Product Engineering and QAPublicly listed capability

Stop paying for the same incident twice and keep your product secure, current and improving.

We provide application support, upgrades, monitoring and security remediation with root cause analysis, so maintenance reduces incidents over time and frees budget for new features.

Kindlebit publicly lists this capability on its website or a third party profile. Named, approved project evidence is being compiled and will be added when Kindlebit confirms it.

Support loop

  1. Monitor
  2. Triage
  3. Fix
  4. Root cause
  5. Prevent
  6. Report

Reference design. Components are options, not a statement of what is deployed at any customer.

Problems this service is built to solve

These are situations we expect buyers to recognise. Each one states why it happens, what it costs and how we would approach it.

Recurring incidents

Every month end, the reporting job fails and someone restarts it. It has been restarted forty times and the ticket is closed each time.

Why it happens
Support is measured on closing tickets, not on removing causes, and nobody has time or ownership for the root fix.
What it costs
Repeated disruption and a team stuck in reactive mode.
How we approach it
We classify incidents, run root cause analysis on the top recurring ones, fix causes, add monitoring and track recurrence as a service metric.
What to measure
Incidents per month by cause, repeat incident rate and mean time to restore.

Technical debt

Changes take weeks because nobody is confident about side effects. The test suite is thin and the code mixes concerns.

Why it happens
Delivery pressure favoured speed and the debt was never scheduled for repayment.
What it costs
Slow delivery, defects and developer attrition.
How we approach it
We measure debt hot spots, agree a budget each sprint, add tests around risky areas first and refactor with safety nets.
What to measure
Lead time for changes, change failure rate and test coverage in hot spots.

Delayed security updates

A vulnerability in a web framework is announced. The team knows it exists but the upgrade requires changes that no one has time for, and it waits six months.

Why it happens
Dependencies are not tracked, upgrades are deferred and there are no tests to prove upgrades are safe.
What it costs
Exposure to known exploits and compliance findings.
How we approach it
We track dependencies, scan continuously, prioritise by exploitability, upgrade in small steps with tests and report to security owners.
What to measure
Time to patch critical vulnerabilities, open vulnerabilities by severity and unsupported component count.

Maintenance consuming product budgets

Seventy percent of the engineering team's time goes to keeping the lights on, leaving little for the roadmap.

Why it happens
Unreliable components, manual operations and unclear support boundaries.
What it costs
Stalled product growth and frustrated stakeholders.
How we approach it
We separate support from product work, automate repetitive operations, fix top cost drivers and set service levels with transparent reporting.
What to measure
Share of capacity on maintenance, cost per incident and support hours trend.

Solutions we engineer

Concrete capabilities, each with the need it serves, how it integrates, what you receive and the value to expect.

Application support

Tiered support with service levels, triage, fixes and communication.

Customer need
A dependable team for production issues.
Integration
Your ticketing and on call tools.
Deliverable
Support service and reporting.
Business value
Faster resolution and clear accountability.

Upgrades and modernisation

Framework, runtime, dependency and database upgrades with tests and rollback plans.

Customer need
Stay on supported platforms.
Integration
Your pipelines and environments.
Deliverable
Upgrade plan and execution.
Business value
Security and developer productivity.

Monitoring and observability

Logging, metrics, tracing, uptime checks and alerts tuned to reduce noise.

Customer need
Find issues before users do.
Integration
Datadog, Grafana, New Relic, CloudWatch or Azure Monitor.
Deliverable
Dashboards and alerts.
Business value
Early detection and faster diagnosis.

Security remediation

Dependency scanning, static analysis, penetration test remediation and secrets hygiene.

Customer need
Close known gaps.
Integration
Security tools and reports.
Deliverable
Remediation backlog and fixes.
Business value
Reduced exposure.

Performance and cost tuning

Query and code profiling, caching and right sizing of infrastructure.

Customer need
Faster and cheaper to run.
Integration
Cloud billing and monitoring.
Deliverable
Tuning report and changes.
Business value
Better experience and lower cost.

Continuous improvement

A monthly improvement plan combining defects, debt and small enhancements.

Customer need
Evolve, not just survive.
Integration
Product backlog.
Deliverable
Roadmap and monthly reports.
Business value
Predictable progress.

How we solve it

A delivery sequence built around architecture, testing, CI/CD and operational readiness.

Take over knowledge

Review code, infrastructure, runbooks and incident history, and record the gaps.

Define service levels

Agree severity levels, response and resolution targets, escalation and communication.

Stabilise and monitor

Add monitoring and alerting, fix the noisiest alerts and create runbooks for common incidents.

Operate support

Triage, fix and communicate, with code review and tests for every change.

Analyse root causes

Review incidents regularly, find patterns and plan permanent fixes.

Maintain and upgrade

Patch and upgrade on a schedule with regression tests and staged rollout.

Report

Provide monthly reports on incidents, vulnerabilities, performance, cost and improvement work.

Plan the next stage

Review budgets and risks, and agree priorities between maintenance and new features.

Solution in action: Taking over support for a business critical web application

Reference Architecture An illustrative scenario. It describes how we would structure the work, not a delivered customer project.

Starting problem

The original developers have moved on and incidents are rising.

Existing workflow

There is no monitoring, no runbooks and releases are manual. Issues are reported by users by email.

Improved workflow

The team documents the system, adds monitoring and alerting, sets up a ticket queue with service levels and creates a regression suite for the riskiest flows. Recurring incidents are traced to root causes and fixed.

An alert fires or a user reports an issue.

Systems involved

Application, database, hosting platform, monitoring, ticketing, pipeline.

Data movement

Logs, metrics and incident history.

Human decisions

On call engineers triage and fix. A product owner prioritises improvements.

Automation opportunities

Alerts, dependency scanning and regression tests on every change.

Exception handling

Critical incidents trigger an escalation path with defined communication.

Resulting user experience

Users report fewer issues, and when issues occur the team already knows and communicates.

KPIs to evaluate

  • Incidents per month
  • Mean time to restore
  • Repeat incident rate
  • Open critical vulnerabilities

What you receive

Concrete deliverables for this service, written so you can check them against the contract.

  • System and runbook documentation
  • Monitoring dashboards and alert rules
  • Support service with agreed service levels
  • Incident and root cause reports
  • Upgrade and patch plan with execution
  • Security remediation log
  • Regression test suite for critical flows
  • Monthly service and improvement report

Technology and engineering

Options we would evaluate for this service. Unless a group is marked as publicly listed on kindlebit.com, treat each tool as a proposed implementation option. Naming a tool does not imply a vendor partnership.

Monitoring (proposed implementation options)

  • Datadog
  • Grafana
  • Prometheus
  • New Relic
  • Sentry
  • CloudWatch
  • Azure Monitor

Security and quality

  • Dependabot
  • Snyk
  • SonarQube
  • OWASP ZAP

Delivery

  • GitHub Actions
  • GitLab CI
  • Azure DevOps
  • Docker
  • Terraform

Publicly listed Kindlebit capabilities

  • Server management
  • Backup management
  • Server and website security
  • AWS, Azure and Google Cloud services

Relevant Kindlebit work and evidence

We use the strongest evidence available and say which kind it is.

Reference ArchitectureInteractive demo with simulated data

Support loop with monitoring, root cause analysis and regression testing

A reference operating model. The SaaS demonstration includes an observability panel built with simulated data.

Open the demonstration

Business outcomes and success criteria

These are the measures we would agree before work starts. They are criteria for success, not results from past engagements.

Incident rate

Incidents per month and repeat incident rate.

Restore time

Mean time to restore service.

Patch time

Days to patch critical vulnerabilities.

Capacity

Share of engineering time spent on maintenance.

Questions buyers ask

What do your service levels look like?

We agree severity definitions, response and resolution targets, and hours of cover that match your business. Targets are in the contract with reporting against them.

Can you support software you did not build?

Yes. We start with a knowledge transfer and review, record risks and then agree what we will support.

How do you prevent regression when you change something?

By adding automated tests around critical flows before changes, using code review and staged releases.

How are security updates handled?

Through continuous dependency scanning, prioritisation by severity and exploitability, and scheduled patch windows with tests.

How is maintenance priced?

Typically as a monthly retainer based on scope, hours of cover and service levels, with defined handling of larger enhancements.

Can we move maintenance in house later?

Yes. Documentation, runbooks and tests are written for handover, and we can help transition.

Review what it costs you to keep your product running.

Tell us about the application, its incident history and the team supporting it. We will outline a support model that reduces repeat work.