres-disk",
        disk_size="150Gi",
    ))

deploy.add_microservice(
    PGBouncerDatabase(
        name="pgbouncer-pumpwood-estimation",
        postgres_database="pumpwood_estimation",
        postgres_secret="postgres-main",
        postgres_host="postgres-main",
    ))

deploy.add_microservice(
    PumpWoodEstimationMicroservice(
        app_version=os.getenv("PUMPWOOD_ESTIMATION_APP"),
        repository="my-registry.example.com",
        db_host="pgbouncer-pumpwood-estimation",
        db_database="pumpwood_estimation",
        db_password=secrets["postgres_password"],
        microservice_password=secrets["microservice--estimation"],
        app_replicas=1,
        app_debug="FALSE",
    ))

deploy.create_deploy_files()
deploy.deploy_microservices()

Environment variables

PUMPWOOD_ESTIMATION_APP=2.1.0

If the rendered manifest matches what is already on the cluster, kubectl apply produces no changes — safe for rolling image updates.

---

Configuration reference

Required

Parameter	Description
app_version	Image tag for pumpwood-estimation-app

Application database

Connection metadata for the app. Passwords are stored in the estimation secret and mounted at runtime.

Parameter	Default	Description
db_host	pgbouncer-pumpwood-estimation	Postgres host
db_port	5432	Postgres port
db_database	pumpwood	Database name
db_username	pumpwood	Database user
db_password	pumpwood	Stored in estimation secret
microservice_password	microservice--estimation	Estimation service user
repository	GCR default	Docker registry for the app

Application

Parameter	Default	Description
app_replicas	1	Number of app pods
app_debug	FALSE	Debug flag
app_workers	10	Granian workers (GRANIAN_WORKERS)
app_timeout	300	Request timeout (seconds)
app_limits_memory	60Gi	Memory limit
app_limits_cpu	12000m	CPU limit
app_requests_memory	20Mi	Memory request
app_requests_cpu	1m	CPU request

---

Health check

The app Deployment exposes a readiness probe at:

GET /health-check/pumpwood-estimation-app/  (port 5000)

Use this path for ingress and load balancer health checks.

---

Migration note

Older deploy scripts imported from the monolithic package:

# Before
from pumpwood_deploy.microservices.pumpwood_estimation.deploy import (
    PumpWoodEstimationMicroservice)

# After
from pumpwood_deploy_estimation import PumpWoodEstimationMicroservice

Removed from the satellite API (use cluster-level config instead):

• bucket_name — now from storage ConfigMap
• test_db_* — use PostgresDatabase / PGBouncerDatabase from core
• worker_version, datalake_db_*, worker_* — raw-data worker deploy removed from this package

---

Related packages

Package	Role
pumpwood-deploy	Orchestrator, Kong, RabbitMQ, Postgres
pumpwood-deploy-datalake	Datalake microservice
pumpwood-deploy-auth	Authorization microservice

Full platform documentation: Murabei Open Source — pumpwood-deploy.

---

Development

pip install -e ../pumpwood-deploy
pip install -e .

PYTHONPATH="src:../pumpwood-deploy/src" \
  python3 -m unittest discover \
  -s src/pumpwood_deploy_estimation/tests -p "test_*.py" -v

ruff check src/

---

License

BSD-3-Clause — see LICENSE.