---
esco_uri: http://data.europa.eu/esco/skill/897b393f-e7e0-4248-a40d-d77119694e83
esco_label: "distributed computing"
relation: essential
onet_soc: 15-1242.00
source: model-knowledge
confidence: high
qa_count: 0
generator: gemma3:27b (prompt-designed and spot-checked by Claude)
generated: 2026-07-10
---

# distributed computing — Database Administrator

As a Database Administrator, 'distributed computing' isn’t about *writing* distributed systems – it’s about *managing* them. Increasingly, databases aren't monolithic servers; they're clusters of nodes (think Oracle RAC, SQL Server Always On Availability Groups, PostgreSQL with streaming replication, or cloud-native solutions like Amazon Aurora/DynamoDB). Your daily tasks involve monitoring the health and performance of these distributed database instances, ensuring data consistency *across* those instances, and managing failover scenarios. This means understanding concepts like two-phase commit, consensus algorithms (even if you don't implement them!), and how network latency impacts transaction times.

Typical tools shift from single-server monitoring to cluster-aware solutions: things like Prometheus/Grafana with custom exporters for database metrics, specialized RAC/AG monitoring tools, or cloud provider dashboards. You’ll be troubleshooting replication lag, identifying slow nodes impacting overall performance, and diagnosing network issues that cause data inconsistencies.  Pitfalls include assuming a single server's diagnostic approach will work on a distributed system – you need to consider the *entire* cluster state. Also, complex configurations can easily lead to split-brain scenarios or incorrect failover behavior if not carefully planned and tested.

Good looks like proactively identifying potential issues before they impact users. This means setting up robust alerting based on cross-node metrics (e.g., replication lag exceeding a threshold *on multiple* nodes), automating routine maintenance tasks across the cluster, and having well-documented disaster recovery plans that account for network partitions or node failures.  It also involves understanding how your database’s distributed architecture impacts application design – advising developers on best practices for data access patterns to minimize cross-node communication.

Finally, 'distributed computing' competence extends to related technologies like caching layers (Redis, Memcached) often deployed *alongside* databases to improve performance and scalability.  DBAs need to understand how these systems interact with the database cluster and ensure data consistency between them.

## Weitere Anreicherung

Stage-2 source for future practitioner grounding: arXiv cs.SE (software-engineering preprints).
