Observability as a strategic advantage

Move from monitoring to fixing

Dashboards don’t fix outages  –  people do. And unless observability changes that equation, you’re not building resilience, you’re just watching failure in high definition. The point of observability isn’t to see more, it’s to fix more.

Observability has to become an operational discipline, connecting telemetry to outcomes, fixing faster, smarter and automatically. If your programme doesn’t reduce tickets, speed up recovery and prevent incidents, it isn’t delivering outcomes it’s wasting screen time.

Go from “See” to “Solve”

Monitoring tells you something looks wrong. Observability should tell you why it’s wrong and triggers what to do next. That leap from ‘see’ to ‘solve’ needs more than logs, metrics and traces. It requires context, service health, user impact, business criticality and the ability to act.

To truly be effective observability must become cultural. For it to deliver, it must be woven into how organisations work; shared ownership, continuous learning, runbooks as code and automation pre-approved with guardrails. In regulated industries like financial services, under DORA, observability is not optional – it’s required.

“If your observability doesn’t trigger action, it’s just screen time.”

Avoid the analysis paralysis trap

Too many teams build ‘observability theatres’ beautiful graphs, noisy alerts, brittle playbooks. The result is always the same – plenty of signal, little prioritisation.

Break the cycle:

• Use XLAs as well as SLOs  –  measure not just reliability, but real user experience. For COTS applications, which dominate most estates and are often black boxes, observability can finally expose outcomes; smooth logins, fast transactions, and responsive performance.
• Tie every alert to impact  –  error-budget burn, XLA degradation, or customer consequence.
• Enrich every signal  –  add ownership, cost and change context so data becomes actionable.
• Demand a response plan  –  no dashboard without a runbook, no alert without an owner.

Broaden the data and narrow the action.

Logs, metrics and traces are necessary but not enough. To act quickly, fold in:

• ITSM/ITOM  –  ownership, change windows, maintenance states.
• IT Asset Management  –  what’s where, who owns it, how it’s configured.
• FinOps  –  cost anomalies and budget guardrails.
• Identity  –  secure response with MFA, just-in-time access and time-boxed elevation.

Focus only on what breaks SLOs, harms customers, or drives cost. Everything else can wait.

Automate the Obvious First

If it can be fixed the same way twice, automate it. High-value patterns include:

• Self-healing infrastructure: rolling restarts, cache purges, scaling.
• Safe rollbacks: feature flags, version pinning.
• Guardrails: cost caps, throttling, circuit breakers.
• Configuration drift repair: reconcile intended vs. actual state.
• Proactive hygiene: credential rotation, certificate renewal, queue clean-up.

With AIOps and AI-infused automation, enterprises can go further. Machine learning reduces noise, surfaces anomalies and prioritises fixes by business impact. AI can trigger self-healing before users notice. This is autonomous operations.

Automation should be treated like product development: backlog, tests, staged rollout, telemetry. The KPI is not “alerts closed” but incidents auto-resolved and tickets prevented.

People and process still decide the outcome

Observability fails without the right operating model. Success combines SRE practices (SLOs, error budgets, post-mortems) with service management (incident, problem, change) and makes observability cultural:

• Runbooks as code  –  versioned, reviewed, with pre-conditions and rollback.
• Change without friction  –  pre-approved pathways so fixes aren’t blocked at 2 a.m.
• Learning loops  –  every incident must change a runbook, automation, or threshold.
• Shared mindset  –  developers, operators, security, finance and business use observability data as a common language.

Do Cloud and COTS the right way

Cloud multiplies both opportunity and risk. Elastic systems generate more telemetry and change faster, so drift and misconfiguration appear sooner. Observability and guardrails must be built in from day one, logging standards, trace propagation, golden signals, budgets, identity boundaries and automation hooks.

And don’t forget the reality, many estates run on COTS applications, historically, these were unobservable black boxes. Today observability can map their impact through XLAs, finally quantifying user experience and aligning it with resilience, compliance and cost.

“Dashboards don’t fix outages. Runbooks do. Better yet: runbooks that run themselves.”– Andy Dunbar, Managing Director – Software & Security

SCC can help without the hype

Enterprises don’t struggle because they lack tools, but because the last mile from signal to fix crosses teams and disciplines. SCC’s strength is operating across those seams, blending service management with SRE, attaching ITAM and FinOps context and building automation pathways that make self-healing real across on-prem, public cloud and hybrid estates.

If you want a single, low-friction step, try an Observability Action Audit:

• Map your ten most common incidents.
• Identify 10–15 safe automations.
• Implement the first five.
• Publish an Actionability Score your board can understand.

That’s observability that moves from watching to fixing.

Author : Andy Dunbar, Managing Director – Software & Security