Understanding Scaleway's Architecture and Service Model

Key Service Layers

Scaleway's main offerings include:

• Compute Instances (DEV1, GP1, PLAY2, etc.)
• Object Storage (S3-compatible)
• Kubernetes Kapsule
• Serverless Functions and Containers
• Load Balancers and Private Networks

These services are tied together using IAM, Organization Projects, and APIs accessible via CLI or console. Understanding how services interconnect is essential for diagnosing cross-service issues.

Regions and Availability Zones

Scaleway provides multiple AZs across France and the Netherlands. Some services are region-specific, which can cause deployment errors if not handled carefully.

Common Operational Issues and Root Causes

1. Instance Boot Failures or Delays

Instances may fail to boot or experience long provisioning times during peak usage. This often correlates with resource saturation in specific AZs.

scw instance server create name=prod-app-1 commercial-type=DEV1-S region=fr-par-1

Workaround: Try alternative AZs (e.g., fr-par-2) or increase resource quotas via support.

2. Intermittent Network Throttling

Some users report degraded network throughput on lower-tier instance types. This is due to soft caps placed on burstable bandwidth.

Fix: Use GP1 or higher tiers for stable bandwidth. Monitor network metrics via the Scaleway console or custom Prometheus exporters.

3. Object Storage Inconsistencies

S3-compatible object storage may return inconsistent headers or slow reads during high I/O. The lack of strong eventual consistency can affect CI/CD artifact fetches.

Mitigation: Use pre-signed URLs with explicit caching headers and retry logic. Avoid concurrent HEAD requests for the same object.

4. API Rate Limits

Scaleway imposes undocumented or soft rate limits on their public API, especially when used via CI/CD scripts.

Workaround: Implement exponential backoff and logging when using scw CLI or Terraform provider in automation flows.

5. Billing Surprises and Ghost Resources

Instances left in a stopped state still incur storage charges. Unlinked volumes, orphaned IPs, and unused snapshots also contribute to unexpected bills.

scw instance volume list | grep -i available

Fix: Regularly audit resources using scripts or the Scaleway Inventory service.

Diagnostics and Monitoring

Using Scaleway CLI for Auditing

scw instance server list
scw instance volume list
scw instance ip list
scw object bucket list

Use --output json for scripting and integration with log aggregation tools.

Monitoring via Metrics and Logs

Enable metrics on Kubernetes and Instances using:

scw monitoring contact create
scw monitoring alert create --metric-type=cpu.usage --threshold=80

Integrating with External Monitoring

Use Prometheus exporters and Fluent Bit to ship metrics/logs to Grafana, Datadog, or ELK. For object storage access metrics, log S3 events to webhook endpoints.

Step-by-Step Troubleshooting Guide

Step 1: Validate Resource Quotas

Check quotas in the project settings, especially if automation scripts start failing unexpectedly:

scw account quota list

Step 2: Switch Availability Zones

Provisioning errors may be region-specific. Adjust the zone parameter in CLI or Terraform configs.

region=nl-ams-1 zone=nl-ams-1a

Step 3: Audit Orphaned Resources

Scan for unattached volumes, stale IPs, and unused snapshots:

scw instance volume list --output json | jq '.[] | select(.server == null)'

Step 4: Handle Rate Limits Gracefully

Wrap API calls with retry/backoff logic in CI/CD jobs:

until scw instance server list; do sleep 5; done

Step 5: Monitor for Network or Storage Anomalies

Use instance metrics or system-level tools like iftop and iotop to detect throttling in real time.

Best Practices for Enterprise Use

• Use GP1 or PRO instance types for production workloads
• Set up auto-cleanup jobs for stopped instances and detached volumes
• Avoid relying on a single AZ or region for availability
• Use IAM roles and access tokens with tight scoping
• Tag all resources for traceability and billing

Conclusion

Scaleway is a flexible and modern cloud provider, but like all platforms, it introduces operational challenges at scale. By understanding its architecture, proactively monitoring resources, and scripting defensive automation, technical leads can minimize outages, billing shocks, and degraded performance. For enterprise-grade reliability, teams must treat Scaleway with the same rigor as AWS, GCP, or Azure—especially when running production workloads or CI/CD pipelines.

FAQs

1. Why do stopped instances still incur charges?

While CPU/RAM is paused, the storage volumes remain allocated. These volumes continue to generate costs until deleted or detached.

2. Can Scaleway handle production-grade Kubernetes?

Yes, Kapsule is stable for production use, but it lacks advanced autoscaling features compared to EKS or GKE. Ensure multi-AZ setups for HA.

3. How do I avoid hitting API rate limits?

Use exponential backoff, avoid aggressive polling, and throttle automation scripts. Also consider batching resource queries.

4. What monitoring tools integrate best with Scaleway?

Prometheus, Grafana, Datadog, and ELK integrate well using exporters and agents deployed within instances or Kubernetes pods.

5. How can I optimize object storage performance?

Use multi-part uploads for large files, set proper cache headers, and avoid frequent metadata requests. Distribute access load via pre-signed URLs.