We set reliability targets with SLO/SLA/SLI definitions; observability infrastructure detects issues proactively and chaos engineering proves resilience.
The critical topics this service addresses and the outcome we deliver in each.
We deliver the SLO dashboard, error budget tracker, an installed observability stack and incident runbooks; the output is evidenced in a structured monitoring stack.
We design rotation-based on-call, escalation policies and chaos experiments; the exercise cadence and blast-radius limits are defined within contract scope.
We set SLO targets for availability, latency and error rate; we measure operational time against targets with the error budget and dashboard, managing by measured values rather than promising them.
With a blameless post-mortem template, toil automation and training we build your team's capacity to sustain SRE practices independently; the handover is validated on your side.
How we phase the service across delivery, governance, and connected service pillars.
SLO design: we define SLO/SLI for availability, latency, throughput and error rate and balance speed against reliability with an error budget policy.
Observability: we build the metrics, logs and traces layer with Prometheus, Grafana and OpenTelemetry and find the source of issues quickly with distributed tracing.
Resilience: we design incident management and on-call processes, demonstrate resilience with controlled chaos-engineering experiments and reduce toil through automation.
Illustrative surfaces where this service is commonly activated.
Organisations that cannot foresee failures because of rising complexity and inadequate monitoring.
Teams that cannot balance speed and reliability because they have no SLO/SLI definitions.
Teams whose capacity is consumed by repetitive manual operations work and that want automation.
This service's depth on sector-specific technical and compliance topics.
We define SLOs for availability, latency and error rate and set a measurable balance between release speed and reliability work with an error budget policy.
We build the metrics/logs/traces layer with Prometheus, Grafana, OpenTelemetry and Jaeger and reduce noise while raising meaningful signal with multi-tier alerting.
We run blast-radius-limited experiments with Azure Chaos Studio and Litmus and turn every incident into a system improvement through a blameless post-mortem culture.
Systems that lack formal reliability engineering practices accumulate operational risk invisibly until a major outage exposes gaps in observability, incident response, and capacity planning. Without Service Level Objectives and error budgets, engineering teams have no quantitative basis for balancing feature delivery against reliability investment. Our SRE and Reliability Engineering service installs the practices, tooling, and culture that allow your systems to meet defined availability targets while maintaining sustainable development velocity.
Make risk and response indicators visible through measured controls, rehearsed playbooks, and evidence review
Shorten operational cycle time against agreed measurement targets and acceptance criteria
Turn the outcome into a measurable target with baseline, owner, and review cadence
The engagement covers the full reliability lifecycle from measurement baseline through operational maturity. We assess your current observability coverage, incident management process, and deployment safety practices, then build the tooling and processes needed to reach your target reliability tier. Scope includes both the technical implementation and the organizational practices needed to sustain reliability improvements.
Establish a quantitative reliability baseline that makes future improvement measurable and defensible
Make operational speed, resilience, and response outcomes measurable through contracted scope and acceptance criteria
Build organizational muscle for blameless postmortems that drive systemic reliability improvement
The SRE engagement delivers a functioning observability platform, a library of SLO-backed dashboards and runbooks, and an on-call program that your team can operate and evolve independently. All deliverables are documented and transferred with hands-on training to ensure operational self-sufficiency.
SLO dashboards provide real-time reliability visibility to both engineering and executive stakeholders
Runbook library reduces cognitive load during incidents and enables junior engineers to resolve common issues independently
Postmortem process drives measurable reduction in repeat incidents over a 90-day period
We begin with a two-day SLO definition workshop with your engineering and product leadership to identify the top three to five user journeys that define system reliability from a business perspective. From these journeys, we define SLIs and set initial SLO targets, then implement the instrumentation needed to measure them within the first sprint.
An error budget is the allowed amount of downtime or errors within your SLO window. When the budget is healthy, teams can deploy aggressively. When it is nearly exhausted, deployment velocity is reduced and reliability work is prioritized. This creates a data-driven, conflict-free mechanism for product and engineering to negotiate the reliability versus velocity tradeoff.
We offer both models. An embedded engagement places SRE specialists within your delivery teams to transfer knowledge and build internal capability over a defined period, typically three to six months. An advisory model provides SRE expertise and tooling implementation without embedding, suitable for teams that already have strong operational practices.
We use OpenTelemetry auto-instrumentation agents and sidecar proxy patterns to add observability to legacy applications without requiring code changes. For systems where auto-instrumentation is insufficient, we identify the minimum set of critical instrumentation points and guide developers in adding targeted metrics and structured logging.
We recommend a quarterly SLO review cadence that evaluates whether current targets remain aligned to business expectations, whether error budget policy is being followed, and whether observability coverage has gaps revealed by recent incidents. Initial SLOs are often intentionally conservative and tightened as reliability improves.
A chaos game day is a scheduled exercise where controlled failure scenarios are injected into a staging or production environment to validate that monitoring detects the failure, alerts fire correctly, runbooks are accurate, and the on-call team can recover the system within SLO targets. Game days build team confidence and expose gaps before real incidents occur.
This short form routes your request to the right support team. We clarify context first, then define the safe sharing method.
Privacy-aware first contact; safe sharing flow when needed; no sales pressure.
