Observability consulting: framework, SLOs, monitoring and logs
We design your observability framework and then build it: the SLIs and SLOs that define a good user experience, Real User Monitoring, synthetic monitoring, application performance monitoring, AIOps and a centralised log management solution. We work in the tools you already use, with hands-on experience of Datadog, Grafana, OpenTelemetry, CloudWatch and Playwright.
Book a discovery conversationTools we work with: Datadog, Grafana, OpenTelemetry, CloudWatch, Playwright.
What we do
Most teams already have monitoring. What they lack is a coherent design: which signals matter, what good looks like, who is paged and why. We write that design down and build it with you, in seven parts.
| Capability | What it covers |
|---|---|
| Observability framework design | A written plan for what to measure, where the data comes from and who acts on it. |
| SLIs, SLOs and error budgets | Targets for the user experience, with error budgets and burn-rate alerts that page on real risk. |
| Real User Monitoring (RUM) | What real visitors experience: Core Web Vitals, page load and front-end errors. |
| Synthetic monitoring | Scripted browser journeys and API checks that catch problems before customers do. |
| Application performance monitoring (APM) | Distributed tracing and service metrics, instrumented with OpenTelemetry. |
| AIOps and alert noise reduction | Alert correlation and anomaly detection that cut noise and speed up diagnosis. |
| Centralised log management | One searchable place for logs, with structure, retention and cost under control. |
Observability framework design
A written plan for what you will measure, where the data comes from and who acts on it. We start from your services, your users and your incident history rather than from a tool, so the framework fits the way your team works.
Typical deliverables
- Service and dependency map with the signals each one needs (metrics, logs, traces, user and synthetic data)
- Instrumentation standard: naming, tags and labels, trace propagation and structured log fields
- Tooling recommendation with trade-offs, including what to keep, consolidate or retire
- Ownership model and on-call routing, so every alert has a person and a runbook behind it
- Phased roadmap with the cost drivers called out
SLIs, SLOs and error budgets
We turn "the site should be fast and reliable" into numbers you can track. For each critical user journey we pick service level indicators (SLIs) that reflect what users feel, set service level objectives (SLOs) the business agrees to, and define how the error budget is spent.
Typical deliverables
- SLI definitions per journey, such as availability, latency percentiles and correctness
- SLO targets agreed with product and engineering, with the reasoning written down
- Error budget policy: what happens when the budget is spent, and who decides
- Burn-rate alerts that page on real risk and stay quiet on harmless blips
- SLO dashboards for engineers and a one-page view for leadership
Real User Monitoring (RUM)
Real User Monitoring measures what actual visitors experience in their own browsers and devices, including Core Web Vitals (LCP, INP and CLS), page load, front-end errors and slow third-party scripts. We design what to collect, how to sample it and how to keep it consistent with UK GDPR and PECR.
Typical deliverables
- RUM rollout in Datadog RUM, CloudWatch RUM or an OpenTelemetry-based setup, chosen to suit your stack
- Core Web Vitals and front-end error dashboards segmented by page, device and release
- Sampling, retention and consent design so the data is useful and lawful
- Links from front-end sessions to back-end traces, so a slow page can be followed to its cause
Synthetic monitoring
Scripted checks that run on a schedule and catch problems before customers do: is the site up, can a user log in, does checkout complete, is the API returning the right answer. We build browser journeys with Playwright and API checks, and wire them to alerts that mean something.
Typical deliverables
- Journey inventory ranked by business impact
- Playwright-based browser journeys and API checks, kept in your repository and reviewed like code
- Check locations, frequency and alert thresholds tuned to avoid false alarms
- Run in Datadog Synthetics, CloudWatch Synthetics or your own pipeline, depending on what you already use
Application performance monitoring (APM)
Distributed tracing and service-level metrics that show where time and errors come from inside your application. We instrument services with OpenTelemetry where it makes sense, so you are not locked to one vendor, and send the data to the backend you choose.
Typical deliverables
- OpenTelemetry instrumentation and Collector configuration, including sampling and data scrubbing
- Service maps, RED metrics (rate, errors, duration) and latency breakdowns per endpoint
- Database, queue and third-party dependency visibility
- Backend setup in Datadog, Grafana or CloudWatch, with dashboards and alerts that follow the SLOs
AIOps and alert noise reduction
AIOps means using correlation, anomaly detection and automation to cut alert noise and speed up diagnosis. It only works on clean, well-labelled signals, so we get the foundations right first, then add the pieces that earn their keep.
Typical deliverables
- Alert audit: which alerts get acted on, which are ignored, which can be deleted
- Event correlation and grouping so one incident produces one page, not fifty
- Anomaly detection used where static thresholds fail, with a review process for false positives
- Automation for the first diagnostic steps and runbook links attached to every page
Centralised log management
One searchable place for application, infrastructure and audit logs, with structure, retention and cost under control. Logs are linked to traces by ID so you can jump from a failing request to the exact lines that explain it.
Typical deliverables
- Log pipeline design: collection, parsing, enrichment and routing
- Structured logging standard for your services
- Retention tiers and sampling to keep the bill predictable
- Redaction of personal data and secrets before logs leave your network
- Implementation in Datadog Logs, Grafana (Loki) or CloudWatch Logs
How an engagement works
- Discover: We review your architecture, current tooling, recent incidents and alert history, and interview the people who are paged. The output is a short findings report with the biggest gaps ranked.
- Design: We write the framework: signals, SLIs and SLOs, tooling, ownership and rollout order. You review it and agree the scope before anything is built.
- Implement: We instrument services, build the pipelines, dashboards, synthetic checks and alerts, working in your repositories and your cloud accounts through normal pull requests.
- Hand over: We document what was built, run a walkthrough for your engineers and leave runbooks and a backlog of next steps. Everything we build lives in your repositories and your accounts.
Ways to engage
- Assessment and roadmap: The Discover and Design phases on their own, for teams that want a clear plan and will build it themselves.
- Design and implementation: All four phases, for teams that want the framework designed and then built alongside their engineers.
- Targeted help: One capability, for example SLOs and burn-rate alerting, or a log cost clean-up, scoped to a defined outcome.
Who it is for
- Engineering teams that have monitoring but still hear about outages from customers.
- Teams drowning in alerts, where most pages are ignored.
- Companies moving to the cloud or to microservices that need visibility from day one.
- Organisations running several monitoring tools that want fewer, better ones.
- Start-ups and scale-ups without a dedicated SRE team, preparing for growth or a customer security review.
What it is not
- We are not a managed service or a 24/7 operations team. We design and build; your team runs it.
- We do not offer a fixed price or fixed timeline on this page, because the right scope depends on your systems. Both are agreed after a short discovery conversation.
Frequently asked questions
What is observability consulting?
Observability consulting helps a team decide what to measure in its systems, collect that data in a consistent way and turn it into alerts and dashboards people can act on. It covers metrics, logs, traces, real user data and synthetic checks, plus the service level objectives that tell you whether users are getting a good experience.
What is the difference between monitoring and observability?
Monitoring checks for problems you already know about, such as a server being down. Observability is the ability to ask new questions of your system from the data it emits, so you can work out why something is slow or broken even when you did not predict the failure. Good practice needs both.
What is an SLI, an SLO and an error budget?
A service level indicator (SLI) is a measurement of user experience, such as the proportion of requests that succeed. A service level objective (SLO) is the target for that measurement over a period, for example 99.9 percent over 30 days. The error budget is the allowed shortfall: 99.9 percent over 30 days leaves about 43 minutes of full unavailability to spend on changes and incidents.
Do we need to buy a new tool?
Often not. We work with the tools you already have and recommend a change only when it solves a clear problem. We have hands-on experience with Datadog, Grafana, OpenTelemetry, CloudWatch and Playwright, and we use OpenTelemetry where practical to keep your data portable.
What is the difference between RUM and synthetic monitoring?
Real User Monitoring records what real visitors experience, so it shows the full variety of devices, networks and behaviour but only after someone has been affected. Synthetic monitoring runs scripted checks on a schedule, so it finds problems when nobody is using the site, such as overnight, but only for the journeys you have scripted. Most teams need both.
What does AIOps actually do?
AIOps applies correlation, anomaly detection and automation to operational data. In practice the most valuable uses are grouping related alerts into one incident, detecting unusual behaviour that fixed thresholds miss, and automating the first diagnostic steps. It depends on clean, consistently labelled data, which is why the framework comes first.
Does this replace the SREmonitor product?
No. SREmonitor is a ready-made service for uptime, performance and privacy-policy checks on websites, and it needs no setup. Consulting is for teams who need a bespoke observability design across their own applications and infrastructure. The two are separate, and you can use either on its own.
How do I get started?
Send an enquiry using the form on this page. Tell us what you run and what is hurting, and we will reply by email to arrange a short discovery conversation. There is no obligation.
Send an enquiry
Tell us what you run and what is not working. We will reply by email to arrange a short discovery conversation, with no obligation.