---
esco_uri: http://data.europa.eu/esco/skill/9ba8fd27-275d-4bad-8c48-f668aa99a578
esco_label: "balance database resources"
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
---

# balance database resources — Database Administrator

As a Database Administrator (DBA), 'balancing database resources' isn’t about theoretical optimization – it’s *constant* firefighting and proactive tuning. Daily, you're looking at things like CPU utilization on your database servers, disk I/O bottlenecks, memory pressure, and network latency. Typical tasks include monitoring long-running queries that hog resources (using tools like Performance Monitor in Windows or `top`/`iotop` in Linux), identifying tables needing indexing adjustments, and configuring connection pooling to prevent resource exhaustion from too many simultaneous requests. You'll also be managing storage – adding disk space, archiving old data, and potentially migrating to faster storage tiers.

A big part of this competence is understanding *how* different applications use the database. A poorly written application can easily overwhelm a perfectly tuned system. So you’re often collaborating with developers to review queries, suggest code changes, or implement caching strategies. Tools like SQL Server Profiler/Extended Events, Oracle's AWR reports, or PostgreSQL's `pg_stat_statements` are your bread and butter for pinpointing problem areas.  Pitfalls include blindly applying 'best practices' without understanding the specific workload, ignoring slow-but-frequent operations (they add up!), and failing to monitor proactively – waiting until users complain is too late.

The ‘cost/risk ratio’ aspect means you aren’t just maximizing performance at any cost.  You need to balance speed with storage costs, server licensing fees, and the potential for downtime during maintenance or upgrades. For example, choosing between more RAM (expensive) versus optimizing queries (time-consuming but cheaper). Reliability is key – ensuring backups are running correctly, disaster recovery plans are tested, and servers have sufficient redundancy.

Good looks like a database that consistently meets service level agreements (SLAs), minimal performance complaints from users, predictable resource usage patterns, and the ability to scale efficiently as data volumes grow. It's about *preventing* problems before they impact business operations, not just reacting to them.

## Weitere Anreicherung

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