Services

SLA support for applications and data platforms

Software does not stop needing attention at go-live. Veratas SLA support gives your custom applications, data platforms, and integrations a named, accountable team working to documented severity definitions and response targets, so issues are resolved and root causes addressed, not just logged.

Talk to our team
The problem

Why most support quietly fails

The gap is rarely effort. It is accountability, knowledge, and the absence of root-cause work.

Plenty of support arrangements look fine on paper and disappoint in practice. A ticket queue absorbs issues, a first response acknowledges receipt rather than diagnosing anything, and the same incident recurs every few weeks because nobody is funded to fix its cause. The business ends up with a process for logging problems rather than a service for resolving them, and the people raising tickets lose confidence in it.

Three things separate support that works from support that does not. The first is accountability: severity definitions and response targets written down, so both sides know what is committed and there is no argument about whether a problem is urgent. The second is knowledge: the engineer who picks up an incident understands the system, so the first reply is a diagnosis and not a request for more information. The third is root-cause analysis, the discipline of treating a recurring incident as a defect to be removed, so the support load falls over time instead of compounding.

Custom applications and data platforms need this more than packaged software does, because there is no vendor helpdesk behind them. A failed overnight pipeline, a Power BI dataset that will not refresh, an integration that has silently stopped, these have business consequences within hours and need a team that knows the system and is accountable for it. That is what SLA support is, and it is deliberately different from a ticket queue.

What we cover

Support that keeps systems running

We support the applications, data platforms, and integrations we build, and those built by others, under clear written SLAs.

Application support

Support for custom .NET, React, and ABP.io applications: incident resolution, bug fixes, security patching, and small enhancements, all delivered against an agreed SLA with defined severities and response targets.

Data platform support

Support for data warehouses, Microsoft Fabric estates, data pipelines, and Power BI: pipeline monitoring, failure investigation, refresh management, and resolution when an overnight load or a dataset refresh breaks.

Integration support

Monitoring and support for integration pipelines and APIs, keeping data flowing reliably between systems and resolving failures quickly, including the silent failures that otherwise surface only when a number looks wrong.

Monitoring and alerting

Proactive monitoring through Application Insights, Azure Monitor, and pipeline alerts, so failures are detected and triaged by us, often before users notice, rather than waiting for a ticket.

Root-cause analysis

Formal root-cause analysis on recurring or significant incidents, with a documented fix, so the underlying defect is removed and the support load trends down rather than up.

Enhancement and advisory

A clear channel for small changes and enhancement requests, plus advisory input on the platform’s direction, so systems keep evolving in step with the business instead of stagnating.

How it works

Support delivered to documented SLAs

SLA support runs on a clear operating model: defined severities, response and resolution targets, named engineers, and regular reporting.

01

Onboard

We run knowledge transfer, review system documentation, set up access and monitoring, and build runbooks for common scenarios. We agree the support scope, severity definitions, and SLA targets in writing before cover begins.

02

Triage

Issues are logged and triaged by severity against agreed definitions, with response targets matched to business impact: fastest for a critical outage, standard for a minor defect. Every issue gets a clear priority and owner.

03

Resolve

Investigation and resolution are handled by engineers who know the system, so the first response is diagnosis. Fixes are tested and released through a controlled pipeline, with progress visible to you throughout.

04

Report

We report regularly on incident volumes, response and resolution performance against SLA, recurring themes, and recommendations, so you have an evidenced view of how the systems and the service are performing.

05

Improve

We run root-cause analysis on recurring incidents and fix the underlying causes, so the support load falls over time. Support becomes a route to a more stable platform, not just a place issues are absorbed.

Our approach

Named engineers, written commitments, falling incident volumes

Good support is measured by whether problems stop recurring, not by how fast tickets are acknowledged.

Our SLA support is built around engineers, not a queue. The people who resolve your incidents understand your systems, often because they built them, or because onboarding gave them genuine working knowledge. That means the first response is a diagnosis with a likely cause and an estimate, not a holding acknowledgement. It also means fixes are made with full awareness of the system, so a quick patch does not create the next incident elsewhere.

The commitments are written and specific. Severity levels are defined against business impact, and each has a response target and, where it applies, a resolution target. A critical incident, a production outage or a failed load blocking the business, carries the fastest response; a cosmetic defect carries a standard one. Everyone knows what is committed, which removes the friction of arguing about priority while a system is down. The exact targets are agreed with you during onboarding so they fit your operational reality.

And the service is designed to shrink its own workload. Every recurring or significant incident gets root-cause analysis and a documented permanent fix, so the same problem does not return. Regular reporting makes the trend visible. Done well, the incident volume falls quarter on quarter, which is the clearest possible evidence that support is improving the platform rather than merely keeping pace with its faults.

FAQ

Frequently asked questions

Quick answers to questions you may have. Can't find what you're looking for? Check out our full documentation.

Incident resolution, bug fixes, security patching, monitoring, root-cause analysis, and small enhancements for custom applications, data platforms, and integrations. Everything is delivered against documented severity definitions and response targets agreed during onboarding. It covers both systems we built and, after an onboarding phase, systems built by other teams.
Issues are triaged into severity levels defined by business impact. A critical incident, such as a production outage or a failed load blocking the business, carries the fastest response target; minor or cosmetic defects carry a standard one. Each severity has a response target and, where applicable, a resolution target. The exact figures are agreed with you during onboarding so they suit your operations.
Microsoft managed services cover the Microsoft cloud estate itself: Microsoft 365, Azure, Dynamics 365, and security. SLA support covers the custom applications, data platforms, integrations, and Power BI solutions built around and on top of that estate. They address different layers and complement each other, and many clients use both, one for the platform, one for what runs on it.
Yes. We begin with an onboarding phase: knowledge transfer, a review of existing documentation, access setup, and building runbooks for common scenarios. This gives our engineers genuine working knowledge of the system before cover begins, so we can support applications, data platforms, and integrations built by other teams or partners with the same accountability as systems we built ourselves.
When an incident recurs or is significant, we treat its cause as a defect to be removed rather than just restoring service. We investigate why it happened, document the finding, and implement a permanent fix, a code change, a pipeline correction, a configuration adjustment. Over time this reduces incident volume, which is why our regular reporting tracks the trend, not just individual tickets.
Both. We set up monitoring through Application Insights, Azure Monitor, and pipeline alerts, so many failures are detected and triaged by us before users notice. Combined with root-cause analysis on recurring issues, this makes the service genuinely proactive: the aim is fewer incidents over time, not just a faster reaction to each one as it arrives.
Yes, the scope is flexible. You can cover a single application or a whole estate, add systems as they go live, adjust SLA tiers, or change the enhancement allowance as priorities shift. The arrangement is reviewed regularly and scales up or down with your estate, so you are not locked into a fixed scope that no longer matches what you run.
Regular reporting covering incident volumes, response and resolution performance against the agreed SLA, recurring themes, root-cause findings, and recommendations. You get an evidenced, honest view of how both the systems and the service are performing, which supports decisions about where to invest, what to stabilise, and whether the support scope still fits.
Get started

Give your systems accountable, expert support

Custom applications and data platforms need a support team that knows them and is accountable for them. Start with a conversation about what you need covered.

Schedule a discovery call