Collection pipelines
Fluent Bit, Elastic Agent or a cloud-native shipper takes logs off every node and delivers them reliably, with buffering so a brief outage does not lose the evidence.
Reliability & Performance
Centralised Logging
Every log line searchable in seconds, with retention that does not outspend your compute.
The work
What this actually does
Ask an engineer to find the error behind a failed payment and watch what happens. If the answer is a sequence of SSH sessions and grep across four hosts, you do not have logging, you have log files. We build a pipeline where every service writes structured events to one place, and a search returns results while the user is still describing the problem.
Cost is the other half of the job. Raw logs are the fastest-growing line on many cloud bills, so we set retention and tiering deliberately: hot storage for the last few days, cold archives for audit windows, and nothing collected simply because it was easy. You keep the search you need without paying to store noise forever.
If any of these sound familiar
- Nobody can find anything in the logs
- Each service logs in a different, inconsistent format
- Log storage costs more than the workload it describes
- Debugging means logging into servers one at a time
Scope
What's included
Every engagement on this page covers the following, sized to your setup rather than delivered as a fixed package. If something here is not relevant to you, it comes off the scope and off the price.
Structured logging standards
We agree field names, severity levels and correlation ids, so a query can filter by request or user instead of matching free text and hoping.
Retention and tiering
Hot, warm and cold tiers with lifecycle rules that move old data automatically, keeping recent logs fast to search and older ones cheap to keep.
Access control and redaction
Pipelines strip personal data and credentials before storage, and queries are scoped by role, so logs do not become an unmanaged copy of your database.
Log-based metrics
Counts of errors, warnings and specific events are extracted at ingest and charted over time, which turns a wall of text into a trend you can watch.
Query cookbook
A set of saved searches for the questions that come up during incidents — who saw this error, when did it start, and which release introduced it.
What changes
What teams typically see
secondsTypical log search time
40%Typical log storage saving
1 queryFind a request across services
Handover
What you keep
Everything produced during the engagement is yours: the repositories, the accounts, the documentation. There is no proprietary layer and nothing to unlicense if you take the work in-house.
- Ingestion pipeline configuration held in version control
- Written logging standard with field and severity conventions
- Retention and lifecycle policy per data tier
- Saved searches for the top recurring questions
- Cost baseline and savings estimate for log storage
Tooling
Tools we use here
A starting point, not a requirement. We work in whatever you already run wherever it does the job.
Elastic
Grafana
AWS
Kubernetes
OpenTelemetry
Datadog
How it runs
From first call to handover
The same four steps on every engagement. You see each one before it starts and can stop at any of them.
- 01
Audit current log sources
We count how much is being produced, where it lands, and what it costs per month. Most teams find a handful of services responsible for the majority.
- 02
Define the schema
Field names, levels and correlation identifiers are agreed and documented, so application teams have one format to follow instead of inventing their own.
- 03
Stand up the pipeline
Collectors, parsing rules and storage are deployed as code, tested against real traffic in staging before they touch production volumes.
- 04
Cut volume and hand over
We drop the debug-level noise, tighten retention, show your team the saved searches, and leave the cost dashboard in place to catch drift.
Questions
Asked before we start
Do we have to move off our existing log platform?
No. We will happily improve a Splunk or Datadog estate, and often the biggest win is simply sending less. Migration only makes sense when cost or query limits have become a genuine constraint, and that is a decision we would cost first.
How do you stop logs leaking sensitive data?
Redaction rules run at the collector, before anything is written to storage, and we test them against sample payloads that contain credentials and personal fields. It is not perfect, so we also restrict who can query which index.
What about logs from legacy applications?
Older services that only write plain text are handled by parsing rules in the pipeline, which extract structure without touching the application. Where that proves fragile, a small logging shim in the app is usually a day of work.
How long until the search is actually useful?
Once the pipeline is live, days rather than months, because usefulness comes from the schema and the saved queries. Making every team adopt the standard takes longer and is the part that usually needs persistence.
Reliability & Performance
Often needed alongside this
Reliability & Performance
Monitoring & Observability
Know what broke, why it broke and who it affects — before your customers have to tell you.
- Prometheus, Grafana, Datadog & CloudWatch
- OpenTelemetry tracing and structured logging
- SLO dashboards and actionable alert routing
Reliability & Performance
Distributed Tracing
Follow a single request across every service and see exactly which hop added the 800ms.
- OpenTelemetry instrumentation and collectors
- Jaeger, Tempo and vendor backends
- Trace-to-log correlation for fast triage
Optimisation & Advisory
24/7 Managed DevOps Support
An on-call team on the other end of the pager, with agreed response targets and monthly incident reporting.
- 24/7 monitoring, triage and incident response
- Contractual response and resolution targets
- Monthly reliability and cost reporting
Worth a conversation about Centralised Logging?
Bring the specific problem. We will tell you honestly whether this is the service that fixes it, and what it would take.