Home Software operations Operational transparency

Observability and operational transparency for stable systems

Alexandra Mittmann

Alexandra Mittmann

Team Lead Project Management

+41.. Show number
Get expert advice. Our References

Expert knowledge for your project

Alexandra Mittmann is a team leader in project management at soxes. With a bachelor’s degree in business psychology from EBC University and as a certified Scrum Master, she manages projects with a clear eye for structures, people, and goals. She quickly recognizes where potential lies and implements targeted improvements.

Contents

Operational transparency

The real operational risk is often hidden

The systems are running, interfaces are feeding data, users are working—and yet a nagging feeling remains: when things go wrong, it gets uncomfortable. Not because the team isn’t responding, but becausewhen a failure occurs, no one can immediately pinpoint exactly where the problem lies or why it’s happening right now.

In mature production systems, this happens time and again: errors seem to occur randomly, cannot be reliably reproduced, and cannot be clearly explained. Several people analyze the issue in parallel, each with different assumptions, until eventually someone finds the cause. Exactly how this happens often remains unclear.

On this page, you'll learn

How to Spot a Lack of Operational Transparency

Why logs, monitoring, and
dashboards often don't help
during an incident

Why this issue
is particularly critical
for legacy and mission-critical systems

What does operational transparency mean?

Operational transparency means that the status of a system can be easily tracked at any timeduring day-to-day operations .

You should be able to answer the following at any given moment:

  • What is happening in the system right now?
  • Where does a behavior originate?
  • Which components are involved?
  • How did this state develop?
  • Is everything working correctly again after a failure or a restore?

Without this transparency, you see a lot of data but don’t understand the system’s state.

Why does this challenge often go unnoticed for years?

As long as nothing happens, operations appear stable. That is precisely what makes the situation deceptive.

Only when something unexpected occurs does it become clear how little the system can be explained in detail:

  • An incident takes longer than expected
  • A restore leaves uncertainty
  • A release becomes a source of anxiety
  • New employees are slow to understand the operations

Why does this affect so many companies?

Over the years, new interfaces, new requirements, new components, and integrations emerge. Systems grow organically alongside the company. Logs are generated. Monitoring is implemented. Dashboards are created. Yet this information often exists in isolated silos.

This is precisely where issues such as logging structures and meaningful metrics become crucial. Without them, data may exist, but it cannot be meaningfully interpreted in the event of a failure.

Many companies already have logs, monitoring, dashboards, and alerts in place. Nevertheless, operations feel chaotic when a failure occurs . Most often, there is a lack of structure, context, and a unified view of system behavior.

Monitoring shows whether something is wrong. Operational transparency (or observability) shows why it is wrong.

Business Risks Associated with a Lack of Operational Transparency

  • Daily Life and Impact

    A lack of operational transparency rarely remains a purely technical issue. It manifests itself in day-to-day operations and has a direct impact on stability, speed, and security.

  • Prolonged disruptions

    Outages last longer because the causes cannot be pinpointed quickly enough.

  • Working in parallel without shared signals

    Several teams are searching for errors simultaneously without looking at the same system signals.

  • Cautious releases

    Releases are planned more carefully because no one knows for sure what impact changes will have.

  • More manual checks

    Manual checks are on the rise because of a lack of trust in automated processes and system statuses.

  • Knowledge limited to individuals

    Knowledge is concentrated in individual people rather than being transparently visible within the system.

  • Statements without supporting data

    Statements are based on experience rather than on data, logs, metrics, or clear dependencies.

  • Uncertainty after the restore

    After a restore, there is still uncertainty as to whether systems, data, and interfaces are fully functional again.

  • A more gradual onboarding process

    New employees take longer to get up to speed because the interrelationships, dependencies, and operational logic are difficult to grasp.

This is how soxes restores operational transparency in systems

Observability does not result from additional tools, but rather from a structured examination of:

  • system boundaries and dependencies
  • Logging structures and metrics
  • Traceable data flows
  • A unified view of components and services
  • Correlation of logs, metrics, and traces

How can you tell right away when observability is good?

You don’t recognize good observability by the technologies, but in everyday use.

  • Issues can be pinpointed and isolated.
  • Correlations are visible.
  • Statements are based on system data rather than experience.
  • New employees understand operations more quickly.
  • Releases feel manageable.

Why is this issue critical for mature and legacy systems?

The longer a system has been in use, the more has been added to it: new features, new interfaces, new requirements, special cases, and integrations.

What used to be straightforward is now a web of dependencies:

  • Processes span multiple components.
  • Logic has evolved over time and is barely documented.
  • Knowledge is scattered among individual employees.

It is not the software itself that becomes a risk, but its accumulated lack of transparency. Operational transparency is crucial, especially for Access, Delphi, and Excel-based solutions or highly integrated production systems.

Frequently asked questions

  • What is the difference between monitoring and observability?

  • Why are logs often insufficient when a failure occurs?

  • How can I find the cause of a software error faster?

  • How can I tell if my system lacks operational transparency?

  • Why is observability particularly important for legacy systems?

  • How does observability help with releases?

  • How does observability help after a restore?

  • How does observability reduce reliance on individuals?

How transparent is your business really today?

If you can’t answer these questions with certainty, your system lacks the necessary transparency.

  • Where and how does a certain behavior arise?
  • Which components are involved?
  • Does everything really run correctly after a restore?
  • What are the actual effects of releases?

Direct number

+41 55 253 00 53
Request an operational check now!

Trusted by Leading Brands

TUS
OYM AG
Inrate AG
Kanton Aargau
KPMG
Raiffeisen Gruppe
Electrolux AG
CelsiusPro AG
Bistum St. Gallen
REFCO Manufacturing Ltd.
Sulzer AG
Kanton Solothurn
Zürcher Kantonalbank
Credit Suisse
Wiegand AG
AXA Winterthur
Basler Kantonalbank
Bossard AG
ETH Zürich
Hirslanden-Gruppe Schweiz
UBS AG
Universitätsspital Zürich
Vontobel Holding AG
Zürich Versicherung
Nez Rouge
Stadler Rail
NeoVac ATA AG
OEKO-TEX
Huber+Suhner
Bucher Hydraulics
Civil Engineering Office Zug
Emmi Group
Rieter AG
EFCO AG
Reichmuth & Co.
Canon (Switzerland) AG
Testex
BBT software for insurance
Sika Schweiz AG
Glencore International AG

This might interest you

Contact

Do you have any questions? Would you like to find out more about our services?
We look forward to your enquiry.

Contact us
Sofia Steninger

Sofia Steninger
Solution Sales Manager