ServiceNow is the backbone of your IT operations, and its optimal performance is crucial for your business’s success. Oblytech’s Proactive Monitoring & Maintenance service is designed to help keep your ServiceNow instance healthy, secure, and efficient, and to catch potential issues before they affect your operations.
We tailor our monitoring and alerting systems to your specific needs and requirements, ensuring you receive timely notifications about critical events or potential issues.
We provide regular reports on your ServiceNow instance’s health, performance, and security, giving you valuable insights into its operation and potential areas for improvement.
An IT operations lead deciding whether to hand monitoring to a supplier usually has a specific worry: that something important will fail quietly and be discovered only when a user complains. That worry is reasonable, and the answer depends on separating what the platform itself reveals from what sits around it. Inside a ServiceNow instance, the useful signals are failed scheduled jobs, integration transactions that error or time out, queues that grow faster than they drain, certificates and credentials that approach expiry, and response times that drift upward across weeks. Outside it, the signals include the network path to the instance, the availability of identity services that users sign in through, and the health of the systems on the other end of each integration. A monitoring service that covers only the first group leaves blind spots that matter during an outage, and a buyer should ask which group the proposal covers.
Monitoring also has a limit that is easy to forget. It detects deviation from the thresholds someone has configured. It does not judge whether a process is correct, whether a rule is sensible or whether a team is using the platform the way it was designed to be used. Those judgements belong to governance and improvement work, and a proposal that presents monitoring as a substitute for them overstates what it delivers.
Most monitoring setups fail through noise rather than silence. A rule that fires every time a job runs slightly long produces an alert that people learn to ignore, and when a serious alert arrives among them it is ignored too. The design goal is fewer alerts, each tied to a named owner and a first action. Start from the questions the business needs answered: is a customer-facing process working, is a data flow intact, is a security control still in force. Then build the alerts that answer those questions, and drop the ones that only describe activity.
Thresholds need to reflect normal behavior for each process. A job that normally takes a long time at month end should not alert at month end unless it exceeds its own historic pattern. Deduplication matters as well. One underlying fault can generate dozens of records in a few minutes, and the responder should receive one grouped signal with the affected components listed, not a stream of identical items. Event management capabilities can correlate these signals, but the correlation rules have to be reviewed against real incidents, because a rule that merges unrelated faults hides the second problem behind the first.
Maintenance is the work that keeps the platform healthy between releases. It includes clearing old data, reviewing license use, checking certificates, housekeeping logs, and confirming backups and restore points. Most of it is low risk when done alone and higher risk when several tasks run together in one window. The schedule therefore matters as much as the tasks.
| Maintenance activity | Usual rhythm | Risk if done carelessly | Approval expected |
|---|---|---|---|
| Reviewing failed jobs and integration errors | Daily or per shift | Repeated failures continue unnoticed for days | None for review; a change ticket for any fix |
| Clearing or archiving old operational data | On a set cycle | Deleting data that a report or audit still needs | Owner of the data class, recorded in advance |
| Certificate and credential expiry checks | Ahead of each expiry date | An integration stops at a time nobody planned for | Standard change, scheduled before the expiry |
| License and usage review | Monthly or quarterly | Access granted or retained without a business reason | Platform owner and the license holder |
| Restore testing | On a fixed cycle | Backups exist but have never been proven to restore | Platform owner, with the result recorded |
A rule that keeps this table honest is that each activity has a named owner, a recorded result and a path for anything that needs change. Maintenance that finds a fault and fixes it silently has done only half the job, because the same fault will return and no one will know why.
An alert is only useful if the person receiving it knows the first move. A short, written first-response sequence removes most of the hesitation. It normally starts by confirming that the alert is current and not a duplicate, then checking whether the affected business process is reporting problems from the user side, then reviewing recent changes that could explain the signal. Only after those checks should the responder decide whether to restart a component, apply a documented workaround or raise an incident. Responders who are not permitted to take a given action should know that before the alert arrives, and the escalation route should be written beside the alert, not in a separate document no one opens.
A monthly health report is often the only view of monitoring that a sponsor sees, so its contents matter. A useful report shows the trend in failed jobs and integration errors, the number of alerts that led to action compared with those that did not, the maintenance tasks completed on time, and any finding that has been turned into a change or a project. It should avoid long lists of raw counts that cannot be interpreted. A short set of trends with a note on each one tells the sponsor where attention is needed.
The report should also say what was not monitored. A buyer is better served by an honest list of gaps, such as an integration whose far end cannot be observed, than by a report that implies complete coverage.
Monitoring is designed to keep the platform running. When it shows a structural problem, such as an integration that fails every time a particular volume is reached, or a scheduled job that has grown beyond the window it was given, the answer is usually a redesign rather than more maintenance. The transition point should be defined in advance, so that repeated patches do not hide a need for larger work. A reasonable trigger is recurrence: the same finding returning after it has been fixed twice, or a fix that needs a change to design rather than configuration.
For anything that affects how users reach the platform, yes. Watching the instance from the inside cannot tell you that the sign-in service is down or that the network path is broken. An external check of availability and response time covers that gap.
Remove alerts that no one acts on, group related signals, and review each alert after each incident to ask whether it helped. Alert fatigue is a sign that the alert set has grown without anyone deciding to grow it.
Only the people who can take the first action should be paged, and only for signals that need action before the next working period. Everything else should go into a queue that is reviewed on a fixed rhythm.
No. Monitoring shows that something is failing in production. Testing is how a fault is prevented from reaching production. Each finding from monitoring is a candidate for a test that would have caught it earlier.
If alerts are arriving but nobody is sure which ones matter, the useful first exercise is to review the current alerts against the business processes they protect, and to record an owner and a first action for each one that remains. Monitoring is one strand of the wider support work, and the support and maintenance overview lists proactive monitoring of an instance among the services it describes. The guide to event rules explains how an event rule processes incoming events and decides what happens to each one.