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This is a hard difficulty System Design question, commonly asked during Technical Screen rounds at Current.

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This question is commonly asked for Software Engineer candidates at Current during technical interviews.

Design a metrics monitoring system | Current Interview Question

Quick Overview

This question evaluates system design and distributed-systems competency, focusing on large-scale time-series monitoring including ingestion pipelines, compression and tiered storage, query language and alerting, multi-tenant isolation, and operational resilience in the System Design category.

System Design: Metrics Monitoring Platform

Context

Design a cloud‑native, multi‑tenant metrics monitoring system for internal services. The system must support counters, gauges, and histograms with labels/tags, ingest via pull and push, provide a query language, alerting, dashboards, and strong operational characteristics (HA, scale, quotas, isolation).

You may assume an illustrative scale (adjust as needed):

Aggregate ingest: up to 10M samples/sec across tenants.
Retention: 7 days hot, 12 months cold.
Query SLO: p99 < 2s for 6h range queries.
Availability target: 99.9%.

Requirements

Ingestion
- Collect numeric metrics (counter/gauge/histogram) with labels/tags.
- Support pull (scraping endpoints) and push ingestion.
- Handle high throughput and provide backpressure.
Storage
- Efficient time‑series storage with compression.
- Retention tiers: hot vs. cold storage; support downsampling.
Query
- Provide a query language for aggregations, label filtering, and downsampling.
- Support federated queries across hot/cold tiers.
Alerting
- Threshold and SLO‑based alerts; silencing, deduplication, routing.
Operations
- High availability, horizontal scalability, and multi‑tenant isolation.
- Control cardinality growth; enforce quotas and rate limits.
- Expose dashboards and APIs.
Architecture Deep Dives
- Discuss data model, sharding, indexing.
- Detail write/read paths, failure handling, and consistency choices.

Deliverables

End‑to‑end architecture proposal with components and data flow.
Rationale and trade‑offs for key design choices.
Guardrails for cardinality, quotas, and backpressure.
Failure scenarios and recovery strategies.
API surface and operability plan (dashboards, SLOs).

Quick Overview

Context

You may assume an illustrative scale (adjust as needed):

Aggregate ingest: up to 10M samples/sec across tenants.

Retention: 7 days hot, 12 months cold.

Query SLO: p99 < 2s for 6h range queries.

Availability target: 99.9%.

Requirements

Ingestion

Collect numeric metrics (counter/gauge/histogram) with labels/tags.
Support pull (scraping endpoints) and push ingestion.
Handle high throughput and provide backpressure.

Storage

Efficient time‑series storage with compression.
Retention tiers: hot vs. cold storage; support downsampling.

Query

Provide a query language for aggregations, label filtering, and downsampling.
Support federated queries across hot/cold tiers.

Alerting

Threshold and SLO‑based alerts; silencing, deduplication, routing.

Operations

High availability, horizontal scalability, and multi‑tenant isolation.
Control cardinality growth; enforce quotas and rate limits.
Expose dashboards and APIs.

Architecture Deep Dives

Discuss data model, sharding, indexing.
Detail write/read paths, failure handling, and consistency choices.

Design a metrics monitoring system

Quick Overview

System Design: Metrics Monitoring Platform

Context

Requirements

Deliverables

Solution

Submit Your Answer

Design a metrics monitoring system

Quick Overview

System Design: Metrics Monitoring Platform

Context

Requirements

Deliverables

Solution

Submit Your Answer