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Instaclustr (NetApp)

Managed Cloud Data Platform

Instaclustr, part of NetApp, is a managed cloud platform for open-source data technologies. I worked on performance, reliability, security, and observability for provisioning and operating distributed data infrastructure.

Senior Software EngineerCompany ↗
CloudData InfrastructureJavaTypeScriptPythonAWSDockerTerraformAnsibleDatadog
Managed Cloud Data Platform screenshot

Overview

Instaclustr, part of NetApp, provides a managed cloud platform for open-source data technologies in Australia. Organizations use it to provision, deploy, and operate scalable data infrastructure across cloud environments.

As a Senior Software Engineer, I focused on platform performance, reliability, security, and observability.

The Challenge

Running a managed data platform means customers depend on it to provision and operate distributed clusters, not just to host a single service. Performance problems show up as slow queries and system bottlenecks. Security work includes finding and addressing vulnerabilities. Operators also need enough visibility to understand what the platform is doing in production.

The platform exposes that capability through APIs and Terraform, so the services behind provisioning and cluster management have to stay reliable as infrastructure is automated.

My Role

  • Designed and developed cloud-native microservices
  • Optimized database queries and identified system bottlenecks
  • Assessed and addressed security vulnerabilities through CVE reviews
  • Peer PR review and involved with team on Software Development
  • Developed infrastructure automation
  • Enhanced system monitoring with Datadog
  • Supported APIs and Terraform integrations used to provision and manage distributed data clusters

Architecture

Customers and automation reach the platform through APIs and Terraform. Those entry points sit in front of cloud-native microservices that provision and operate distributed data clusters.

The services run on AWS with Docker. Ansible is part of the infrastructure automation. Datadog provides the monitoring used to observe the platform. The diagram is a simplified view of those integrations, not a full system design.

Engineering highlights

  1. 01

    Performance and reliability

    Contributed to cloud-native microservices, optimized database queries, and identified system bottlenecks on the managed data platform.

  2. 02

    Security

    Assessed and addressed security vulnerabilities through CVE reviews.

  3. 03

    Observability

    Improved system monitoring with Datadog so platform behavior was easier to see in production.

  4. 04

    Cluster provisioning

    Supported APIs and Terraform integrations used to provision and manage distributed data clusters, along with infrastructure automation and technical design reviews.

Architecture (simplified)

┌──────────────────────┐
│   APIs / Terraform   │
└──────────┬───────────┘
           │
           ▼
┌──────────────────────┐
│ Cloud-native         │
│ microservices        │
│                      │
│ Provisioning         │
│ Operations           │
└──────────┬───────────┘
           │
           ▼
┌──────────────────────┐
│ Distributed clusters │
│                      │
│ AWS · Docker         │
│ Ansible · Datadog    │
└──────────────────────┘