Eighty client environments, multiple backup platforms, and no way to prove it all worked. Now every job result funnels into one nightly pipeline: failures become prioritized tickets in five minutes, repeats escalate, and each client gets a branded monthly report.
Typical results
99.6%
Backup success rate, was 92%
80
Client environments covered nightly
1 hr
Monthly reporting, down from 16
Figures reflect typical results for this kind of automation.
The challenge
Backup results for 80 client environments lived in three different platform consoles that a technician checked each morning — when there was time. Failures could sit unnoticed for twelve hours or more, silent agents longer, and the true success rate hovered near 92%. Monthly client reports meant sixteen hours of copy-paste, so most clients simply never got proof.
Before and after
Time to catch a failure
−99%Backup success rate
+8%Monthly reporting time
−94%The automation
We funneled results from every backup platform into a single normalized pipeline that runs each night. A failed job opens a prioritized ticket within five minutes, tagged with the client, system and error pattern; a second consecutive failure escalates to the team lead automatically. Jobs that fail to report at all are treated as failures, which catches dead agents. On the first of each month, every client receives a branded report proving their data-protection posture.
How it works
- 01
Every platform, one feed
Results from all backup platforms funnel into a single normalized pipeline each night.
- 02
Failures ticket themselves
A failed job opens a prioritized ticket within five minutes, tagged with client, system and error pattern.
- 03
Repeats escalate
A second consecutive failure raises priority and pings the team lead automatically.
- 04
Silence counts as failure
Jobs that never report in are treated as failed — catching dead agents, not just errors.
- 05
Monthly proof, branded
Each client receives a branded report proving their data-protection posture.
Starts from
- Nightly backup job results
- Three backup platforms
Delivers
- Prioritized failure tickets
- Repeat-failure escalations
- Branded monthly reports
The impact
Failed backups are now caught in five minutes instead of half a day, and the portfolio-wide success rate climbed from 92% to 99.6%. Monthly reporting collapsed from sixteen hours to one, all eighty clients receive branded proof of protection, and failing jobs typically get fixed long before anyone needs a restore.
Questions about this automation
Can it work with more than one backup platform?
Yes. Results from each backup platform are pulled through their APIs, reports or alert emails and normalized into one format each night, so a failed job looks the same whatever tool produced it. Adding another platform means adding one more connection to the same pipeline, not a new process for the team.
How does it catch backups that never report in?
Every expected job is on a list per client environment. If a job has not reported a result by the expected time, it is treated as failed and ticketed like any other failure. That catches dead agents and disabled schedules, which would otherwise look like silence rather than a problem.
What goes into the monthly client report?
Each client gets a branded report on the first of the month with the success rate for their systems, any failures and how they were resolved, and the last successful backup per system. The reports are built from the same nightly data, so nobody copies results from platform consoles by hand.