Understanding Knowledge in IT and hosting: What It Is
When people talk about “knowledge” in IT and hosting, they don’t mean just files or facts. Knowledge is a mix of raw data, proven procedures, context about systems, and the practical experience engineers use to make decisions. You can think of it as three connected layers: the facts (IP addresses, config values), the explanations (why a service fails under load), and the practiced know-how (the steps you take during a migration or an outage). In hosting and IT, that bundled understanding is what keeps services running, helps teams respond to incidents fast, and allows new members to pick up complex chores without repeating mistakes.
Types of Knowledge You’ll Encounter
Explicit knowledge
This is the stuff you can write down: manuals, configuration files, API docs, diagrams, runbooks, and code. Explicit knowledge is the easiest to store, search, and version. For example, an Infrastructure-as-Code template or a checklist for deploying a load balancer is explicit knowledge,anyone who reads it can replicate the steps.
Tacit knowledge
Tacit knowledge lives in people. It’s the intuition a senior sysadmin has about a flaky network card, the pattern recognition that helps an engineer spot a slow-degrading service, and the shortcuts learned over years. Tacit knowledge is hard to write down but extremely valuable during an incident. It often shows up in mentoring, pair troubleshooting, or an experienced engineer’s offhand tip that fixes a problem quickly.
Contextual knowledge
Context is what connects explicit and tacit knowledge: business priorities, service-level objectives, historical incidents, and relationships between systems. Knowing that a particular database is low-risk versus mission-critical changes how you respond to alerts and prioritize fixes.
How Knowledge Actually Works in Hosting and IT
Knowledge flows through a simple cycle: capture, organize, share, apply, and update. In practice, this cycle determines how effective your team will be at running and evolving infrastructure.
First you capture knowledge,through documents, recorded run-throughs, or code. Then you organize it so it’s findable: tag documents, maintain a knowledge base, or link runbooks to services in your configuration management database. Sharing happens via meetings, onboarding sessions, and shared wikis. Applying knowledge is day-to-day operations: follow a runbook during a deploy, use a diagnostic procedure during an outage. Finally, you update knowledge after any significant action: postmortems add corrections, automation replaces manual steps, and lessons learned become part of the next iteration.
Practical pathways: how this looks on the job
Imagine an outage: monitoring alerts fire, on-call engineers consult runbooks and dashboards, they run diagnostic commands, and make a change to restore service. After the incident, they write a postmortem, update the runbook with the steps that actually worked, and commit configuration fixes to version control. That whole loop,alert, diagnose, fix, document,keeps knowledge current and reduces time to recovery on future incidents.
Tools and Practices That Make Knowledge Work
Some tools are better suited to capturing explicit knowledge, others help preserve tacit knowledge, and many do both. The effective use of these tools is less about having every product and more about making them part of routine work so knowledge stays fresh and discoverable.
- Documentation systems: wikis, Confluence, or Markdown repositories for runbooks and architecture notes.
- Version control: git for configs, IaC, and docs so changes are tracked and reversible.
- Ticketing and CMDB: track incidents, link assets and services, and keep ownership visible.
- Chat ops and recorded sessions: searchable chat logs, session recordings, and shared commands (with care for secrets).
- Postmortems and retrospectives: a place to capture what worked, what failed, and corrective actions.
- Automation: CI/CD pipelines, configuration management, and playbooks to codify manual steps.
- Onboarding and shadowing: structured shadowing sessions to pass tacit knowledge to new team members.
Common Problems and How Knowledge Breaks Down
Knowledge fails when it’s stale, siloed, or hard to find. Stale docs give a false sense of safety; automated systems drift, and the documentation doesn’t match reality. Siloed knowledge exists only in a few people’s heads; if they leave, you lose the context. Poor searchability or inconsistent organization means the right procedure may exist but you can’t find it in time. There are also cultural issues: if teams don’t update runbooks after an incident, knowledge doesn’t improve. Finally, security concerns can make teams hide information, which can block quick responses during emergencies,balancing openness and access control is essential.
How to Improve Knowledge Flow in Your Hosting and IT Work
You can take several practical steps that pay off quickly. The simplest is to require a short postmortem and runbook update after any significant change or outage. Have a template for runbooks that includes symptoms, quick checks, mitigation steps, and escalation paths. Use version control and include links to commits that fixed an issue. Automate repetitive, error-prone tasks so the knowledge is encoded in scripts rather than buried in people’s heads. Pair engineers on critical operations and rotate on-call duties to spread tacit knowledge. Make search a priority: tag content, add summaries, and keep documentation concise and indexed.
Checklist: actions to take this week
- Create or update a runbook for your top 5 services.
- Store runbooks in version control and link them to monitoring alerts.
- Schedule at least one shadowing session for each new hire.
- Run a short postmortem template after any incident and log action items.
- Automate the most common manual deployment or recovery steps.
Examples: Knowledge in Real Hosting Scenarios
If you’re migrating from on-prem to cloud hosting, explicit knowledge includes migration scripts, network diagrams, and cost estimates. Tacit knowledge includes the quirks you learned about legacy systems,like a service that only accepts connections from a specific subnet. Capturing both means recording the migration steps, tagging any special cases, and scheduling walkthroughs so the operations team understands the trade-offs. In another scenario, an intermittent performance issue might require combining monitoring metrics (explicit) with an experienced engineer’s pattern recognition (tacit) to identify slow GC cycles and then automate heap dumps when latency spikes.
Measuring Knowledge Health
You can gauge how healthy your knowledge is by measuring a few signals: mean time to recovery (MTTR) often drops as knowledge improves, the number of incidents repeated for the same root cause should decline, and onboarding time for new hires should shorten. Other signals include the percentage of incidents with completed postmortems, the frequency of runbook updates, and search success rates in your documentation system. Use these metrics to focus improvement work,if MTTR isn’t improving, look at runbook quality and on-call training.
Summary
Knowledge in hosting and IT is more than documents or commands; it’s the blend of facts, context, and experience that lets teams run, repair, and evolve systems reliably. To make knowledge useful, capture it, organize it, share it, apply it, and update it. Use tools like version control, wikis, and automation to reduce the burden on people, and encourage practices like postmortems and shadowing to preserve tacit know-how. With consistent habits, you make your infrastructure more resilient and your team faster at solving problems.
FAQs
1. What’s the difference between documentation and knowledge?
Documentation is the recorded part,manuals, diagrams, runbooks. Knowledge includes documentation plus the experience and intuition people use in real situations. Documentation captures explicit knowledge; experience captures tacit knowledge.
2. How do I prevent knowledge loss when people leave?
Encourage documentation of important procedures, require handover sessions, record critical troubleshooting runs, and rotate responsibilities so more than one person understands each system. Exit interviews and shadowing help transfer tacit knowledge.
3. Should runbooks be automated or human-readable?
Both. Keep human-readable runbooks for understanding and escalation, and automate repeatable steps when possible. Automation reduces human error, while readable runbooks help humans make judgment calls when automation fails.
4. How often should I update my knowledge base?
Update it after any significant change: post-incident, after deployments that change behavior, or when someone discovers a better approach. Regular reviews,quarterly for critical services,are a good discipline to catch drift.
